- Current Issue
- Online First
- Adopt
- Most Downloaded Archive
-
ZHU Hairong, PENG Peiying, CHEN Xiaomeng, WU Yahui, WANG Jianhua
2022,43(2):119-126, DOI: 10.7535/hbkd.2022yx02001
Abstract:
In order to study the oscillating heat transfer enhancement mechanism of the cooling oil gallery of highly-enhanced piston,the oscillatory flow and heat transfer process of engine-oil in the cooling oil gallery of piston were analyzed by the field synergy theory.CFD software FLUENT was used to simulate the velocity field and temperature field distribution of the fluid in the elliptic and the variations of mean field synergy number and cosine value of synergy angle in both two gallery structures under different conditions were obtained.The results reveal that the field synergy principle could well explain the oscillating heat transfer enhancement performance of cooling oil gallery in highly-intensified piston efficiently.The synergy angles at the inner and outer walls of the water droplet oil gallery are smaller than that of elliptic oil gallery,and the mean field synergy number and cosine value of synergy angles of water droplet oil gallery are larger than that of elliptic oil gallery,which indicates that the synergy degree of water droplet oil gallery and its effect of heat transfer enhancement are much better.Using the field synergy theory to guide the structure design of cooling oil gallery of piston will open up a new way to improve the heat transfer enhancement ability of cooling oil chamber gallery.
-
YANG Wenhuan, ZHAI Yu, YIN Yaping, WANG Xiaojun
2022,43(2):127-136, DOI: 10.7535/hbkd.2022yx02002
Abstract:
Aiming at the problems of poor real-time performance and easy drift in the existing research methods in the field of multi-target tracking,a multi-target detection and tracking algorithm was proposed based on YOLOv3 algorithm and KCF algorithm.Firstly,the trained YOLOv3 network was used to obtain the location of the target in the video,and the ID of each target was allocated;Secondly,multiple targets were input into the tracking module based on kernel correlation filter in parallel for target tracking;Then,the conditions for starting the correction strategy were judged,if they were met,the results of the detection module were used to correct the results of the tracking module;Finally,the kernel correlation filter model was updated by using the tracking results.The experimental results show that when the algorithm is applied to four groups of video sequences containing multiple interferences in OTB2015 data set,the tracking accuracy reaches 82.4%,the tracking success rate reaches 81.1%,and meets the requirements of real-time tracking.Therefore,the algorithm is not only valid,but also has stronger robustness to provide a new research method for the field of multi-target tracking.
-
LEI Tianxiang, LYU Fangcheng, LIU Jiaomin, FENG Jiahao, ZHANG Rui′en
2022,43(2):137-143, DOI: 10.7535/hbkd.2022yx02003
Abstract:
In order to solve the limitation of intrinsic carbon nanotubes in SF6 gas sensing detection,a method was proposedto study the gas-sensitive properties of SF6 discharge decomposition based on modified carbon nanomaterials.The air plasma was used to modify the intrinsic carbon nanotubes and pretreat the surface of carbon nanotubes,and the gas sensing response characteristics of the modified carbon nanotubes in detecting the decomposition components of SF6 was investigated.The results show that the air plasma-modified carbon nanotube gas sensor is more sensitive to the resistance change of H2S gas than the intrinsic carbon nanotube,and has a shorter response time,good repeatability and stability.The air plasma modified carbon nanotube gas sensor is much less sensitive to the change in resistance of SO2 gas.Carbon nanotube gas sensors with different dopant ratios have different sensitivity responses to SOF2 and SO2F2 respectively.Therefore,the intrinsic carbon nanotube gas sensor modified by air plasma can accurately reflect the discharge decomposition of SF6 gas and provide a basis for the detection of SF6 gas composition.
-
LI Chunhua, HAO Nana, LIU Yukun
2022,43(2):144-153, DOI: 10.7535/hbkd.2022yx02004
Abstract:
The classical video salient object extraction model does not make full use of time-domain saliency cues,and is susceptible to the background noise interference.The extracted salient objects are incomplete.This paper proposed a video salient object extraction model under the guidance of spatio-temporal contrast.Firstly,adaptive fusion of RGB color space contrast and motion contrast was used to determine the prior information of prominent targets.Then,the energy function was composed of the foreground extraction item of the current frame and the position constraint item of the adjacent frames,which was used to guide the spatio-temporal saliency cue fusion.Finally,the complete video salient target was extracted by super-pixel smoothing optimization.The experimental results show that the model is tested on Visal,SegTrack V2 and DAVIS data sets.The MAE values in Visal,SegTrack V2 and DAVIS data sets are 0.030,0.024 and 0.032,respectively,and the F-measure values are 0.772,0.781 and 0.812,respectively,with good accuracy and robustness.This algorithm can effectively detect the visible targets in the video,thus providing theoretical reference and method basis for the monitoring system and target tracking.
-
WAN Lei, YU Fei, LU Tongwei, YAO Jing
2022,43(2):154-161, DOI: 10.7535/hbkd.2022yx02005
Abstract:
The high randomness and uncertainty of load data make it difficult to improve the accuracy of short-term load forecasting.In order to improve the accuracy of short-term load forecasting,a short-term load forecasting method based on a combined model of fully adaptive noise ensemble empirical mode decomposition (CEEMDAN),convolutional neural network (CNN) and gated recurrent unit (GRU) was proposed.First,the CEEMDAN model was used to decompose the complex original load sequence into several relatively simple sub-sequences;secondly,CNN and GRU were used to establish a prediction model for each component,and the normalized components were input into the training model to obtain the predictive subsequence.Finally,the results of all components were summarized to get the final prediction results.Experimental results show that the CEEMDAN-CNN-GRU combined model has a significant improvement in accuracy compared with the LSTM model,GRU model,CNN-GRU and CEEMDAN-GRU combined model,with an average increase of 25.08%,23.59%,20.41% and 13.53%.The CEEMDAN-CNN-GRU combined model can extract nonlinear features from historical load data,effectively improve the accuracy of short-term load forecasting,and provide strong support for power system construction.
-
LI Yunsheng, XU Yaqian, WANG Zehan, HOU Zhongming
2022,43(2):162-171, DOI: 10.7535/hbkd.2022yx02006
Abstract:
To research the influence of the hanger system on the mechanical properties of suspension footbridge,the finite element models of a suspension footbridge with vertical and inclined hanger systems were established respectively by using Midas/Civil software.The calculation of finding reasonable cable shape was carried out,and the static and dynamic properties of the two models were analyzed.The results indicate that,the internal force of the vertical hanger is uniform,and the influence line is positive,while the internal force of the outward-tilting inclined hanger is larger than that of the inward-tilting hanger,and the influence line has both positive and negative value;In the vertical hanger model,the internal force of the main cable is basically uniformly distributed with almost no axial force in the main beam and larger displacement in both the main cable and the main beam.Compared with the vertical hanger model,the declined hanger model has larger gradient but smaller value in the internal force of the main cable,larger axial force in the main beam,smaller displacement in both the main cable and the main beam,and larger vibration frequencies in first ten order modes.Under the static wind load,the internal force and displacement of the wind resistance system in both two models are similar to each other,and are less affected by the hanger form.Both the lateral and vertical stiffness of the inclined hanger model are larger than those of the vertical hanger model,which is more suitable for suspension footbridge with small live load.The suspension footbridge with vertical suspender system and inclined suspender system can be comprehensively compared and analyzed from the perspective of static and dynamic performance,which provides a theoretical basis for the structural system optimization of this kind of bridge.
-
CHEN Bingqi, CAI Yingpeng, XU Ying, FU Yan, LIU Jiye
2022,43(2):172-180, DOI: 10.7535/hbkd.2022yx02007
Abstract:
In order to quantify the degree of rock damage caused by high temperature,the Fangshan marble under high temperature was used to explore the degree of rock thermal damage and evolution process from the basic physical parameters,mesostructure and microstructure.First,samples were treated at eight temperatures within the range of 25~850 ℃.Then,the microstructure evolution of rock with temperature was obtained through CT scanning technology and SEM test.The coefficient of phase variation proposed in this paper,combined with microscopic characteristics of marble after heating,wave velocity,density and CT value described the thermal damage.The results show that the four indexes embody different sensitivity with the change of uniaxial compressive strength at different temperature stages.Among them,the wave velocity response is the most obvious in the range of 25~250 ℃;at 250~450 ℃,the CT value can best reflect the change of thermal damage;at 450~700 ℃,the coefficient of phase variation is the most sensitive to the degree of damage.Based on the results,the uniaxial compressive strength prediction formula of rock treated by high temperature containing damage index is established in sections.The uniaxial compressive strength can be predicted based on some sensitive factors,which has some reference for the excavation of rock mass and the design of supporting structure in deep underground engineering.
-
ZHAI Junwei, QU Ying, GUO Fei, LIU Bin
2022,43(2):182-193, DOI: 10.7535/hbkd.2022yx02008
Abstract:
Bibliometrics is a science to quantitatively analyze literature knowledge units by using mathematical and statistical methods and reveal the internal knowledge content of literature.Co-occurrence network analysis is a visual method to analyze the data relationship of document characteristic items in bibliometric research.According to the number of analyzed characteristic items,it can be divided into single co-occurrence network analysis and multiple co-occurrence network analysis.Compared with single co-occurrence network analysis,multi co-occurrence network analysis increases the dimension of feature items and presents literature knowledge more deeply.However,due to the increase of the dimension of the analyzed feature items,the number of nodes in the co-occurrence network increases,and the connection coincidence degree and crossover frequency between nodes are too large,which reduces the visualization effect of literature measurement.Therefore,at present,the bibliometric co-occurrence network analysis mainly focuses on single co-occurrence,and the visualization effect of multiple co-occurrence network analysis needs to be improved. 河北科技大学学报 2022年 第2期 翟君伟，等：基于LDA主题模型的文献特征项多重共现可视化方法 In order to solve the problems of too many nodes,too large connection density,disadvantage of discovering the value of data and low visualization effect in multi co-occurrence network,LDA topic model was introduced and the method of spatial division was adopted to transform the global visualization problem of feature items into subspace visualization problem.Firstly,the key words were extracted by using sati document title information analysis software,and the TF-IDF calculation was carried out.The calculation results were taken as the experimental data.Secondly,Python is used to construct a topic model for topic cluster analysis of the target literature set.Finally,Ucinet software was used to analyze the multiple co-occurrence of subspace documents with different topics,and the subspace analysis results are superimposed and reconstructed,so as to complete the structural expression of the multiple co-occurrence visualization system.The results show that compared with the original multi co-occurrence visualization method,the improved multi co-occurrence visualization method based on LDA topic model reduces the number of nodes in the co-occurrence network and the connection density between nodes due to the reduction of the scale of the multi co-occurrence network analysis system,that is,the number of documents and feature words in the subspace.It makes the structure of the multi co-occurrence visualization system clearer,increases the readability of the data,highlights the data value,and effectively improves the multi co-occurrence visualization effect.To a certain extent,this study can promote the in-depth research on knowledge mining of multiple combinations of literature constituent elements,and then improve the quality of empirical research on literature metrology in different fields.
-
[JP, LIU Bin, MEI Wei, XU Yunfeng, GU Lidong, YU Pengshuai, SHI Yu, WEI Xifeng
2022,43(2):194-203, DOI: 10.7535/hbkd.2022yx02009
Abstract:
Overlapping community discovery is an important basic work in complex network mining.It can be applied to the data analysis of social networks,communication networks,protein interaction networks,metabolic path networks,transportation networks and other networks,so as to serve the fields of intelligent transportation,infectious disease prevention and control,public opinion analysis,new drug development and human resource management.The traditional stand-alone computing architecture has been difficult to meet the analysis and computing requirements of various large-scale complex networks.Researchers in the field of artificial intelligence propose to apply community discovery to the field of network representation learning to enrich the characteristics of nodes and edges in the network.However,the traditional overlapping community discovery algorithm fails to consider the relevant requirements from the network representation learning task in its design,only focuses on the community division of nodes,and lacks consideration of the internal structure and external boundary of the community.For example,it does not involve the weight of nodes within the community and the attribution ranking belonging to multiple communities,so it cannot provide richer characteristic information of nodes and communities in the network,resulting in insufficient support for network representation learning tasks. Aiming at the problem that the traditional single machine overlapping community discovery algorithm is not suitable for large-scale complex network mining and cannot support the relevant requirements of network representation learning tasks,a distributed overlapping community discovery algorithm based on community forest model (DCFM algorithm) was proposed.Firstly,the network dataset was stored in the distributed file system,the data were divided into blocks,and the distributed computing framework was used to execute the CFM algorithm on each data block;then,the community consolidation was performed;Finally,the community division results were summarized,and the algorithm was run on the spark cluster by using the real DBLP dataset and was evaluated by F Value and running time.The results show that the f-means of DCFM algorithm is slightly inferior to that of CFM algorithm,but its operation time decreases linearly with the increase of nodes.While sacrificing a small part of f-means,DCFM algorithm has the ability to process large-scale network data;the number of split copies has a great impact on the calculation time,which can be found in com DBLP ungraph.Txt data set,CFM algorithm needs 192 min to process data,while DCFM algorithm needs about 91 min to divide the data into 6 parts,and only about 13 min after dividing into 100 parts.Therefore,on the big data platform,DCFM algorithm uses distributed computing backbone to divide and merge communities,which is a feasible large-scale complex network mining method.By dividing the network,it can greatly improve the speed of community division and the efficiency of community discovery.
-
GUO Lifeng, HAO Yanzhong, REN Yingke, PEI Juan
2022,43(2):204-210, DOI: 10.7535/hbkd.2022yx02010
Abstract:
In order to solve the instability of MAPBI3 in perovskite solar cells and improve the performance of the cells,TiO2 nanorod array was used as electron transport layer and Sb2S3:P3HT blend was used as modification layer of perovskite MAPbI3. Firstly,Sb2S3 nanospheres with appropriate size were prepared by solvothermal method,in which SbCl3 and Na2S2O3 were used as antimony and sulfur sources. Secondly,Sb2S3 and P3HT were mixed in chlorobenzene solution by ultrasonic dispersion method to obtain Sb2S3:P3HT blend,which was coated on TiO2 nanorod array deposited with MAPbI3 thin film to form FTO/TiO2NR/MAPbI3/Sb2S3:P3HT composite film,and Sb2S3:P3HT blend modified TiO2 nanorods array MAPbI3 solar cell was fabricated.Finally,the solar cell was characterized and tested with SEM,XRD,J-V curves and uv-vis absorption spectroscopy.The results show that the maximum power conversion efficiency (PCE) for the FTO/TiO2NR/MAPbI3/Sb2S3:P3HT/Spiro-OMeTAD/Ag solar cell is 14.73%.Compared with the PCE of TiO2 nanorod array MAPbI3 solar cell without Sb2S3:P3HT blend modification,the power conversion efficiency of the Sb2S3:P3HT blend modified solar cell was significantly improved.Therefore,Sb2S3:P3HT blend can efficiently avoid the instability of perovskite MAPbI3 oxidation,which provides a reference for improving the performance of TiO2 nanorod array MAPbI3 solar cell.
-
JU Yongjian, NI Wen, LI Ying, BA Haojing, ZHANG Siqi, LI Keqing
2022,43(2):211-220, DOI: 10.7535/hbkd.2022yx02011
Abstract:
In order to solve the problem of massive storage of refining slag and improve the strength of solid waste based cementitious materials with large amount of converter slag,the material composition of refining slag,converter slag,blast furnace slag and desulfurization gypsum was optimized in this paper.Firstly,the effects of refining slag,converter slag,blast furnace slag and desulfurization gypsum on the compressive strength of cementitious materials were investigated by orthogonal experiment,and the regression analysis was carried out.Then,a nonlinear regression model was established to optimize the mix proportion of cementitious materials.Finally,the synergistic mechanism of refining slag,converter slag,blast furnace slag and desulfurization gypsum was analyzed by XRD,SEM and TG-DSC.The results show that when the content of converter slag in group Ⅰ is greater than 40%,the compressive strength of the experimental mortar is up to 39 MPa,and there is no significant difference between the predicted value and the experimental value,which verifies the reliability of the nonlinear regression model.The early hydration of the refining slag produced C2AH8,which participated in the synergistic effect of the four element system.The hydration products of all ages were mainly ettringite and C-S-H gel.Synergistic hydration promoted the formation of ettringite and C-S-H gel and enhanced the strength of hardened specimens.The results provide theoretical basis and data support for refining slag utilization.
Volume 43,2022 Issue 2
Special Column: National Young Scholar/Local Science Foundation
Mechanical, Electronics and Information Science
Civil and Architectural Engineering
Special Column: Data Analysis and Calculation
Special Column: Chemistry and Chemical Industry
-
Blend of P3HT and Spiro-OMeTAD as photoactive layer and hole transport layer in Sb2S3 nanopartical sensitized TiO2 nanorod array hybrid solar cell
Abstract:
In order to reduce the charge recombination and improve the performance of hybrid solar cells, the mixture of P3HT and Spiro-OMeTAD is used as the photoactive layer and hole-transport layer, then spin it onto TiO2 nanorod/Sb2S3 nanoparticles composite film. By means of SEM, XRD, UV visible absorption spectrum, steady-state fluorescence spectrum and J-V curve , the microstructure, photovoltaic performance of the hybrid solar cell are characterized and tested. The results show that the power conversion efficiency of the hybrid solar cell with FTO / TiO2NR/ Sb2S3 / P3HT:Spiro-OMeTAD (15mg/1mL) / Ag structure is 4.57%.
- 1
-
Recent progress on nonprecious metal catalysis in cathode hydrogen generation by seawater electrocatalysis
Abstract:
Due to its high energy density, green and sustainable advantages, hydrogen energy is considered to be the ideal energy for human society. The abundant seawater resources make seawater electrolysis for hydrogen production become the strategic direction of hydrogen energy industry in the future. The activity and stability of cathode hydrogen evolution catalyst are very important for the development of hydrogen production from seawater electrolysis. The precious metal Pt-based electrocatalyst have excellent catalytic performance for hydrogen evolution, the high price and limited resources limit its large-scale application. In recent years, a large number of researchers have introduced other non-noble metals or non-metallic atoms into the non-noble metals to adjust the d-band center and the free energy of hydrogen adsorption, to improve the catalytic activity for cathode hydrogen evolution reaction. The research progress on non-noble metal phosphides, nitrides, oxides/hydroxides, carbides, chalcogenides, non-noble metal single atom, alloys and hybrid catalysts as cathodic catalysts for seawater electrolysis was reviewed. Finally, large-scale seawater electrolysis for hydrogen production in the future was discussed. Combine electronic engineering, defects engineering, interface engineering and nano structure strategy for modulating electron structure, increasing active sites, enhancing the electrocatalytic activity and stability with advanced in situ characterization techniques and theoretical calculation for delving into the HER reaction mechanism and corrosion resistance mechanism in seawater, develop high-efficient, stable and easy non-noble metal catalysts for promoting hydrogen generation by seawater electrocatalysis.
- 1
-
The Electro-Hydraulic Control System of Large Caliber Pipeline Bender Based on PLC
LIU Wenxue, ZHAO Shaopeng, WANG Leigang
Abstract:
The electro-hydraulic control system based on PLC as the control core is proposed to improve the large caliber pipeline bender degree of automation and reduce labor intensity. In this paper, systematic composition,SworkingSprinciple, hydraulic system and PLC control process of the large caliber pipeline bender is analyzed and illustrated. The completion of automatic hydraulic control system for it realizes the high precision and high efficiency goals.
- 1
-
Effect of mechanical vibration on segregation structure and hardness of ZL205A alloy
贾丽敏, ZHANG Yaqing, Tan Jianbo, Liu Xiaoli, Zhang Shuangjie
Abstract:
The electromagnetic vibration table is used as the vibration source, and the effects of vibration frequency, amplitude and time on the segregation structures and mechanical properties of ZL205A alloy cast in sand mold were studied. The results show that with the increase of vibration frequency from 25 Hz to 55 Hz, the proportion of segregation structures decreases firstly and then increases. When the vibration amplitude increases from 1mm to 4mm, the proportion of segregation structures decreases gradually and tends to be stable, and with the increase of vibration time from 30 seconds to 75 seconds, the proportion of segregation structures increases gradually and tends to be stable. The results of hardness analysis show that the hardness decreases firstly and then increases with the increase of amplitude and frequency, and the hardness increases firstly and then decreases with the increase of vibration time. Among the above vibration parameters, the vibration frequency has the most significant effect on the segregation structures and hardness of the alloy, the second is time, and the last is amplitude. Through the research and analysis, the vibration parameters corresponding to the minimum segregation and the maximum hardness can be determined respectively.
- 1
-
Synthesis of Suvorexant
Abstract:
In order to explore the synthetic route of Suvorexant, clarify the physicochemical properties and spectral data of intermediates, lay the foundation for its industrial process, the synthetic method of Suvorexant is studied. The target compound is synthesized from 2-amino-5-methylbenzoic acid, followed by diazotization reaction, iodination reaction, Ullmann reaction, amidation reaction, deprotection reaction, nucleophilic substitution reaction. By optimizing the synthesis parameters, Suvorexant and intermediates can be directly obtained by using recrystallization method instead of column chromatography purification. The results show as follows: Hydrochloric acid aqueous solution is used as the solvent in the diazotization reaction and the iodination reaction, n (2-amino-5-methylbenzoic acid): n (sodium nitrite): n (potassium iodide) = 1: 1.2: 1.4, the yield is 92.31%; N, N-dimethylformamide is used as the solvent in the Ullmann reaction, n (compound 2): n (2H-1,2,3-triazole): n (copper iodide) = 1: 2: 0.05, the yield is 63.47%; Acetonitrile is used as the solvent in the deprotection reaction, n (compound 5): n (p-toluenesulfonic acid) = 1: 1.2, the yield is 93.02%; the total yield of the route is 47.99% after optimization, and the purity is 99.89%. The structure of the target compound is confirmed by 1H-NMR and 13C-NMR. The optimized route has advantage of mild reaction conditions, simple process and workup operation, and is suitable for industrial production.
- 1
-
Influence of pouring method on properties of WCp/Fe
Abstract:
To find a more suitable wear-resistant material forming method for current industrial applications, WCp/Fe monolithic composites were prepared by the lost foam casting process. The effects of casting method on the hardness and wear resistance of WCp/Fe composites were studied. The results show that after adding different particle sizes of WC particles, the three casting methods of top casting, gap casting, and bottom casting all significantly improve the hardness and wear resistance of the WC/Fe composite test blocks. Under the same casting method, with the decrease of WC particle size, the hardness and wear resistance of the test blocks gradually increase. Because the filling process of gap casting is relatively stable, the hardness and wear resistance of the test blocks are higher than the top and bottom casting methods. With the decrease of WC particle size, the hardness and wear resistance increase. When the WC particle size is 2 500 mesh, the hardness reaches HRC 50, which is 2.21 times higher than the wear resistance of the base material.
- 1
-
Modification of Nickel-Rich Ternary Layered Transition Metal Oxides Positive Materials
Abstract:
Nickel-rich ternary layered transition metal oxide anode materials have attracted extensive attention because of their high specific capacity, low price and environmental friendliness. However, its further application was hindered by its structural instability, fast capacity degradation in high temperature during the cycling. This is caused by Li/Ni mixing, phase transition reaction, gas generation, microcrack, transition metal dissolution and surface structure change. Focusing on the optimization research of nickel-rich ternary layered transition metal oxide cathode materials, the optimization methods including synthesis of surface coating materials, preparation of element-doped materials, preparation of core-shell structural materials, and synthesis of concentration gradient materials. The future development is prospected. The optimization of the cathode material provides a direction for the development of high energy density lithium-ion batteries
- 1
-
Anisotropy of B+F Dual-phase X80 Pipeline Steel under Slow Strain Tension in Simulated Seawater
Abstract:
Anisotropy of dual-phase pipeline steel is an important factor affecting the safe service of pipeline steel. In this paper, the slow strain tension and polarization behaviors in simulated seawater of hot rolled ferrite + bainite dual-phase X80 pipeline steel at different angles (0, 45 and 90°) with rolling direction were studied. The microstructures, tensile curves, scanning electron microscopy and polarization curves were analyzed. The results show that X80 pipeline steel is composed of polygonal ferrite and lath bainite, the content ratio of which is about 1:1. The yield strength of X80 pipeline steel with different rolling direction in simulated seawater environment are decreased significantly, which indicates that X80 pipeline steel is obviously corroded under stress. For the dual-phase pipeline steel parallel to the rolling direction (0°), the stress-strain curve presents dome shape. The yield strength and tensile strength are the highest, the yield strength ratio is 0.81, yet the ductility is relatively low. Dual-phase pipeline steel perpendicular to the rolling direction (90°) has lower strength, smallest fracture radiation area and the best ductility. However its corrosion resistance to seawater is the worst. The self-corrosion potential of dual-phase pipeline steel at 45° with rolling direction in simulated seawater is the most positive showing that the corrosion resistance is best.
- 1
-
Single machine scheduling with state maintenance strategy and step-deteriorating jobs
Abstract:
In order to achieve low-cost production of customized components, production scheduling needs to analyze the reliability and stability of equipment on the basis of processing efficiency and quality for integrating appropriate equipment maintenance strategy. For machining, the actual process also needs to consider the deteriorating effect brought by cutters’ wear. In order to solve the single machine scheduling problem with state-strategy maintenance and step-deteriorating jobs, this paper analyzes continuous fault detection and discrete fault detection, and formulates the single machine scheduling model with minimization of tardiness and maintenance costs when considering piecewise linear deterioration and maintenance unavailable time windows. Through the normalization of decision-making conditions, the advantages and disadvantages of maintenance strategies are discussed. Based on single-factor and two-factor tuning parameter analysis, the impact of related parameter changes on scheduling optimization is analyzed. The computational results show that discrete fault detection easily causes over-maintenance or under-maintenance. Once adopting normalization in the two strategies better results can be obtained, but cannot offset the penalty time of deterioration. In that situation, the target cost is not always the smallest.
- 1
-
Effect of the number of SiO2 film coating layers on the high temperature oxidation resistance of 304 stainless steel
Abstract:
In order to improve the oxidation resistance of 304 stainless steel, SiO2 thin films were prepared on the stainless steel surface by sol–gel method using tetraethyl orthosilicate (TEOS) as raw material. The effect of coating number on the high-temperature oxidation resistance of stainless steel at 900℃ was studied. X-ray diffractometer (XRD), oxidation kinetics, and scanning electron microscope (SEM) analysis results show that the SiO2 film effectively reduces the oxygen partial pressure at the interface between the substrate and the film, and promotes the selective oxidation of the stainless steel surface to produce Cr2O3 and NiCr2O4 with good high temperature resistance. Furthermore, the high temperature oxidation resistance of stainless steel is significantly improved. The sample coated with three layers of SiO2 film has the best high temperature oxidation resistance. Too many coating layers increase the internal stress of the film, which will cause cracks and peeling of the film to reduce the high temperature oxidation resistance of stainless steel.
- 1
-
Study on preparation and properties of pH-sensitive hydrogel loaded metformin hydrochloride
LIU Zhaoxia, ZHANG Meimei, ZHANG Dongmei
Abstract:
Objective To prepare pH-sensitive hydrogel loaded metformin hydrochloride and investigate its pH sensitivity and release behavior. Methods The formulation and process of pH-sensitive hydrogel loaded metformin hydrochloride were optimized with the simple factor investigation and the orthogonal experimental design. The morphology was characterized by SEM. The entrapment efficiency and drug-loaded amount were determined by UV. Meanwhile, the dissolution rate of the prepared hydrogel was determined, and pH-sensitive behaviour in different pH medium was investigated.Results The optimized prescription was as follows:chitosan and sodium alginate with a total concentration of 2%(w/v),chitosan:sodium alginate=1:1(g/g),drug:sodium alginate=2:5,3.5% CaCl2(w/v). In vitro release rate showed that the release was less than 4% in artificial gastric juice within 6h,and 99.3% in artificial intestinal juice within 6h.Conclusion The prescription and the preparation process are stable and reliable.The hydrogel had obvious pH sensitivity.
- 1
-
A gesture recognition algorithm based on improved yolov3
Abstract:
Aiming at the problems of low recognition accuracy and easy to be affected by illumination conditions in gesture recognition based on yolov3 algorithm, a gesture recognition algorithm based on improved yolov3 is proposed. Firstly, a smaller detection scale is added to the original three detection scales to improve the detection ability of small targets. Secondly, the mean square error loss was replaced by loss to improve the accuracy of prediction frame and regression speed. At the same time, the adaptive balance parameter and focus parameter are used to improve the focal loss function and add it to the total loss function to alleviate the imbalance problem of training samples. The experimental results show that the map index reaches 90.38%, which is 6.62% higher than that before the improvement, and FPS is improved nearly twice.
- 1
-
Process analysis and simulation of flat forging and forming steel tie rod U-shaped head preforms with super large height-diameter ratio bars
LU Suling, YAN Huajun, HU Xilei, WANG Tonghui, WANG Hao
Abstract:
Traditional U-shaped steel tie rods have disadvantages such as backward production technology, long processing cycle and low material utilization. Based on this, an integrated steel tie rod forming technology is proposed. In the integrated U-shaped steel tie rod forming technology, the U-shaped head is formed by a back extrusion process, and the blank used is called a preform. The research object of this paper is the forming of preforms. The forming process is the problem of upsetting forming with large height-diameter ratio, which is also a forming difficulty. Aiming at the preform of 35 steel tie rod U-shaped head, a three-pass heating upsetting method was proposed to prepare the preform. Using different process parameters, the DEFORM software was used to numerically simulate the forming process of the preform prepared by the three-pass upsetting method. The temperature field, stress field, load and metal streamline distribution were analyzed, and the hot forming process parameters with better forming effect were obtained, and the feasibility of forming was verified through experiments.
- 1
-
The effect of Al on the microstructure and high temperature oxidation performance of Cu-20Ni-19Fe Alloy
Liang zhimin, Wang Liwei, Peng Zhenzhen, Wang Dianlong
Abstract:
In this paper, Cu-20Ni-19Fe-xAl (x=0wt%, 6wt%, 8wt%, 10wt%) alloys with different contents of Al were prepared by vacuum smelting. The effect of Al on the microstructure and high temperature oxidation performance of Cu-20Ni-19Fe alloy were studied. The high-temperature oxidation experiments were carried out at 850℃, 1atm oxygen partial pressure for 100h. The results show that the as-cast Cu-20Ni-19Fe alloy is composed of Cu-rich a phase and Ni-Fe rich dendritic phase. Al was dissolved in the Cu-20Ni-19Fe alloy matrix with 6wt% content of Al added. The needle-like or blocky NiAl phase was formed in the microstructure of Cu-20Ni-19Fe alloy with 8wt% and 10wt% Al added. The content of NiAl phase increased with the increasing addition of Al. The oxidation kinetics of Cu-20Ni-19Fe alloy under 850℃, 1atm oxygen partial pressure follow the straight line. After the addition of Al, the oxidation kinetic curve of Cu-20Ni-19Fe alloy follow an exponential law. The oxidation rate index of the Cu-20Ni-19Fe-xAl alloy was much smaller with the more content of Al. The high-temperature oxidation resistance of Cu-20Ni-19Fe alloy was greatly improved by the addition of Al. This can provide the Cu-20Ni-19Fe alloy as an alternative anode material for aluminum electrolysis.
- 1
-
Electrodeposition of Ni nanowire arrays and their magnetic properties
Abstract:
Anodic alumina (AAO) templates with different pore sizes were prepared by secondary anodic oxidation method, and then Ni nanowire arrays were grown in AAO templates with different pore sizes by template-assisted electrodeposition method.The morphology, microstructure and composition of the prepared Ni nanowire arrays were characterized by SEM, TEM, XRD and EDS techniques. The magnetic properties of Ni nanowires were investigated by physical property measurement system (PPMS).The results show that the growth mechanism of Ni nanowires is the interaction between the reduction of positive half period Ni2+ by alternating current and the dissolution of negative half period Ni atoms. Ni nanowires have magnetic anisotropy, and with the increase of the diameter, the easy magnetization direction of Ni nanowires gradually changes from parallel to the axis of the nanowire to perpendicular to the axis of the nanowire. The change of easy magnetization direction is caused by the change of the effective anisotropic field and the magnetic domain structure with the diameter of the nanowire.
- 1
-
Analysis on water damage mechanism and influencing factors of embankment slope under rainfall
Abstract:
Rainfall is one of the most important factors to induce landslides. The erosion and infiltration of rainwater on the slope during rainfall will significantly reduce its structural stability, which will easily lead to slope failure. In this study, the main factors and influence rules of subgrade slope water damage are found out by combining with slope model test and GeoStudio (slope / W and seep / W coupling) program in order to simulate the effect of rainfall on subgrade slope under the specific soil quality, compaction degree and erosion infiltration time control conditions. The results show that: in the process of rainfall, the external structure of the slope is damaged due to the erosion of the slope surface by rainwater, while the internal structure of the slope is reduced due to the infiltration of rainwater, and both of them act simultaneously from the outside to the inside, resulting in the overall failure of the slope; With the compactness of the two kinds of soil slopes increased from 85% to 95%, the erosion volume of sandy soil slope decreased by 46.18%, and the internal safety factor of the slope increased by 13.74%, while the erosion volume of cohesive soil slope decreased by 33.7%, and the safety factor increased by 10.21%; With the increase of rainfall time, the scour depth of cohesive soil slope tends to be stable, while that of sandy soil slope tends to increase. The overall safety factors of cohesive soil slope and sandy soil slope decrease by 26.32% and 32.87% respectively; Under the same control conditions, the water damage resistance and overall stability of cohesive soil slope are better than that of sandy soil slope.
- 1
-
Evaluation of glass-forming ability for AlNiZr alloys
Abstract:
Al-based amorphous alloys have large potentiality in marine equipment protection due to their high strength-to-mass ratio and great corrosion and wear resistance. However, Al-based alloys are prone to precipitate α-Al crystals during the formation process, which could greatly weaken the glass-forming ability. The glass-forming ability was hard to evaluate because of the low glass-forming ability for Al-based alloys. In order to overcome the difficulty, a simple method to evaluate glass formation ability was supported: the first, ribbons were prepared by means of a single-roll ribbon spinning method under the same conditions; the second, amorphous contents of ribbons were calculated by fitting the XRD patterns; the higher the amorphous content is, the higher the glass-forming ability is. The influence of Ni and Zr on the glass-forming ability of AlNiZr alloys was presented based on the amorphous contents of ribbons with different compositions which were Al100-x-yNixZry (x=5, 10 and 15; y=3, 6 and 9), respectively. The result showed that as the content of Ni increased, glass forms Capacity increased; with the increase of Zr content, glass-forming ability decreased. Subsequently, it was determined that the Zr content was 3 at.%, and the Ni content was further increased to 20 at.% and 25 at.%. It was found that the glass-forming ability of the alloy was reduced. Finally, the optimized alloy composition was considered as Al82Ni15Zr3.
- 1
-
A general variable neighborhood search for the multi-AGV scheduling problem with sorting operations
Abstract:
Lots of packages are sorted quickly by using multiple automatic guided vehicles (AGVs) in the logistics sorting centers. With the consideration of power consumption and charging demand of the AGVs, how to determine the assignment of transferring packages to AGVs and the sequence of sorting tasks for each AGV is the key to the sorting operation. In order to solve the large-sized problem instances, this paper proposes a general variable neighborhood search (GVNS) algorithm to minimize the sorting operation makespan. The GVNS algorithm adopts traversal insertion heuristic to generate the initial solution, and uses ten neighborhood operator to obtain the neighbor solutions. Different scaled test instances are used to analyze the performance of the proposed GVNS. Compared with mixed integer programming model and constraint programming model, the GVNS performs better, in terms of solution time and solution quality. Moreover, the impacts of the sorting efficiency are also analyzed when considering the AGVs with different charging speed and different available quantity. This work is helpful to improve the efficiency of logistics sorting, enrich the research content of multi-AGV scheduling.
- 1
-
Analysis of droplet transfer of 30CrMnSiA metal powder-cored welding wire and preliminary study on arc additive
Abstract:
Metal powder-cored flux-cored wire benefits from simple powder configuration and high transition coefficient of alloying elements. It is considered to be a material that can replace solid wires. Wire and arc additive manufacturing technology (WAAM) is a technology for rapid prototyping of metal parts. In this study high-strength steel powder-cored flux-cored wire has been adopted, high-speed camera and electrical signal system were used to analyze the characteristic of droplet transfer and arc stability of high-strength steel powder-cored flux-cored wire. Moreover, the formation, microstructure and mechanical properties of WAAM high-strength steel parts under the pulse process were analyzed deeply. The feasibility of high-strength steel flux-cored welding wire was preliminarily explored. The experimental results showed that the droplet transfer type of high-strength steel powder-cored flux-cored wire is a non-axial droplet short circuit transition with multiple pulses and one drop, and the forming quality of the multilayer single-pass deposit is good. The transverse and longitudinal mechanical properties of the sedimentary layer are different. The tensile strength, yield strength and elongation along the transverse are better than longitudinal ones. The SEM observation of the tensile fracture shows that there are a large number of dimples in both of the transverse and longitudinal fractures of the deposited parts, which suggest that the fracture mode are ductile fracture.
- 1
-
Short Term Traffic Flow Prediction Based on CEEMD-GRU Combination Model
ZHANG Weijian, HU Yanran, HUANG He
Abstract:
In order to improve the accuracy of short-term traffic flow prediction, a short-term traffic flow prediction method based on the combined model of complementary ensemble empirical mode decomposition and gated recurrent unit is proposed. Firstly, the unstable original traffic flow time series data are decomposed into relatively stable multiple modal components by complementary ensemble empirical mode decomposition algorithm; Then, a GRU model is established for each decomposed modal component sequence for one-step prediction. Finally, the predicted value of each component is superimposed to obtain the final prediction result. Using the measured traffic flow data of Shanghai to verify and analyze, the experimental results show that CEEMD-GRU combination model is superior to GRU neural network model, EMD-GRU combination model and EEMD-GRU combination model, and the average prediction accuracy is improved by 33.4%, 25.6% and 18.3% respectively.
- 1
-
Preparation of Albendazole Tablets
Abstract:
OJECTIVE To explore the prescription and preparation process of albendazole tablets with high drug content. METHODS (1)The effect of adding surfactants or preparing inclusion compounds on dissolution was investigated to increase the solubility of albendazole. (2)Adhesives, disintegrants, and solubilizers were screened by single factor experiment with compressibility,hardness, disintegrating time,and dissolution as indicators to optimize the formulation and preparation process of albendazole tablets.(3) Three batches of albendazole tablets prepared by the optimal prescription and process were examined by the statutory standard. The content and dissolution of albendazole were measured using UV-spectrophotometry.RESULTS (1)Surfactants can be added to assist dissolution of albendazole.(2)The albendazole tablets were prepared with wet granulation. The optimal prescription:Albendazole was 8.3%,PVPP was 16%(with an internal and external ratio of 1:1), SDS was 3%, Tween80 was 2%，HPMC was 3.2%.(3)Three batches of tablets all met the quality requirements. The accumulated dissolution of albendazole tablets within45 minutes was more than 65%.CONCLUSION The prescription and the preparation process of albendazole tablets prepared are stable and reliable.The quality is good in vitro and meets the experimental expectation.
- 1
-
Effect of Heat input on Microstructure and toughness of coarse Grain Zone of X70
JIA Shujun, YANG Hao, LIANG Xiaokai, ZHANG Liang, FAN Yingning
Abstract:
In order to study the effect of different thermal cycles on the microstructure and toughness of welding coarse grain heat affected zone (CGHAZ) of deep-sea X70 pipeline steel, the CGHAZ of deep-sea X70 pipeline steel under different heat input (HI) of 10~60kJ/cm was simulated by Gleeble-3800 thermal simulator, and the microstructure and toughness of CGHAZ were characterized by optical microscope, scanning electron microscope and Charpy impact test. The experimental results show that the sample is composed of granular bainite (GB), bainite ferrite (BF) and Mmura A component (MmurA component). When HI increases, the proportion of BF decreases, the proportion of GB increases, the Mmura A component coarsening, the impact absorption energy increases at first, and the excellent combination of BF and GB is obtained in 20kJ/cm. The fracture surface is ductile fracture and the impact absorption energy can reach 173.8J. When HI is greater than 20kJ/cm, the fracture is dissociation fracture, and the impact absorption energy decreases sharply, and the lowest is 18.8J.
- 1
-
Numerical simulation of scrap preheating in EAF steelmaking
lusuling, wanggongliang, huaqinian, liuzhiwen
Abstract:
In order to make full use of the waste heat of electric arc furnace flue gas to preheat scrap, a three-dimensional unsteady random distribution local model of scrap preheating process was established on the platform of computational fluid dynamics software FLUENT. The temperature distribution law of different kinds of scrap in the shaft was explored by numerical simulation. The simulation results show that the preheating temperature of scrap increases obviously with the increase of preheating time, but the temperature rise rate decreases gradually; Under the same preheating conditions, the average temperature of light and thin scrap is about 1600 K, medium and heavy scrap is about 1000 K and heavy scrap is about 700 K; Increasing the specific surface area can improve the preheating temperature of various types of scrap to a certain extent. Considering the impact of scrap melting on smelting quality during preheating, the specific surface area of bottom scrap should be controlled below 1.5 m2 / m3. At the same time, in order to improve the preheating effect of heavy scrap, the specific surface area should be controlled above 0.25 m2 / m3; High temperature flue gas will preferentially pass through the area with good porosity, and the flue gas velocity in the densely stacked plate scrap area is small, so as to reduce its preheating temperature.
- 1
-
Detection of Power Frequency Magnetic Field Disturbance Signal of Underwater Target Based on Hybrid Neural Network and Attention Mechanism
Abstract:
In order to solve the problems of fast attenuation, strong interference and ambiguous disturbance characteristics of magnetic signals in the magnetic field proximity detection of underwater targets, a time series disturbance signal detection method for underwater targets with industrial frequency magnetic field based on hybrid neural network and attention mechanism (att-CNN-GRU) is presented. This method combines CNN, GRU neural network and Attention mechanism to fit the signal, and constructs a classification neural network to classify and identify the target signal. The prediction and detection performance of this method is compared with that of CNN-LSTM model without attention mechanism and single CNN and LSTM network model. The measured results show that the fitting effect reduces the error by 36.24%, 14.44%, 4.878% and the target detection accuracy reaches 83.3% compared with the above traditional methods. This method can be widely used in underwater target detection as an auxiliary detection method.
- 1
-
Study on creep characteristics of surrounding rockof slate tunnel considering temperature effect
Abstract:
The deformation of surrounding rock of slate tunnel after excavation is fast, large and lasting for a long time, which affects the safety of tunnel construction and the long-term stability of later operation. Taking a highway tunnel under construction in Southwest China as the research background, the field monitoring test of surrounding rock displacement and temperature for 0~120 days is carried out. The test results show that: (1)The tunnel has strong environmental sensitivity, the surrounding rock stress is released after tunnel excavation, and the surrounding rock is in tension state and creep accumulation;(2)The displacement of surrounding rock shows a power-law accumulation law. The accumulation rate is fast from 0 to 60 days, and gradually slows down after 60 days. At 120 days, the displacement time history curve tends to converge, with the maximum displacement of -9.93 mm and the minimum displacement of -0.05 mm;(3)The monitoring temperature of surrounding rock has an inverse proportional attenuation relationship with time, and the temperature gradually decreases with time. After 120 days, the final temperature will be basically consistent with the outdoor temperature. Based on the law of temperature change, the improved Harris temperature time relationship expression is established and embedded into the head creep model, so as to obtain a new improved head creep constitutive model considering temperature effect. The feasibility and rationality of the model are verified, and the creep deformation law of surrounding rock after 500 days is predicted by using the model. The research results provide a certain reference for the study of creep characteristics of tunnel surrounding rock and tunnel construction and operation.
- 1
-
Research on performance of 2024-T42 Aluminum Alloy Spot Welded Joints
Abstract:
In order to improve the performance of spot welded joints of 2024-T42 aluminum alloy, it was analyzed and compared with the mechanical properties, microstructure, hardness and fracture mode in RFSSW joint, resistance spot welded and riveting. Experiments showed that the best mechanical properties was RFSSW joint, the tensile shear property was 7.23kN, which could get 115.8% higher than riveting property and 37.6% higher than resistance spot welded joint; the pull-out property was 3.09kN, which could get 3.69% higher than riveting property and 137.7% higher than resistance spot welded joint; the hardness of RFSSW joint was higher than that of resistance spot welded joint, and the hardness of nugget zone was close to the base metal, as the hook defect was in the joint The lowest hardness was in notch and HAZ, nevertheless, the lowest hardness resistance spot welded joint was in equiaxed crystal zone in nugget zone, just only get 50% of the base metal, just as pores and crack defect were inside. On the basis of analysis of SEM, the fracture morphology in characterized were in ductile fracture and mixed fracture respectively in RFSSW and resistance spot weld joints. The analysis of the performance of the 2024-T42 aluminum alloy spot welding join could provide a theoretical and technical basis for the application of aluminum alloy structural spot welding.
- 1
-
A Multi-target Detection and Tracking Algorithm
Abstract:
This paper proposes a multi-target detection and tracking algorithm based on the YOLOv3 architecture to achieve target detection and core-related filtering algorithms to achieve target tracking. First, use the trained YOLOv3 network to obtain the location of the target in the video, and assign ID to each target; second, input multiple targets in parallel to the tracking module based on nuclear correlation filtering for target tracking; then, determine whether the start correction is satisfied If the conditions of the strategy are met, the results of the detection module are used to modify the results of the tracking module; finally, the tracking results are used to update the kernel correlation filter model. Through experimental analysis, the overall average success rate of the algorithm proposed in this paper has reached 81.2%, which verifies the effectiveness of the algorithm.
- 1
-
A robust GNSS interference suppression algorithm in high dynamic environment
张秀清, FAN Yunting, WANG Xiaojun
Abstract:
In order to solve the problem that the interference signal changes rapidly in the high dynamic environment and moves out of the null of the beam, which leads to the reduced performance of the anti-interference algorithm, a robust beamforming algorithm based on null broadening and deepening is proposed. The algorithm first set multiple virtual interference in the interference interval instead of a single interference, and then modified the covariance matrix by the covariance matrix forward and backward spatial smoothing technique. Simulation results show that the proposed algorithm can not only effectively widen and deepen the null in the direction of interference signal, but also make the array have good output signal to noise ratio, and still maintain strong robustness when the interference changes rapidly. The proposed algorithm has better performance than other algorithms so is more suitable for high dynamic environments.
- 1
-
Optimal Design of Vibration Reduction of Interior Radial Permanent Magnet Synchronous Motor for Vehicle
Abstract:
In order to reduce the electromagnetic vibration and noise caused by the radial electromagnetic force, the electromagnetic vibration and noise performance of a interior radial permanent magnet synchronous motor for a vehicle is studied by using the finite element analysis method of electromagnetic field, structure field and acoustic field coupling. An optimization measure based on the offset of the magnetic bridge structure. The position of the magnetic isolation bridge of the motor is shifted to the magnetic pole direction along the circumferential track of the outer diameter of the rotor, and the adjacent distance between the magnetic isolation bridge and the length of the isolation magnetic bridge are optimized. Calculate the motor radial magnetic density amplitude, output torque average value, and ripple torque content under each structural offset distance, comprehensively consider the motor vibration and noise level and motor performance to determine the offset distance, and establish the motor stator iron The 3D finite element model of the core to calculate its natural frequency. The results show that this optimization method can effectively reduce the electromagnetic vibration and noise of the motor, and will not have a large impact on the performance of the motor. It can provide a reference for the optimization design of vehicle permanent magnet synchronous motor to reduce vibration and noise.
- 1
-
An improved mapping method in PCSS communication and ranging composite system
Abstract:
In order to improve the communication rate of the communication and ranging composite system, the parallel combinatory spread spectrum(PCSS) technology is applied to the composite system, and the Gold sequence with good correlation characteristics is used as the spread spectrum sequence. To realize the complete data mapping and increases the transmittable data bits, an improved r_combinatory data-sequence mapping method is proposed. The proposed mapping method is used to implement the data spreading transmission at the transmitter, and an improved generalized cross-correlation algorithm is adopted to estimate the transmission tine delay and data despreading at the receiver, then the information transmission and distance measuring can be implemented at the same time. The simulation results show that the improved PCSS communication and ranging composite system realizes the uniqueness of mapping, improves the data mapping efficiency and the information transmission ability of the system, the improved generalized cross-correlation algorithm has better delay estimation performance under low signal-to-noise ratio (SNR), which makes the system accomplish ranging tasks and communication tasks more effectively.
- 1
-
Scale-adaptive correlation filter tracking algorithm fusing depth features and FHOG features
Abstract:
Aiming at the problem of the occlusion of the tracking target and the change of the target scale by the nuclear-related tracking filter algorithm in complex scenes, a correlation filter target tracking algorithm that combines depth features and scale adaptation is proposed. First, the deep residual network (ResNet) is used to extract the depth features of the tracked area in the image, and then the target area directional gradient histogram feature (FHOG) is extracted, and multiple response maps are obtained through the kernel correlation filter learning. Perform weighted fusion to obtain the tracking target position. Secondly, the scale filter is trained through the directional gradient histogram (FHOG) feature to realize the estimation of the target scale, so that the algorithm has a good adaptive ability to the change of the target scale. Finally, according to the peak fluctuation of the response graph, the model update strategy is improved and the re-detection mechanism is introduced to reduce the probability of model drift and improve the algorithm's ability to resist occlusion. Compare with other 6 target tracking algorithms in the standard data set OTB100. The experimental results show that the accuracy of the original KCF algorithm is improved by 29.3%, and the success rate is improved by 25.3%. The algorithm in this paper can have a higher tracking success rate and accuracy in the environment of illumination interference and occlusion.
- 1
-
Co-combustion kinetic and synergistic effects analysis of penicillin residue and coal
Abstract:
：Aiming at the problem that antibiotics residue can not be utilized in a short time，In this work, the combustion kinetics and synergistic effects of penicillin residue and its mixture with coal (denoted as 5~30% for the mass fraction bacterial residue) were investigated by using thermogravimetric analysis. The experiments were performed via a thermogravimetric simultaneous thermal analyzer at five heating rates (10, 15, 20, 25 and 30 ℃/min) with a changing temperature ranged from room temperature to 900℃. The combustion process of blends was systematically investigated, and the activation energy of the combustion process of the blends was calculated by Flynn-Wall-Ozawa(FWO) and Vyazovkin(V), the kinetic mechanism function was solved by the integral master graph method. The results showed that co-combustion of the blends mainly consisted of two processes which were the volatile matter combustion of bacterial residue and the combustion of coal fixed carbon, synergistic effects existed for all the blends. With the increase of the bacterial residue blending ratio, the activation energy of the blends present an increasing trend. While the bacterial residue blending ratio was 10%, the average activation energy of the blends was the lowest and the synergistic effects was the strongest, the activation energy calculated by the two methods were 139.63 kJ/mol (FWO) and 141.67 kJ/mol (V), respectively. The mechanism function was further solved by integrating master graph method, and the mechanism function of the first stage of combustion reaction was [-ln(1-α)]4, the reaction mechanism was “random nucleation and subsequent growth”, the mechanism function of the second stage was α2, and the reaction mechanism was “one-dimensional diffusion”. The results provide a preliminary theoretical basis for the co-operation disposal of penicillin residue and coal in cement kiln. The experimental results can effectively understand the combustion characteristics of antibiotics residue and coal, and provide theoretical reference for the co-processing of antibiotics residue.
- 1
-
Fixed Time Multi-constraint UAV Trajectory Planning Based on Particle Swarm Algorithm
Abstract:
Multi-constraint trajectory planning method for unmanned aerial vehicles（UAVs）has been widely used in military and civil field, and trajectory solving method is an effective way to improve the efficiency of mission completion. In previous studies, the particle swarm optimization algorithm, which regards the UAV as a particle for trajectory planning, ignores the flight time, angle and other parameters of the UAV, and only contains position information. Aiming at the problem of UAV trajectory planning with fixed time and multiple constraints, a trajectory planning method based on particle swarm optimization and UAV kinematic model is proposed. Firstly, considering that the optimization of each control variable will cost a lot of time, the flight time of UAV is discretized as a certain number of Chebyshev points, they are the moments that the control variables are optimized, and can reduce the computational burden. On this basis, the angular velocity is taken as control variable, the function of angular velocity solved by curve fitting, and the function of angular and position of UAV is obtained by integration. The results are substituted into the particle swarm optimization model and combined with the UAV kinematic model to optimize the solution. Then, the angular velocity, angle and position are calculated according to the allocated time. Finally, the simulation of UAV trajectory planning in complex environment is carried out, and different situations are listed for compare and verification. In order to verify the effectiveness of the proposed method, Monte-Carlo simulation is used. Simulation shows that the proposed method can accurately calculate the kinematic parameters, plan a smooth trajectory and successfully avoid the obstacles in the process of forward. Besides the dimension of solution and feasibility of trajectory planning are improved effectively.
- 1
-
A Comprehensive Survey on Target Tracking based on Siamese Network
Abstract:
In recent years, the target tracking algorithm based on Siamese network has attracted much attention because it can achieve a good balance between tracking accuracy and tracking efficiency. Through the intensive study of the literature of target tracking algorithm based on Siamese network, the existing target tracking algorithm based on Siamese network is comprehensively summarized. In this paper, Firstly, the author introduce the basic framework of target tracking based on Siamese network, and then analyze the advantages and disadvantages of shallow network and deep network, and focus on the application of optimized backbone network. Secondly, the target tracking algorithm of mainstream Siamese network based on visual attention mechanism and the algorithm with anchor and anchor-free is described in detail. The advantages and disadvantages of the algorithm as well as the target tracking performance are analyzed. Finally, the latest development and application of twin network target tracking algorithm are comprehensively analyzed. The future research focuses on the following aspects: 1) Explore the training of background information, realize the dissemination of background information in the scene, and make full use of background information to achieve target positioning.2) In the process of target tracking, the target feature information becomes richer and the target tracking box adaptive change. 3) From the global information transmission between frames to the target local information transmission research, to provide support for the accurate target positioning and tracking.
- 1
-
Adaptive finite-time control for quadrotor UAV with time-varying load based on disturbance observer
Abstract:
For the quadrotor unmanned aerial vehicle (UAV) system with time-varying load, the finite-time control strategy is studied in the presence of unknown external disturbances and unknown drag coefficients. Firstly, a complete mathematical model of quadrotor UAV through the Newton-Euler method is established. An adaptive trajectory tracking controller with unknown drag coefficient is designed by combining the adaptive parameter correction method of position loop with backstepping control to estimate load. Then, in order to improve the convergence rate and reduce the impact of the external disturbances, a finite-time sliding mode controller is proposed based on the disturbance observers. By using the Lyapunov stability theory, the position loop and the attitude loop are proved to be asymptotically stable and finite-time stable, respectively. Finally, the effectiveness and superiority of the proposed controller are validated by numerical simulations.
- 1
-
Development of Continuous Carbon Fiber Reinforced Composite Three-dimensional Printing Nozzle
Abstract:
The nozzle is a key component during the three-dimensional print process of continuous carbon fiber reinforced composite, and its Rationality structural design and precise control will also directly affect the continuity and stability of the three-dimensional printing process. Based on the characteristics that the nozzle will be lifting and jumping frequently during the forming process, a new three-dimensional print nozzle was developed which could realize controlled import, high efficiency melting and extrusion, and real-time clipping of the composite wire, and the structure and function of each component of the nozzle were analyzed in this paper. Based on the structural design of the nozzle, the control system for the nozzle clipping device was also designed. Finally, the melting extrusion and clipping test of pre-impregnated continuous carbon fiber reinforced composite wire were performed by using the developed three-dimensional print nozzle. As a result, the blade showed effective clipping for the composite wire at the end of the nozzle, and the clipping fracture was smooth, thus verified the reliability and practicality of the new developed three-dimensional printing nozzle.
- 1
-
Co-simulation and analysis of electro-magnetic-thermal of aviation carbon fiber composite board
Abstract:
Carbon fiber reinforced composites (CFRP) are widely used in aerospace and other fields. CFRP can realize rapid internal heating through electromagnetic induction. There are a lot of engineering applications in CFRP, such as curing, welding, deicing and so on. Firstly, the physical principle of eddy current heat is analyzed. Based on the design of carbon fiber composites with different lay numbers, the number of composite layers on the eddy current thermal effect is analyzed, and the influence of eddy current coil input power is studied according to the law of electromagnetic eddy heat generation. The electro-magnetic-thermal finite element model(FEM) is established. The electromagnetic eddy current field and temperature distribution in the induction heating process are studied by FEM Co-simulation. Finally, the results of FEM are verified by experiments. Results show: in the eddy current effect, the carbon fiber board can produce a closed-loop induced current, and the induced current is low in the middle and high around of the carbon fiber board. Under the fixed input voltage of 25V, the heating effect of single layer carbon fiber board is most significant, and the stable temperature is about 141.4 C. With the increase of input voltage, the eddy current thermal effect of double carbon fiber composite plate increases, and the thermal stabilizing time is increased synchronously. The present work provide an instruction for promoting the engineering application of eddy current heating in aviation carbon fiber composites.
- 1
-
Cogging torque reduction method of internal permanent magnet motor based on stator tooth shoulder chamfering
WANG Jing, YAN Shilong, YIN Hongbin, ZHOU Yingchao
Abstract:
In order to reduce the cogging torque of interior permanent magnet synchronous motor (PMSM) for electric vehicles, a method of stator tooth shoulder chamfering was proposed in this paper, the equivalent model of air gap length before and after the chamfer of stator tooth shoulder was established, and the effective air gap length distribution function was deduced, so as to analyze the mechanism of stator tooth shoulder chamfering reducing the low harmonic amplitude of air gap magnetic density and weakening the cogging torque. To explore the optimal shapes and sizes of the chamfer based on a PMSM with three phase 36-stator-slot/8-rotor-pole topology, the finite element method was purposely utilized for conducting optimization. The comparative analysis results show that the elliptic chamfer of stator tooth shoulder can effectively reduce the amplitude of air gap magnetic dense harmonic wave, improve the sinusoidal waveform of motor back EMF and weaken the cogging torque. The peak value of the cogging torque of the optimized motor is reduced by 77.2%, the amplitude of the 9th, 13th, 15th, 17th, 19th and 21st harmonics of the back EMF is significantly reduced, and the output quality of the motor is significantly improved.S
- 1
-
Prediction of stator temperature of hydro-generator based on magnetic-thermal coupling characteristics
li yong, chen bo, wang zongshou, LI Shichang, 李争
Abstract:
In today’s power system, the installed capacity of hydro-generators is increasing, resulting in an increase in its loss, which in turn leads to an increase in the temperature of hydro-generators and affects the performance of generators. In the temperature fault of hydro-generator, the stator part accounts for 38%, so the research on the stator is also increasingly important. Based on the hydro-generator of Zhanghewan Pumped Storage Power Station, this paper analyzes the electromagnetic field and stator loss of the hydro-generator under working conditions from the electromagnetic field theory, and then establishes its three-dimensional finite element model. The temperature field distribution of the stator of the hydro-generator is calculated by magneto-thermal coupling. Then the artificial fish swarm algorithm and BP neural network algorithm are combined to construct the temperature prediction model of stator winding and stator top, and the simulation results are compared with the measured data after monitoring and transformation. The results show that the optimization of BP neural network by artificial fish swarm algorithm(AFSA) improves the accuracy of the stator temperature prediction model, It provides a way of thinking for motor stator temperature fault analysis and monitoring determination.
- 1
-
Fault detection based on integrated kernel entropy component analysis algorithm
Abstract:
Aiming at the problem of kernel parameter selection in kernel entropy component analysis (KECA), an fault detection algorithm based on ensemble kernel entropy component analysis (EKECA) is proposed. Firstly, a series of kernel functions with different parameters are selected to project the nonlinear data into the kernel feature space, and the eigenvalues and eigenvectors that contribute a lot to Renyi entropy are selected to obtain the score matrix, and the entropy component analysis model of multiple subkernels is established; Then, the kernel matrix of the original data is projected onto the subspace formed by the principal axis of KPCA, and the statistics of each sub KECA model are calculated to obtain the detection results; Finally, the detection results of each KECA sub model are converted into probability by Bayesian decision, and the total probability of the detection results is calculated by ensemble learning method to get the statistics and judge whether it is beyond the control limit. The algorithm is applied to a numerical example and the TE process. Simulation results show that the algorithm can effectively improve the fault detection rate and reduce the false alarm rate compared with traditional EKPCA, KECA and other algorithms. This method provides a reference for the traditional KECA algorithm to solve the problem of selecting different fault kernel parameters.
- 1
-
An automated refactoring approach for asynchronous mechanism
Abstract:
As synchronization blocking will waste system resources and affect program performance in concurrent processing, an automatic refactoring approach on the asynchronous mechanism of CompletableFuture was proposed. Firstly, several static analyses by Wala static program analysis tool, such as visitor pattern analysis, alias analysis, and data flow analysis are used in this approach. The operation mode of shared variable data is determined, and then four asynchronous refactoring modes are set based on the asynchronous mechanism of CompletableFuture. Finally, the code is refactored according to different modes. An automatic tool AsynRef was implemented as the plugin by Eclipse JDT and four large-scale practical applications such as HSQLDB, Jenkins, JGroups, and SPECjbb2005 are automatically refactored by AsynRef. AsynRef is evaluated via the number of refactored locks, changed lines of code, accuracy, program performance after refactoring. The experimental results show that AsynRef can effectively complete the asynchronous refactoring of code and save time and effort compared with the traditional manual refactoring.
- 1
-
Research on Grid Frequency Self-adaptation Based on Harmonic Extraction Technology
Abstract:
Aiming at the problem of voltage distortion and frequency fluctuation caused by harmonic interference of the power grid, which affects the stable operation of the power grid, a frequency adaptive phase lock method is proposed. Based on the harmonic extraction circuit, a new second-order generalized integrator (NSOGI) phase-locked loop with the function of filtering out grid harmonics is designed. Using a frequency-locked loop (FLL) combined with a second-order generalized integrator (SOGI). FLL tracks the frequency of the input signal, and has a great deal of distortion and harmonics in the grid voltage. Good suppression, high frequency locking accuracy. The harmonic extraction circuit extracts and utilizes the harmonic current to avoid energy waste caused by direct filtering of harmonics. Compare the frequency deviation in the circuit before and after harmonic extraction with DSOGI-FLL, verify the harmonic extraction effect and phase-locking accuracy of the circuit, and verify the feasibility and correctness of this method through theoretical analysis and simulation.
- 1
-
Study on Character Recognition Algorithm for End Faces of Bundled Special Steel Bars
Abstract:
In order to realize the traceability of the whole process of special steel bar production information, the special steel bar production environment and shape characteristics are analyzed. The marking scheme based on double mark points is adopted for marking and the machine vision technology is used to realize the character recognition of the end face of the bundled special steel bars. First, Hough transform is used to segment the end image of the bundle of special steel bars into single ones. Secondly, an image enhancement algorithm based on wavelet transform is used to enhance the end image of a single special steel bar. Then, the MSER algorithm and the edge detection algorithm are combined to complete the detection of the character area of a single special steel bar, and the character segmentation is completed based on the projection method. Finally, the end face character recognition of each special steel bar is completed by creating and training an SVM classifier, and the end face character recognition results of the bundle of special steel bars are output and saved. The special steel bar production environment is simulated in the laboratory and the character recognition algorithm is tested. The results show that the algorithm in this paper can meet the character recognition requirements in the production process of bundled special steel bars, and lay the foundation for the realization of the traceability goal of the whole process of special steel bar production information.
- 1
-
Damage evolution and constitutive model of granite under microwave irradiation
Abstract:
In order to further analyze the mechanism of microwave rock breaking, the damage evolution law and constitutive behavior of hard rock under microwave irradiation are studied, firstly, the elastic micro element hypothesis of rock is carried out. Combined with the micro element strength criterion and three parameter Weibull distribution, the damage evolution equation, constitutive model and parameter determination formula of hard rock after microwave irradiation are derived, Then, the model is verified by ultrasonic testing and uniaxial compression test results of granite irradiated with different microwave power. The results show that the theoretical curve of the model is in good agreement with the experimental curve, which shows that the model can reflect the stress-strain process of granite fracture, the physical significance of the parameters of the model and the influence law on the model are clear, and there is a certain deviation in the fitting after the peak, but the model can still basically reflect the weakening law of rock after microwave irradiation. The research results can provide some reference value for the related calculation and numerical simulation of microwave irradiated rock.
- 1
-
Non-intrusive load identification based on CF-MF-SE joint feature
安国庆, Liang Yufei, Jiang Ziyao, Li Zheng, 安琪, Li Zheng, Wang Qiang, Bai Jiacheng
Abstract:
In order to solve the problems of the current non-intrusive load identification, such as too long model training time and low identification accuracy of electrical appliances with similar load characteristics, a non-intrusive load identification method based on CF-MF-SE joint feature was proposed. Based on the steady-state current signal, the method extracted the peak factor to represent the distortion degree of the waveform, the margin factor to represent the stability degree of the signal, the spectral entropy to represent the complexity degree of the spectrum structure, and combined with PSO-SVM to realize load identification. Experimental results show that this method can reduce the training time, improve the recognition accuracy and efficiency, which solve the problem that the electrical current waveform is too similar to identify successfully. This method introduces vibration signal characteristics as load characteristics into the field of load identification, which provides a new idea for feature selection of non-invasive load identification technology. As a key feature sensitive to load, spectral entropy can significantly improve the identification rate when combined with other features, which provides guidance for the flexible selection of load characteristics in practical application.
- 1
-
A Review of Research on Tip-Timing and Tip Clearance Measurement Technology
Abstract:
Turbine blades will fail due to fatigue fracture caused by vibration at high-speed rotation, resulting in damage to rotating machinery. Blade tip-timing measurement technology is the most promising non-contact blade vibration real-time monitoring method. At the same time, the change of the blade tip clearance is closely related to the vibration state of the blade. Therefore, real-time monitoring of blade vibration state and blade tip clearance is the key to ensure the safe, stable, and reliable operation of rotating machinery. The principles of blade tip-timing and blade tip clearance measurement technology and the research results in domestic and international are summarized are systematically reviewed. It is clarified that the current research is still in the incomplete maturity stage of simulation and experimental measurement, and the prospects of their development are provided. It is pointed out that future research on blade tip-timing and tip clearance measurement technology can be carried out in the following aspects. 1) Combining blade tip-timing and tip clearance measurement technology to achieve blade vibration measurement; 2) Conducting asynchronous blade vibration measurement without the once per revolution (OPR) sensor method and putting it into engineering application; 3) Developing an effective dynamic calibration scheme to measure the relationship between the output voltage and the blade tip clearance when the blade is rotating; 4) Developing the sensors capable of high-precision and long-period measurements in harsh environments.
- 1
-
Influence of composite slab on seismic performance of prefabricated steel frame joints
Abstract:
To solve the problems of complex structure and unclear force transfer mechanism of joint area in prefabricated steel frame, a bolted end-plate joint considering composite slab was proposed. Two groups of prefabricated beam-column joints with end-plate connection were designed and manufactured, and the low-cyclic loading test was carried out. The numerical model of joint specimens was established, and the influence of composite slab on failure mode, hysteretic performance, bearing capacity, semi-rigid performance and stress characteristics of joints was analyzed. The results showed that the main failure mode of the end-plate connection joint was the bending deformation of the end-plate, and the addition of the composite slab will make the hysteretic curve pinch to a certain extent, and at the same time, it will cause the cracking failure of composite slab. After adding the composite slab, the initial rotational stiffness, ultimate bearing capacity and energy dissipation capacity of the end-plate connection joint increased by about 22%, 13% and 22% respectively. When the composite slab and the upper flange of steel beam worked together, the load was transferred to the column web through the composite slab. Compared with the joint of closed profiled steel sheeting-concrete composite slab, the initial rotational stiffness and ultimate bearing capacity of the joint with open profiled steel sheeting-concrete composite slab were increased by 13% and 9% respectively. Therefore, the composite slab can effectively improve the seismic performance of end-plate joints, expand the force transmission range in the core area of joints, and enhance the beam-column force transmission mechanism. It was suggested to adopt the open profiled steel sheeting-concrete composite slab, which can provide reference for further improving the performance of prefabricated joints.
- 1
-
Sentiment analysis of tourism reviews with weighted word vectors of sentiment information
Abstract:
Sentiment analysis of travel reviews is actually to judge the emotional polarity of travel review texts, which can provide important references for potential tourists to choose tourist attractions. At present, there are few researches on the analysis of sentiment orientation of tourism reviews at home and abroad. Some sentences in the review text have no contribution to the sentiment orientation of the text, and in the sentiment tendency analysis studies，distributed word representation is mostly used, which ignore the sentiment information of the word. Therefore, this paper improves the feature word extraction according to the dictionary and semantic rules, and proposes a representation method of weighted word vector integrated with sentiment information and improved TF-IDF algorithm, which is applied to the task of sentiment analysis of tourism review text. Through the experiment on the collected data of tourism reviews in Hebei Province, the proposed method is compared with the four groups of control experiments set in this paper, the experimental results show that the proposed method has higher accuracy, recall and F value.
- 1
-
Role of astrocytic mitochondria in ischemic stroke
Abstract:
Ischemic stroke is a common acute cerebrovascular disease in middle-aged and old people. It is the most dangerous diseases in the world today. Astrocytes are emerging into the limelight as central components of CNS functioning and astrocytic mitochondria is essential in promoting neural survival and neurological improvement following ischemic stroke. This review will first describe what happens in terms of bioenergetic changes and intracellular mitochondrial dynamics within astrocytes and their mitochondria during ischemia. Subsequently, we will move to the transfer of functional mitochondria from astrocytes to neurons. Lastly, The regulation of astrocytic mitochondria on cerebral blood flow was reviewed. Thus targeting astrocytic mitochondria may be a novel approach to improve clinical treatment effect.
- 1
-
Effect of Induction Remelting on Microstructure and Properties of Hot Spraying Coating for High Speed Rolling Mill Bearings
Abstract:
In order to improve the microstructure and properties of hot spraying coating for bearing of high speed rolling mill, induction remelting was carried out on the Ni60A coating which was prepared on the surface of GCr15 Bearing Steel by high energy flame spraying. The porosity, microstructure and microhardness of the coating before and after induction remelting were analyzed comparatively by metallographic microscope, scanning electron microscope, X-ray diffractometer and microhardness tester. The effect of induction remelting on the microstructure and microhardness of the coating and interface was investigated. The results show that the porosity of nickel based coating prepared by high energy flame spraying is as high as 5.09%, and there are many surface pore defects, as well as there are obvious interface cracks and pore defects at the interface between the coating and the substrate, showing typical mechanical bonding and poor interface bonding properties. However, after the induction remelting, the microstructure of the coating is dense, the porosity is only 0.27%, and the defects of the coating are obviously reduced, and the bonding interface between the coating and the substrate shows strong metallurgical fusion characteristics. Additionally, the amount of hard phase in the coating increases significantly, and the microhardness of the coating and interface is greatly improved. Therefore, the induction remelting process can not only improve the surface quality of hot spraying coating for high-speed rolling mill bearings, but also improve the interface bonding characteristics of the coating. As a result, the research can provide a theoretical basis for the application of induction remelting technology in the surface strengthening of high-speed rolling mill bearings.
- 1
-
Matching control of energy recovery retarder for electric semi-trailer train
杨坤, WANG Jie, MA Chao, XIAO Jinzhao, TAN Shunliang
Abstract:
In order to improve the serious problem of "collision" when the retarder is installed in the transmission system of a semi-trailer vehicle, and to improve the braking energy recovery rate during retarding conditions, a scheme of energy recovery type retarder installed in the hub on both sides of the front axle of semi-trailer was proposed. According to the regulation of retarder braking performance in GB/T 32692, the retarder parameters are matched, and the corresponding retarder control strategy is proposed. According to the quality requirements of the electric semitrailer train in the control strategy, the quality estimation algorithm was studied, and based on the particle swarm algorithm, the braking torque distribution at low braking intensity is studied. A joint simulation platform was built through Matlab/Simulink and TruckSim to simulate and verify the quality estimation algorithm, the economy of electric semitrailer trains and braking safety. The simulation results show that the quality estimation algorithm can accurately estimate the quality of electric semitrailer trains; The energy recovery retarder can meet the retardation requirements of electric semi-trailer vehicles, improve the braking energy recovery rate, and can effectively improve the "collision" problem of the electric semi-trailer train during slow braking. Related research provides new ideas for improving the braking energy recovery rate of electric semi-trailer vehicles during slow braking, and can improve the "collision" problem and improve braking safety.
- 1
-
Injury Prediction for Advanced Automatic Crash Notification System
Abstract:
When a vehicle collision occurs, the Advanced Automatic Crash Notification (AACN) system can predict the driver’s injury in the vehicle based on the driver’s injury prediction algorithm. It helps the rescue center make early judgments as well as positive and effective decisions, which improves rescue efficiency and saves more lives of seriously injured drivers. First, by selecting the amount of speed change, the direction of the accident, the driver’s age, gender, whether to wear the seat belt, and whether the driver’s side airbag inflated as the influencing factors of the driver’s injury, a Logistic regression model was analyzed and built based on road accident data. Next, the effectiveness of the model was verified by using the Hosmer-Lemeshow test table, and the best trigger threshold was obtained through sensitivity analysis. Then, a driver injury prediction algorithm was proposed, and the overall design of the AACN system terminal was realized based on this algorithm. Finally, an actual case was used to test the accuracy of the injury prediction algorithm. The results of the case study show that the proposed driver injury prediction algorithm has a high accuracy rate, can effectively predict the driver’s injury, and improve the accuracy of the AACN system.
- 1
-
Design of Universal Convolutional Layer IP Core Based on FPGA
Abstract:
With the integration and development of convolutional neural network and FPGA technology, more and more structures of convolutional neural network based on FPGA have been studied. Aiming at the problems of miniaturization and parallelization of convolutional neural network, this paper proposes a design of high-speed universal convolutional layer IP core using VHDL language according to the characteristics of convolutional neural network and FPGA devices. This design is different from traditional mode of customization of convolution layer based on FPGA, and greatly improves the portability of convolution module by encapsulating the convolution layer into IP core. In this design, the size of convolution window is changed by changing the transfer parameters, and the convolution operation is carried out by pipeline. The simulation results show that the IP core structure of the convolutional layer not only increases the portability of the convolutional module, but also ensures the computing speed, which provides a feasible implementation method for the implementation of convolutional neural network on miniaturized devices.
- 1
-
Progress in synthesis technology of cyanuric acid
Abstract:
Cyanuric acid, which as an important chemical intermediate, can be used as raw material to synthesize a wide range of cyanuric acid derivatives. At present, there is a great demand for cyanuric acid in the market, and there is still room for further expansion. According to the different reaction media, the synthesis method of cyanuric acid can be divided into two major processes: solid phase and liquid phase. The solid-phase method has been maturely used in industry, and has the characteristics of simple operation and good economy. However, its poor operating conditions and high energy consumption limit its development, especially the problem of substandard environmental protection. Although the liquid-phase method has not yet been applied in industry, its characteristics of continuous production and simple follow-up process are in line with the current development goals of cleaner production processes. Through a review of various methods derived from the solid phase method and the liquid phase method, their advantages and disadvantages are compared, and the industrial development prospects of the liquid phase method and some other cyanuric acid synthesis methods are prospected, and they are expected to be realized. The goal of green cleaning process.
- 1
-
Location privacy protection scheme for LBS users based on differential privacy
Abstract:
In order to take into account the availability of Shared location data and privacy protection requirements, Aiming at the Shared location information collected by the third party, this paper proposes a location privacy protection scheme of LBS users based on differential privacy. First of all, the Shared location data set is preprocessed and Trie tree structure is adopted to store location data and frequency. Secondly, frequent location selection is carried out in the Trie tree, and Laplacian mechanism under differential privacy is used to disturb the location frequency. Finally, we optimize the perturbed data based on the two techniques of upward post-processing and consistency constrained post-processing, and theoretically prove that the proposed scheme satisfies -differential privacy. Simulation results and analysis show that this scheme can effectively protect the user"s location privacy and make the Shared location data have good availability.
- 1
-
Study on the synthesis process of Naphazoline Hydrochloride
Abstract:
According to the relevant regulation of ICH Q11 on the development and manufacture of drug substances, the advantages and shortcomings of reported synthetic methods of Naphazoline Hydrochloride and the possible origination of it’s impurities specified in the European Pharmacopoeia were analyzed, and then the modified synthesis route was designed to control the generation of impurities based on the concept of Quality by Design. Using 1-naphthylacetic acid as the starting material, the target compound was obtained through amidation reaction, amide dehydration reaction, catalytic addition-cyclization reaction and salt formation reaction. The results show as follows: In the amidation reaction, using dichloromethane as the solvent, n (1-naphthylacetic acid): n (di-tert-butyl dicarbonate)﹕n (ammonia) = 1﹕1.2﹕1.2, the yield is 88.6％; In the dehydration reaction and the addition-cyclization reaction, N, N-dimethylformamide is used as the solvent, the workup procedure is simple and the intermediate purity is high; In the salt formation reaction, n (Naphazoline free base)﹕n (36％ Hydrochloric acid) = 1﹕1.48, the yield is 90.1％. After optimizing the process parameters, the total yield is 50.83％ with four successive steps, and the four impurities listed in the European Pharmacopoeia are not detected. The synthesis process has advantage of mild reaction conditions, which is suitable for industrial application.
- 1
-
Thermal performance of supercritical carbon dioxide in straight pipe casing
Abstract:
The numerical simulation of straight tube air cooler is carried out by using FLUENT software. The operation pressure, the mass flow rate of carbon dioxide, the mass flow rate of cooling water and the inlet temperature are changed for numerical calculation, the temperature distribution of carbon dioxide and cooling water along the length of the pipeline is obtained. According to the second law of thermodynamics, the distribution of entropy generation along the pipe length is obtained by calculating the thermal process in straight pipe casing. The results show that, with the increase of the pressure, the entropy production along the length of the pipe increases gradually; with the increase of the mass flow rate of carbon dioxide, the entropy production decreases; with the increase of the mass flow rate of cooling water, the entropy production does not increase significantly; with the increase of the inlet temperature of the cooling water, the entropy production decreases.
- 1
-
Fault detection algorithm of industrial process based on DW-ICA-SVM
Abstract:
In order to effectively improve the fault detection and monitoring performance of the support vector machine (SVM) algorithm in the industrial process fault detection algorithm based on DW-ICA-SVM is proposed. Firstly, standardize the training data, used Independent Component Analysis (ICA) to obtain the independent component matrix of the data, extract hidden non-Gaussian information and generate IC. Then used the Durbin-Watson (DW) criterion to calculated the DW value of the IC. The important IC is extracted by comparing the DW value, and the training data containing important IC information is used as the input of the SVM model to obtain the weight vector and displacement. Finally, the test data is input to the model for fault detection and monitoring. While extracting hidden non-Gaussian information, this method uses DW method to effectively extract important noise information, reduces autocorrelation between samples, reduces non-random behavior, and combines SVM for fault detection, which effectively improves fault detection performance. The method is applied to nonlinear numerical examples and Tennessee-Eastman industrial process, and compared with PCA, LPP, ICA, SVM and ICA-SVM methods, the simulation experiment results further verify the effectiveness of the algorithm.
- 1
-
Inherent Characteristics Analysis of Powertrain Mounting Systems by Considering Parametric Uncertainty and Correlation
Abstract:
In order to effectively analyze the influences of parametric uncertainty and correlation on the inherent characteristics of automotive powertrain mounting system (PMS), a method for analyzing the inherent characteristics of PMS is proposed based on the multi-dimensional parallelepiped model, in which both the parametric uncertainty and correlation are considered. In the proposed method, the multi-dimensional parallelepiped model is firstly constructed to describe the PMS parameters with uncertainty and correlation. Then, the uncertain responses of the natural frequency and decoupling rate are calculated by integrating the regulation technique, Taylor series expansion and central difference method. The analysis procedure of the proposed method is presented as well. The numerical results show that the proposed method can deal with the coexistence of correlation and independence of uncertain parameters. Taking Monte Carlo method as a reference method, the proposed method has acceptable computational accuracy, and it can greatly improve the computational efficiency on solving the uncertainty responses of the PMS inherent characteristics. The proposed method and the analysis results can provide important reference for the calculation, evaluation and optimization design of the inherent characteristics of automotive PMS.
- 1
-
Localization and Evaluation of Interturn Short Circuit Fault in BLDC Motor Based on Transfer Learning and Feature Fitting
Abstract:
Brushless direct current (BLDC) motors have been widely used in industry and factory automations, and electric vehicles. Interturn short circuit fault is one of the dominated faults for a BLDC motor, and this fault affects precision control, induces noise and vibration, and even causes motor burn down and fires. Hence, diagnosis of interturn short circuit fault of BLDC motor is of significance. This paper proposes a method that combines of transfer learning and features fitting to realize accurate fault localization and evaluation. First, the three-phase current signals of the motor stator windings are synchronously sampled. The one-dimensional current signals are transformed to an image, and then a transfer learning-based convolutional neural networks model is trained for fault localization. When the fault phase has been localized, the sensitive features are extracted and selected from the corresponding phase current, and then features fitting method is designed to qualitative evaluate the fault levels. Experimental results indicate that the proposed method can localize the faults with accuracy of 100%, and the relative average error of fault quantitative assessment is 4.33%. The proposed method shows potential applications for accurate localization and evaluation of stator winding faults in permanent magnet motor systems.
- 1
-
Residual Current Grounding Fault Intelligent Sensing Technology Based on Wavelet Packet Decomposition
Abstract:
In order to solve the problem that the fault line cannot be accurately identified after single-phase grounding fault occurs in power grid, an intelligent sensing method of residual current grounding fault based on wavelet packet decomposition is proposed. Based on wavelet analysis and intelligent sensing principle, the residual current generated by grounding fault is collected, and the collected residual current information is analyzed and compared to sense the grounding fault and identify the fault. Based on the research of on-line monitoring of residual current of AC power supply and arc grounding fault diagnosis technology based on wavelet transform, the time-frequency characteristics of current obtained by wavelet packet decomposition are used for fault line selection; then the difference of current characteristics between fault line and normal line is analyzed, and the fault line is accurately identified; finally, the fault line based on the proposed wavelet packet decomposition is analyzed in the simulation software The simulation results show that the method is effective, which provides a reference for the design of intelligent sensing system of AC power grounding fault.
- 1
-
Fast matching method of bullet rifling traces based on shared connection triplet convolutional neural network
PAN Dilin, Pan Shibo, LIU Haishi, JIANG Xuemei, LIU Yi
Abstract:
Traditional bullet trace detection generally uses laser to detect rifling traces to extract the signal of the rifling traces. The signal form is complex and random, which severely restricts its practical application. Aiming at the problems of low precision and complicated operation of traditional bullet trace detection, this paper adopts multi-scale registration, elastic shape measurement and convolutional neural network technology, and uses adaptive control method based on multi-mode elastic drive to establish the end of the specimen. Position and attitude parameter distribution model. At the same time, the isolated forest algorithm is used to detect the signal for anomaly processing, and the variable-scale morphological filtering algorithm is used to remove non-small features. The square velocity function is introduced to optimize the elastic shape measurement algorithm to complete the curve contour embedding layer mapping. Aiming at the matching part of the rifle line shape, a convolutional neural network model of optimized parameter sharing connection triples suitable for trace features is established, and the network is trained to convergence by calculating the similarity of the embedding layer and minimizing the triple loss function. The method solves the accuracy and operability problems faced in the traditional bullet trace detection, the cost is greatly reduced compared with the traditional detection method, and the stability of the detection result can be guaranteed. The comparison of similarity matching experiment results can also strongly prove the superiority of this method.
- 1
-
Secondary development of ABAQUS in the simulation of dynamic shear extrusion connection based on Python
Yan Huajun, Zhang Shuangjie, Shao Haitao, Zhang Chao
Abstract:
When the finite element software is used to analyze the influence of multi parameter changes on the research object, it is necessary to repeatedly model, define and modify parameters. The dynamic shear extrusion connection of intermediate billet is taken as an example. The python language was used for secondary development of ABAQUS pretreatment. The kernel script program of dynamic shear extrusion connection simulation was writed. The graphic user interface of dynamic shear extrusion connection was established by using RSG plug-in. Users can input different process parameters, die parameters and blank parameters according to the actual situation to complete the pre-processing operation automatically and carry out simulation analysis. It not only effectively solves the problems of complicated and error prone model assembly, but also improves the accuracy of model assembly and simulation results. Finally, the rationality of the simulation results is compared. The feasibility of the secondary development program and graphical user interface is verified. It provides a powerful tool for the follow-up study of the influence of different reduction, overlap, edge width and other parameters on the dynamic shear connection quality of intermediate billet, and provides a reference for the secondary development of ABAQUS in other fields.
- 1
-
Mathematical models for multi-AGV scheduling problem with charging requirements and time windows
Abstract:
Logistics sorting center is the important hub for express delivery, and its sorting efficiency is closely related to the delivery time of express delivery to a certain extent. In order to improve the scheduling efficiency of Automatic Guided Vehicle (AGV) in the logistics sorting centers, the characteristics of pure electric driven AGV should be considered, including the electricity consumption and charging demand in the process of transportation. Therefore the effect of AGV's charging task and the departure time of the package out of warehouse on the actual operation should be analyzed. In order to minimize the sorting cycle time, a mixed integer programming (MIP) model was established with the consideration of AGV remaining power and package time window. Then, a constraint programming (CP) model is proposed, in which interval variables are used to represent the performance of tasks and cumulative functions are used to record the changes of electric quantity. The solution efficiency of the constraint programming model is verified by different instances, and the effect of charging rate on the objective function is considered. The constraints of the problem are extended to solve the related problems.
- 1
-
Facial expression recognition based on face texture feature fusion
Abstract:
In facial expression recognition, the recognition rate will be disturbed due to inherent limitations including light, pose variations, noise, and occlusion. In this paper, a hybrid approach of facial expression based on sentiment analysis has been presented combining local and global features. Feature extraction is performed to fuse the histogram of oriented gradients (HOG) descriptor with the uniform local ternary pattern (U-LTP) descriptor. After the experimental analysis of U-LTP parameters, the most appropriate HOG parameter set is selected to improve the performance of the proposed technique for facial images containing noise points and occlusion. Features extracted by HOG and U-LTP are fused into a single feature vector, and the feature vector is sent to a multi-class support vector machine classifier for facial classification. Experiments in three public facial expression image databases show that the recognition rate of the proposed method is better than that of other facial expression recognition methods.
- 1
-
The spatio-temporal characteristics of human infection with H7N9 in China
Abstract:
Objective To understand the spatiotemporal transmission characteristics of H7N9 infection in China. Methods Based on World Health Organization statistics on H7N9, the time-space transmission characteristics of human infection with H7N9 in China were investigated by means of time series analysis and standard deviation ellipse analysis. Results In time, from the first detection of human infection with H7N9 in 2013 to the last infection case in 2018, the entire epidemic formed five stages from October of that year to September of the following year. The number of cases increased from 134 in the first stage to 338 in the second stage, then decreased to 144 in the fourth stage, and finally an explosive 830 cases were formed in the fifth stage. There is a gap in the high incidence period at each stage; January to February is a month, and the number of cases in the outbreak month accounts for 51.74%. In space, the center of the standard deviation ellipse shifts from Huzhou near the coast to Fuzhou and Luzhou inland, and finally reaches Huanggang. The elliptical coverage area has also expanded from the more concentrated Shanghai, Zhejiang, and Jiangsu provinces to cover nearly half of China''s provinces including Shandong, Henan, Sichuan, Hubei, and Guangdong. And through the spatio-temporal analysis of the three typical regions of the Yangtze River Delta, the Pearl River Delta, and the Beijing-Tianjin-Hebei region and the surrounding areas, the differences in epidemic situation in different regions of our country are obtained: severe areas that occur frequently in winter and spring represented by the Yangtze River Delta; More severe areas with periodic outbreaks; gentle areas with fewer cases represented by Beijing, Tianjin and Hebei. These results further validate the spatiotemporal propagation characteristics of different regions. Conclusion The development of H7N9 epidemic in China has obvious periodicity and seasonality in time. The period of high incidence is from December to May each year. The epidemic in space is concentrated in the southeast coastal area.
- 1
-
Preparation of Cu2O/CPAN/SiO2 Composite Material and Study on Photocatalytic Reduction Performance
王朋, 朱学旺, Yan Xuesong, 王德松
Abstract:
With porous SiO2 as the carrier, Cu2O/CPAN/SiO2 (cuprous oxide/cyclized polyacrylonitrile/silicon dioxide) composite photocatalyst was prepared by solution impregnation and in situ thermal decomposition. The morphology, composition and structure of the composite were characterized by TEM, SEM, XRD, FTIR, BET and EDS, and the photoelectric properties of the composite particles were analyzed by UV-VIS, DRS, PL, EIS and photocurrent methods. The photocatalytic catalytic properties of Cu2O/CPAN/SiO2 composite particles were estimated through the photoreduction of p-nitrophenol with visible light. The results showed that porous SiO2 carrier greatly increased the specific surface area of Cu2O/CPAN. The heterojunctions of Cu2O in octahedral crystal and CPAN are evenly distributed on the surface of SiO2 and significantly improve the absorption of visible light and the separation efficiency of photogenerated electron-hole pairs. When the Cu2O content is 2%, the heat treatment temperature is 260℃, and the heat treatment time is 3h, the prepared Cu2O/CPAN/SiO2 composite particles exhibit the best photocatalytic activity. The method can effectively improve the specific surface area and electron-hole separation efficiency of the material, and provides a method basis for preparing a high-efficiency composite catalyst.
- 1
-
Numerical simulation and experimental study on springback deformation of duplex stainless steel heat exchanger sheet
Abstract:
Abstract：The significant springback deformation of metal sheet makes the development of plate and frame heat exchanger extremely difficult for duplex stainless steel. In this work, a coupled explicit to implicit finite element methods is adopted for predicting springback deformation in forming processes of metal sheet for high strength duplex stainless steel FDX27 sheet. The explicit method is initially utilized to analyze the contact-based forming operation of a production stamping process. Then, an implicit method is performed to simulate the springback deformation when the forming die is removed. By using numerical simulation method, effects of different mold radius and friction coefficients on springback deformation of FDX27 sheet were analyzed. Meanwhile, effect of material strength property on springback deformation was studied by choosing three different sheets. Different product experiments are performed to verify the accuracy of springback simulation results. And the experimental results are in good agreement with the simulation results, which shows that the springback numerical analysis method is reliable.
- 1
-
Simulation and Optimization of Low Pressure Casting Process for AlSi9Mg Gearbox Lower Case
Abstract:
Use Pro/Engineer software to draw three-dimensional solid models of the lower case of the gearbox with two different gating systems. Based on the better pouring scheme, study the effect of pouring temperature, mold temperature and filling pressure on the low pressure casting process of the lower case of AlSi9Mg gearbox. The influence of liquid filling and solidification process. ProCAST software is used for numerical simulation, and the test results are effectively analyzed with a standardized orthogonal table. The better process parameters are as follows: pouring temperature 700 ℃, mould temperature 350 ℃, filling pressure 45 KPa. Under this process parameter, the defect volume of the lower shell casting of the aluminum alloy gearbox is reduced from 1.537cc to 1.425cc.
- 1
-
Research on community discovery method of heterogeneous network
Abstract:
In recent years, with the advancement of science and technology, complex networks have grown exponentially in scale and complexity. Research in multiple fields in complex networks has gradually become a hotspot in multidisciplinary research. Among them, the community structure is an important field widely studied in complex networks, and it is also one of the important characteristics of complex networks. The community in the network is a collection of densely connected vertices, which are tightly connected within the community and sparsely connected with nodes outside the community. Community discovery plays an important role in understanding the functions of complex networks. At present, the research on homogeneous networks based on a single relationship type is relatively mature. However, most networks in the real world are heterogeneous networks with multiple relationships and multiple types. At the same time, as the scale of data continues to expand and demand changes, the research on heterogeneous networks has gradually become a hot spot in this field. This article summarizes the definitions and evaluation indicators of problems found in communities under heterogeneous networks. Then, according to the different methods, the existing community discovery algorithms under the heterogeneous network are summarized and sorted out, and then various methods are explained in detail by category. Secondly, related applications discovered by the community are introduced, including social network influence, link prediction, etc. And organize the commonly used data sets for researchers'' reference. Finally, the development trend of community discovery is summarized and prospected.
- 1
-
Research on the Application of Threat Intelligence Technology in Network Security Situation Awareness
Abstract:
General secretary Xi Jinping gave instructions in 2016 at the cybersecurity and informatization work symposium: to strengthen big data mining and analysis, to make better situation awareness and to prevent risks in cybersecurity. In response to the call of national policies, many large industries and enterprises actively advocate, build and apply situational awareness systems to deal with the severe challenges faced by network security. Cyber security situation awareness refers to the collection of comprehensive security elements in the network environment, and performs data fusion on them. Not only a macroscopy understanding of the security situation but also a prediction of security trend can be made in this process, which can be used to effectively protect network security. The research on network security situation awareness is generally divided into three parts, namely, situation awareness, situation understanding and situation projection. The process of cyber security situation awareness is to collect the security elements of the target system, and analyze the impact of security incidents. Finally, by using cyber security situation awareness, it can be realized the behavior recognition of various activities, attacks detection, evaluation and prediction of the cyber situation in the network, so as used to provide correct decisions for the cyber security response. Using situation awareness to discover potential threats and respond to them has become the focus on the research. The cyber security situation awareness technologies and methods currently proposed are mostly based on small-scale networks. With the continuous expansion of network scales and appearance of new advanced attack technologies such as APT, the accuracy of current cyber situation awareness technologies is greatly reduced. Maneuverability has also been gradually decreased. In recent years, threat intelligence has brought new ideas about the research of situation awareness. Threat intelligence is evidence-based knowledge, including context, mechanism, label, meaning, and recommendations that can be implemented to deal with threats. The knowledge is related to existing or growing threats or hazards faced by assets, and can be used to give support or response to deal with them. Threat intelligence is usually obtained by using big data, distributed systems or other methods. With the help of threat intelligence, the efficiency and accuracy of situation awareness analysis can be improved greatly. At the same time, threat intelligence has a strong ability to update autonomously. As increase or updates of security incidents, threat intelligence will be updated accordingly to provide the latest security event data. The self-renewal ability of threat intelligence greatly improves the ability to detect new and advanced dangers in cyber security situation awareness. And by using the sharing mechanism in the threat intelligence, organizations of the same field can obtain targeted threat intelligence, so that security stuff can understand the threat environment of their organization, such as attackers, tactical techniques used by them and defense strategies, which can help organizations understand the security threats they are facing or will be faced in the future. The threat intelligence can improve the accuracy of situation comprehension and situation projection in the process of situation awareness, and improve the ability of security situation prediction and response to security incidents.
- 1
-
The new border of Digital Twin - A Multi-sensory oriented Model construction method
Abstract:
As one of the important supporting technologies for the construction of CPS(Cyber-Physical Space), the application of digital twin has appeared in many fields such as aerospace, intelligent manufacturing, smart city, smart medical care, smart education, etc., but some problems in the practice process has also appeared, such as the generalization of the concept of digital twin, which easily leads to misunderstanding; The lack of general and effective methods in concrete implementation, which results in the lack of universal practical cases and difficulty in forming recognized typical cases. To solve these problems, it is necessary to restrict the concept boundary of digital twin and extend the boundary of digital twin method, so as to form a new boundary of digital twin, promote the formation of consensus, increase implementation methods and promote its development better. Conceptually, physical entity is a collection of materials with various properties, which is characterized by complexity, authenticity and immediacy, and can dynamically evolve according to objective laws with the change of external conditions. In the study of mapping physical entities to digital twins, it is easy to expand the scope of concepts, such as the simulation of dynamic evolution process, external conditions, data, and even objects, such as physical entities. As a result, the concept of digital twins will lose its core and it is difficult to reach an agreement. In terms of methods, based on the detailed investigation and analysis of related applications in multi-scenarios, the existing research on digital twin often goes beyond the perception process of physical entities, and directly relies on the models or model building methods in the original professional fields. While this method has made some progress, its limitations have already appeared. First, the existing models are mostly focused on subdivision fields, which cannot be used universally among fields. Secondly, there are few existing models that reflect the characteristics of high fidelity, multi-scale and multi-physical fields of the digital twin model, and even less information flow corresponding to the whole life cycle. Direct application cannot guarantee the effective realization of digital twin; Thirdly, entering the modeling process directly from the height of existing cognition may cause huge costs. For example, the ADT program, a typical case recognized by the US military in the world, has a construction time of ten years and huge investment in manpower and material resources, which further hinders the industry from entering the digital twin practice. In order to meet these challenges, in terms of conceptual boundary, this paper proposes that the digital twin should return to the essence of its digital model, and take the model as the center for effective restraint, so as to promote the understanding of all parties involved in production, education and research to reach an agreement. As for the extension of method boundary, this paper puts forward a method of constructing digital twin model for multi-sensory, that is, according to the general process of human understanding of the physical world-firstly, obtaining perceptual knowledge of features through various perception methods, and then further forming rational knowledge through various cognitive processes-from shallow to deep, from easy to difficult, from simple to complex. Firstly, the digital twin initial model of physical entity is established by multi-sensing methods such as visual perception, auditory perception, tactile perception and dynamic perception, gustatory/taste perception, and combination with control data reflecting the change of conditions, thus focusing on the complexity and authenticity of physical entity at the beginning of the model establishment, fully embodying the characteristics of the digital twin model, and effectively enhancing the practicability and universality of the model; Then, the initial model is gradually matched with the existing cognitive knowledge framework, and the control data returned from the physical entity is used for continuous iteration. In this way, information such as various property changes, real-time/near-real-time reactions, various objective laws and behavioral logics affecting the physical entity under specific external conditions can be gradually added to the digital twin model according to the actual needs of the research field, thus effectively controlling the scale and cost of the model and gradually realizing the information flow in the whole life cycle; Then, the optimized digital twin model is further used in theoretical and practical research, such as simulation, planning, optimization, decision-making, etc., to promote the development of various studies. This paper also reviews and looks forward to the existing technical basis and development prospect of the construction method of digital twin model for multi-sensory.
- 1
-
Study on information personalized recommendation based on system dynamics
LIU Bin, LIU Yu, SUN Zhongxian, LIU Zengjie
Abstract:
Recommender system has become an important application of big data technology. In order to master the complex influencing factors of dynamic feedback of recommendation system on information platform, based on the theory of system dynamics, this paper analyzes the causal relationship of each element of personalized recommendation system of news information, draws the causality diagram, and establishes the system dynamics flow chart of influencing personalized recommendation, the simulation equations are constructed and simulated with Vensim software. The results show that the number of articles, the characteristic tags and the interest factors of articles have important influence on the recommendation effect, which are also the key problems to be solved in the design of the recommendation system. At the same time, it can also solve the key problems of the news information recommendation system, such as cold start, real-time and information cocoon room.
- 1
-
Research on adaptive clutter suppression for Ground penetrating Radar based on Wavelet transform and K-SVD
Abstract:
Abstract：In view of the presence of a large amount of clutter noise mainly composed of surface direct waves in the original GPR images, In order to extract target signals effectively, an adaptive bilateral filtering method based on wavelet transform and K-means singular value decomposition is proposed. The original radar data wavelet decomposition, then K-SVD transform sparse coding and update the atoms, and get the updated sparse coefficient and small dictionary, finally will be small, the reconstructed image wavelet inverse transformation to adaptive bilateral filtering to get the image after image, to implement the wavelet transform, K-SVD algorithm and adaptive bilateral filtering method complementary advantages. The experimental results show that the proposed method has good clutter suppression effect, and the comparison with other methods shows that the proposed method has better performance in peak signal-to-noise ratio and target image entropy, and has certain application value in practical radar survey tasks.
- 1
-
Backstepping Controller Based on Extended State Observor for Magnetic Levitation Ball
Abstract:
Aiming at the characteristics of non-linearity, uncertainty and susceptibility to disturbance of single-degree-of-freedom magnetic levitation ball system, a backstepping control method based on extended state observer is proposed to improve the control performance of the system. The method uses the extended state observer to estimate the position, velocity and disturbance information of the levitation ball in real time when the system is disturbed by uncertainty. In the method, the estimation is combined with the controller design, and then the backstepping method is used to design the levitation position tracking control law of the magnetic levitation ball, and the Lyapunov method is used to prove the final bounded convergence of the tracking error of the system. The simulation results show that when there is uncertainty in the system, the designed control law can realize the stable suspension of the ball, and can realize the position tracking according to the required suspension height position.
- 1
-
Research progresses of bionic painless injection needle
Abstract:
Medical needle injection is a commonly used treatment method in modern medical treatment. However, the pain caused by skin irritation in the injection process brings out a great trouble to patients. Scholars have conducted a large number of studies to reduce the pain caused by needle injection. Insects, including mosquitoes and gadflies, are difficult to be detected when penetrating human skin, which have been regarded as a bionic prototype to the biomimetic development of painless injection needle. Starting from the generation mechanism of pain sensation, we summarized the function mechanism of bionic painless injection needle, and the pain detection methods. The bionic prototype and bionic mechanism of painless injection needle were introduced, and the research progress of painless injection technology was focused. Besides, the problems existed in the current researches, as well as the application prospect of the bionic mechanism of painless injection needle in low resistance suture needle, were analyzed. This review can deepen the understanding of the biomimetic painless injection needle and provide a referential idea for the research of low-resistance suture needle.
- 1
-
Research progress on force measurement technology of bionic prototype
Abstract:
Depending on the body structure and movement characteristics obtained by the natural evolution, many animals have become excellent bionic prototypes, which provide effective solutions for the complex problems in the engineering field. Based on the demand for quantitative characterization of the functional characteristics of bionic prototypes, the force measurement technology of biomimetic prototype has been studied extensively, in order to reveal the mechanical principle and movement mechanism of these bionic prototypes. In this review, starting from the excellent functional characteristics of bionic prototypes, we summarized the force measurement technology used in bionic prototypes. Especially, we focused on the latest research progress of the force measurement technology, including the technology with sensor as the core component, the technology based on centrifugal principle, and the technology depended on image processing. This review can deepen the understanding of researchers to the force measurement technology, and provide technical support for the research of engineering bionics. Finally, we pointed out that the force measurement technology should be conducted in the aspect of contact-reaction force with micro-Newton accuracy, which produced by the flying insects during their take-off/landing without interference.
- 1
-
Antimicrobial mechanism and application prospects in medicine of antimicrobial peptides
Abstract:
As a kind of new antibiotics, antimicrobial peptides (AMPs) which are small molecular polypeptides composed of 10~100 amino acid residues, have been paid much attention for their broad-spectrum antibacterial activity, thermal stability and unique mechanism of action. In recent years, studies have shown that the possibility of bacterial drug-resistance has been greatly reduced for the multi-target action mechanisms, including membrane-targeted, non-targeted and immune regulation of AMPs in vivo. AMPs combat pathogen infection and promote apoptosis of cancer cells in vivo. Furthermore, they are also used as chemotherapeutic agents against virus and antibacterial materials for hospital settings, with a broad scope in biomedical field. This review article covers the recent developments related to antimicrobial mechanisms. Meanwhile, scientific problems in potential medicine application fields of AMPs are analyzed and the resolution strategies are also offered to provide new insights into the further research and development of AMPs.
- 1
-
A survey of Heterogeneous network representation learning
Abstract:
A large number of real-world graphs or networks are inherently heterogeneous, involving multiple types of nodes and relationships. Heterogeneous network representation learning is to embed the rich structure and semantic information of heterogeneous networks into low-dimensional node representations. The purpose of heterogeneous network representation learning is to find a meaningful vector representation for each node to facilitate downstream task applications, such as link prediction, personalized recommendation, and node classification. With the development of machine learning and deep learning, heterogeneous network representation learning has been widely used due to its powerful modeling capabilities and extensive applications. This paper mainly summarizes the methods and applications of heterogeneous network representation learning. First, the current heterogeneous network representation learning methods at home and abroad are categorized into different groups, including random walk-based methods，second-order proximity-based methods，matrix factorization-based methods，graph attention network-based methods and graph convolutional network-based methods. Then, various models are described in detail by category, and various aspects of the model are explained. The characteristics are comprehensively compared. Secondly, the related applications of network representation learning are introduced, including the recommended system field, the biological field, etc., and the commonly used datasets, open source implementation of heterogeneous network representation learning models are organized for researchers. Finally, the development trend of heterogeneous network representation learning is summarized and prospected. This research provides a comprehensive review reference, as well as some representation learning models and commonly used datasets for scholars in the field of heterogeneous network representation learning.
- 1
-
Effect of Carbon-Chain Length and Hydroxyl Number on Tribological Performance of Alcohols
Abstract:
In order to investigate the lubrication performance of alcohols under high loads and fast speeds conditions, especially the relationship between carbon-chain length and hydroxyl number and lubrication performance, the influence of carbon-chain length of monohydric alcohols and hydroxyl number of polyhydric alcohols on their lubricity was well investigated. The tribological properties of a series of alcohols were investigated by a four-ball tribological machine, and the effects of the length of carbon-chain length and the number of hydroxyl on their lubricating properties were investigated by means of viscometer, transmission electron microscopy (TEM) and Raman. Experiments show that with increasing the carbon-chain length of monohydric alcohols, the run-in stages and the time for achieving stable friction coefficient were shorted, the wear was reduced (a mixmum 34% reduction); with the increase of the hydroxyl number of polyhydric alcohols, which results in reducing wear(21% and 54% reduction, respectively), no obvious run-in stage, the fluctuation of friction coefficient for ethylene glycol and continuously reducing of friction coefficient for glycerol. It was found that friction-induc ed graphene superior to amorphous carbon was effectively conducive to making the tribosystem achieve the stable friction coefficient and shorting run-in stage.
- 1
-
A Survey of Aspect-Based Text Sentiment Classification
Abstract:
Sentiment classification is also called tendency analysis, which is a text classification task in the field of natural language processing. The object of traditional text classification tasks is the objective content of the text, while the object of tendency analysis is the "subjective factors" of the text. Aspect-Based sentiment classification is a fine-grained classification task, whose purpose is to judge the sentiment polarity of the aspect given in the text. The article mainly summarizes the aspect-based sentiment classification method. First, sort out and classify the aspect-level sentiment classification methods based on deep learning at home and abroad, and subdivide them into convolutional neural network methods, memory neural network methods, recurrent neural network methods, recurrent neural network methods, and attention recurrent neural network methods, and the method based on graph convolutional network and attention graph convolutional network. Then, the research work is introduced by category, focusing on the method based on graph convolutional network and attention graph convolutional network as the latest research progress. Secondly, it briefly introduces the specific application scenarios of sentiment classification, and organizes the commonly used data sets of aspect-based sentiment classification for researchers' reference. Finally, the development of aspect-based emotion classification is summarized and prospected. This study provides a comprehensive review reference for researchers in the field of aspect-based sentiment classification.
- 1
-
Optimization of microwave remediation of naphthalene contaminated soil by response surface methodology
Abstract:
In order to study the best technology of microwave remediation of petroleum contaminated soil, the typical semi volatile organic compounds Naphthalene (Nap) in petroleum contaminated soil was selected as the target pollutant, and the simulated Nap contaminated soil was taken as the test soil. On the basis of single factor experiment, the Box-Behnken experiment design of response surface method was adopted, and the removal rate of Nap was taken as the response value. The quadratic multiple regression model was established with microwave power, irradiation time, soil thickness and soil moisture content as the influencing factors. The ANOVA model reached a very significant level, in which the microwave power had the most significant effect. The results showed that the wave power was 768 W, the irradiation time was 19 min, the soil thickness was 3.2 cm, the water content was 16 %, and the removal rate of Nap was 97.3%. The results showed that the removal rate of Nap was 97.0%, which was only 0.31% different from the predicted results. The results showed that the process parameters optimized by response surface methodology were reasonable and feasible.
- 1
-
Based on non-cooperative indoor environment UWB centreless networking positioning
Abstract:
In order to improve the positioning ability of ultra wideband network in non-cooperative indoor environment, the theory of no-centrality positioning algorithm is used to solve and analyze the output distance information of ultra-wideband ranging, and the relative positioning results are obtained. The positioning results of the system are compared with the results of the photoelectric calibration system, and the accuracy is evaluated. The results show that compared with the traditional ultra-wideband positioning model, the combination of ultra-wideband ranging and centralization-free positioning algorithm can realize the centralization-free positioning and the relative positions among nodes, and finally determine the relative positions among nodes. The combination of UWB ranging and centralless positioning algorithm has good stability and accuracy in relative positioning, and can be widely used in various indoor and outdoor scenes.
- 1
-
Bayesian Model Saliency Detection Algorithm Based on Improved Convex Hull
Abstract:
Aiming at the problem that the traditional Bayesian model algorithm needs to improve the accuracy of significant region detection, an improved convex hull bayesian model significance detection algorithm is proposed.Firstly, the image foreground is extracted by the popular manifold ranking algorithm as the prior probability of the Bayesian model.Secondly, the color-enhanced Harris corner detection algorithm was used to detect the feature points of the image in the three color Spaces of RGB, HSV and CIELab respectively, and the convex envelope intersection of the three color Spaces was obtained to obtain a reasonable convex envelope, and the probability of observation likelihood was obtained by combining with the color histogram.Finally, according to the calculated prior probability and the observed likelihood probability combined with the Bayesian model, the significance region diagram is obtained.The test results in two public data sets, MSRA-1000 and ECSSD, show that this algorithm has good visual detection effect, and the objective evaluation index F-measure value and accuracy-recall rate curve are superior to the traditional classical algorithm.The validity and accuracy of the proposed algorithm are verified.
- 1
-
Research on Impulse Interference Suppression Method Based on Short Time Fractional Fourier Transform
Abstract:
In order to solve the problem that the pulse interference near the service frequency band of aviation radio navigation affects the receiver, and further improve the anti-jamming ability of GNSS system, a pulse interference suppression method based on STFRFT(short time fractional Fourier transform) is proposed. This method determines the best rotation order of the received signal, and then STFRFT is applied to the signal to obtain the two-dimensional distribution of time-frequency surface through coordinate rotation. Under the optimal order, the adaptive time-varying filter is used to separate the interference and signal, and then the interference is suppressed. The simulation results show that the algorithm retains more useful signals and improves the ability of interference suppression.
- 1
-
Rearch on UAV route planning based on adaptive multi heuristic ant colony algorithm
YIN Yanan, WU Xiaojing, ZHANG Chunyue
Abstract:
In order to solve the problem that ant colony algorithm was easy to fall into local optimum in UAV route planning, an improved ant colony algorithm was proposed. The upper and lower limits of pheromone volatilization factor and pheromone were set to prevent ants from falling into local optimum because pheromone on short path was too high or pheromone on long path was too low. At the same time, under the influence of multiple heuristic factors, the overall length of the path was taken as an adaptive heuristic function factor to determine the state transition probability. When the path length was large, the adaptive heuristic function factor was smaller, which made the probability of ant colony choosing the path reduce. The experimental results show that the improved algorithm reduces the path length by 6.4% and the variance of the optimal path length by 85.78%, which increases the consideration of environmental integrity, shortens the path length, reduces the number of iterations, and jumps out of the local optimum. In the case of increasing environmental complexity, the algorithm can effectively provide a theoretical basis for UAV route planning and choose a better path after introducing the adaptive heuristic function factor.
- 1
-
Research progress on caffeic acid phenethyl ester in natural propolis
Abstract:
Propolis is a natural substance,which has been widely used in foods and health care products to prevent diseases. Its various and prominent biological activities play an important role in human health.Caffeic acid phenethyl ester(CAPE) is the main active component of propolis, which has been widely studied for its various pharmacological effects such as antioxidative,anti-inflammation,immunomodulatory,antibacterial,antitumoral and so on. This article systemically reviewed the recent progress in the separation and extraction, structure and synthetic methods,pharmacological activity,and other aspects of Caffeic acid phenethyl ester,which will help further development and application of the medicinal value of Caffeic acid phenethyl ester.
- 1
-
Numerical Simulation of Nautilus Isometric Spiral Wind Turbine and Analysis of Building Turbulence
Abstract:
In order to improve the performance of the wind turbines, the problem that the wind turbine is affected by the building in actual operation is solved. Using the simulation analysis software Fluent, the aerodynamic performance of the new Nautilus equiangular spiral wind turbine with different numbers of blades is studied, and the torque characteristics and wind energy utilization of the wind turbine are analyzed. The layout model of buildings and wind turbines are established and the turbulence characteristics of buildings and compare the torque performance of wind turbines in the turbulent environment are analyzed. The results show: the overall performance of the three-blade wind turbine is more superior, and the tangential speed near the building is significantly increased. The performance of the new Nautilus equiangular spiral wind turbine near the building has been significantly improved and the feasibility of installing the Nautilus equiangular spiral wind turbine near the building is verified. The proposed arrangement of wind turbines can effectively improve the performance of wind turbines, and provide references for the optimal design of wind turbine structures and the arrangement of wind turbines near buildings.
- 1
-
Design and numerical analysis of internal support for long strip deep foundation pit in sensitive environment
Abstract:
In order to explore what kind of internal support layout can ensure the safety and stability of adjacent existing buildings and long strip deep foundation pit under sensitive environment, taking the actual project as the background, Midas GTS NX is used to analyze the three-dimensional interaction of soil and structure in foundation pit, the deformation control indexes of the building and foundation pit under various types of internal support are compared, and compared with the monitoring alarm value and field monitoring data. The results showed that: internal support of opposite brace and angle brace type is more suitable than other types; the layout of the inner support has a significant effect on the change of the basement uplift, but has little effect on the amount of the uplift; it is suggested to increase the stiffness at the weak point when using the corner brace type and the double circular ring beam type inner support. The proposed internal bracing can not only ensure the safety of foundation pit, but also better control the deformation of adjacent existing buildings, which has certain reference value for the design, construction and deformation control of similar projects.
- 1
-
Point-of-interest recommendation algorithm integrating multiple impact factors
Abstract:
In order to solve the problem of data sparseness in the task of point-of-interest recommendation and make full use of the diverse information in the location-based social network to further improve the quality of personalized recommendation, a point-of-interest recommendation algorithm integrating multiple impact factors is proposed. The algorithm performs geographic influence modeling and social influence modeling on geographic information and social information, and combines temporal information and geographic information to model temporal and spatial influence, and then integrates the three influence scores in a weighted summation manner to obtain user’s preference score. According to the user’s preference score, each user is provided with a recommendation list containing Top-N points of interest. The experimental results show that on the two public datasets, the point-of-interest recommendation model that integrates multiple impact factors performs better than the baselines. Therefore, in addition to user’s check-in frequency, geographic-social-spatial-temporal influence is also a key part of the point-of-interest recommendation task, and the modeling of these three influences is of great significance. The proposed algorithm provides a certain reference value in the research of point-of-interest recommendation that integrates key information.
- 1
-
B1C navigation signal acquisition algorithm based on PCO + FFT
Abstract:
The acquisition method of navigation signal based on piecewise correlation code (PCO) phase search and fast Fourier transform (FFT) Doppler frequency measurement has been proved to be an effective method, which can be applied to the acquisition of BOC signals. Firstly, a specific acquisition scheme of PCO + FFT Doppler frequency measurement is proposed after deeply analyzing the characteristics of B1C signal. Secondly, the algorithm is deeply deduced from aspects of coherent integral gain, uncorrelated integral gain, Doppler frequency measurement range and resolution, detection probability, acquisition time and so on. Then, the FPGA implementation scheme of this algorithm is provided, especially the implementation of center control based on state machine. Finally, the simulation performance of this algorithm is given to illustrate the effectiveness of the algorithm. The correctness of the implementation scheme is verified by the actual measurement on the FPGA hardware platform.
- 1
-
Design and implementation of BeiDou signal fast acquisition algorithm based on FPGA+DSP
Abstract:
In BeiDou satellite receiver, a fast BeiDou signal acquisition algorithm based on coherent down-sampling is proposed to solve the problem that the large amount of data to be processed by the Fourier transform affects the acquisition speed of satellite signals in the traditional parallel frequency acquisition algorithm. The coherent down-sampling module is added to the traditional parallel frequency acquisition algorithm. After the carrier and pseudo random code are stripped, the sampling frequency is reduced to reduce the number of points to be processed in the Fourier transform, and then a three-dimensional search on the satellite signal is performed. This algorithm is designed and implemented with FPGA+DSP (field-programmable gate arrays + digital signal processors). Theoretical analysis shows that the algorithm can reduce the amount of calculation by more than 80%. The experiments of the actual BeiDou signal show that the average acquisition time of each star is 9.95ms, and the memory resource consumption is reduced by 42% compared with the traditional parallel frequency acquisition algorithm. This algorithm can effectively improves the acquisition speed while saving resources, thereby realizing the rapid acquisition of BeiDou satellites.
- 1
-
Emotion Recognition Neural Network Based on Auxiliary Modal Supervised Training
Abstract:
In order to solve the problem of imbalance of data samples in multi-modal data, It use resource-rich text modal knowledge to help model resource-poor audio modalities, and construct a supervised training method that uses similarity between auxiliary modalities. Emotion recognition neural network. The network can simultaneously recognize emotions and generate feature vectors for emotion recognition tasks of another modality. It consists of two independent text and audio modal representation modules and a cross-modal information interaction module. In the learning process, the emotion recognition features of the text modal are used as labels, and the similarity task with the audio modal is used to Supervise the representation model of the audio modal, which helps the audio modal to achieve better results in its own emotion recognition task. Experimental results show that this neural network can perform four emotion classifications on the IEMOCAP data set to achieve a weighted accuracy of 82.6% and an unweighted accuracy of 81.3%. It provides a reference and method basis for emotion recognition and auxiliary modeling in the multi-modal field of artificial intelligence.
- 1
-
Design and Control of Special Carrier Platform Self-Balancing Cockpit
江开航, PI Dawei, RUAN Jianfeng, fanjingjing
Abstract:
A self-balancing cockpit system based on the principle of dual-axis gyro is proposed to solve the problem of improving maneuverability of special carrier platform under large roll and pitch motions. The structural modeling of the self-balancing cockpit system is completed by Creo, and the movement model is built in Adams/View in combination with the road model and the driving system of the vehicle. The three-dimensional model of the cockpit is decomposed and mapped into two planes that embody the dynamics of roll and pitch, and the dynamic mathematical model is formed respectively. A self-balancing control strategy for real-time correction of the cockpit attitude is designed. Considering the influence of different types of roads on the attitude of the cockpit, a control threshold module based on the load transfer rate is designed to clarify the working range of the self-balancing control algorithm. The Simulink-Adams self-balancing control joint simulation model was built in the Matlab/Simulink environment, and the virtual tests under various working conditions were performed to verify the effectiveness of the control system. The results show that the self-balancing control system can effectively correct the roll angle and pitch angle of the cockpit in real time, and reduce the impact of the vehicle roll and pitch motion on the driver. This paper innovatively uses the self-balancing cockpit system to break through the performance limitations of the suspension system, and more fully improves the adaptability of the off-road special carrier platform to harsh off-road roads.
- 1
-
Optimization of fermentation conditions for Bacillus subtilis against to plant soft rot
REN Yuanyuan, LIU Yazhen, LU Tianhua, Liu Liqiang
Abstract:
In order to increase bacterial yield and obtain more target protein products, orthogonal method and response surface method were used to optimize the fermentation process of probiotic Bacillus subtilis expression strain Asr. The results showed that the three main factors affecting bacterial yield were leaching yeast powder, MgSO4 and CaCl2. The optimized fermentation medium formulation was: sucrose 20 g/L, peptone 10 g/L, leaching yeast powder 8.65 g/L, K2HPO4 3.0 g/L, MgSO4 0.27 g/L, CaCl2 0.53 g/L. The bacterial yield increased by 1.76-fold compared with that before optimization, with an average of 3.25×108 CFU/mL. After optimum of culture media, the fermentation conditions were optimized by single factor test in 3 L fermentor: the optimal temperature was 37 ℃, the initial pH value was 7.0, the inoculation volume was 10%, and the stirring speed was 250 r/min. The highest yield of Bacillus subtilis Asr reached 7.30×108 CFU/mL, and the test results laid a foundation for the subsequent expansion of fermentation tanks to increase biomass production.
- 1
-
Advanced treatment flux change of pharmaceutical wastewaterwith membrane separation
赵 平, WANG Zhen, ZHANG Yueping, YANG Wenling
Abstract:
Comprehensive pharmaceutical wastewater was treated with advanced nanofiltration and reverse osmosis. The membrane flux change and cleaning effect were studied in single-stage and cyclic modes as the appropriate cleaning time, flux and water yield rate were measured. The results show that the daily physical wash time was 7 minutes to nanofiltration, the intensive acid and alkali wash time was 90 minutes respectively, the average flux was 16.1 L/(m2 h) in single-stage and 7.7 L/(m2 h) in circulation, the water yield rate was 73 %. The daily physical wash time was 12 minutes to reverse osmosis, the intensive acid and alkali wash time was 90 minutes respectively, the average flux were 12.8 L/(m2 h) in single-stage and 7.2 L/(m2 h) in circulation, the water yield rate was 74 %. The suiTab.treatment and wash schemes were suggested for industrial application of membrane separation to pharmaceutical wastewater according to the flux change.
- 1
-
A context-sensitive approach of detecting data race
Abstract:
To improve the correctness of data race detection, an approach to detect the data races based on the context-sensitive analysis in multithreaded programs was proposed. Firstly, control flow analysis was used to construct context-sensitive call graphs, and then escape analysis was employed to find thread-escaped objects. Secondly, context-sensitive alias analysis was conducted to reduce false positives and false negatives. Finally, the happens-before analysis was performed to remove false positives caused by ignoring thread interactions. A data race detection tool ConRacer was implemented by the WALA framework based on this approach and compared it to existing tools SRD and RVPredict. The experimental results show that ConRacer is the most precise tool compared with SRD and RVPredict and it can not only detect data races but also reduce false positives and false negatives effectively. ConRacer improves detection accuracy by combining context-sensitive with static detection methods, which helps find concurrent errors and optimize software performance.
- 1
-
Application of improved implicit generalized predictive control in main steam pressure of gas-fired power boiler
Abstract:
Aiming at the characteristics of non-linearity and variable model parameters of the main steam pressure control system of gas-fired power generation boiler, an improved implicit generalized predictive control strategy is proposed. First, the forgetting factor recursive least squares method is used to identify the model parameters, and a discrete mathematical model of the main steam pressure is established. An implicit generalized predictive control system for main steam pressure is established on the basis of conventional generalized predictive control theory, which simplifies the control algorithm and improves the robustness of the system by adding a PI structure to the objective function. The simulation results show that: compared with the cascade PID and conventional implicit generalized predictive control, the proposed control strategy reduces the adjustment time by up to 20s when the model is adapted; the overshoot decreases by up to 5.08% and the adjustment time by up to 36s when the model is mismatched Robustness and anti-interference ability are stronger. Engineering application shows that after using the proposed strategy, the main steam pressure control deviation is within ± 0.2Mpa, and the control accuracy is significantly improved.
- 1
-
Multi Dimensional Evaluation and Analysis of Street Quality in Rail Transit Station Area Based on Multi-Source Big Data——Take the Third Ring Road of Chengdu as an Example
Abstract:
The promotion of TOD (transit oriented development) concept has given new optimization requirements to the street space of rail transit station area. The scientific evaluation and quantitative research of station area construction environment need to be carried out urgently. As an important transportation corridor in rail transit station area, the space quality of street is an important level of built environment. In this paper, 73 subway stations in Chengdu are selected to support multi-source big data such as street network, POI (point of interest), street view pictures, etc., using machine learning and spatial design network Analysis (sDNA) and other technologies, constructed an evaluation system with convenience, functionality and comfort as the core, carried out large-scale quantitative evaluation of the station area street space quality, and proposed guidance and control strategies for different levels of stations. The results show that 68.03% of the station area streets score is lower than the medium level, the street function and comfort are generally good, and the convenience is poor; at the station level, the street space quality presents the distribution characteristics of high in the South and low in the north, high in the West and low in the East, high in the inside and low in the outside. The research makes the analysis accuracy of human-oriented scale, the analysis depth of site scale and the analysis breadth of urban scale can be taken into account, which is helpful to create an efficient dynamic feedback mechanism of urban management.
- 1
-
Research progress on continuous anaerobic dry fermentation ofagricultural waste
LI Zaixing, YAO Zonglu, LUO Juan, ZHAO Lixin
Abstract:
China is a big agricultural country, and the production of agricultural waste is increasing year by year. However, the utilization rate of resources is still low. Continuous anaerobic dry fermentation technology is a new kind of anaerobically dry fermentation technology, which is mainly used to treat solid organic matter between 20% and 40% of TS. It is an effective way to recycle agricultural waste. Continuous anaerobic dry fermentation technology has the advantages of high dry matter degradation rate and gas production stability. It has been applied industrially in foreign countries, but the research and application of continuous anaerobic dry fermentation technology in China is still less. This paper status of continuous anaerobic dry fermentation at home and abroad in recent years is reviewed, analyzes and compares the typical continuous anaerobic dry fermentation technology, summarizes the continuous anaerobic dry fermentation project built in China in recent years, analyzes the effects of mixed proportion of raw materials, inoculation ratio, temperature, residence time, stir and other technological conditions on the operation of anaerobic dry fermentation, puts forward the shortcomings of the current continuous anaerobic dry fermentation process, and prospects the future development trend of the technology. aIt provides a reference for further optimization of continuous anaerobic dry fermentation process.
- 1
-
Kinetics of degradation of Cefuroxime Axetil in acetone
LIU Baoshu, HAN Kang, ZHANG Junli, 孙华
Abstract:
In order to study the stability of cefuroxime axetil acetone solution. Using high-performance liquid chromatography, a single-factor experiment was used to study the law of the content of cefuroxime axetil in the solution over time under different conditions such as the initial solution pH, temperature, oxidant species and so on. The chemical reaction kinetics method was used to establish the degradation reaction kinetics models of cefuroxime axetil under different conditions. The model parameters were obtained by regression and the half-life (t1/2) was predicted. The results show that the degradation of cefuroxime axetil acetone solution under the above conditions is in line with the first-order reaction kinetics. When pH value is less than 9.54, cefuroxime axetil acetone solution is basically stable. When the pH value is greater than 9.54, the chemical stability of cefuroxime axetil acetone solution becomes worse, the degradation rate increases rapidly with the pH value, and the color of the solution becomes darker with the pH value increasing. The chemical stability of cefuroxime axetil acetone solution decreases with the increase of temperature. Provide data support for production process, crystallization process design, storage and application.
- 1
-
Prognostic Analysis of Breast Cancer Based on Conditionally Associated Complementary Genes
张屹, YAN Shuang-shuang, ZHANG Cheng, WANG Guan-fang, HUANG Hai-yun, HAN Shan-shan
Abstract:
Objective: In order to improve the survival rate of breast cancer patients and improve the clinical treatment of patients, it is necessary to study the pathogenic genes of breast cancer from a molecular mechanism. Methods: Firstly, the differential expression of 113 normal tissues and 1109 cancer tissues was analyzed. Then, a group of complementary genes was grouped in a conditional joint analysis method for differentially expressed genes, and a set of gene fitting prognostic models was selected using stepwise cox regression. Results: The six genes VWCE, SPDYC, CRYBG3, DEFB1, SEL1L2, and NMNAT2 have a harmful effect on survival rate. The four genes AMZ1, GJB2, CXCL2, and ALDOC are beneficial to survival rate.The final prognostic model of the 10 genes can significantly divide the sample into high-risk group and low-risk group, and predict the 5-year and 10-year survival rates of breast cancer patients, and the time-dependent AUC values are both Up to 0.7 or more. Conclusion: This method can take advantage of the correlation between genes to reduce dimensionality of high-dimensional data and eliminate the problem of collinearity between genes. The prognostic model of these 10 genes can predict the clinical outcome of patients provide help.
- 1
-
Study on seismic behavior of k-eccentrically braced steel structures with multi-shear links
Abstract:
To study the seismic performance of the eccentric braced structure with shear multi-links proposed in this paper, on the basis of the test model, the link cross section was designed into a multi-link model based on the constant shear area of the link web. Then eight multi-link numerical models were established using ABAQUS software, and monotonic loading analysis and cyclic loading analysis were performed. The changes of failure modes, hysteresis curve, bearing capacity, stiffness and energy dissipation capacity with the number of links were analyzed. The results show that the plastic deformation of the link is fully developed, which effectively protects other non-energy dissipation members; the bearing capacity, yield displacement and energy dissipation capacity of the structure are better than those of the single link mode; The difference in initial stiffness of each multi-links model is small (within 4%), which is smaller than that of single-link model, but the multi-link model can delay the degradation rate of stiffness. In general, the multi-links model can improve the seismic performance and it is recommended to use 2 to 4 links which is worth popularizing as a new K-eccentrically braced steel frame structure.
- 1
-
Fuzzy Predictive Control Strategy of Permanent Magnet Linear Synchronous Motor
Abstract:
In order to solve the problem that the model predictive control seeks the optimal control variable, due to the unreasonable selection of the weight coefficient, the actual current cannot closely follow the given current or the predicted output voltage fluctuates too much. Attempt to apply fuzzy control to the selection of the weight coefficient. A model predictive control method based on fuzzy control dynamically selecting weight coefficients is proposed, which can send the optimal weight coefficients to the currently running model predictive control system online. And through three groups of experiments to simulation, comparison and analysis different weight coefficients, the reasonable interval of the weight coefficient is obtained. The simulation results show that the weighting coefficient based on fuzzy control has good performance. When the load change is gentle, the output voltage fluctuation will be reduced under the condition that the current can follow the given current. The improved control system improves the anti-disturbance ability, and the weight coefficient can be changed automatically according to the actual demand.
- 1
-
Research on New DC-APF Control Strategy for DC Microgrid
Qiao Yu, Sun Huiqin, Wang Lei, Tian Jin
Abstract:
The ripple component of the DC bus voltage will affect the power supply quality of the entire DC microgrid and the safety of equipment operation. Therefore, a new DC active power filter (DC-APF) control strategy is proposed to suppress the DC bus voltage ripple. Aiming at the problems of delay in the traditional DC bus voltage ripple detection algorithm and the slow response speed and poor dynamic performance of the traditional PI compensation control current algorithm, the ripple detection method and suppression scheme are optimized based on the analysis of various work modes of DC-APF. In terms of detection, a DC bus voltage ripple detection method based on wavelet transform Mallat algorithm is proposed, which can realize rapid detection of ripple. On the basis of traditional and fuzzy PI control, an improved fuzzy adaptive PI control is proposed to realize the tracking control method of compensation current to improve dynamic performance of the system. A DC micro-grid system model with DC-APF is built in MATLAB/Simulink, and the simulation results show that compared with the traditional DC-APF control strategy, the new type DC-APF control strategy can achieve rapid detection of DC bus voltage ripple and has good ripple compensation effect. The research results can provide new ideas for ripple detection and suppression in DC microgrid.
- 1
-
Advances in Microalgae Cell Wall Disruption
Abstract:
Microalgae are the focus in the scientific research and technical development since many valuable products, including astaxanthin, lutein, high-unsaturated fatty acids and lipids, etc. could accumulate in Microalgae cells and Microalgae cultivation shows the advantages of high photosynthesis efficiency, good environmental adaptability, fast growth etc. However, cell disruption is the key step to the product recovery process. In this review, the characteristics of three microalgae are discussed, and then cell disruption strategies, including ball mill, homogenizer, hydrodynamic cavitation, ultrasonication, microwave and electromagnetic wave, pulsed electric field disruption, steam explosion, hydrothermal liquefaction, ionic liquids, nano particles, oxidation, and biological disruption, are discussed on the current situation and trends in scientific research and technical development in order to promote the commercial utilization of microalgae.
- 1
-
Computational study of the control of the electron excitation property of triphenylamine sensitized dye
LIU Yumin, ZHAO Ruihong, LI Qing, QIAN Xin, ZHANG Fan, XUE Zhiwei
Abstract:
Focusing on the intramolecular reflux phenomenon in the electron transfer process of the classical D-A-π-A triphenylamine sensitized dye RL1, four different conjugated units, including Benzene, Thiophene, Oxole, and Pyridine, were added separately between the additional receptors and π-bridge. Then the control regulation of the excitation property of dye RL1 was investigated by the quantum chemistry based on First Principle Calculation. The results show that the Benzothiadiazole could push and pull on the electron as the extra receptor. However, due to the strong electron absorption ability of the Benzothiadiazole, the electron reflux has happened in the electron transfer process. Compared with dye RL1 , the conjugated units not only could weaken the electron-absorbing ability of Benzothiadiazole, but also play a role as an electron donor. So the electron-absorbing ability of Cyanoacetic acid group could be significantly enhanced.
- 1
-
Study on adsorption properties of molecular sieves for VOCs
Abstract:
Experiments were performed using 7 adsorbents (K-A, Na-A, Ca-A, Ca-X, Na-X, Na-Y, and Na-ZSM5 zeolite molecular sieves) and 3 adsorbents (benzene, methanol, n-hexane). the study. By studying the static adsorption of adsorbents by A-type and X-type molecular sieves, the results show that molecules with a kinetic diameter smaller than the pore size of the molecular sieve are more easily adsorbed, and the molecular sieve adsorbs more polar molecules than non-polar molecules (methanol> benzene > n-hexane), using different AlO4 content (Na-X, Na-Y, Na-A and Na-ZSM5) and different balanced cations (K-A, Na-A, Ca-A and Ca-X, Na-X) molecular sieves Microwave desorption shows that the AlO4 content of the molecular sieve and its equilibrium cations have a significant effect on its microwave desorption effect (Molecular sieves with high AlO4 structure content are more suitable for microwave desorption, and molecular sieves with balanced cations Na + have strong wave absorbing ability For K + and Ca2 +).
- 1
-
Single machine scheduling with time-based maintenance and step-deteriorating jobs
Abstract:
Nowadays, the demand of “personalization” and “multiple varieties and small batch production” in machining is increasing dramatically. The great challenges of scheduling are brought about by the high flexibility of production and the necessity of equipment maintenance, and the scheduling problems are more complex due to the deteriorating effect of the production process. In this paper, the processing time is described by the piecewise linear function. Based on the properties of the periodic maintenance and the flexible periodic maintenance, two scheduling models were established respectively to minimize the tardiness penalties and maintenance cost. The single machine scheduling problem with step-deteriorating jobs and fixed periodic maintenance strategy was studied. According to the numerical experiments and parameter analysis, the key factors and non-key factors of maintenance decision were determined. The result shows that flexible periodic maintenance has no idle time between adjacent batches, and can “adaptively” compensate for the penalty time due to deterioration, which performs better significantly than fixed periodic maintenance strategy.
- 1
-
Visual Contrast Analysis of Green Logistics Research at Home and Abroad Based on Knowledge Map
Abstract:
【Purpose/significance】Under the concept of building an ecological civilization and sustainable development, green logistics is bound to be a new logistics model. The scientific knowledge map can visually show the overview and trend of green logistics research.【Method/process】A comparative study of 936 domestic and foreign data retrieved by CNKI and Web Of Science through the visualization software citespaceⅤ, from the knowledge map analysis of literature co-citation, keyword co-occurrence, keyword clustering, time zone map, and mutation words Hotspots, evolution paths and frontiers of green logistics at home and abroad.【Result/conclusion】The analysis shows that China''s green logistics research is more at the macro level, and foreign research focuses on innovation and micro level research. China''s green logistics research should focus on micro level research, and use technological innovation to accelerate the process of green logistics.
- 1
-
Research progress of water strider in bionic characteristic and engineering application
Abstract:
The water strider is a small insect in lakes, ponds, and wetlands, it relies on the excellent superhydrophobic property of legs that results from the composite micro-nano structure to stand stably on water. Characteristics of the water strider leg have attracted numerous studies and become hot topic. Scholar has conducted the investigation on the locomotion characteristic of water strider, in order to acquire design inspirations to develop superhydrophobic surface and bionic water surface robot. Starting from the locomotion characteristic of water strider, we introduced the testing method of water strider’s locomotion force. Especially, we focused on the development progress of superhydrophobic surface preparation and development of water walking/jumping robot, which belongs to engineering bionic field. The preparation of superhydrophobic surface should need to lucubrate these aspects of micro-morphological characteristic, preparation process and production cost, the development of bionic surface robot needs to consider the motion, driving mode and supporting characteristic. Based on the micro-morphological structure characteristic of water strider leg, superhydrophobic surface with remarkable and lasting efficacy and bionic water strider robot with excellent performance, complete function and highly similar motion characteristic were developed, that will be the main development trend in the future.
- 1
-
Multi-feature weighted nearest neighbor data association and tracking algorithm based on Kalman Filter
陈丰, 王利辉, 陈俊吉, 张明, 徐伟业, 李进军, 赵超
Abstract:
Aiming at the problem that the traditional nearest neighbor data association algorithm has low accuracy and is prone to missing the association, this paper proposes a multi-feature weighted nearest neighbor association algorithm. This algorithm defines a similarity function based on the obstacle data obtained by the intelligent vehicle environment perception system, and proposes a method to calculate the effective correlation degree based on the life cycle, so as to determine whether the objects are related. Then, based on Kalman filter, the associated target is updated iteratively to realize the tracking of the target. Finally, the tracking trajectory of stationary target, low-speed moving target without interaction and low-speed moving target with interaction are compared through experiments. Experimental results show that compared with the conventional nearest neighbor data association algorithm, the improved algorithm proposed in this paper, can realize accurate continuous connection of the low-speed moving target tracking, there will be no target lost or position mutation phenomenon, and the interaction and hiding between the targets have little effect on the tracking performance, so it has high validity and practicality.
- 1
-
Disambiguation of name entities embedded in meta-path heterogeneous networks
Abstract:
In the heterogeneous network formed by many online systems, such as social search and academic search, name entity disambiguation is a key problem and also a very tricky problem.Name entity disambiguation is designed to resolve the ambiguity caused by the author of the same name.This paper proposes a disambiguation model of named entity based on meta-path heterogeneous network embedding for the disambiguation problem of DBLP database.This model firstly extracts the author information, title and conference name of the article, then generates the publication journal name and the publication title matrix through word2vec model tool for word embedding.Then it is input into the GRU network for training. The GRU network is a variant of LSTM in the neural network of the computer, and then a PHNet is constructed for random walk and the meta path-based walk is used to capture the relationship between different types of nodes.Finally, the weighted heterogeneous network is embedded to realize name disambiguation.The raw data set of the experiment is the open data set of the large-scale online academic search system DBLP, and the experimental results show that the algorithm has good performance in accuracy, recall rate and other indicators.
- 1
-
An online health community user intention identification method based on BERT-BiGRU-Attention
严馨, ZHOU Feng, XU Guangyi, ZHANG Lei
Abstract:
To understand the user"s query intention is an important task in the field of QA. Traditional user intention recognition mainly uses methods based on template matching or artificial feature set, aiming at its high cost and low scalability, a hybrid neural network intention recognition model based on BERT word embedding and BiGRU-Attention is proposed. The model treats intention recognition as a classification problem. Firstly, the word embedding pre-trained by BERT is used as the input. Secondly, complete context learning is carried out through BiGRU network and the final representation of continuous statements is obtained. Through the attention mechanism, the neural network can be assisted to give more weight to the words that have a direct effect on intention recognition in sentences, making intention recognition more explicit. Finally, user intention recognition is realized through classification. Experimental results show that the proposed method can effectively improve the accuracy of intention recognition accuracy.
- 1
-
Assisted Aiagnosis of Thyroid SPECT Image Based on RESNET Model
Abstract:
Thyroid disease has become the second largest disease in the field of endocrinology. SPECT imaging is especially important for the clinical diagnosis of thyroid disease. In order to reduce the workload of clinicians, reduce the rate of misdiagnosis, and improve the accuracy of deep learning algorithm in recognizing the features of cross images in nuclear medical image-assisted diagnosis. The deep convolution generated countermeasures network (DCGAN) and high resolution generated countermeasures network (SRGAN) were used to generate images and improve the resolution to make up for the deficiency of training data.At the same time, the residual block output information is added to the cross-feature image information, and the learning of the cross-feature is added on the basis of retaining the learned image features, so as to improve the model. For cross-image features, a cross-training set is proposed to retrain the improved ResNet neural network model that has been trained with a single feature image.The experimental results show that after 100 rounds of iteration, the verification accuracy of the improved residual neural network model trained by the cross-training set is as high as 96.33%, and the verification loss is reduced to 0.1187 and tends to be stable.The recall rate, precision rate, specificity and F1 score were all above 93.8% in the recognition results. Finally, the improved neural network model and the new training method showed higher typical symptom recognition rate for thyroid SPECT imaging than other methods based on convolutional neural network (CNN).
- 1
-
Research on Fluid Flow and Heat Transfer Performance in Corrugated Tube Based on Fluent
Abstract:
In this paper, CFD software Fluent was used to simulate the fluid flow and heat transfer performance in the corrugated tube. The heat transfer performances of the corrugated tube under the conditions of different inlet velocity v(0.3m/s, 0.5m/s, 0.7m/s, 0.9m/s), peak diameter D1 (28mm, 30mm, 32mm, 34mm, 36mm), and arc length S1 (34mm, 23mm, 17mm, 13mm, 10mm) were studied respectively. The results show that the Nusselt number ,the pressure drop and comprehensive performance of different types of corrugated tube increases with the increase of inlet velocity, and increases firstly and then decreases with the increase of peak diameter D1 (arc section length S1), and finally remains as a relatively stable value. The heat transfer performance of corrugated tube is the best at the peak diameter D1of 34mm, and the Nusselt number is the largest at the length of arc section S1of 23mm, and the comprehensive performance is best. Through the parameter orthogonal analysis, it can be concluded that the inlet velocity v has the greatest influence on the wall heat transfer effect of the corrugated tube in the research scope of this paper.
- 1
-
Design of bionic prototype milli-micro Newton level two-dimensional force test system
Abstract:
In mechanical bionics field, it is necessary to measure the bionic prototypes generated milli-micro force. To satisfy the test requirement, we designed a milli-micro Newton two-dimensional force measuring system. Hardware of the system mainly includes self-developed parallel double spring cantilevers and its matched eddy current displacement sensors, milli-micro force measurement platforms which can realize the easy installation of samples, transducer output signal conditioning module and data sampling card, data processing and displaying program designed based on LabVIEW. To test the designed milli-micro Newton two-dimensional force test system, we measured the bionic prototypes provided friction force, normal force piercing resistance force. The results confirmed that the system can obtain these force values with milli-micro magnitude accurately, and display these force values in interface window in real time and intuitively, as well as realize the storage of these force values in the form of force trajectory diagram and data group effectively. Accuracy and range of this milli-micro Newton two-dimensional force measuring system is respectively up to 50μN and 800mN. Our designed system can accurately measure the milli-micro Newton two-dimensional force produced by bionic prototypes, and provide a technique & method of force measurement used in mechanical bionics.
- 1
-
Multi-objective analysis of distributed energy system driven under different operation strategy
JIA Na, ZHANG Jing, LEI Bingyin, SUN Weizhe
Abstract:
In order to seek the coordination of energy supply system in economy, security, environmental protection and energy conservation, relying on the "Internet plus", a distributed cooling, heating and power system is proposed integrated with power generation unit (PGU), ground source heat pump and energy storage system in this paper. The models about off-design condition of each device are illustrated. On this basis, four kinds of operation strategy are put forward: following electric load, following thermal load, following hybrid load and following max efficiency of PGU. Then operation cost, carbon dioxide emission and primary energy are employed as objectives to analyze the operating time, output and performances of the proposed system under off-design condition. Results show that the proposed system has better economy, lower emissions and lower primary energy consumption than conventional separate system. Under FTL strategy, the operation cost and carbon dioxide emission are lowest, which reduce by 32.7% and 45.3%, respectively. Because of the continuous operating, the reduction of primary energy is most, which is 86.7%.
- 1
-
Real-time Estimation of Road Friction Coefficient in Different Road Conditions
Abstract:
This paper proposed an method for road friction coefficient estimation based on wheel speed and braking torque of front and rear wheels in braking condition. The braking dynamic model of two-wheeled vehicle was built in Matlab/Simulink considering load transfer of front and rear axles. Sliding mode control method was used to build the ideal braking torque controller, which control objective is to control the actual wheel slip ratio of front and rear wheels tracking the ideal wheel slip ratio. In order to eliminate chattering problem of the sliding mode controller, integral switching surface was used to design the sliding mode surface. Road friction coefficient can be observed by second order linear extended state based on wheel speed and braking torque of front and rear wheels. The simulation results show that the proposed method can estimate road friction coefficient exactly with strong robustness in different road conditions, which can resist external disturbance.
- 1
-
Intelligent evacuation system guidance sign calculation and evacuation path simulation
GUO Baoliang, ZHAO Guohua, Liu Huixian
Abstract:
Nowadays, intelligent evacuation systems were widely used in large-scale integrated buildings. When emergencies such as fires, how to combine complex building structures and plan a reasonable and safe evacuation route had become one of the key research topics. A multi-start and multi-egress path planning method based on improved A* algorithm is proposed in this paper. The three-dimensional grid method was used to establish the floor map. By increasing the turning penalty value, the number of path turns was reduced. At the same time, the real-time information of the fire affected area was combined with the distance of the fire center point to improve the evaluation function, so that the search direction was more clear and the search efficiency was improved. The searched optimal path calculates the direction of each guide mark in the floor, thereby guiding people at different positions to evacuate from the optimal path. By using Matlab simulation, compared with the traditional A* algorithm, the improved A* algorithm was more smooth and the running time was shorter when calculating multi-start and multi-export evacuation path planning. At the same time, combined with fire information to ensure the safety of evacuation path, the Pathfinder evacuation simulation experiment shows that compared with the traditional static guidance mark, the improved guidance algorithm dynamically adjusts the direction of the guiding sign, so that personnel can safely and quickly evacuate and escape.
- 1
-
Research progress and development prospect of superhydrophobic bionic prototype preparation technology
Abstract:
Superhydrophobic surface can make the water droplet show a static contact angle larger than 150° and a sliding angle smaller than 10°. Based on bionic engineering principle, scholars have comprehensively researched the typical superhydrophobic bionic prototypes, and successfully prepared surfaces with excellent superhydrophobic function, which are widely used in many engineering fields, such as self-cleaning, anti-corrosion, hydrophobic ice suppression and ship drag reduction. In this review, based on the surface micromorphology and mechanism of several typical superhydrophobic prototypes of animals and plants in nature, the relationship between structural characteristics and superhydrophobic wettability properties is reviewed, and basic characterization models of surface wetting behaviors and mathematical models of superhydrophobic wetting properties are introduced. Especially, we focus on the recent progress in bionic superhydrophobic surface preparation technology, mainly including the traditional preparation methods of superhydrophobic surface, the 3D printing technology of superhydrophobic surface preparation, and the wettability characterization methods of fabricated superhydrophobic surface. Meanwhile, several aspects that should be paid attention to in near future are highlighted. This review enriches the further understanding of superhydrophobic wettability, and promotes the development of new ideas, new methods and new technologies in superhydrophobic surface preparation.
- 1
-
Curb recognition algorithm based on geometric characters and 3D point cloud features
Abstract:
Typical curb recognition algorithms have difficulty in balancing real-time performance and reliability. In this paper, with a multi-line LiDAR used, a curb recognition algorithm based on geometric features and 3D point cloud features of curb areas is proposed, which reaches a tradeoff between real-time performance and reliability. Faced with the large amount of point cloud data, the algorithm firstly proposes a ground segmentation method based on RANSAC algorithm, filtering out the ground points in the preset region of interest, and then the orderly rasterization of the remaining disordered points is carried out for matching and screening curb areas according to the curb’s geometric characters and the points’ distribution feature. After which, the least square method fused with RANSAC is proposed to achieve the robust fitting of curb curve. Experiments show that the recognition accuracy of the algorithm is more than 95% in both straight and bend scenes, and the time-consuming is less than 15ms, which indicates the good accuracy and real-time performance of the proposed algorithm. The algorithm can effectively identify road curb, thus providing a theoretical reference and method basis for intelligent vehicle driving area recognition and its’ control.
- 1
-
Modeling and hardware-in-the-loop simulation of Z-shaped aircraft
刘东辉, WANG Jinhao, SUN Xiaoyun, WANG Xiao, XU Jingjing
Abstract:
In order to improve the flight quality of UAV, study the hardware-in-the-loop simulation application of UAV control, form a set of universal UAV flight control law design and hardware-in-the-loop simulation method, the Z-shaped aircraft with complex aerodynamic characteristics is studied. According to the shape parameters of Z-shaped aircraft, the aerodynamic data are obtained. On this basis, the longitudinal linear model is established by using the principle of small disturbance linearization. The longitudinal static stability of the model is studied by adding disturbance pulses. The transfer function of each link is selected, the pitch control loop is established, the PID parameters are adjusted, the longitudinal control law is designed, and use Simulink and hardware-in-the-loop simulator for simulation. The simulation results show that UAV has good static stability, reasonable selection of PID control parameters, small system overshoot and short adjustment time, which can improve the flight quality of UAV. Hardware-in-the-loop simulation can more truly and intuitively reflect the advantages of UAV attitude. The modeling and simulation methods used can be applied to other solid systems. Fixed-wing UAV has certain versatility.
- 1
-
Research on Job Shop Scheduling Problem Based on Improved Genetic Algorithm
Abstract:
In the research of job shop scheduling problem based on genetic algorithm, the improved genetic algorithm is used to obtain the optimal scheduling results. The scheduling model is established with the shortest processing time of the workpiece as the target. An adaptive crossover and mutation probability formula is proposed, and the elite retention strategy is used to solve job shop scheduling problem. The benchmark cases LA01 and FT06 are used as simulation objects. The corresponding Gantt chart and the search process curve are obtained, and the feasibility of the improved algorithm is obtained from the simulation results.
- 1
-
Fuzzy adaptive control strategy of voltage outer loop for single-phase PWM rectifier
Abstract:
For the rectification problem of the input stage in small energy router, single-phase full-bridge PWM rectifier circuit is used in input stage and the idea of fuzzy control is introduced into voltage outer loop control strategy. Combing fuzzy control with traditional PI control, a fuzzy adaptive control strategy of voltage outer loop is proposed. Then compared with the traditional control strategy, the control strategy proposed in this paper has good dynamic characteristics and achieves rectification or inversion of the rectifier under the condition of unit power factor, which meets the requirements of energy bidirectional transmission of small energy routers.
- 1
-
Structural Analysis and Optimum Design of ECM Machine Tool Based on Variable Density Method
Abstract:
In order to improve the precision and quality of electrochemical machining of complex surface/cavity parts, the design of horizontal electrochemical machine tool which can realize the compound feeding motion of straight line and rotation was carried out. Under the impact of large processing current and high-speed electrolyte, the machine tool needs to have high stiffness to withstand dynamic and static loads. In this paper, UG software is used to build three-dimensional model of horizontal machine tool, and the simplified model is imported into ANSYS Workbench software for static analysis. The structural stiffness of the machine tool is analyzed based on deformation and stress distribution nephograms. The first six natural frequencies and modes of motion platform are determined by modal analysis, and the optimal design is carried out by using the variable density topology optimization method. Finally, the design is redesigned on the basis of considering the technological characteristics of the structure, and the lightweight design goal is achieved. The designed ECM machine tool has sufficient stiffness and stability, and can meet the requirements of actual processing.
- 1
-
Resistance welding parametric modeling based on CATIA CAA
WU Quan, XU Weiping, TANG Geng
Abstract:
CATIA CAA object extension is the most important way of self-defined object creation and is also the difficulty of development. Based on analysis of processing parameters and restrains of resistance welding, a framework for welding spot modeling via the technical route of CAA user interface design, self-defined object, parameter validation and entity creation, is advanced. Furthermore, problems of parameter automatic computing and validation are studied through examples of spot diameter computation of nut side weld and distance computation between spot center and sideline. Finally, parametric modeling of plate projection weld and nut weld of resistance welding of resistance welding for vehicle seat framework (VSF) is realized by CATIA CAA redevelopment, which improves weld design efficiency of VSF parts and provides fundamental for multi-type welding (including spot welding, arc welding, etc.) management system development.
- 1
-
Mesh Reconstruction Algorithm based on Laplace Harmonic Equation
Abstract:
Parameterization and reconstruction from unstructured mesh is one of the most important ways of improving numerical modeling and calculation. Upon triangular mesh, gradient field via harmonic equation is created, integral flow is tracked and parameterized mesh is reconstructed. First, gradient field construction theory based on discrete Laplace equation, its data structure model and solution scheme of sparse matrix are constructed. Then, one uniform algorithm for solving flow line node by integration of local coordinate transformation and parameterized equation is advanced. And schemes like gradient convergence, shortest distance and extreme parameter are optimally occupied upon special cases of no intersection or multiple intersections when tracing flow line. Finally, harmonic theory and its application in mesh reconstruction are verified via case studies, which also indicate algorithm robustness and uniqueness for mesh reconstruction representation.
- 1
-
Numerical analysis of bi-stable piezoelectric energy harvesting system with elastic support
Abstract:
In this paper, the dynamic behavior of a piezoelectric cantilever energy harvesting system with bi-stable state under elastic support is studies.Based on the magnetic force model which can induce bi-stable phenomena, the mathematical model of the system with two degree of freedom under harmonic base motion is firstly established using Newton's second law and Kirchhoff's law. By the Routh-Hurwitz criterion, the static bifurcation of equilibrium point is secondly analyzed after reducing the dimensionless governing equation. In addition, the variation of the piezoelectric cantilever beam and the variation of the output voltage with the system parameters and excitation parameters and the bifurcation diagram are obtained by Matlab numerical simulation. The results show that the amplitude-frequency curves of the system are in hard characteristic. However the variation of the amplitude of piezoelectric cantilever beam with mass and stiffness ratio are in soft characteristic. That is, within some parameters, the harmonic response of the system occurs bifurcation and leads to chaotic motion. The motion of the system can take place near the zero or non-zero equilibrium point, even jump with large amplitude between the two non-zero equilibrium points. Under the same parameters, the system has a richer form of motion when it is in bi-stable relative mono-stable state, and significantly increases the voltage output and response frequency band of the system.
- 1
-
An overview of braking intention recognition for longitudinal dynamic control of vehicles
尘帅, WANG Jizhong, ZHANG Xilong, LV Lin, ZHENG Longyue
Abstract:
As a prerequisite for the control of the brake by wire system, the identification of braking intention has a direct impact on the accuracy of the vehicle control system,and then it affects the vehicle runing safety under specific working conditions,thus in order to improve the active safety and braking performance of the vehicle, aiming at the longitudinal stability control problem in vehicle dynamics, the braking intention is taken as the breakthrough point,and the classification of braking intentions is introduced in this paper. At the same time, the vehicle dynamics control of braking intention recognition based on the research status at home and abroad is outlined. Besides, combining with the braking intention recognition feature selection problem, this paper focused on the comparative analysis of several typical braking intention recognition method including fuzzy inference system、neural network 、adaptive neural fuzzy inference system、hidden markov modle、cluster analysis. Considering the status quo of research, the research emphasis and direction of braking intention recognition for vehicle dynamics control is pointed out.
- 1
-
Research on influencing factors of heat transfer and CFD numerical simulation of oblique tee
LU Hongliang, CUI Haiting, DENG Xiaoye
Abstract:
In order to study the flow and heat transfer process of the fluid in oblique tee, the CFD simulation of flow and heat transfer processes of the fluid in oblique tee with the included angle of 20o-90o, the velocity ratio of 2-3.5 and the branch position of 500mm-1000mm were carried out based on Fluent software, and the sensitivity analysis of various parameters influencing the average heat transfer coefficient of wall surface was conducted by orthogonal experimental design. The results show that as the included angle or velocity ratio increases, the maximum velocity of fluid at the outlet of oblique tee increases gradually, and the influence of velocity ratio is more significant. The average heat transfer coefficient of wall surface also increases with the increases of included angle and velocity ratio, but the decrease of branch position; the branch position mainly affects the average heat transfer coefficient of wall surface, and its influence on the velocity is negligible. The average heat transfer coefficient of wall surface is increasing with the decrease of the branch position. According to the different effects of various parameters on average heat transfer coefficient of wall surface, branch position l > velocity ratio λ >included angle θ, which means that the closer the branch pipe is to the inlet of main pipe, the greater the velocity ratio, and the greater the included angle, the better the heat transfer effect of wall surface will be. Therefore, the branch position is the primary factor to influence the heat transfer effect of oblique tee.
- 1
-
ZHANG Chunhui, WANG Laigui, ZHAO Quansheng, LI Weilong
2015,36(1):90-99, DOI: 10.7535/hbkd.2015yx01016
Abstract:
How to quantitatively evaluate the permeability change of coalbed subjected to liquid nitrogen cooling is a key issue of enhanced-permeability technology of coalbed. To analyze the evolution process of permeability of coupled coal deformation, failure and liquid introgen cooling, the coal is supposed as elastic, brittle and plastic material. Its deformation process includes elastic deformation stage, brittle strength degradation stage and residual plastic flow stage. Combined with strength degradation index, dilatancy index of the element and Mohr-Column strength criterion, the element scale constitutive model with the effects of confining pressure on peak-post mechanical behaviors is built. Based on the deformation process of coal rock, there exist two stages of permeability evolution of the element including decrease of permeability due to elastic contraction and increase due to coal rock element's failure. The relationships between the permeability and elastic deformation, shear failure and tension failure for coal are studied. The permeability will be influenced by the change of pore space due to elastic contraction or tension of element. Conjugate shear zones appear during the shear failure of the element, in which the flow follows so-called cubic law between smooth parallel plates. The calculation formulas of the permeability and the aperture of the fractures are given out based on the volumetric strain. When tension failure criterion is satisfied with the rock element fails and two orthogonal fractures appear. The calculation formulas of the permeability and the width of the fractures are given out based on the volumetric strain. Further, combined with the thermal conduction theory the permeability evolution model of coupled coal deformation, failure and liquid nitrogen cooling is presented. Then Fish function method in FLAC is employed to perform the model. The permeability's evolution process for coal bed cryogenically stimulated by flowing liquid nitrogen through gas production well in Wangyingzi mine, Liaoning province, is simulated and the results include: 1) When liquid nitrogen(LN2) is injected into a rock at warm reservoir temperature, heat from the rock will quickly transfer to the liquid nitrogen resulting in rapid cooling and contraction of coal bed. The nearer the position is to bore hole, the bigger the shrinkage deformation and thermal stress and coal fail when tension stress sufficiently built up. In this paper the tension failure band after 10 days' LN2 cooling is 0.65 m. 2) In tension failure area the cracks from cooling stimulation lead to the significant growth of permeability. The maximum permeability for element is 1.97×105 times more than that before cooling. 3) Apart from the bore hole, the thermal tensile stress leads to the growth of permeability at a rate of 1%~14%, far less than that in the tension failure area. 4) With increasing time the failure area gradually slowly grows up. It indicates that the longer cooling time does not mean better effects. 5) The cooling fracturing area is found to have a 1.0 m band. In practical engineering the pressure in hole bore and phase transition of water also influences the deformation and failure of coal, which leads to much more failure zone of cooling. 6) The evolution process of permeability of coupled coal deformation, failure and liquid introgen cooling can be better reflected by the model in this paper. This study is hoped to provide a simple but reasonable description of the permeability evolution of rocks subject to liquid nitrogen cooling.
-
WANG Jianxia, LIU Menglin, XU Yunfeng, ZHANG Yan
2021,42(1):48-59, DOI: 10.7535/hbkd.2021yx01007
Abstract:
Most of the real-life networks are heterogeneous networks that contain multiple types of nodes and edges, and heterogeneous networks integrate more information and contain richer semantic information than homogeneous networks. Heterogeneous network representation learning to have powerful modeling capabilities, enables to solve the heterogeneity of heterogeneous networks effectively, and to embed the rich structure information and semantic information of heterogeneous networks into low-dimensional node representations to facilitate downstream task applications. Through sorting out and classifying the current heterogeneous network representation learning methods at home and abroad, reviewed the current research status of heterogeneous network representation learning methods, compared the characteristics of each category model , introduced the related applications of heterogeneous network representation learning, and summarized and prospected the development trend of heterogeneous network representation learning methods. It is proposed that in-depth discussion can be carried out in the following aspects in future: First, avoid predefined meta-paths and fully release the automatic learning capabilities of the model; Second, design heterogeneous network representation learning method suitable for dynamic and large-scale networks.
-
MA Jing, WANG Ruiyang, WEN Ning
2021,42(1):75-81, DOI: 10.7535/hbkd.2021yx01010
Abstract:
In order to improve the oxidation resistance of 304 stainless steel, SiO2 thin film was prepared on the surface of stainless steel by sol-gel method with tetraethyl orthosilicate (TEOS) as raw material. The effect of film layers on the high temperature oxidation resistance of stainless steel at 900 ℃ was studied by means of oxidation kinetics, XRD, SEM and EDS. The results show that the adhesion of SiO2 film to stainless steel matrix is good, which promotes the selective oxidation on the stainless steel surface and the formation of protective Cr2O3 and NiCr2O4 oxide layers. The high temperature oxidation resistance of stainless steel is improved remarkably. The oxidation resistance of the sample coated with three layers of SiO2 film proforms the best, and the oxidation weight gain and oxidation spalling of the sample are only 58.1% and 41.4% of the uncoated sample after 100 hours of cyclic oxidation at 900 ℃. The high temperature oxidation resistance of stainless steel is effectively improved through SiO2 film coating, which is another attempt of surface treatment method applied to high temperature environment, and provides reference for other thin films prepared by sol-gel method.
-
CHEN Qi, ZHANG Renhui, HE Zhongyi, XIONG Liping
2021,42(1):1-7, DOI: 10.7535/hbkd.2021yx01001
Abstract:
In order to explore the lubrication performance of alcohols under high loads and high speeds conditions, especially the relationship between carbon-chain length and hydroxyl number and lubrication performance, the effects of carbon-chain length and hydroxyl number on the lubrication performance were well studied. The tribological properties of a series of alcohols were investigated by a four-ball tribological machine, and the effects of the carbon-chain length and the hydroxyl number on their lubricating properties were investigated by means of viscometer, transmission electron microscopy (TEM) and Raman. Experiments show that with the increasing of the carbon-chain length, the run-in period and the time for achieving stable friction coefficient were shorted, and the wear was reduced; with the increasing of the hydroxyl number, the wear decreased with no obvious run-in period and consistent fluctuation of friction coefficient for ethylene glycol and continuous decrease of friction coefficient for glycerol. It is found that friction-induced graphene is superior to amorphous carbon in effectively promoting the tribosystem to achieve the stable friction coefficient and shorten run-in period, which provides reference for the application of alcohols in the field of mechanical equipment.
-
SUI Bingdong, ZHANG Pai, WANG Xiaojun
2021,42(1):22-29, DOI: 10.7535/hbkd.2021yx01004
Abstract:
In order to solve the problems of low recognition accuracy and easily affected by illumination conditions in the gesture recognition, an improved YOLOv3 gesture recognition algorithm was proposed. Firstly, a smaller detection scale was added to the original three detection scales to improve the detection ability of small targets; secondly, DIoU was used instead of the original mean square error loss function as the coordinate error loss function, the improved focal loss function was used as the confidence loss function of the boundary frame, and the cross entropy was used as the loss function of the target classification loss function. The results show that when the improved YOLOv3 gesture recognition algorithm is applied to gesture detection, the map index reaches 90.38%, which is 6.62% higher than that before the improvement, and FPS is nearly twice as high as before. After the new model is trained by the improved YOLOv3 method, the gesture recognition accuracy is higher, the detection speed is faster, the overall recognition efficiency is greatly improved, the loss weights of simple samples and difficult samples are balanced, and the training quality and generalization ability of the model are effectively improved.
-
2021,42(1):67-74, DOI: 10.7535/hbkd.2021yx01009
Abstract:
As the side effects of antibiotics are becoming increasingly prominent and the number of approvals is declining year by year, it is urgent to develop other active substances that are similar in functions and not easy to develop drug resistance. Antimicrobial peptides (AMPs) have broad-spectrum antibacterial activities, thermal stability and unique mechanism of action. They can not only play the role of anti-bacterial infection in vivo and promote apoptosis of cancer cells, but also be used as chemotherapeutic agents against virus and antibacterial materials for hospital settings. In this paper, developments related to antimicrobial mechanisms and activities of antimicrobial peptides against drug-resistant bacteria, anticancer and antiviral infection in the field of medicine are systematically reviewed. The problems of stability, hemolytic and toxicity of antimicrobial peptides are elucidated and the development prospects of AMPs in medicine are provided. Further research on AMPs can be carried out in the following aspects in the future. 1) Antibacterial mechanism in vivo are studied to promote the development and application of antimicrobial peptides；2）Structures of AMPs are optimized by replacing and modifying amino acid residues and hybrid peptides are synthesized to improve their activities, reduce side effects and prevent drug resistance; 3）Application of delivery systems for AMPs or combination of AMPs with green natural extracts is investigated to improve their antibacterial activity and bioavailability.
-
2021,42(1):8-14, DOI: 10.7535/hbkd.2021yx01002
Abstract:
In order to improve the positioning ability of ultra wideband network in non-cooperative indoor environment, the theory of centreless positioning algorithm was used to solve and analyze the output distance information of ultra-wideband ranging, and the relative positioning results were obtained. The positioning results of the system were compared with the results of the photoelectric calibration system, and the accuracy was evaluated. The results show that, compared with the traditional ultra-wideband positioning model, the combination of ultra-wideband ranging and centreless positioning algorithm can realize the centreless positioning and the relative positions among nodes, and finally determine the relative positions among nodes. The combination of UWB ranging and centreless positioning algorithm has good stability and accuracy in relative positioning, and can be widely used in various indoor and outdoor scenes.
-
Research on impulse interference suppression method based on short time fractional Fourier transform
WANG Xiaojun, XUE Linbo, WANG Yanpeng
2021,42(1):15-21, DOI: 10.7535/hbkd.2021yx01003
Abstract:
In order to solve the problem that the impulse interference near the service frequency band of aviation radio navigation affects the receiver, and further improve the anti-jamming ability of GNSS system, a impulse interference suppression method based on STFRFT (short time fractional Fourier transform) was proposed. The optimal rotation order of the received signal was determined, and STFRFT was applied to the signal to obtain the two-dimensional distribution of time-frequency surface through coordinate rotation. Under the optimal order, the adaptive time-varying filter was used to separate the interference and the signal, so as to suppress the interference. The simulation results show that the adaptive filtering algorithm based on STFRFT has the best effect of eliminating interference compared with several traditional methods, and retains more useful signals while suppressing impulse interference. By combining STFRFT and adaptive time-varying filtering technology, the ability of suppressing impulse interference is improved, which provides some reference for the impulse anti-jamming technology of aviation radio navigation service.
-
XIE Yinghua, LIU Zhaoxia, ZHANG Meimei, ZHANG Dongmei
2021,42(1):60-66, DOI: 10.7535/hbkd.2021yx01008
Abstract:
In order to avoid the irritation of metformin hydrochloride to the stomach and realize its release in the intestine, with metformin hydrochloride as the main drug and chitosan/sodium alginate as the composite support, the optimal formulation and preparation technology of metformin hydrochloride loaded pH-sensitive hydrogel microspheres were selected, and the pH-sensitivity and in vitro drug release characteristics were investigated. The formulation and process were optimized by single factor test and orthogonal test. The morphology was characterized by SEM. The entrapment efficiency and drug-loaded amount were determined by UV. The release degree was studied by rotating basket method. The results show that the optimized prescription is as following: chitosan and sodium alginate with a total concentration of 2%(mass-volume ratio), mass ratio of sodium alginate to chitosan =1∶1, mass ratio of drug to sodium alginate=2∶5, and 3.5% CaCl2(mass-volume ratio). The cumulative release rate is less than 4% in artificial gastric juice within 6 h, and up to 96.4% in artificial intestinal juice within 6 h. The formulation and process are stable and reliable, and the hydrogel microspheres have high mechanical strength, good biodegradability and stability. So it is a new metformin hydrochloride delivery system.
-
LI Chunhua, QIN Yunfan, LIU Yukun
2021,42(1):30-37, DOI: 10.7535/hbkd.2021yx01005
Abstract:
Aiming at the problem of poor precision performance of traditional Bayesian model saliency detection algorithm, a Bayesian model saliency detection algorithm based on improved convex hull was proposed. Firstly, the foreground of the image was extracted by the manifold ranking algorithm, which was used as the prior probability in Bayesian model. Secondly, Harris corner detection algorithm based on color enhancement was used to detect the feature points of the image in three color spaces of RGB, HSV and CIELab; the convex hulls in RGB, HSV and CIELab spaces were constructed respectively; and the intersection of convex hulls were obtained. Thirdly, the saliency region map was calculated by Bayesian model according to the prior probability and the observed likelihood probability obtained by combining convex hulls and color histograms. Finally, the proposed algorithm was tested in two public data sets MSRA and ECSSD. The experimental results show that the proposed algorithm can suppress the background noise effectively and detect the salient areas completely. The test results of F-measure value in MSRA and ECSSD databases are 0.87 and 0.71 respectively, and the accuracy-recall rate curve is higher than that of traditional classical algorithms in complex image databases. The proposed algorithm improves the detection effect of the traditional classical algorithm and the accuracy of saliency map detection.
-
YIN Yanan, ZHEN Ran, WU Xiaojing, ZHANG Chunyue, WU Xueli
2021,42(1):38-47, DOI: 10.7535/hbkd.2021yx01006
Abstract:
In order to solve the problem that ant colony algorithm is easy to fall into local optimum in UAV route planning, an improved ant colony algorithm was proposed. The upper and lower limits of pheromone volatilization factor and pheromone were set to prevent ants from falling into local optimum because pheromone on short path was too high or pheromone on long path was too low. At the same time, under the influence of multiple heuristic factors, the overall length of the path was taken as an adaptive heuristic function factor to determine the state transition probability. When the path length was large, the adaptive heuristic function factor was small, which reduced the probability of choosing the path by the ant colony. The experimental results show that the improved algorithm reduces the path length by 6.4% and the variance of the optimal path length by 85.78%, which increases the consideration of environmental integrity, shortens the path length, reduces the number of iterations, and jumps out of the local optimum. In the case of increasing environmental complexity, the algorithm can effectively choose a better path and provide a theoretical basis for UAV route planning after introducing the adaptive heuristic function factor.
-
MENG Zhian, LU Suling, YAN Huajun, HAN Pengbiao, HU Xilei, WANG Tonghui, WANG Hao
2021,42(1):82-90, DOI: 10.7535/hbkd.2021yx01011
Abstract:
In order to solve the problems of backward production technology, long processing cycle and low material utilization rate in traditional U-shaped steel tie rods, an integrated steel tie rod forming process was proposed. Taking the preform forming of 35 steel tie rod U-shaped head as the research object, a three-pass heating upsetting method was designed. The DEFORM-3D finite element software was used to analyze the simulation results of the temperature field and stress field after upsetting under different process conditions. The hot forming process parameters with better forming effect were discussed, and the feasibility of forming was verified through experiments. The results show that the optimum hot forming process parameters of each pass are as follows: the initial forging temperature of the first pass is 1 150 ℃, while the punch speed is 20 mm/s; the initial forging temperature of the second pass is 1 150 ℃, while the punch speed is 30 mm /s; the initial forging temperature of the third pass is 1 100 ℃, while the punch speed is 20 mm/s. Under the hot forming process parameters, the forming forces of each pass are 1 520, 2 090, 5 290 kN, and the expansion forces of each pass are 5 870, 6 710, 8 830 kN, respectively. After upsetting, the metal streamline distribution is reasonable, there is no crossover and folding phenomenon, and the forming effect is good. The equivalent stress distribution inside the part is relatively uniform while preparing the preform in the three-pass hot upsetting method, which can form a good quality part. It provides a certain reference for the upsetting aggregate process design and equipment selection of the U-shaped head perform of 35 steel tie rod.
-
LIU Qing, LIU Bin, WANG Guan, ZHANG Chen, LIANG Zhixing, ZHANG Peng
2019,40(1):68-78, DOI: 10.7535/hbkd.2019yx01011
Abstract:
In recent years, the research on Digital Twin is in the ascendant. As a new paradigm or concept, it shows great potential. However, the connotation and scope of the Digital Twin concept is still uncertain, especially the Digital Twin Model definition is not clear.According to the pattern category, the Digital Twin Model can be divided into general model and special model, in which the special model is still the focus of current research, and the research content is mainly embodied in the use of Digital Twin method to model specific projects. It also includes concept for developing specialized models. These specific projects in addition to the traditional manufacturing related to parts measurement and quality control, manufacturing, design and work processes, as well as system management, but also in the field of biomedical applications and applications for petroleum engineering and so on. There are many tools and techniques for developing special models, such as general industrial software, special industrial software, simulation platform and self-developed secondary development tools, etc.The research object of the Digital Twin general model is not specific to a specific project, but how to represent the controlled elements of the model as a group of common objects and the relationships between these objects. This provides a consistent approach to the management and communication of controlled elements between different environments. The research on the general model is mainly divided into the conceptual research and the model implementation method; the research heat of the two directions is almost the same. Conceptual research ranges from product lifecycle management to system behavior description, such as general system behavior and system reconfiguration, and to product configuration management, to specific workflow, such as design methods, manufacturing systems and manufacturing processes. The research content is relatively divergent, and there is no particularly prominent hot spot. The research of Digital Twin general model implementation is mainly reflected in the modeling language construction, the model development methods exploration, the specific tools usage, the Meta-model concept implantation and the model algorithm exploration.Digital Twin Model is one of the core areas of Digital Twin research. Its future research focuses on how to integrate the external features and intrinsic properties from different Digital Twin artifacts into a model with interoperability, interactivity and scalability for more efficiently realizing the information flow between the physical world and the digital world, thus achieving the universal Digital Twin application, and then supporting the CPS (Cyber Physical Space) and CPPS (Cyber Physical Production System) construction. To this end, the next problem in the Digital Twin Model needing to be solved first is how to dock the standard reference architecture, such as the RAMI4.0 (Reference Architecture Model Industrial 4.0) proposed by Germany and the IMSA (Intelligent Manufacturing System Architecture) by China, etc. Secondly, the Digital Twin Model needs a unified method to describe and it also needs consistent conclusions, in order to standardize the models established by independent development, thus improving the interoperability and scalability of the model. Otherwise, the performance of the model will decrease significantly as the system scales raise. Thirdly, the research on China's Digital Twin Model requires the support of domestic professional industrial software and modeling software, so that the Chinese scholars can carry out in-depth research that is more in line with national conditions.
-
WEN Juan, LI Fu, DING Junjun, LI Gang
2015,36(1):1-8, DOI: 10.7535/hbkd.2015yx01001
Abstract:
Urban rail transit vehicles have been more and more attractive to people as a kind of fast, comfortable, energy-saving, environmental protection and safe transportation. But because of the vehicle noise and vibration, urban rail vehicles also face severe challenges. The research of resilient wheels has been continuously developed and improved. Based on the review of development background and structure sorts of resilient wheels, the advantages of resilient wheels are described, and the research status of noise and vibration reducing, infinite element strength analysis, vehicle dynamic analysis and the wheel-rail wear of resilient wheels are discussed. Taking the low-floor LRVs (light rail vehicles) in domestic and overseas as example, the development and application of the resilient wheels in city rail transit is described, and the application prospects of the resilient wheels in LRVs in domestic and the future research direction of elastic wheel are discussed.
-
CUI Hai-ting, ZHANG Gai, JIANG Jing-zhi
2012,33(5):453-458, DOI: 10.7535/hbkd.2012yx05016
Abstract:
By using the solidification/melting model of FLUENT software, the melting and solidification process of the aluminum-silicon alloy in a cylinder heat storage with double wall were simulated numerically. Considering the third kind of boundary condition, the dynamic temperature field distribution and the position of the phase interface change moving with time are obtained. And the melting and solidification duration time is also calculated. The results have important reference value for the numerical simulation of the phase change problem and the design of phase change energy storage device.
-
QIN Si-liang, WANG Qing-guo, QU Zhao-ming, LEI Yi-san
2012,33(4):309-312, DOI: 10.7535/hbkd.2012yx04007
Abstract:
The permittivity of carbon fibers in different composites is calculated and discussed by using M-G equations, Bruggeman equations and generalized M-G equation. Results show that for high draw ratio fibers, all the three equations can calculate out the permittivity with the same numerical level and variation trend. Generalized M-G equation and M-G equation have a similar result but Bruggeman''s result is smaller. All three equations become invalidation when fibers'' concentration reaches its percolation threshold, which means that all three equations are useful at low concentration.
-
2008,29(4):299-304, DOI: 10.7535/hbkd.2008yx04010
Abstract:
Based on the developed rehabilitation manipulator, study on the control system is carried out, such as embedded system platform with the ARM microprocessor S3C2410as its core, motor control module and data acquisition module based on serial peripheral interface (SPI) bus, control software and graphical user interfaces (GUI) etc. According to the mechanical system, a sensor system is also designed to realize the function of acquisition of rehabilitation dada during rehabilitation motion. The test proves the feasibility of the system which can be used in clinic in future.
