Abstract:Turbine blades will fail due to fatigue fracture caused by vibration at high-speed rotation,resulting in damage of rotating machinery.Blade tip-timing measurement technology is the most promising non-contact blade vibration real-time monitoring method at present,and 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 and research results of blade tip-timing and blade tip clearance measurement technology in domestic and international were summarized.It was clarified that the current research is still in the incomplete maturity stage of simulation and experimental measurement,and the research prospects of blade tip-timing and blade tip clearance measurement technology were provided.It was pointed out that future research 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.

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 were studied.Firstly,the elastic micro element hypothesis of rock was carried out,and by combining 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 were derived.Then,the model was 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,and the physical significance of the parameters of the model and the influence law on the model are clear;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 in-depth study of the rock constitutive equation after microwave irradiation can provide some reference for the related calculation and numerical simulation of microwave irradiated rock,and improve the development of microwave-aided rock breaking technology.

Abstract:In order to improve the accuracy of short-term traffic flow prediction,a short-term traffic flow prediction method of expressway based on the combined model of complementary ensemble empirical mode decomposition (CEEMD) and gated recurrent unit (GRU) was proposed.Firstly,the unstable original traffic flow time series data were decomposed into relatively stable multiple modal components by complementary ensemble empirical mode decomposition algorithm.Then,a GRU model was established for each decomposed modal component sequence for one-step prediction.Finally,the predicted value of each component was superimposed to obtain the final prediction result,and the measured traffic flow data of north-south elevated expressway in Shanghai was used to verify and analyze the model.The experimental results show that the prediction effect of 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 [BF]33.4%[BFQ],[BF]25.6%[BFQ] and [BF]18.3%[BFQ],respectively.CEEMD-GRU combination model can effectively extract the characteristic components of traffic flow data and improve the prediction accuracy,which provides scientific decision-making basis for traffic control management.

Abstract:Aiming at 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 peak factor was extracted to represent the distortion degree of the waveform,the margin factor was extracted to represent the stability degree of the signal,the spectral entropy was extracted to represent the complexity degree of the spectrum structure,and PSO-SVM was combined to realize load identification.Experimental results show that this method can solve the problem that the electrical current waveform is too similar to identify successfully,reduce the training time,and improve the recognition accuracy and efficiency.This method introduces the 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 reference for the flexible selection of load characteristics in practical application.

Abstract:In order to realize the traceability of the whole process of special steel bar production information,the production environment and shape characteristics of special steel bar were analyzed.The marking scheme based on double mark points was adopted,and the machine vision technology was used to realize the character recognition of the end face of the bundled special steel bars.First,Hough transform was used to segment the end face image of the bundle of special steel bars into single ones.Secondly,an image enhancement algorithm based on wavelet transform was used to enhance the end face image of a single special steel bar.Then,the MSER algorithm and the edge detection algorithm were combined to complete the detection of the character area of a single special steel bar,and the character segmentation was completed based on the projection method.Finally,the end face character recognition of each special steel bar was completed by creating and training an SVM classifier,and the end face character recognition results of the bundle of special steel bars were output and saved.The results show that the new algorithm can meet the requirements of character identification in the production process of bundles,and the accuracy of character recognition can reach [BF]97.35%[BFQ].With combination of the Hough transform,the wavelet transform image enhancement algorithm,MSER algorithm,edge detection algorithm,projection method,and SVM classifier and other algorithms to character identification of special steel bar end face,the new algorithm provides reference for information acquisition,information transfer and information traceability of special steel bar production.

Abstract:To solve the problem caused by kernel entropy component analysis (KECA) for selecting the same kernel parameters for different faults,a fault detection of industrial process based on ensemble kernel entropy component analysis (EKECA) was proposed.Firstly,a series of kernel functions with different width parameters were selected to project the nonlinear data into the kernel feature space.The eigenvalues and eigenvectors with large contribution to Rényi entropy were selected to obtain the transformed score matrix.The multiple KECAsubmodels were established.Secondly,the test data were projected onto each KECA submodel.The statistics of each KECA submodel were calculated to obtain the detection results.Finally,the detection results of each KECA submodel were turned into probability by Bayesian decision.The unified statistics were calculated by ensemble learning strategy and judged whether it exceeds the control limit.The algorithm was applied to a numerical example and the TE process.The simulation results show that the proposed algorithm can effectively improve the fault detection rate and reduce the false alarm rate compared with traditional EKPCA,KECA and other algorithms.This method solves the problem of selecting kernel parameters for different faults in the traditional KECA algorithm and provides a reference for improving the performance of KECA algorithm in fault detection of nonlinear industrial processes.

Abstract:A hybrid neural network and attention mechanism (Att-CNN-GRU) is presented to solve the problems of fast attenuation,strong interference,ambiguous disturbance characteristics and ineffective signal detection in magnetic field proximity detection of underwater targets.A method for detecting time series disturbance signal of underwater target with power frequency magnetic field is presented.The 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 method is compared with the prediction and detection performance of CNN-LSTM model without attention mechanism and single CNN and LSTM network model.The results show that the error of signal fitting is reduced by [BF]36.24%[BFQ],[BF]14.44%[BFQ],[BF]4.878%[BFQ] and the target detection accuracy is [BF]83.3%[BFQ] compared with the traditional methods.Therefore,the CNN-GRU model with Attention mechanism has better performance than CNN,LSTM and CNN-GRU models.As an auxiliary means,it can effectively solve the problems of weak disturbance signal,unclear disturbance law and more background noise in power frequency magnetic field detection,to realize the fitting and detection of power frequency magnetic disturbance signal to underwater target.

Abstract:As synchronous blocking wastes system resources and affects program performance in concurrent processing,an automatic refactoring approach based 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 were used in this approach,so that the operation mode of shared variable data was determined.Then four asynchronous refactoring modes were set based on the asynchronous mechanism of CompletableFuture.Finally,the code was refactored according to different modes.An automatic tool AsynRef was implemented by Eclipse and four large-scale practical applications such as HSQLDB,Jenkins,JGroups,and SPECjbb2005 were automatically refactored by AsynRef.AsynRef was evaluated via the number of refactored locks,changed lines of code,accuracy,program performance after refactoring.Among the 919 synchronous methods contained in the four programs,387 asynchronous mechanism conversions were completed.After Asynref was used for asynchronous mechanism refactoring,the program execution performance was improved by 8% to 39%.AsynRef can refactor for aynchronized mechanism effectively.Compared to manual refactoring,the refactoring efficiency is improved significantly.

Abstract:In order to explore the feasibility of arc additive processing of metal powder-cored welding wire,30CrMnSiA high-strength steel powder-cored wire was adopted,combined with high-speed camera and electric signal synchronous acquisition system,to analyze the droplet transfer characteristics and arc stability of the wire under pulse melting and gas shielded welding process.Under certain process parameters,the influence of pulse process WAAM on formability,microstructure and mechanical properties of deposited parts of high-strength steel powder-cored wire was discussed.The experimental results show that the droplet transfer type of high-strength steel powder-cored welding wire is a short circuit transition with non-axial droplet and multiple pulses one drop;the transverse and longitudinal mechanical properties of the deposited part are different;both the strength and toughness along with transverse are better than that of longitudinal direction;there are a large number of dimples on the transverse and longitudinal fractures of the deposited parts,which suggest that the fracture modes are both micropore aggregation plastic fracture,and the size of dimples on the longitudinal fracture is significantly larger than that in the transverse fracture.Therefore,when the metal powder-cored wire is applied to the field of additive processing,its performance meets the application requirements,and the deposited parts with excellent microstructure and mechanical properties can be obtained.The research results provide reference for improving the additive processing efficiency and performance of the metal powder-cored wire.

Abstract:In order to solve the embrittlement problem of coarse grain zone (CGHAZ) of deep-sea X70 pipeline steel in actual welding,the thermal simulation study of X70 pipeline steel was carried out under different thermal cycle processes.X70 pipeline steel CGHAZ was simulated by Gleeble-3800 thermal simulator to study the microstructure and toughness of CGHAZ under different heat input (HI) conditions in the range of 10~60 kJ/cm.The microstructure and toughness of CGHAZ were characterized by means of optical microscope (OM),scanning electron microscope (SEM) and Charpy impact test.The results show that the microstructure of the test steel under different heat input is mainly composed of granular bainite (GB),bainite ferrite (BF) and martensite-austenite component(M-A component).When HI increases continuously,the proportion of BF decreases,the proportion of GB increases,the M-A component coarsens,and the impact absorption energy first increases and then decreases.In the case of 20 kJ/cm,the excellent combination of BF and GB is obtained,the fracture is ductile fracture,and the impact absorption energy reaches [BF]173.8[BFQ] J;when HI is greater than 20 kJ/cm,the fracture is dissociated and fractured,and the impact absorption energy decreases obviously,with the lowest of [BF]18.8[BFQ] J.Therefore,lower heat input can improve the toughness of CGHAZ,make X70 pipeline steel have high strength,high toughness and good weldability,and provide some theoretical guidance for the optimization of welding process.

Abstract:To solve the intractable multiple automatic guided vehicles (AGVs) scheduling problem encountered in the sorting processes of the logistics sorting centers,a large-scale AGV scheduling problem was studied on the basis of considering the sorting time windows and charging requirements.A general variable neighborhood search (GVNS) algorithm was proposed to minimize the makespan of the sorting operations,in which the assignment of transferring packages to AGVs and the sequence of sorting tasks for each AGV were determined.The traversal insertion heuristic was developed to generate the initial solution of the developed algorithm to ensure the constraint of time windows.Ten neighborhood operators were designed to optimize the initial solution for the iteration of the algorithm.Different sized test instances were compared,and the impacts of AGV charging rate and quantity configuration on sorting efficiency were analyzed.The results show that the GVNS algorithm is superior in computing time and solution performance.It can obtain the approximate optimal solution in a short time.The average computing time of GVNS is only [BF]532.78[BFQ] s，which is obviously better than the mixed integer and constraint programming models;when the number of packages is 100,the most suitable number of AGVs is 14.Therefore,GVNS can effectively solve the large-scale and multi-AGV scheduling problem with charging demand and hard time window,improve the efficiency of logistics sorting,and help enterprises find the scientific and reasonable AGV configuration scheme.

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 were analyzed.The results show that the main failure mode of the end-plate connection joint is 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 joints increase by about 22%,13% and 22%,respectively.When the composite slab and the upper flange of steel beam work together,the load is 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 are 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,which provides reference for further improving the performance of prefabricated joints.