作为网络物理空间CPS（Cyber-Physical Space）建设的重要支撑技术之一，数字孪生的应用在航空航天、智能制造、智慧城市、智慧医疗、智慧教育等多领域都已出现，但在实践过程中也出现了一些问题，如数字孪生概念泛化,易导致理解偏差从而造成产学研用目标不一致、实践结果不受目标用户认同；具体实施缺乏通用有效方法,导致成果受局限从而造成缺乏普遍性实践案例、较难以形成公认的典型案例。为解决这些问题，需对数字孪生概念边界进行约束，并对数字孪生方法边界进行延伸，从而形成数字孪生的新边界，促进共识形成，增加实施方法，更好地推动其发展。 在概念上，物理实体是一种具备多种性质的物质集合体，其具有复杂性、真实性、即时性的特点，可随外界条件变化按照客观规律进行动态演化。在进行将物理实体映射到数字孪生的研究时，极易将概念范围不断进行扩张，如将动态演化过程模拟——仿真，外界条件——数据，甚至对象——物理实体等全部包含在内。如此以来，数字孪生的概念将丢失其核心，不易达成一致意见。 在方法上，基于对在多场景下相关应用的详细调研分析，现有数字孪生研究往往越过对物理实体的感知过程，直接依托原有专业领域的模型或模型构建方法进行实施。这种方法在取得一些进展的同时，局限性已显现：首先，已有模型多聚焦于细分领域，在领域间无法通用；其次，已有模型中既少有体现数字孪生模型高保真、多尺度、多物理场的特点，更罕有涉及对应全生命周期的信息流动的内容，直接套用无法保证数字孪生的有效实现；再次，从已有认知的高度直接进入建模过程可能造成成本巨大，如美军的世界公认的典型案例ADT计划，建设时间以十年计，投入人力物力巨大，这也对产业界进入数字孪生实践造成进一步阻碍。 为应对这些挑战，在概念边界方面，本文提出数字孪生应回归其数字化的模型的本质，以模型为中心进行有效约束，从而促使产学研用各方的理解达成一致。而对于方法边界的延伸方面，本文提出了一种面向多感知的数字孪生模型构建方法，即按照人类对物理世界的一般认识过程——先经由各种感知方法对特征获得感性认识，而后经各种认知过程进一步形成理性认识——由浅入深、由易到难，由简到繁的来进行数字孪生的实践。首先，通过视觉、听觉、触觉和动力感知、嗅/味觉、与反映条件变化的控制数据相结合等多感知方法建立物理实体的数字孪生初始模型，从而在模型建立之初就聚焦于物理实体的复杂性和真实性，充分体现数字孪生模型的特点，有效增强模型的实用性和通用性；其后，将初始模型逐步与已有认知的知识框架进行匹配，并使用从物理实体处返回的控制数据进行不断迭代，这样可以将物理实体在特定外界条件变化下的各种性质变化、实时/近实时反应、对其有影响的各种客观规律、行为逻辑等信息按照研究领域的实际需要逐步加入数字孪生模型中，从而有效地控制模型规模和成本，逐步实现全生命周期的信息流动；继而，将优化成型的数字孪生模型进一步用于理论和实际研究中，如仿真、规划、优化、决策等，促进各项研究的发展。本文还对面向多感知的数字孪生模型构建方法的已有技术基础和发展前景进行了回顾和展望。
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.
河北省创新能力提升计划项目(20551801K)；河北省省级科技计划资助(20310802D, 18210109D)；河北省高层次人才资助项目(A2016002015)； 石家庄市科学技术研究与发展计划项目（19SCX01006, 191130591A）