作為網絡物理空間CPS（Cyber-Physical Space）建設的重要支撐技術之一，數字孿生的應用在航空航天、智能制造、智慧城市、智慧醫療、智慧教育等多領域都已出現，但在實踐過程中也出現了一些問題，如數字孿生概念泛化,易導致理解偏差從而造成產學研用目標不一致、實踐結果不受目標用戶認同；具體實施缺乏通用有效方法,導致成果受局限從而造成缺乏普遍性實踐案例、較難以形成公認的典型案例。為解決這些問題，需對數字孿生概念邊界進行約束，并對數字孿生方法邊界進行延伸，從而形成數字孿生的新邊界，促進共識形成，增加實施方法，更好地推動其發展。 在概念上，物理實體是一種具備多種性質的物質集合體，其具有復雜性、真實性、即時性的特點，可隨外界條件變化按照客觀規律進行動態演化。在進行將物理實體映射到數字孿生的研究時，極易將概念范圍不斷進行擴張，如將動態演化過程模擬——仿真，外界條件——數據，甚至對象——物理實體等全部包含在內。如此以來，數字孿生的概念將丟失其核心，不易達成一致意見。 在方法上，基于對在多場景下相關應用的詳細調研分析，現有數字孿生研究往往越過對物理實體的感知過程，直接依托原有專業領域的模型或模型構建方法進行實施。這種方法在取得一些進展的同時，局限性已顯現：首先，已有模型多聚焦于細分領域，在領域間無法通用；其次，已有模型中既少有體現數字孿生模型高保真、多尺度、多物理場的特點，更罕有涉及對應全生命周期的信息流動的內容，直接套用無法保證數字孿生的有效實現；再次，從已有認知的高度直接進入建模過程可能造成成本巨大，如美軍的世界公認的典型案例ADT計劃，建設時間以十年計，投入人力物力巨大，這也對產業界進入數字孿生實踐造成進一步阻礙。 為應對這些挑戰，在概念邊界方面，本文提出數字孿生應回歸其數字化的模型的本質，以模型為中心進行有效約束，從而促使產學研用各方的理解達成一致。而對于方法邊界的延伸方面，本文提出了一種面向多感知的數字孿生模型構建方法，即按照人類對物理世界的一般認識過程——先經由各種感知方法對特征獲得感性認識，而后經各種認知過程進一步形成理性認識——由淺入深、由易到難，由簡到繁的來進行數字孿生的實踐。首先，通過視覺、聽覺、觸覺和動力感知、嗅/味覺、與反映條件變化的控制數據相結合等多感知方法建立物理實體的數字孿生初始模型，從而在模型建立之初就聚焦于物理實體的復雜性和真實性，充分體現數字孿生模型的特點，有效增強模型的實用性和通用性；其后，將初始模型逐步與已有認知的知識框架進行匹配，并使用從物理實體處返回的控制數據進行不斷迭代，這樣可以將物理實體在特定外界條件變化下的各種性質變化、實時/近實時反應、對其有影響的各種客觀規律、行為邏輯等信息按照研究領域的實際需要逐步加入數字孿生模型中，從而有效地控制模型規模和成本，逐步實現全生命周期的信息流動；繼而，將優化成型的數字孿生模型進一步用于理論和實際研究中，如仿真、規劃、優化、決策等，促進各項研究的發展。本文還對面向多感知的數字孿生模型構建方法的已有技術基礎和發展前景進行了回顧和展望。
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.
河北省創新能力提升計劃項目(20551801K)；河北省省級科技計劃資助(20310802D, 18210109D)；河北省高層次人才資助項目(A2016002015)； 石家莊市科學技術研究與發展計劃項目（19SCX01006, 191130591A）