WO2023231257A1 - 一种数字孪生模型组装方法 - Google Patents

一种数字孪生模型组装方法 Download PDF

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WO2023231257A1
WO2023231257A1 PCT/CN2022/122458 CN2022122458W WO2023231257A1 WO 2023231257 A1 WO2023231257 A1 WO 2023231257A1 CN 2022122458 W CN2022122458 W CN 2022122458W WO 2023231257 A1 WO2023231257 A1 WO 2023231257A1
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model
twin
models
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data
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刘晓军
叶大鹏
倪中华
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东南大学
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    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/21—Design, administration or maintenance of databases
    • G06F16/211—Schema design and management
    • G06F16/212—Schema design and management with details for data modelling support
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/23—Updating
    • G06F16/2379—Updates performed during online database operations; commit processing
    • G—PHYSICS
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    • G09B25/00—Models for purposes not provided for in G09B23/00, e.g. full-sized devices for demonstration purposes

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  • the invention relates to a digital twin model assembly method, belonging to the technical field of digital twin modeling.
  • Digital twin was first proposed by American scholar Grieves as a new term to describe physical products and virtual products and the connection between the two. It was first used for the health maintenance and security of aerospace vehicles. In recent years, it has received widespread attention from domestic and foreign scholars and has been widely used in many industrial fields. In 2012, NASA gave a conceptual description of digital twins: Digital twins refer to making full use of physical models, sensors, operation history and other data to integrate multi-disciplinary and multi-scale simulation processes. It serves as a mirror image of physical products in virtual space, reflecting The entire life cycle process of the corresponding physical physical product. Digital twin models are an important part of digital twins and an important prerequisite for realizing digital twin functions.
  • the present invention is aimed at the problems existing in the prior art, and provides a digital twin model assembly method.
  • the method includes two main digital twin model assembly methods, and proposes a digital twin model assembly process method. This strategy defines the digital twin model assembly process.
  • the assembly method of twin models under different business logic standardizes the digital twin model assembly process and greatly improves the efficiency of digital twin modeling.
  • the model assembly method includes the following two types of assembly methods:
  • the fusion and assembly process of the digital twin model is as follows:
  • the physical entities of the main model also include additional entity models generated when the physical bodies are fused and assembled;
  • the virtual entity of the main model also includes additional virtual models generated when the twin models are fused and assembled;
  • the service model of the main model is a new twin service model that is rebuilt when the twin models are fused and assembled;
  • twin data of the main model also includes additional twin data generated when the twin models are fused and assembled;
  • connection model of the main model is a rebuilt connection model when the twin models are fused and assembled.
  • digital twin model fusion assembly means assembling multiple digital twin models through fusion. After the fusion assembly is completed, on the one hand, the original sub-models are retained in terms of physical entities, virtual entities, and twin data, and a new and updated one is constructed. Complex main model; on the other hand, after model fusion and assembly, new twin service models and connection models are built based on the business logic and application scenarios of the new model;
  • DT ⁇ represents the digital twin model obtained by the combination operation
  • the symbol ⁇ represents the combination operation
  • the symbol ⁇ represents the logical union operation.
  • PE i is the physical entity of the i-th sub-model
  • VE i is the virtual entity of the i-th sub-model.
  • Ss i is the twin service model of the i-th sub-model
  • DD i is the twin data of the i-th sub-model
  • CN i is the connection model of the i-th sub-model
  • VE i ′ is a partial model of VE i
  • DD i ′ is DD i Part of the data information
  • PE x is the physical model other than the original physical model generated during the assembly of the digital twin model
  • VE x is the virtual model other than the original virtual model generated during the assembly of the digital twin model
  • DD x is In addition to the original twin data generated during the assembly of the digital twin model, the twin service model is built based on the business logic and application scenarios of the new model after the Ss model is assembled.
  • Ss is a brand new twin service model, not all sub-services.
  • a collection of models, CN is a connection model built based on the business logic and application scenarios of the new model after model assembly.
  • CN is a brand new connection model, not a collection of all sub-connection models.
  • the digital twin model after fusion and assembly is updated according to actual on-site information, mainly including updates to physical entities, virtual entities, twin services, twin data, and connection models:
  • connection model of the main model needs to be rebuilt.
  • This digital twin fusion assembly method is suitable for application scenarios where workshop equipment unit level is assembled into production line level. Its characteristics are: the equipment unit level refers to the smallest production unit in the workshop, and the production process is completed by the interaction of multiple equipment level units. Production line-level functions and services are the result of the interaction and integration of various equipment-level units. A new twin connection model is built for the needs of the assembled production line. At the same time, a new twin service is built based on production tasks and needs.
  • the physical entities of the main model also include additional entity models generated when the physical bodies are connected and assembled;
  • the virtual entities of the main model also include additional virtual models generated when the twin models are connected and assembled;
  • twin service model of the main model also includes additional twin service models generated when the twin models are connected and assembled;
  • twin data of the main model also includes additional twin data generated when the twin models are connected and assembled;
  • connection model of the main model also includes additional connection models generated when the twin models are connected and assembled.
  • digital twin model connection assembly means assembling multiple digital twin models through connection. After the connection assembly is completed, on the one hand, all the original sub-models are retained, and on the other hand, a new more complex main model is constructed;
  • DT ⁇ represents the digital twin model obtained by the combination operation
  • the symbol ⁇ represents the combination operation
  • the symbol ⁇ represents the logical union operation
  • PE i is the physical entity of the i-th sub-model
  • VE i is the virtual entity of the i-th sub-model
  • Ss i is the twin service model of the i-th sub-model
  • DD i is the twin data of the i-th sub-model
  • CN i is the connection model of the i-th sub-model
  • PE x is in addition to the original physical model generated during the assembly of the digital twin model
  • the entity model, VE x is a virtual model other than the original virtual model generated during the assembly of the digital twin model
  • Ss Twin data other than the original twin data generated during the assembly of the digital twin model
  • CN x is a connection model other than the original connection model generated during the assembly of the digital twin model.
  • the digital twin model after connection and assembly is updated according to actual on-site information, mainly including updates to physical entities, virtual entities, twin services, twin data, and connection models:
  • connection models and additional connection models in each sub-model need to be updated to complete the connection model update of the main model.
  • This digital twin connection assembly method is suitable for application scenarios in which production line-level units are assembled into an entire workshop. Its characteristics are: a production line-level unit refers to a production line in a workshop with independent and complete functions and services such as processing, transportation, assembly, and testing. The entire workshop It is completed by the mutual cooperation of multiple independent production line-level units. The functions and services of the workshop are the result of the mutual interaction of multiple production lines. According to the production tasks and needs, based on the complete service and connection of each existing production line On top, build additional twin services and additional connection models for the entire workshop.
  • This technical solution explores two methods of digital twin assembly and two main application scenarios of workshop model assembly, basically meets the workshop digital twin model assembly requirements, and can provide digital twins for the production workshop.
  • This method provides guiding suggestions for transformation.
  • this method defines the assembly methods of digital twin models under different conditions, clarifies the model assembly elements of digital twins in different application scenarios, standardizes the digital twin model construction process, and reduces the number of errors due to application Efficiency loss caused by unclear scenarios and unclear assembly methods.
  • Figure 1 is a schematic diagram of the fusion assembly process of the digital twin model of the present invention
  • Figure 2 is a schematic diagram of the connection and assembly process of the digital twin model of the present invention
  • FIG. 3 is a schematic model diagram of the present invention taking processing equipment M1 as an example
  • Figure 4 is a schematic model diagram of the present invention taking processing equipment M2 as an example
  • Figure 5 is a schematic diagram of the model of the present invention using the robot R1 equipment as an example
  • Figure 6 is a schematic model diagram of the present invention taking the conveyor belt C1 equipment as an example
  • Figure 7 is a schematic diagram of the present invention integrating and assembling the processing equipment M1, processing equipment M2, robot R1, conveyor belt C1 and other sub-models into the main model PL1;
  • Figure 8 is a schematic diagram of a model of the present invention taking product processing line PL as an example
  • Figure 9 is a schematic diagram of the model of the present invention taking the product detection line TL1 as an example
  • Figure 10 is a schematic diagram of the model of the present invention taking the product packaging line PAL1 as an example;
  • Figure 11 is a schematic diagram of the present invention connecting and assembling sub-models such as the product processing line PL, product testing line TL1, product packaging line PAL1, etc. into the main model PW1.
  • Embodiment 1 Referring to Figure 1 and Figure 2, a digital twin model assembly method includes the following two types of construction methods:
  • the physical entities of the main model also include additional entity models generated when the physical bodies are fused and assembled;
  • the virtual entity of the main model also includes additional virtual models generated when the twin models are fused and assembled;
  • the service model of the main model is a new twin service model that is rebuilt when the twin models are fused and assembled;
  • twin data of the main model also includes additional twin data generated when the twin models are fused and assembled;
  • connection model of the main model is a rebuilt connection model when the twin models are fused and assembled.
  • digital twin model fusion assembly means assembling multiple digital twin models through fusion. After the fusion assembly is completed, on the one hand, the original sub-models are retained in terms of physical entities, virtual entities, and twin data, and a new and updated one is constructed. Complex main model; on the other hand, after model fusion and assembly, new twin service models and connection models are built based on the business logic and application scenarios of the new model;
  • DT ⁇ represents the digital twin model obtained by the combination operation
  • the symbol ⁇ represents the combination operation
  • the symbol ⁇ represents the logical union operation.
  • PE i is the physical entity of the i-th sub-model
  • VE i is the virtual entity of the i-th sub-model.
  • Ss i is the twin service model of the i-th sub-model
  • DD i is the twin data of the i-th sub-model
  • CN i is the connection model of the i-th sub-model
  • VE i ′ is a partial model of VE i
  • DD i ′ is DD i Part of the data information
  • PE x is the physical model other than the original physical model generated during the assembly of the digital twin model
  • VE x is the virtual model other than the original virtual model generated during the assembly of the digital twin model
  • DD x is In addition to the original twin data generated during the assembly of the digital twin model, the twin service model is built based on the business logic and application scenarios of the new model after the Ss model is assembled.
  • Ss is a brand new twin service model, not all sub-services.
  • a collection of models, CN is a connection model built based on the business logic and application scenarios of the new model after model assembly.
  • CN is a brand new connection model, not a collection of all sub-connection models.
  • the digital twin model after fusion and assembly is updated according to actual on-site information, mainly including updates to physical entities, virtual entities, twin services, twin data, and connection models:
  • connection model of the main model needs to be rebuilt.
  • This digital twin fusion assembly method is suitable for application scenarios where workshop equipment unit level is assembled into production line level. Its characteristics are: the equipment unit level refers to the smallest production unit in the workshop, and the production process is completed by the interaction of multiple equipment level units. Production line-level functions and services are the result of the interaction and integration of various equipment-level units. A new twin connection model is built for the needs of the assembled production line. At the same time, a new twin service is built based on production tasks and needs.
  • the physical entities of the main model also include additional entity models generated when the physical bodies are connected and assembled;
  • the virtual entities of the main model also include additional virtual models generated when the twin models are connected and assembled;
  • twin service model of the main model also includes additional twin service models generated when the twin models are connected and assembled;
  • twin data of the main model also includes additional twin data generated when the twin models are connected and assembled;
  • connection model of the main model also includes additional connection models generated when the twin models are connected and assembled.
  • digital twin model connection assembly means assembling multiple digital twin models through connection. After the connection assembly is completed, on the one hand, all the original sub-models are retained, and on the other hand, a new more complex main model is constructed;
  • DT ⁇ represents the digital twin model obtained by the combination operation
  • the symbol ⁇ represents the combination operation
  • the symbol ⁇ represents the logical union operation
  • PE i is the physical entity of the i-th sub-model
  • VE i is the virtual entity of the i-th sub-model
  • Ss i is the twin service model of the i-th sub-model
  • DD i is the twin data of the i-th sub-model
  • CN i is the connection model of the i-th sub-model
  • PE x is in addition to the original physical model generated during the assembly of the digital twin model.
  • VE x is a virtual model other than the original virtual model generated during the assembly of the digital twin model
  • Ss Twin data other than the original twin data generated during the assembly of the digital twin model
  • CN x is a connection model other than the original connection model generated during the assembly of the digital twin model.
  • the digital twin model after connection and assembly is updated according to actual on-site information, mainly including updates to physical entities, virtual entities, twin services, twin data, and connection models:
  • connection models and additional connection models in each sub-model need to be updated to complete the connection model update of the main model.
  • This digital twin connection assembly method is suitable for application scenarios in which production line-level units are assembled into an entire workshop. Its characteristics are: a production line-level unit refers to a production line in a workshop with independent and complete functions and services such as processing, transportation, assembly, and testing. The entire workshop It is completed by the mutual cooperation of multiple independent production line-level units. The functions and services of the workshop are the result of the mutual interaction of multiple production lines. According to the production tasks and needs, based on the complete service and connection of each existing production line On top, build additional twin services and additional connection models for the entire workshop.
  • PE mainly includes various subsystems, deployed sensors and data;
  • VE mainly includes geometric model Gv, physical model Pv, behavioral model Bv, rule model Rv.
  • the four-layer model is integrated in function and structure to form a complete mapping of physical entities; CN enables physical devices, virtual devices, and services to maintain interaction, consistency, and synchronization during operation, and the data generated by physical devices, virtual devices, and services are stored in twin data in real time, and enables twin data to drive the operation of the three; DD mainly includes physical entities Data, virtual entity data, service data, domain knowledge, and converged data are the drivers for the operation of physical equipment, virtual equipment, and services; Ss refers to the various types of data, models, algorithms, simulations, and results required in the digital twin application process.
  • Service-oriented packaging refers to "functional services” that support the operation and implementation of internal functions of digital twins in the form of tool components, middleware, module engines, etc., and "functional services” that meet the different business needs of different users in different fields in the form of application software, mobile APP, etc. business services”.
  • the main model PL1 of the production line is assembled by the integration and assembly of two processing equipment M1, M2, robot R1, conveyor belt C1 and other sub-models;
  • the physical entities of the main model PL1 include the physical entities of the sub-models M1, M2, R1, and C1, that is, the union of the physical entities of all sub-models; at the same time, according to the specific business needs of the site, a Additional entity models such as spatial constraint relationships between sub-models, production logic, process flow, etc.;
  • a new digital twin service model is rebuilt, such as operation guidance services for on-site operators based on the production line PL1, dynamic optimization scheduling services, dynamic process simulation services, etc.
  • twin data model of this part of the sub-model M1 is selected as The twin data model of the main model.
  • additional twin data for this part needs to be established.
  • connection dimension for the main model PL1, a new connection model needs to be established to realize the interconnection of various components of the production line, such as the data connection between the processing equipment M1 and the robot R1.
  • the main model PW1 of the production workshop is connected and assembled by sub-models such as the product processing production line PL, the product testing line TL1, and the product packaging line PAL1.
  • the sub-models PL, TL1, and PAL1 have independent and complete physical entities.
  • the physical entities of the main model PW1 include all the physical entities of the sub-models PL, TL1, and PAL1, that is, the union of the physical entities of all sub-models. Set; at the same time, according to the specific business needs of the site, additional entity models such as spatial constraint relationships between sub-models, material flow, and information flow need to be established;
  • the sub-models PL, TL1, and PAL1 have independent and complete virtual entities.
  • the virtual entity of the main model PW1 includes all the virtual entities of the sub-models PL, TL1, and PAL1, that is, the union of the virtual entities of all sub-models.
  • additional entities such as spatial constraint relationships, material flow, and information flow generated when the sub-models are connected and assembled are virtually mapped to form an additional virtual model of the main model.
  • the sub-models PL, TL1, and PAL1 have independent and complete twin service models.
  • the twin service model of the main model PW1 includes all the twin service models of the sub-models PL, TL1, and PAL1, that is, the twins of all sub-models.
  • the union of service models; at the same time, additional digital twin service models are built according to the specific business needs of the site, such as operation guidance services for on-site operators based on the production workshop PWL1, organization, coordination and management services between various subsystems, etc. .
  • the sub-models PL, TL1, and PAL1 have independent and complete twin data models.
  • the twin data model of the main model PW1 includes all the twin data models of the sub-models PL, TL1, and PAL1, that is, the twins of all sub-models. Union of data models; at the same time, according to the specific business needs of the site, for research on the production capacity and scheduling of the entire workshop, additional twin data for this part needs to be established.
  • connection dimension the sub-models PL, TL1, and PAL1 have independent and complete connection models.
  • the connection model of the main model PW1 includes all the connection models of the sub-models PL, TL1, and PAL1, that is, the union of the connection models of all sub-models. ;At the same time, in order to realize data interconnection and interoperability of each production line, an additional connection model for this part needs to be established.
  • the acquisition system extracts the model-driven data of the virtual entity, realizes the synchronous simulation of the virtual entity and the physical entity of each sub-model, and then realizes the two-way mapping of the virtual entity and the physical entity of the main model, and collects all sub-models PL, TL1, PAL and other production lines Real-time data, update the twin data model of each sub-model, and then update the additional twin data model information, thereby updating the twin data of the main model PW1, and collecting all the connection data of each sub-model to update the connection model of each sub-model, and then Update the additional connection model information to update the main model PW1 connection model.
  • connection and assembly of the digital twin model of the production workshop PW1 is realized.

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Abstract

本发明涉及一种数字孪生模型组装方法，该方法包含两种主要的数字孪生模型组装方式，并提出了数字孪生模型组装流程，分别为：数字孪生模型融合组装，数字孪生模型连接组装。该策略定义了数字孪生模型在不同应用场景下的组装方法，规范了数字孪生模型组装流程，减少了因应用场景不明确、组装方法不明确导致的效率损失。

Description

一种数字孪生模型组装方法 技术领域
本发明涉及一种数字孪生模型组装方法，属于数字孪生建模技术领域。
背景技术
数字孪生最早是由美国学者Grieves提出用来描述物理产品和虚拟产品以及两者之间联系的新名词，最早用于航空航天飞行器的健康维护与保障。近些年来，受到国内外学者的广泛关注，并已经广泛应用于诸多工业领域。2012年NASA给出了数字孪生的概念描述：数字孪生是指充分利用物理模型、传感器、运行历史等数据，集成多学科、多尺度的仿真过程，它作为虚拟空间中对实体产品的镜像，反映了相对应物理实体产品的全生命周期过程。数字孪生模型是数字孪生的重要组成部分，是实现数字孪生功能的重要前提，当前针对数字孪生建模的研究或应用主要集中在几何模型的构建，但是对模型的组装与融合研究较少。通过模型的多维度融合、多类模型相互关联以及多级模型相互协同，才能将数字孪生模型表征为一个统一的整体，在运行过程中产生和收集有效的多尺度融合数据，实现基于融合模型和融合数据的全局决策和优化。
当前数字孪生模型组装面对不同的业务逻辑和应用场景，存在缺失系统的数字孪生模型组装策略、数字孪生模型组装流程不明确的问题。
发明内容
本发明正是针对现有技术中存在的问题，提供一种数字孪生模型组装方法，该方法包含两种主要的数字孪生模型组装方式，并提出了数字孪生模型组装流程方法，该策略定义了数字孪生模型在不同业务逻辑下的组装方法，规范了数字孪生模型组装流程，极大的提高了数字孪生建模效率。
为了实现上述目的，本发明的技术方案如下，一种数字孪生模型组装方法，模型组装方法包含以下两类组装方式：
(1)数字孪生模型的融合组装：
(2)数字孪生模型的连接组装。
其中，数字孪生模型的融合组装流程如下：
11)主模型的物理实体除了包括所有子模型的物理实体的并集，还包括物理体融合组装时所产生的附加实体模型；
12)主模型的虚拟实体除了包括所有子模型的虚拟实体一部分模型的并集，还包括孪生模型融合组装时所产生的附加虚拟模型；
13)主模型的服务模型是孪生模型融合组装时，重新构建的新孪生服务模型；
14)主模型的孪生数据除了包括所有子模型的孪生数据一部分模型的并集，还包括孪生模型融合组装时所产生的附加孪生数据；
15)主模型的连接模型是孪生模型融合组装时，重新构建的连接模型。
16)将组装后主模型信息更新为实际信息。
其中，数字孪生模型融合组装表示将多个数字孪生模型通过融合的方式进行组装，融合组装完成后，一方面在物理实体、虚拟实体，孪生数据方面保留原有子模型，并构建一个新的更加复杂的主模型；另一方面模型融合组装后，根据新模型的业务逻辑和应用场景，构建新的孪生服务模型和连接模型；
Figure PCTCN2022122458-appb-000001
式中，DT ∑表示组合操作得到的数字孪生模型，符号∑表示组合操作，符号∪表示逻辑并运算,PE i,是第i个子模型的物理实体，VE i是第i个子模型的虚拟实体，Ss i是第i个子模型的孪生服务模型，DD i是第i个子模型的孪生数据，CN i是第i个子模型的连接模型，VE i′是VE i的部分模型，DD i′是DD i的部分数据信息，PE x是在数字孪生模型组装时产生的原有物理模型之外的实体模型，VE x是在数字孪生模型组装时产生的原有虚拟模型之外的虚拟模型，DD x是在数字孪生模型组装时产生的原有孪生数据之外的孪生数据，Ss模型组装后根据新模型的业务逻辑和应用场景构建的孪生服务模型，Ss是一个全新的孪生服务模型，不是所有子服务模型的集合，CN是模型组装后根据新模型的业务逻辑和应用场景构建的连接模型，CN是一个全新的连接模型，不是所有子连接模型的集合。
融合组装后的数字孪生模型按现场实际信息进行更新，主要包括对物理实体、虚拟实体、孪生服务、孪生数据、连接模型的更新：
(1)采集各子模型物理实体以及附加物理实体数据，对主模型的物理实体信息更新；
(2)对采集的物理实体数据进行分析，提取出关键信息，同步映射到虚拟实体中，对主模型的虚拟实体部分关键信息更新，以实现与物理实体双向映射与同步仿真要求；
(3)对现场采集的生产实时数据，同步储存到数据库中，更新主模型的孪生数据模型；
(4)当现场的业务逻辑和服务发生变化时，需重新构建主模型的孪生服务模型；
(5)当主模型的物理实体、虚拟实体、孪生数据模型、服务模型发生增删、替换时，需重新构建主模型的连接模型。
该数字孪生融合组装方法适用于车间设备单元级组装成产线级的应用场景，其特点在于：设备单元级是指车间最小的生产单元，生产过程由多个设备级单元的交互配合而完成，产线级功能与服务是由各个设备级单元共同作用相互融合的结果，针对组装的产线需要构建全新的孪生连接模型，同时，根据生产任务与需求构建全新的孪生服务。
其中，数字孪生模型连接组装的流程如下：
21)主模型的物理实体除了包括所有子模型的物理实体的并集，还包括物理体连接组装时所产生的附加实体模型；
22)主模型的虚拟实体除了包括所有子模型的虚拟实体的并集，还包括孪生模型连接组装时所产生的附加虚拟模型；
23)主模型的孪生服务模型除了包括所有子模型的孪生服务模型的并集，还包括孪生模型连接组装时所产生的附加孪生服务模型；
24)主模型的孪生数据除了包括所有子模型的孪生数据的并集，还包括孪生模型连接组装时所产生的附加孪生数据；
25)主模型的连接模型除了包括所有子模型的连接模型的并集，还包括孪生模型连接组装时所产生的附加连接模型。
26)将组装后主模型信息更新为实际信息。
其中，数字孪生模型连接组装表示将多个数字孪生模型通过连接的方式进行组装，连接组装完成后，一方面保留原有所有子模型，另外一方面构建一个新的更加复杂的主模型；
Figure PCTCN2022122458-appb-000002
式中，DT ∑表示组合操作得到的数字孪生模型，符号∑表示组合操作，符号∪表示逻辑并运算,PE i是第i个子模型的物理实体，VE i是第i个子模型的虚拟实体，Ss i是第i个子模型的孪生服务模型，DD i是第i个子模型的孪生数据，CN i是第i个子模型的连接模型， PE x是在数字孪生模型组装时产生的原有物理模型之外的实体模型，VE x是在数字孪生模型组装时产生的原有虚拟模型之外的虚拟模型，Ss x是在数字孪生模型组装时产生的原有孪生服务之外的孪生服务模型，DD x是在数字孪生模型组装时产生的原有孪生数据之外的孪生数据，CN x是在数字孪生模型组装时产生的原有连接模型之外的连接模型。
连接组装后的数字孪生模型按现场实际信息进行更新，主要包括对物理实体、虚拟实体、孪生服务、孪生数据、连接模型的更新：
(1)采集各子模型物理实体数据以及附加物理实体数据，对各子模型的物理实体信息更新，再更新附加物理实体信息，进而对主模型的物理实体信息更新；
(2)对采集的各子模型物理实体数据进行分析，同步映射到各子模型的虚拟实体中，更新各子模型的虚拟实体，再更新附加虚拟实体信息，进而完成对主模型的虚拟实体信息的更新，以实现与主模型的物理实体双向映射与同步仿真要求；
(3)对现场采集各子模型的生产实时数据，同步储存到各子模型的数据库中，更新子模型的孪生数据模型信息，再更新附加孪生数据模型信息，进而完成对主模型的孪生数据模型信息更新；
(4)当现场的业务逻辑和服务发生变化时，需要对各子模型中所有孪生服务以及附加孪生服务更新，进而完成对主模型孪生服务更新；
(5)当主模型的物理实体、虚拟实体、孪生数据模型、服务模型发生增删、替换时，需要对各子模型中连接模型以及附加连接模型更新，进而完成对主模型的连接模型更新。
该数字孪生连接组装方法适用于产线级单元组装成整个车间的应用场景，其特点在于：产线级单元是指车间具有加工、运输、装配、检测等独立完整功能与服务的生产线，整个车间由多个独立产线级单元的相互配合而完成，车间的功能和服务是由多条产线共同作用相互连接的结果，根据生产任务与需求，在现有各产线完整服务与连接的基础上，构建针对整个车间的附加的孪生服务与附加的连接模型。
相对于现有技术，本发明具有如下优点，该技术方案探究了数字孪生组装两种方式以及车间模型组装主要的两种应用场景，基本满足车间数字孪生模型组装需求，能为生产车间的数字孪生转化提出指导性建议,同时，该方法定义了数字孪生模型组装在不同条件下的组装方法，明确了数字孪生在不同应用场景下的模型组装要素，规范了数字孪生模型构建流程，减少了因应用场景不明确、组装方法不明确导致的效率损失。
附图说明
图1为本发明的数字孪生模型的融合组装流程示意图；
图2为本发明的数字孪生模型的连接组装流程示意图；
图3为本发明以加工设备M1为例子模型示意图；
图4为本发明以加工设备M2为例子模型示意图；
图5为本发明以机器人R1设备为例子模型示意图；
图6为本发明以传送带C1设备为例子模型示意图；
图7为本发明以加工设备M1、加工设备M2、机器人R1、传送带C1等子模型融合组装成主模型PL1示意图；
图8为本发明以产品加工产线PL为例子模型示意图；
图9为本发明以产品检测线TL1为例子模型示意图；
图10为本发明以产品包装线PAL1为例子模型示意图；
图11为本发明以产品的加工产线PL、产品检测线TL1、产品包装线PAL1等子模型连接组装成主模型PW1示意图。
具体实施方式
为了加深对本发明的理解，下面结合附图对本实施例做详细的说明。
实施例1：参见图1、图2，一种数字孪生模型组装方法，包括以下两类构建方法：
(1)数字孪生模型的融合组装，构建流程如下：
11)主模型的物理实体除了包括所有子模型的物理实体的并集，还包括物理体融合组装时所产生的附加实体模型；
12)主模型的虚拟实体除了包括所有子模型的虚拟实体一部分模型的并集，还包括孪生模型融合组装时所产生的附加虚拟模型；
13)主模型的服务模型是孪生模型融合组装时，重新构建的新孪生服务模型；
14)主模型的孪生数据除了包括所有子模型的孪生数据一部分模型的并集，还包括孪生模型融合组装时所产生的附加孪生数据；
15)主模型的连接模型是孪生模型融合组装时，重新构建的连接模型。
16)将组装后主模型信息更新为实际信息。
其中，数字孪生模型融合组装表示将多个数字孪生模型通过融合的方式进行组装，融合组装完成后，一方面在物理实体、虚拟实体，孪生数据方面保留原有子模型，并构建一个新的更加复杂的主模型；另一方面模型融合组装后，根据新模型的业务逻辑和应用场景，构建新的孪生服务模型和连接模型；
Figure PCTCN2022122458-appb-000003
式中，DT ∑表示组合操作得到的数字孪生模型，符号∑表示组合操作，符号∪表示逻辑并运算,PE i,是第i个子模型的物理实体，VE i是第i个子模型的虚拟实体,Ss i是第i个子模型的孪生服务模型，DD i是第i个子模型的孪生数据，CN i是第i个子模型的连接模型,VE i′是VE i的部分模型，DD i′是DD i的部分数据信息,PE x是在数字孪生模型组装时产生的原有物理模型之外的实体模型，VE x是在数字孪生模型组装时产生的原有虚拟模型之外的虚拟模型，DD x是在数字孪生模型组装时产生的原有孪生数据之外的孪生数据，Ss模型组装后根据新模型的业务逻辑和应用场景构建的孪生服务模型，Ss是一个全新的孪生服务模型，不是所有子服务模型的集合，CN是模型组装后根据新模型的业务逻辑和应用场景构建的连接模型，CN是一个全新的连接模型，不是所有子连接模型的集合。
融合组装后的数字孪生模型按现场实际信息进行更新，主要包括对物理实体、虚拟实体、孪生服务、孪生数据、连接模型的更新：
(1)采集各子模型物理实体以及附加物理实体数据，对主模型的物理实体信息更新；
(2)对采集的物理实体数据进行分析，提取出关键信息，同步映射到虚拟实体中，对主模型的虚拟实体部分关键信息更新，以实现与物理实体双向映射与同步仿真要求；
(3)对现场采集的生产实时数据，同步储存到数据库中，更新主模型的孪生数据模型；
(4)当现场的业务逻辑和服务发生变化时，需重新构建主模型的孪生服务模型；
(5)当主模型的物理实体、虚拟实体、孪生数据模型、服务模型发生增删、替换时，需重新构建主模型的连接模型。
该数字孪生融合组装方法适用于车间设备单元级组装成产线级的应用场景，其特点在于：设备单元级是指车间最小的生产单元，生产过程由多个设备级单元的交互配合而完成，产线级功能与服务是由各个设备级单元共同作用相互融合的结果，针对组装的产线需要构建全新的孪生连接模型，同时，根据生产任务与需求构建全新的孪生服务。
(2)数字孪生模型的连接组装，构建流程如下：
21)主模型的物理实体除了包括所有子模型的物理实体的并集，还包括物理体连接组装时所产生的附加实体模型；
22)主模型的虚拟实体除了包括所有子模型的虚拟实体的并集，还包括孪生模型连接组装时所产生的附加虚拟模型；
23)主模型的孪生服务模型除了包括所有子模型的孪生服务模型的并集，还包括孪生模型连接组装时所产生的附加孪生服务模型；
24)主模型的孪生数据除了包括所有子模型的孪生数据的并集，还包括孪生模型连接组装时所产生的附加孪生数据；
25)主模型的连接模型除了包括所有子模型的连接模型的并集，还包括孪生模型连接组装时所产生的附加连接模型。
26)将组装后主模型信息更新为实际信息。
其中，数字孪生模型连接组装表示将多个数字孪生模型通过连接的方式进行组装，连接组装完成后，一方面保留原有所有子模型，另外一方面构建一个新的更加复杂的主模型；
Figure PCTCN2022122458-appb-000004
式中，DT ∑表示组合操作得到的数字孪生模型，符号∑表示组合操作，符号∪表示逻辑并运算,PE i是第i个子模型的物理实体，VE i是第i个子模型的虚拟实体，Ss i是第i个子模型的孪生服务模型，DD i是第i个子模型的孪生数据，CN i是第i个子模型的连接模型，PE x是在数字孪生模型组装时产生的原有物理模型之外的实体模型，VE x是在数字孪生模型组装时产生的原有虚拟模型之外的虚拟模型，Ss x是在数字孪生模型组装时产生的原有孪生服务之外的孪生服务模型，DD x是在数字孪生模型组装时产生的原有孪生数据之外的孪生数据，CN x是在数字孪生模型组装时产生的原有连接模型之外的连接模型。
连接组装后的数字孪生模型按现场实际信息进行更新，主要包括对物理实体、虚拟实体、孪生服务、孪生数据、连接模型的更新：
(1)采集各子模型物理实体数据以及附加物理实体数据，对各子模型的物理实体信息 更新，再更新附加物理实体信息，进而对主模型的物理实体信息更新；
(2)对采集的各子模型物理实体数据进行分析，同步映射到各子模型的虚拟实体中，更新各子模型的虚拟实体，再更新附加虚拟实体信息，进而完成对主模型的虚拟实体信息的更新，以实现与主模型的物理实体双向映射与同步仿真要求；
(3)对现场采集各子模型的生产实时数据，同步储存到各子模型的数据库中，更新子模型的孪生数据模型信息，再更新附加孪生数据模型信息，进而完成对主模型的孪生数据模型信息更新；
(4)当现场的业务逻辑和服务发生变化时，需要对各子模型中所有孪生服务以及附加孪生服务更新，进而完成对主模型孪生服务更新；
(5)当主模型的物理实体、虚拟实体、孪生数据模型、服务模型发生增删、替换时，需要对各子模型中连接模型以及附加连接模型更新，进而完成对主模型的连接模型更新。
该数字孪生连接组装方法适用于产线级单元组装成整个车间的应用场景，其特点在于：产线级单元是指车间具有加工、运输、装配、检测等独立完整功能与服务的生产线，整个车间由多个独立产线级单元的相互配合而完成，车间的功能和服务是由多条产线共同作用相互连接的结果，根据生产任务与需求，在现有各产线完整服务与连接的基础上，构建针对整个车间的附加的孪生服务与附加的连接模型。
实施例2：
北京航空航天大学的陶某某等人提出数字孪生的五维模型，分别是物理实体PE、虚拟实体VE、连接CN、孪生数据DD、服务Ss。PE主要包括各个子系统、部署的传感器以及数据；VE主要包括几何模型Gv、物理模型Pv、行为模型Bv、规则模型Rv，四层模型在功能与结构上集成，形成对物理实体的完整映射；CN实现物理设备、虚拟设备、服务在运行中保持交互、一致与同步以及物理设备、虚拟设备、服务产生的数据实时存入孪生数据，并使孪生数据能够驱动三者运行；DD主要包括物理实体数据、虚拟实体数据、服务数据、领域知识、融合数据，是物理设备、虚拟设备、服务运行的驱动；Ss是指对数字孪生应用过程中所需各类数据、模型、算法、仿真、结果进行服务化封装，以工具组件、中间件、模块引擎等形式支撑数字孪生内部功能运行与实现的“功能性服务”，以及以应用软件、移动端APP等形式满足不同领域不同用户不同业务需求的“业务性服务”。
(1)图3-图7所示，以某一加工生产线为例，阐述数字孪生模型的融合组装方法：
该生产线主模型PL1由两台加工设备M1、M2、机器人R1、传送带C1等子模型融合组装而成；
11)在物理实体维度上，主模型PL1的物理实体包含子模型M1、M2、R1、C1的物理实体，即所有子模型的物理实体的并集；同时，根据现场的具体业务需求，产生了子模型之间空间约束关系、生产逻辑、工艺流程等附加的实体模型；
12)在虚拟实体维度上，根据现场的具体业务需求，如研究加工设备M1在加工时切削力变化情况，传送带C1的运输速度等，而对其他物理参数不作关注，则需选取子模型的虚拟实体一部分模型作为主模型的虚拟实体；同时，对子模型融合组装时所产生的空间约束关系、生产逻辑等附加的实体进行虚拟映射，形成主模型的附加虚拟模型。
13)在服务模型维度上，根据现场的具体业务需求，重新构建新的数字孪生服务模型，如基于该生产线PL1的面向现场操作人员的操作指导服务，动态优化调度服务，动态过程仿真服务等。
14)在孪生数据维度上，根据现场的具体业务需求，如研究加工设备M1在加工时刀具的温度变化情况，而对其他物理参数不作关注，则选取子模型M1该部分的孪生数据模型做为主模型的孪生数据模型。同时，对于整条产线的产能、调度等方面研究，则需建立针对该部分的附加孪生数据。
15)在连接维度上，针对主模型PL1，需建立新的连接模型，实现产线各组成部分的互联互通，如加工设备M1和机器人R1之间数据连接。
16)采集现场加工设备M1、M2、机器人R1、传送带C1等设备运行状态与属性数据、实体结构、布局信息等对主模型PL1物理实体进行更新、从传感器等采集系统提取虚拟实体的模型驱动数据，实现对虚拟实体与物理实体同步仿真、采集加工设备M1、M2、机器人R1、传送带C1等部分关键实时数据，实现对主模型PL1孪生数据模型更新，以及采集各子模型的连接关联数据对主模型PL1连接模型进行更新，根据现场业务逻辑的变化，对主模型PL1孪生服务模型更新。
综上所述，实现该产线PL1的数字孪生模型的融合组装。
(2)图8-图11所示，以某一生产车间为例，阐述数字孪生模型的连接组装方法：
该生产车间主模型PW1由产品加工生产线PL、产品检测线TL1、产品包装线PAL1等子模型连接组装而成。
21)在物理实体维度上，子模型PL、TL1、PAL1具有独立完整的物理实体，主模型PW1的物理实体包含子模型PL、TL1、PAL1所有的物理实体，即所有子模型的物理实体的并集；同时，根据现场的具体业务需求，需建立子模型之间空间约束关系、物料流、信息流等附加的实体模型；
22)在虚拟实体维度上，子模型PL、TL1、PAL1具有独立完整的虚拟实体，主模型PW1 的虚拟实体包含子模型PL、TL1、PAL1所有的虚拟实体，即所有子模型的虚拟实体的并集；同时，对子模型连接组装时所产生的空间约束关系、物料流、信息流等附加的实体进行虚拟映射，形成主模型的附加虚拟模型。
23)在服务模型维度上，子模型PL、TL1、PAL1具有独立完整的孪生服务模型，主模型PW1的孪生服务模型包含子模型PL、TL1、PAL1所有的孪生服务模型，即所有子模型的孪生服务模型的并集；同时，根据现场的具体业务需求，构建附加的数字孪生服务模型，如基于生产车间PWL1的面向现场操作人员的操作指导服务，各子系统间的组织、协调及管理服务等。
24)在孪生数据维度上，子模型PL、TL1、PAL1具有独立完整的孪生数据模型，主模型PW1的孪生数据模型包含子模型PL、TL1、PAL1所有的孪生数据模型，即所有子模型的孪生数据模型的并集；同时，根据现场的具体业务需求，对于整个车间的产能、调度等方面研究，则需建立针对该部分的附加孪生数据。
25)在连接维度上，子模型PL、TL1、PAL1具有独立完整的连接模型，主模型PW1的连接模型包含子模型PL、TL1、PAL1所有的连接模型，即所有子模型的连接模型的并集；同时，为实现各个产线的数据互联互通，需建立针对该部分的附加连接模型。
26)采集现场子模型PL、TL1、PAL等产线运行状态与属性数据、布局信息对各子模型的物理实体更新，再更新附加物理实体信息，完成主模型PW1物理实体的更新，从传感器等采集系统提取虚拟实体的模型驱动数据，实现对各子模型的虚拟实体与物理实体同步仿真，进而实现主模型的虚拟实体与物理实体的双向映射、采集子模型PL、TL1、PAL等产线全部实时数据，对各子模型的孪生数据模型更新，再更新附加孪生数据模型信息，进而实现对主模型PW1孪生数据更新，以及采集各子模型的全部连接数据对各子模型的连接模型更新，再更新附加连接模型信息，实现主模型PW1连接模型的更新，根据现场业务逻辑的变化，对各子模型的孪生服务更新，再更新附加孪生服务模型信息，完成对主模型PW1孪生服务模型更新。
综上所述，实现该生产车间PW1的数字孪生模型的连接组装。
需要说明的是上述实施例，并非用来限定本发明的保护范围，在上述技术方案的基础上所作出的等同变换或替代均落入本发明权利要求所保护的范围。

Claims (10)

  1. 一种数字孪生模型组装方法，其特征在于，模型组装方法包含以下两类组装方式：
    (1)数字孪生模型的融合组装；
    (2)数字孪生模型的连接组装。
  2. 根据权利要求1所述的数字孪生模型组装方法，其特征在于，数字孪生模型包含了五个维度，分别是物理实体、虚拟实体、连接模型、孪生数据、孪生服务模型,从这五个维度实现融合组装，数字孪生模型的融合组装流程如下：
    11)主模型的物理实体包括所有子模型的物理实体的并集，还包括物理体融合组装时所产生的附加实体模型；
    12)主模型的虚拟实体包括所有子模型的虚拟实体一部分模型的并集，还包括孪生模型融合组装时所产生的附加虚拟模型；
    13)主模型的服务模型是孪生模型融合组装时，重新构建的新孪生服务模型；
    14)主模型的孪生数据包括所有子模型的孪生数据一部分模型的并集，还包括孪生模型融合组装时所产生的附加孪生数据；
    15)主模型的连接模型是孪生模型融合组装时，重新构建的连接模型；
    16)将组装后主模型信息更新为实际信息。
  3. 根据权利要求2所述的数字孪生模型组装方法，其特征在于，数字孪生模型融合组装表示将多个数字孪生模型通过融合的方式进行组装，融合组装完成后，在物理实体、虚拟实体，孪生数据方面保留原有子模型，并构建一个新的更加复杂的主模型；模型融合组装后，根据新模型的业务逻辑和应用场景，构建新的孪生服务模型和连接模型；
    Figure PCTCN2022122458-appb-100001
    式中，DT ∑表示组合操作得到的数字孪生模型，符号∑表示组合操作，符号∪表示逻辑并运算,PE i,是第i个子模型的物理实体，VE i是第i个子模型的虚拟实体，Ss i是第i个子模型的孪生服务模型，DD i是第i个子模型的孪生数据，CN i是第i个子模型的连接模型，VE i′是VE i的部分模型，DD i′是DD i的部分数据信息，PE x是在数字孪生模型组装时产生的原有物理模型之外的实体模型，VE x是在数字孪生模型组装时产生的原有虚拟模型之外的虚拟模型，DD x是在数字孪生模型组装时产生的原有孪生数据之外的孪生数据，Ss模型组装后根据新模型的业务逻辑和应用场景构建的孪生服务模型，Ss是一个全新的孪生服务 模型，不是所有子服务模型的集合，CN是模型组装后根据新模型的业务逻辑和应用场景构建的连接模型，CN是一个全新的连接模型，不是所有子连接模型的集合。
  4. 根据权利要求2所述的数字孪生模型组装方法，其特征在于，数字孪生模型融合组装之后，需要对数字孪生模型按现场实际信息进行更新，主要包括对物理实体、虚拟实体、孪生服务、孪生数据、连接模型的更新,
    (1)采集各子模型物理实体以及附加物理实体数据，对主模型的物理实体信息更新；
    (2)对采集的物理实体数据进行分析，提取出关键信息，同步映射到虚拟实体中，对主模型的虚拟实体部分关键信息更新，以实现与物理实体双向映射与同步仿真要求；
    (3)对现场采集的生产实时数据，同步储存到数据库中，更新主模型的孪生数据模型；
    (4)当现场的业务逻辑和服务发生变化时，需重新构建主模型的孪生服务模型；
    (5)当主模型的物理实体、虚拟实体、孪生数据模型、服务模型发生增删、替换时，需重新构建主模型的连接模型。
  5. 根据权利要求3所述的数字孪生模型组装方法，其特征在于，数字孪生融合组装方法适用于车间设备单元级组装成产线级的应用场景，其特点在于：设备单元级是指车间最小的生产单元，生产过程由多个设备级单元的交互配合而完成，产线级功能与服务是由各个设备级单元共同作用相互融合的结果，针对组装的产线需要构建全新的孪生连接模型，同时，根据生产任务与需求构建全新的孪生服务。
  6. 根据权利要求1所述的数字孪生模型组装方法，其特征在于，数字孪生模型包含了五个维度，分别是物理实体、虚拟实体、连接模型、孪生数据、孪生服务模型,从这五个维度实现连接组装，数字孪生模型的连接组装流程如下：
    21)主模型的物理实体包括所有子模型的物理实体的并集，还包括物理体连接组装时所产生的附加实体模型；
    22)主模型的虚拟实体包括所有子模型的虚拟实体的并集，还包括孪生模型连接组装时所产生的附加虚拟模型；
    23)主模型的孪生服务模型包括所有子模型的孪生服务模型的并集，还包括孪生模型连接组装时所产生的附加孪生服务模型；
    24)主模型的孪生数据包括所有子模型的孪生数据的并集，还包括孪生模型连接组装时所产生的附加孪生数据；
    25)主模型的连接模型包括所有子模型的连接模型的并集，还包括孪生模型连接组装时所产生的附加连接模型；
    26)将组装后主模型信息更新为实际信息。
  7. 根据权利要求6所述的数字孪生模型组装方法，其特征在于，数字孪生模型连接组装表示将多个数字孪生模型通过连接的方式进行组装，连接组装完成后，保留原有所有子模型，构建一个新的更加复杂的主模型；
    Figure PCTCN2022122458-appb-100002
    式中，DT ∑表示组合操作得到的数字孪生模型，符号∑表示组合操作，符号∪表示逻辑并运算,PE i是第i个子模型的物理实体，VE i是第i个子模型的虚拟实体，Ss i是第i个子模型的孪生服务模型，DD i是第i个子模型的孪生数据，CN i是第i个子模型的连接模型，PE x是在数字孪生模型组装时产生的原有物理模型之外的实体模型，VE x是在数字孪生模型组装时产生的原有虚拟模型之外的虚拟模型，Ss x是在数字孪生模型组装时产生的原有孪生服务之外的孪生服务模型，DD x是在数字孪生模型组装时产生的原有孪生数据之外的孪生数据，CN x是在数字孪生模型组装时产生的原有连接模型之外的连接模型。
  8. 根据权利要求2所述的数字孪生模型组装方法，其特征在于，数字孪生模型连接组装之后，需要对数字孪生模型按现场实际信息进行更新，主要包括对物理实体、虚拟实体、孪生服务、孪生数据、连接模型的更新，
    (1)采集各子模型物理实体数据以及附加物理实体数据，对各子模型的物理实体信息更新，再更新附加物理实体信息，进而对主模型的物理实体信息更新；
    (2)对采集的各子模型物理实体数据进行分析，同步映射到各子模型的虚拟实体中，更新各子模型的虚拟实体，再更新附加虚拟实体信息，进而完成对主模型的虚拟实体信息的更新，以实现与主模型的物理实体双向映射与同步仿真要求；
    (3)对现场采集各子模型的生产实时数据，同步储存到各子模型的数据库中，更新子模型的孪生数据模型信息，再更新附加孪生数据模型信息，进而完成对主模型的孪生数据模型信息更新；
    (4)当现场的业务逻辑和服务发生变化时，需要对各子模型中所有孪生服务以及附加孪生服务更新，进而完成对主模型孪生服务更新；
    (5)当主模型的物理实体、虚拟实体、孪生数据模型、服务模型发生增删、替换时，需要 对各子模型中连接模型以及附加连接模型更新，进而完成对主模型的连接模型更新。
  9. 根据权利要求6所述的数字孪生模型组装方法，其特征在于，数字孪生连接组装方法适用于产线级单元组装成整个车间的应用场景，产线级单元是指车间具有加工、运输、装配、检测独立完整功能与服务的生产线，整个车间由多个独立产线级单元的相互配合而完成，车间的功能和服务是由多条产线共同作用相互连接的结果，根据生产任务与需求，在现有各产线完整服务与连接的基础上，构建针对整个车间的附加的孪生服务与附加的连接模型。
  10. 根据权利要求4或8所述的数字孪生模型组装方法，其特征在于，数字孪生模型更新所需的现场实际信息包括：物理实体运行状态与属性数据、物理实体结构参数、布局信息、工艺流程信息、信号交互信息、虚拟实体的模型驱动数据、孪生服务数据以及模型关联数据。
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