Simulation and management linkage-based digital twin construction and service templating system

Abstract

The application relates to a digital twin construction and service templating system based on simulation and management and control linkage, and belongs to the technical field of industrial digital twins. The system comprises the following: a digital twin construction module integrated with a semantic understanding and interface mapping unit, which intelligently recommends data and event association configuration for a newly-built component; a simulation and management and control linkage configuration module which establishes external driving relationships for the component; a service encapsulation and templating management module integrated with a composite template generation unit, which can mine reusable modes from historical cases and generate structured templates; and a template application and context adaptation module which instantiates the templates and adapts them to a new environment. The application solves the problems of complicated digital twin construction, complex configuration and difficult reuse through intelligent construction, visual linkage configuration, knowledge-based template encapsulation and adaptive application, significantly reduces the technical threshold, and improves the development efficiency and reusability of solutions.

Description

Technical Field

[0001] This invention belongs to the field of industrial digital twin technology, specifically relating to a digital twin construction and service template system based on simulation and control linkage. Background Technology

[0002] With the deepening of industrial digital and intelligent transformation, digital twin technology, as the core carrier connecting the physical world and digital space, has been widely applied in various fields such as industrial manufacturing, smart cities, and energy and power, becoming a key engine driving industrial upgrading. Digital twins, by constructing virtual models that precisely correspond to physical entities and combining real-time data interaction and simulation analysis, enable full lifecycle management of physical entities, significantly improving production efficiency and reducing operation and maintenance costs.

[0003] Currently, existing digital twin systems have initially acquired functions such as virtual model construction, data integration, and basic simulation. However, they still face many pain points that urgently need to be addressed during engineering implementation, severely restricting the large-scale application of the technology. First, the reusability of digital twin components is extremely poor. Existing systems are mostly customized for single projects, and once the components are built, they cannot be effectively reused. Each new project requires the repeated development of similar functions, resulting in lengthy development cycles and high labor costs, making it difficult for small and medium-sized enterprises to afford the relevant investments.

[0004] Secondly, the integration of components with data sources and event streams relies on manual operation, lacking intelligent semantic matching capabilities. Manual configuration of interface protocols and linkage rules is required, which is not only inefficient but also prone to errors leading to delays in virtual-physical linkage, hindering real-time simulation and control. Furthermore, the existing system's template mechanism is inadequate, only enabling simple reuse of single components. It cannot extract frequently occurring component combinations and linkage configuration patterns from historical projects, and lacks directly applicable composite templates.

[0005] In addition, the existing system has weak cross-project adaptability. Different projects have different environmental parameters and resource configurations. The existing twin components and configurations cannot be quickly adapted to new scenarios, requiring a lot of secondary development, which further increases the development cost and cycle. Moreover, the simulation function and the control function are mostly independent of each other and cannot form a closed loop linkage, making it difficult to give full play to the collaborative control value of the digital twin.

[0006] In response to the problems of low efficiency in building digital twins, poor reusability, high difficulty in adaptation, and insufficient linkage between simulation and control in the existing technologies, there is an urgent need for a technical solution that can achieve intelligent component matching, templated linkage configuration, and cross-project adaptive adaptation, so as to reduce the development and application cost of digital twins and promote their large-scale and standardized implementation. Summary of the Invention

[0007] To address the aforementioned problems in the existing technology, this invention provides a digital twin construction and service template system based on simulation and control linkage. The objective of this invention can be achieved through the following technical solutions:

[0008] A digital twin construction and service template system based on simulation and control linkage includes:

[0009] The digital twin construction module provides a visual editing environment to generate digital twin components containing geometric models, logical attributes, and configurable software interfaces based on user operations. It also integrates a semantic understanding and interface mapping unit, which uses semantic parsing and similarity matching algorithms to intelligently associate newly created digital twin components with existing data sources and event streams, and provides configuration recommendations. The logical attributes include business logic attributes, simulation state attributes, and management and control attributes. The configurable software interfaces include data interaction interfaces and event triggering interfaces.

[0010] The simulation and control linkage configuration module is used to establish a driving relationship between the digital twin component and external data sources or event streams, and respond to external inputs to drive its state transition, action execution or business process evolution;

[0011] The service encapsulation and template management module is used to encapsulate the configured digital twin components and their interaction logic into independently callable twin services, and to perform template storage and management of the services; it also integrates a composite template generation unit, which is used to mine reusable component combinations and linkage configuration patterns based on historical cases to generate structured composite templates.

[0012] The template application and context adaptation module is used to instantiate templated twin services and adapt them to the target project environment.

[0013] As a preferred embodiment of the present invention, the semantic understanding and interface mapping unit is specifically used for:

[0014] The functional tags and interface description text of the digital twin components are parsed, and semantic recognition and expansion are performed based on a preset domain ontology library. The domain ontology library contains professional terms, semantic association rules and mapping relationships between components and resources in the field of digital twins.

[0015] Based on the semantic recognition results, data sources and event streams that are protocol compatible and match data types or event types are filtered to form a configuration recommendation list.

[0016] Specifically, the semantic understanding and interface mapping unit further includes a matching optimizer; the matching optimizer is used to obtain the real-time performance indicators and historical call success rates of existing data sources and event streams, and to dynamically prioritize the candidate options in the configuration recommendation list according to a preset weight algorithm; the real-time performance indicators include at least one of data transmission rate, concurrent connection count, and resource utilization rate.

[0017] Specifically, the simulation and control linkage configuration module provides a graphical logic orchestration interface, which offers various types of logic function nodes. Users can drag and drop and connect the logic function nodes with the digital twin components to define the data flow, event response chain, and business processes including conditional judgments between components.

[0018] Specifically, the driving relationship is implemented through a protocol adaptation layer; the protocol adaptation layer encapsulates the processing of MQTT, WebSocket and HTTP API protocols, and is configured to adaptively select or switch between protocols according to network status or service quality requirements.

[0019] Specifically, the composite template generation unit uses graph mining algorithms to analyze the connection relationships, data flow, and event triggering sequence between digital twin components in historical projects, extracts frequently co-occurring component subgraphs, and parses the logical dependencies of components within the component subgraphs, abstracting them into reusable topological logic patterns as the core of the linkage configuration pattern.

[0020] Specifically, the composite template generation unit further includes a template semantic enhancer, which is used to automatically annotate the generated structured composite template with functional semantic tags, generate structured summaries, and establish a semantic association network between the composite template and the basic component library to support semantic-based template retrieval and recommendation; the template semantic enhancer does not participate in the instantiation and environment adaptation of the composite template.

[0021] Specifically, the twin service is defined using a description file that includes interface contracts, data patterns, and dependency information, and is versioned, managed, and published through a built-in service repository.

[0022] Specifically, the template application and context adaptation module is used to: parse the component configuration and logical relationships in the composite template when the user applies the structured composite template; scan and match the available resources of the target project environment; and adapt the abstract definitions in the composite template to specific environmental resources based on semantic mapping or rule mapping to complete parameterized instantiation.

[0023] Specifically, when the target project environment lacks the resources specified by the composite template, the template application and context adaptation module calls the semantic understanding and interface mapping unit to find functionally equivalent alternative resources and automatically reconstruct the corresponding driving relationship or accept user manual mapping instructions to complete the adaptation.

[0024] Specifically, the visual editing environment includes a 3D scene editor and a 2D configuration editor; each editor is connected through a unified component metadata model and a state synchronization bus; in response to any modification operation of the attributes, state or linkage configuration of the digital twin component in any editor, the corresponding update message is distributed to other editors through the state synchronization bus, triggering other editors to refresh their corresponding views and logical models based on the update message.

[0025] Specifically, the system is deployed in a cloud-based microservice architecture; the digital twin construction module, simulation and control linkage configuration module, service encapsulation and template management module, and template application and context adaptation module are independent microservices that communicate and collaborate through a unified event bus and API gateway.

[0026] The beneficial effects of this invention are as follows:

[0027] Significantly improves the efficiency of digital twin construction and reduces development costs. The integrated semantic understanding and interface mapping unit in the visual editing environment of the digital twin construction module can automatically parse component semantics and realize intelligent association and recommendation with data sources and event streams, replacing traditional manual configuration and avoiding configuration errors; at the same time, it clearly defines component attributes and interface types, improves component standardization, lays the foundation for subsequent reuse, and effectively solves the problem of redundant component development in existing technologies.

[0028] This enables deep integration of simulation and control, improving control accuracy and real-time performance. The simulation and control linkage configuration module, through a graphical logic orchestration interface, allows for easy definition of data flow and event response logic between components. Combined with the multi-protocol adaptive switching capability of the protocol adaptation layer, it ensures stable and efficient linkage between digital twin components and internal and external data sources and event flows, controlling data synchronization latency to the millisecond level. This achieves a real-time closed loop between virtual simulation and physical control, fully leveraging the collaborative control value of the digital twin.

[0029] A template-based reuse system is built to promote the large-scale deployment of digital twin technology. The service encapsulation and template management module encapsulates the configured components and interaction logic into independently callable twin services. It also extracts high-frequency reuse patterns from historical projects through the composite template generation unit to generate structured composite templates, achieving "configuration once, reuse many times". The template semantic enhancer, together with the context adaptation module, enables intelligent template retrieval and cross-project adaptive adaptation, eliminating the need for extensive secondary development and lowering the application threshold for SMEs.

[0030] Enhance system adaptability and scalability to meet the needs of various application scenarios. The template application and context adaptation modules can automatically match the target project environment resources, and intelligently match alternative resources and reconstruct driving relationships when resources are missing, thereby improving the system's environment adaptability. The cloud microservice architecture and real-time synchronization design of multiple editors enable the system to flexibly expand functional modules and adapt to the digital twin construction needs of different fields, while ensuring the consistency of multi-role collaborative editing, further improving the system's practicality and scalability.

[0031] In summary, this invention effectively addresses the core pain points of existing digital twin systems through multi-module collaborative innovation, achieving full-process optimization of digital twin construction, linkage, encapsulation, and reuse. It significantly improves development efficiency, reduces application costs, and promotes the development of digital twin technology towards standardization, large-scale production, and intelligence, possessing extremely high industrial application value and promising prospects for promotion. Attached Figure Description

[0032] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings.

[0033] Figure 1 This is a schematic diagram of the architecture of the digital twin construction and service template system based on simulation and control linkage of the present invention;

[0034] Figure 2 This is a flowchart illustrating the entire lifecycle of the digital twin of this invention.

[0035] Figure 3 This is a flowchart of the semantic understanding and interface mapping unit of the present invention;

[0036] Figure 4 This is a flowchart of the protocol adaptation layer adaptive switching process of the present invention;

[0037] Figure 5 This is a flowchart illustrating the template application and context adaptation process of the present invention. Detailed Implementation

[0038] To further illustrate the technical means and effects of the present invention in achieving its intended purpose, the following detailed description of the specific implementation methods, structures, features, and effects of the present invention, in conjunction with the accompanying drawings and preferred embodiments, is provided.

[0039] Please see Figures 1-5 A digital twin construction and service template system based on simulation and control linkage, including:

[0040] The digital twin construction module provides a visual editing environment to generate digital twin components containing geometric models, logical attributes, and configurable software interfaces based on user operations. It also integrates a semantic understanding and interface mapping unit, which uses semantic parsing and similarity matching algorithms to intelligently associate newly created digital twin components with existing data sources and event streams, and provides configuration recommendations. The logical attributes include business logic attributes, simulation state attributes, and management and control attributes. The configurable software interfaces include data interaction interfaces and event triggering interfaces.

[0041] The simulation and control linkage configuration module is used to establish a driving relationship between the digital twin component and external data sources or event streams, and respond to external inputs to drive its state transition, action execution or business process evolution;

[0042] The service encapsulation and template management module is used to encapsulate the configured digital twin components and their interaction logic into independently callable twin services, and to perform template storage and management of the services; it also integrates a composite template generation unit, which is used to mine reusable component combinations and linkage configuration patterns based on historical cases to generate structured composite templates.

[0043] The template application and context adaptation module is used to instantiate templated twin services and adapt them to the target project environment.

[0044] This embodiment adopts a cloud-based microservice architecture and is suitable for digital twin management and control scenarios of production equipment in the industrial manufacturing field. The system as a whole realizes communication and collaboration among various modules through a unified event bus and API gateway. The specific implementation details are as follows:

[0045] The digital twin building block is deployed on a cloud server, providing a visual editing environment that integrates a 3D scene editor and a 2D configuration editor. Users can log in to the editing interface through a browser and generate digital twin components based on drag-and-drop operations. This component includes a geometric model, logical attributes, and configurable software interfaces that correspond to the production equipment at a 1:1 scale. Specifically, the business logic attributes include the production equipment's start-up and shutdown rules and capacity parameters; the simulation status attributes include the equipment's operating temperature and speed; and the management and control attributes include the equipment's fault warning thresholds and adjustment commands. The data interaction interface in the configurable software interfaces is used to receive real-time operating data from the equipment, while the event triggering interface is used to respond to events such as fault alarms and parameter adjustments.

[0046] The semantic understanding and interface mapping unit integrated in this module uses a cosine similarity algorithm to achieve semantic parsing and similarity matching. When a user imports a new production equipment component, the unit automatically parses the component's functional tags (such as "motor speed monitoring") and interface description text. Based on a preset digital twin domain ontology library (containing professional terms in the industrial manufacturing field, and mapping rules between components and data sources), it performs semantic expansion and recognition. Then, it filters existing data sources (historical equipment operation database within the system, and field sensor acquisition systems externally) and event streams that are protocol compatible and data type matching within the system, and generates an intelligent association recommendation list for users to confirm and apply directly, replacing traditional manual configuration and significantly reducing the workload of interface docking and the configuration error rate.

[0047] The simulation and control linkage configuration module communicates with the digital twin construction module through an API gateway, providing a graphical orchestration interface that includes various logical function nodes such as data processing, condition judgment, and event triggering. Users do not need to write code; they can simply drag and drop logical function nodes and establish connections with digital twin components to define the data flow between components (e.g., sensor data → motor component → early warning component), event response chain, and conditional branch logic (e.g., triggering a fault early warning event when the motor speed exceeds a threshold). This establishes a driving relationship between the digital twin components and internal and external data sources and event flows, enabling external inputs (e.g., real-time sensor data, manual adjustment commands) to drive the state transition, action execution, and production business process evolution of the components.

[0048] The service encapsulation and template management module receives component configuration information from the linkage configuration module. It encapsulates the configured digital twin components (such as motor components and early warning components) and their interaction logic into independently callable twin services. These services are defined using a JSON-formatted description file containing interface contracts, data patterns, and dependency information. They are versioned, managed, and published through the system's built-in service repository. The integrated composite template generation unit uses a PageRank graph mining algorithm to analyze historical digital twin project cases of production equipment, extracting frequently occurring component combinations (such as motor + sensor + early warning components) and linkage configuration patterns to generate structured composite templates. These templates contain core information such as component configuration parameters and logical association rules, and support one-click invocation.

[0049] The template application and context adaptation module is used to apply the templated digital twin service to new production equipment management projects. When a user calls the above-mentioned structured composite template, this module first parses the component configuration and logical relationship in the template, scans the available resources of the target project environment (such as field sensor models and server configuration), and adapts the abstract definition in the template to specific environmental resources based on semantic mapping rules, thus completing parameterized instantiation. If the target project lacks a certain type of sensor resource specified by the template, this module will call the semantic understanding and interface mapping unit to find a functionally equivalent alternative sensor in the system resource library and automatically reconstruct the driving relationship to ensure that the template can be quickly adapted to new scenarios, significantly shortening the digital twin construction cycle of new projects.

[0050] This embodiment achieves the entire process of building, configuring, encapsulating services, and reusing templates for digital twins of production equipment through the collaborative work of the four modules mentioned above.

[0051] Specifically, the semantic understanding and interface mapping unit is used for:

[0052] The functional tags and interface description text of the digital twin components are parsed, and semantic recognition and expansion are performed based on a preset domain ontology library. The domain ontology library contains professional terms, semantic association rules and mapping relationships between components and resources in the field of digital twins.

[0053] Based on the semantic recognition results, data sources and event streams that are protocol compatible and match data types or event types are filtered to form a configuration recommendation list.

[0054] Specifically, the semantic understanding and interface mapping unit further includes a matching optimizer; the matching optimizer is used to obtain the real-time performance indicators and historical call success rates of existing data sources and event streams, and to dynamically prioritize the candidate options in the configuration recommendation list according to a preset weight algorithm; the real-time performance indicators include at least one of data transmission rate, concurrent connection count, and resource utilization rate.

[0055] This embodiment is based on a digital twin management and control scenario for industrial manufacturing equipment. The semantic understanding and interface mapping unit is integrated into the cloud service node of the digital twin construction module. It establishes communication with the system's preset domain ontology library, data source management module, and event flow management module to realize intelligent association and configuration recommendation between newly created digital twin components and existing data sources and event flows in the system. The specific working process is as follows:

[0056] When a user creates or imports a new digital twin component (taking the "industrial production line frequency converter component" as an example in this embodiment), the unit first initiates a semantic parsing process to automatically extract the component's function tags and interface description text. The function tags are "frequency converter speed regulation, operating parameter acquisition, and fault signal feedback," and the interface description text is "supports analog / digital signal interaction, requires connection to field sensor data sources and equipment control event streams, and enables real-time reception of speed parameters and output of adjustment commands."

[0057] Subsequently, the unit invokes the system's preset domain ontology library for semantic recognition and expansion. This domain ontology library is custom-built for the industrial digital twin domain and specifically includes three core components: first, digital twin domain terminology, covering industrial equipment and parameter-related terms such as inverters, sensors, PLCs, speed, and fault codes; second, semantic association rules, such as a strong association between "inverter" and "speed adjustment" and "parameter acquisition," and a strong association between "fault signal feedback" and "equipment early warning event stream"; and third, the mapping relationship between components and resources, such as a preset mapping relationship between "inverter component" and "speed sensor data source" and "inverter control event stream." Based on this domain ontology library, the unit expands the semantics of "inverter speed adjustment" to "inverter receives control commands and adjusts the production line's operating speed," and expands the semantics of "fault signal feedback" to "inverter collects its own fault information and outputs it to the equipment early warning event stream," thus completing accurate semantic recognition of component functions.

[0058] After semantic recognition is completed, the unit enters the filtering and matching stage. Based on the identified component functional semantics, it filters out data sources and event streams that are protocol-compatible and have matching data types or event types in the system data source management module and event stream management module. In this embodiment, the filtering logic is as follows: priority is given to matching data sources and event streams that support analog / digital signal interaction, and data sources with data type "speed parameter" (such as assembly line speed sensor data source) and event streams with event type "equipment control" or "fault warning" (such as inverter control event stream and equipment warning event stream). Finally, 3 candidate data sources and 2 candidate event streams are filtered out and integrated to form a configuration recommendation list. The list clearly marks the protocol type, data / event type and matching degree with the current inverter component for each candidate data source and event stream for user confirmation and selection.

[0059] The semantic understanding and interface mapping unit also integrates a matching optimizer, which dynamically prioritizes the above-mentioned configuration recommendation list to further improve the rationality and practicality of the recommendations. Its specific working process is as follows: The matching optimizer obtains real-time performance indicators and historical call success rates of each candidate data source and event stream in the configuration recommendation list through the system monitoring module. The real-time performance indicators include data transmission rate, concurrent connections, and resource utilization. Data transmission rate is collected in real-time by network monitoring tools, concurrent connections are obtained through server log statistics, and resource utilization is collected through server monitoring tools. Simultaneously, the matching optimizer uses the Analytic Hierarchy Process (AHP) to calculate the comprehensive score of the candidate data source / event stream. The core formula and weight allocation are as follows:

[0060] The comprehensive score calculation formula is: S = 0.6 × (0.5 × Vr + 0.33 × Vc + 0.17 × Vo) + 0.4 × Vs, where:

[0061] S represents the overall score of the candidate (range 0-100 points).

[0062] Vr is the normalized value of data transmission rate (actual rate / theoretical maximum rate × 100).

[0063] Vc is the standardized value of the number of concurrent connections ((theoretical maximum concurrency - actual concurrency) / theoretical maximum concurrency × 100);

[0064] Vo is the standardized value of resource utilization rate ((theoretical maximum utilization rate - actual utilization rate) / theoretical maximum utilization rate × 100).

[0065] Vs represents the historical call success rate (number of successful calls / total number of calls × 100).

[0066] Weighting rules: The total weight of real-time performance metrics is 60% (data transmission rate accounts for 30%, concurrent connections account for 20%, and resource utilization rate accounts for 10%), and the weight of historical call success rate is 40%; after standardization, all metrics are in the range of 0-100 points to ensure consistent scoring dimensions.

[0067] Based on the acquired metric data and a preset weighting algorithm, the matching optimizer comprehensively scores the candidates in the recommendation list and dynamically prioritizes them according to the scoring results. The candidate with the highest score, best performance, and most stable call is placed first, followed by the next highest score. For example, a speed sensor data source with stable real-time data transmission rate, low concurrent connections, low resource consumption, and a high historical call success rate has the highest comprehensive score and is ranked first in the recommendation list; a candidate event stream with high resource consumption has a lower comprehensive score and is ranked last. This dynamic prioritization guides users to prioritize data sources and event streams with better performance and more suitable for the current scenario, significantly improving the stability of the linkage between components, data sources, and event streams, and reducing the workload of subsequent configuration adjustments.

[0068] This embodiment clearly realizes all the functions of the semantic understanding and interface mapping unit and the matching optimizer through the above specific implementation methods, and solves the problems of low efficiency and inaccurate matching in traditional manual configuration. Through semantic intelligent recognition, accurate filtering and dynamic optimization sorting, it realizes efficient association between components and data sources and event streams, and provides strong support for the rapid configuration of digital twin components.

[0069] Specifically, the simulation and control linkage configuration module provides a graphical logic orchestration interface, which offers various types of logic function nodes. Users can drag and drop and connect the logic function nodes with the digital twin components to define the data flow, event response chain, and business processes including conditional judgments between components.

[0070] Specifically, the driving relationship is implemented through a protocol adaptation layer; the protocol adaptation layer encapsulates the processing of MQTT, WebSocket and HTTP API protocols, and is configured to adaptively select or switch between protocols according to network status or service quality requirements.

[0071] Specifically, the composite template generation unit uses graph mining algorithms to analyze the connection relationships, data flow, and event triggering sequence between digital twin components in historical projects, extracts frequently co-occurring component subgraphs, and parses the logical dependencies of components within the component subgraphs, abstracting them into reusable topological logic patterns as the core of the linkage configuration pattern.

[0072] Specifically, the composite template generation unit further includes a template semantic enhancer, which is used to automatically annotate the generated structured composite template with functional semantic tags, generate structured summaries, and establish a semantic association network between the composite template and the basic component library to support semantic-based template retrieval and recommendation; the template semantic enhancer does not participate in the instantiation and environment adaptation of the composite template.

[0073] This embodiment describes in detail the specific implementation of the protocol adaptation layer for driving relationships, the composite template generation unit, and the template semantic enhancer based on the digital twin management and control scenario of industrial manufacturing equipment.

[0074] The system is used for digital twin control of multiple production lines in an industrial workshop, covering various digital twin components such as motors, frequency converters, and sensors. The driving relationships between each component and internal and external data sources and event flows are all realized through a protocol adaptation layer. The composite template generation unit and template semantic enhancer are integrated into the service encapsulation and template management module, which collaboratively realize the generation, semantic enhancement, and intelligent retrieval of structured composite templates. The specific implementation details are as follows:

[0075] The driving relationship is implemented through a protocol adaptation layer, which is an independent software functional module deployed on the communication node of the simulation and control linkage configuration module. It establishes bidirectional communication with the digital twin component, the data source management module, and the event flow management module. Its core function is to encapsulate the processing logic of three protocols: MQTT, WebSocket, and HTTP API, so as to realize the adaptive selection and seamless switching of protocols and ensure the stability and efficiency of the driving relationship.

[0076] In this embodiment, the protocol adaptation layer incorporates a protocol detection module and a switching control module. The working logic is as follows: The protocol detection module collects network status parameters (such as network latency and packet loss rate) and service quality requirements (such as data transmission real-time performance and data volume) in real time, and feeds the detection results back to the switching control module. The switching control module automatically selects the appropriate communication protocol based on preset rules: when the control scenario requires high real-time performance (such as transmission of motor speed and inverter fault signals) and has low network latency, the WebSocket protocol is selected to ensure real-time bidirectional data interaction; when the scenario requires low bandwidth and high reliability (such as periodic collection of workshop environmental parameters), the MQTT protocol is selected to reduce network resource consumption; when the scenario involves ordinary data queries and configuration command issuance (such as remote querying of component parameters), with low data interaction frequency and small data volume, the HTTPAPI protocol is selected to improve communication flexibility.

[0077] When network conditions change abruptly (such as sudden network congestion or a sharp increase in packet loss) or service quality requirements are adjusted, the protocol adaptation layer can achieve seamless protocol switching. During the switching process, a caching mechanism temporarily stores data to prevent data loss or corruption, ensuring that the driving relationship between digital twin components and data sources and event streams remains uninterrupted, significantly improving linkage stability and adapting to the complex network environment of industrial workshops. The protocol switching trigger thresholds for the protocol adaptation layer are as follows:

[0078]

[0079] Seamless switching supplementary rules: When switching protocols, the data buffering time is preset to 500ms to ensure that no data is lost during the switching process; after the switching is completed, the integrity of the first 3 sets of data transmissions must be verified. If the verification passes, the switching is confirmed to be successful; otherwise, it will roll back to the original protocol.

[0080] The composite template generation unit is integrated into the service encapsulation and template management module. It uses the PageRank graph mining algorithm as the core algorithm to mine reusable component combinations and linkage configuration patterns based on historical project cases, and generate structured composite templates. The specific working process is as follows:

[0081] First, the composite template generation unit accesses the system's historical project database to extract 10 typical historical project cases of digital twin control of industrial workshop production lines over the past three years. These cases cover different scenarios, including single production lines and multi-production line linkages, and include various digital twin components such as motors, sensors, frequency converters, and early warning components. Then, graph mining algorithms are used to analyze each historical case, focusing on mining the connections between digital twin components (e.g., the connections between sensor components and motor components, and early warning components), data flow (e.g., data collected by sensors → motor components → early warning components), and event triggering sequences (e.g., motor speed exceeding limits → triggering an alarm in the early warning component → issuing a frequency converter adjustment command). The core frequency determination rules of the PageRank graph mining algorithm are as follows:

[0082] High-frequency co-occurrence threshold setting: The preset threshold for the frequency of a component subgraph is 80%. That is, when a component subgraph (such as "sensor + motor + inverter + early warning component") appears ≥ 80% of the total number of cases in historical project cases, it is judged as a "high-frequency co-occurrence subgraph" and included in the topology logic pattern extraction range.

[0083] Additional rules for subgraph selection: In addition to the frequency threshold, the following conditions must be met simultaneously: "Complete logical dependencies of components within the subgraph" (e.g., no breakpoints in the data flow from sensor to motor to early warning component) and "Subgraph adaptation scenario coverage ≥ 70%" (adapting to at least 70% of similar industrial production line scenarios). Only when both conditions are met can it be abstracted into a reusable topological logic pattern.

[0084] Next, the algorithm extracts frequently co-occurring component subgraphs from the aforementioned historical cases. In this embodiment, the high-frequency component subgraph of "sensor + motor + inverter + early warning component" is selected, which appears in 80% of the historical cases. Finally, the logical dependencies of each component within this component subgraph are analyzed (e.g., the sensor depends on the motor to provide operating status data, the inverter depends on the sensor data for speed regulation, and the early warning component depends on the fault signals of the motor and the inverter to trigger the alarm). The component subgraph and its corresponding logical dependencies and linkage configuration rules are abstracted into a reusable topological logic pattern. Based on this, combined with component configuration parameters and protocol selection rules, a structured composite template is generated and stored in the system's template repository, supporting one-click access by users.

[0085] The composite template generation unit also includes a template semantic enhancer. This enhancer communicates with the system's domain ontology library and basic component library. Its core function is to perform semantic enhancement on the generated structured composite templates, supporting semantic-based template retrieval and recommendation. It explicitly does not participate in the instantiation and environment adaptation of composite templates. Its specific working process is as follows:

[0086] After the composite template generation unit generates the above-mentioned structured composite template of "sensor + motor + frequency converter + early warning component", the template semantic enhancer automatically starts the semantic enhancement process: First, it automatically marks functional semantic tags, and combines the domain ontology library to mark the template with core semantic tags such as "industrial production line motor control, speed regulation, and fault early warning". The tags are strongly related to the functions of the template; Second, it generates a structured summary, which clearly defines the applicable scenario of the template (single industrial production line motor control scenario), the types of components included, the core linkage functions (speed acquisition-regulation-fault early warning closed loop) and the compatible protocol types.

[0087] Third, a semantic association network is established. This network links the composite template with atomic components such as sensors, motors, and frequency converters in the system's basic component library using semantic association rules (e.g., a direct semantic association between the template and "motor component" and "speed sensor component," and an indirect semantic association with "fault warning component"). These associations are stored in the semantic database. When a user searches for a template using natural language (e.g., "production line motor fault warning template") or scene features, the system quickly matches the corresponding structured composite template through the semantic association network. This enables intelligent template retrieval and recommendation, significantly improving template retrieval efficiency and allowing users to quickly find templates suitable for their current project scenario.

[0088] Specifically, the twin service is defined using a description file that includes interface contracts, data patterns, and dependency information, and is versioned, managed, and published through a built-in service repository.

[0089] Specifically, the template application and context adaptation module is used to: parse the component configuration and logical relationships in the composite template when the user applies the structured composite template; scan and match the available resources of the target project environment; and adapt the abstract definitions in the composite template to specific environmental resources based on semantic mapping or rule mapping to complete parameterized instantiation.

[0090] Specifically, when the target project environment lacks the resources specified by the composite template, the template application and context adaptation module calls the semantic understanding and interface mapping unit to find functionally equivalent alternative resources and automatically reconstruct the corresponding driving relationship or accept user manual mapping instructions to complete the adaptation.

[0091] Specifically, the visual editing environment includes a 3D scene editor and a 2D configuration editor; each editor is connected through a unified component metadata model and a state synchronization bus; in response to any modification operation of the attributes, state or linkage configuration of the digital twin component in any editor, the corresponding update message is distributed to other editors through the state synchronization bus, triggering other editors to refresh their corresponding views and logical models based on the update message.

[0092] This embodiment is based on the scenario of digital twin management and control of industrial manufacturing equipment. It provides a detailed implementation description of the definition and management of twin services, the workflow of template application and context adaptation modules, and the multi-editor synchronization mechanism of the visual editing environment.

[0093] In this embodiment, the system is used for digital twin management and control of multiple industrial production lines, covering various digital twin components such as motors, sensors, frequency converters, and early warning components. The encapsulation, template adaptation, and visual editing of the twin services are all centered around this scenario. Specific implementation details are as follows:

[0094] The twin service is defined using a description file that includes interface contracts, data patterns, and dependency information, and is versioned, managed, and published through the system's built-in service repository. In this embodiment, the description file is written in JSON format, which is highly readable and extensible, and can clearly define the calling specifications and runtime dependencies of the twin service. A specific definition example is as follows:

[0095] Taking the "Production Line Motor Control Twin Service" as an example, its description file clearly defines the service's input and output interface specifications in the interface contract, including the speed adjustment command input interface and the motor operating status data output interface, and clarifies the parameter types, data formats, and call frequency limits of the interfaces; the data model defines the data structure of service interaction, including the field definitions, data types, and value ranges of core data such as motor speed, operating temperature, and fault codes; the dependency information clarifies the system resources required for service operation, including the semantic support of the domain ontology library, the protocol processing capabilities of the protocol adaptation layer, and the sensor components and early warning component instances in the basic component library.

[0096] After the description file of the twin service is bound to the service ontology, it is uploaded to the system's built-in service repository. The service repository manages it in a versioned manner—assigning a unique version number to each service, recording version update logs (such as interface adjustments, data pattern optimizations, etc.), and supporting service version rollback, updates, and removal. At the same time, the service repository publishes the twin service to the outside world through the API gateway, annotating the service's functional description, applicable scenarios, and calling permissions, so that other modules within the system or external systems can retrieve and call it, greatly improving the manageability and reusability of the service.

[0097] The template application and context adaptation module is integrated into the system's cloud service. It is used to instantiate the templated stored digital twin service and adapt it to the target project environment. This embodiment takes "Building a Digital Twin Management Project for a New Third Production Line" as an example to explain its workflow in detail:

[0098] The first step is that when a user calls the "Structured Composite Template for Production Line Motor Control" in the service repository in a new project, the module first starts the template parsing process, reads the component configuration information (including model parameters and attribute settings of motors, sensors, and early warning components) and logical relationships (data flow between sensors and motors, and event triggering logic between motors and early warning components) in the template, and clarifies the core functions and operational requirements of the template.

[0099] The second step is to scan the available resources of the target project environment, including the sensor models deployed on site, server configurations, existing digital twin component instances, and data sources and event streams that can be called within the system, to form a list of resources in the target environment.

[0100] The third step involves the module adapting the abstract definitions in the template to specific environmental resources based on semantic mapping rules. For example, the abstract "speed sensor" component in the template is mapped to the actual "Hall speed sensor" instance deployed in the target project through semantic matching; the abstract "data transmission protocol" in the template is adapted to the WebSocket protocol supported by the target project environment. Finally, the parameterized instantiation of the template is completed, generating a digital twin component and linkage configuration adapted to the new project. This eliminates the need for users to manually reconfigure, significantly improving the efficiency of building new projects.

[0101] When the target project environment lacks the resources specified by the composite template, the template application and context adaptation module calls the semantic understanding and interface mapping unit to find functionally equivalent alternative resources and automatically reconstruct the corresponding driver relationships or accept user manual mapping instructions to complete the adaptation. In this embodiment, if the newly created project environment lacks the "specific model warning component" specified by the template, the following adaptation process is triggered:

[0102] The template application and context adaptation module sends a resource matching request to the semantic understanding and interface mapping unit to clarify the functional semantics of the required resources ("motor fault warning, speed overrun alarm, command issuance"). Based on the domain ontology library, the semantic understanding and interface mapping unit searches for functionally equivalent alternative warning components (such as another model of component with fault warning and alarm output functions) in the system basic component library and public resource library. After finding the alternative resource, the module automatically calls the protocol adaptation layer and linkage configuration logic to reconstruct the driving relationship between the alternative warning component and the motor and sensor components, ensuring that it can normally receive motor operation data and trigger alarm events. If there are slight differences between the alternative resource and the original template resource, the module will pop up an interactive interface for the user to manually confirm the mapping relationship, complete the final adaptation, and ensure that the template can be normally applied to the target project, avoiding the inability to reuse the template due to resource shortages.

[0103] The visual editing environment includes a 3D scene editor and a 2D configuration editor; each editor is connected through a unified component metadata model and a state synchronization bus; in response to any modification operation of the attributes, state or linkage configuration of the digital twin component in any editor, the corresponding update message is distributed to other editors through the state synchronization bus, triggering other editors to refresh their corresponding views and logical models based on the update message.

[0104] In this embodiment, the 3D scene editor is used to construct the 3D geometric model of the production line and each piece of equipment, and restore the layout of the production site. Users can adjust the 3D position, geometric size and other attributes of motors and sensors in the editor. The 2D configuration editor is used to edit the linkage logic and data flow between components, and presents the connection relationship between sensors and motors, early warning components and event response process in the form of configuration diagram.

[0105] A unified component metadata model standardizes the component data format across the two editors, ensuring consistency in component attributes, states, and linkage configurations. A state synchronization bus enables real-time data synchronization between the two editors, working as follows: When a user modifies the motor's speed warning threshold (from 1500 r / min to 1600 r / min) in the 2D configuration editor, this modification is converted into a standardized update message and distributed to the 3D scene editor via the state synchronization bus. Upon receiving the update message, the 3D scene editor refreshes the motor component's status parameter display based on the unified component metadata model and simultaneously adjusts the linkage configuration logic (ensuring a warning is triggered when the speed reaches 1600 r / min). Conversely, when a user adjusts the sensor's installation position and data acquisition range in the 3D scene editor, this modification is also synchronized to the 2D configuration editor, updating the corresponding configuration diagram and data flow logic. This achieves collaborative editing and configuration consistency between the two editors, significantly improving user editing efficiency and preventing configuration errors caused by multiple editor operations.

[0106] This embodiment clearly realizes the definition and management of digital twin services, cross-project template adaptation, and multi-editor synchronization in the visual editing environment through the above specific implementation methods. It effectively solves the problems of chaotic service management, inconvenient template adaptation, and inconsistent configuration of multiple editors. It further improves the whole process optimization of digital twin construction, reuse, and editing, enhances the practicality and operability of the system, and adapts to complex application scenarios in the industrial manufacturing field.

[0107] Specifically, the system is deployed in a cloud-based microservice architecture; the digital twin construction module, simulation and control linkage configuration module, service encapsulation and template management module, and template application and context adaptation module are independent microservices that communicate and collaborate through a unified event bus and API gateway.

[0108] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. A digital twin construction and service template system based on simulation and control linkage, characterized in that, include: The digital twin building module provides a visual editing environment to generate digital twin components containing geometric models, logical attributes, and software configurable interfaces based on user operations. It also integrates a semantic understanding and interface mapping unit, which provides intelligent association and configuration recommendations for newly built digital twin components with existing data sources and event streams through semantic parsing and similarity matching algorithms; the logical attributes include business logic attributes, simulation status attributes, and management and control attributes; The configurable interfaces of the software include data interaction interfaces and event triggering interfaces; The simulation and control linkage configuration module is used to establish a driving relationship between the digital twin component and external data sources or event streams, and respond to external inputs to drive its state transition, action execution or business process evolution; The service encapsulation and template management module is used to encapsulate the configured digital twin components and their interaction logic into independently callable twin services, and to perform template storage and management of the twin services; the management module integrates a composite template generation unit, which is used to mine reusable component combinations and linkage configuration patterns based on historical cases to generate structured composite templates. The template application and context adaptation module is used to instantiate templated twin services and adapt them to the target project environment.

2. The system according to claim 1, characterized in that, The semantic understanding and interface mapping unit is specifically used for: The functional tags and interface description text of the digital twin components are parsed, and semantic recognition and expansion are performed based on a preset domain ontology library. The domain ontology library contains professional terms, semantic association rules and mapping relationships between components and resources in the field of digital twins. Based on the semantic recognition results, data sources and event streams that are protocol compatible and match data types or event types are filtered to form a configuration recommendation list.

3. The system according to claim 2, characterized in that, The semantic understanding and interface mapping unit also includes a matching optimizer; the matching optimizer is used to obtain the real-time performance indicators and historical call success rates of existing data sources and event streams, and dynamically prioritize the candidate options in the configuration recommendation list according to a preset weight algorithm; the real-time performance indicators include at least one of data transmission rate, concurrent connection count and resource utilization rate.

4. The system according to claim 1, characterized in that, The simulation and control linkage configuration module provides a graphical logic orchestration interface, which offers various types of logic function nodes. Users can drag and drop and connect the logic function nodes with digital twin components to define the data flow, event response chain, and business processes including conditional judgments between components.

5. The system according to claim 1, characterized in that, The driving relationship is implemented through a protocol adaptation layer; the protocol adaptation layer encapsulates the processing of MQTT, WebSocket and HTTP API protocols, and is configured to adaptively select or switch between protocols according to network status or service quality requirements.

6. The system according to claim 1, characterized in that, The composite template generation unit uses graph mining algorithms to analyze the connection relationships, data flow, and event triggering sequence between digital twin components in historical projects, extracts frequently co-occurring component subgraphs, and parses the logical dependencies of components within the component subgraphs, abstracting them into reusable topological logic patterns as the core of the linkage configuration pattern.

7. The system according to claim 6, characterized in that, The composite template generation unit also includes a template semantic enhancer, which is used to automatically annotate the generated structured composite template with functional semantic tags, generate structured summaries, and establish a semantic association network between the composite template and the basic component library to support semantic-based template retrieval and recommendation; the template semantic enhancer does not participate in the instantiation and environment adaptation of the composite template.

8. The system according to claim 1, characterized in that, The twin service is defined using a description file that includes interface contracts, data patterns, and dependency information, and is versioned, managed, and published through a built-in service repository.

9. The system according to claim 1, characterized in that, The template application and context adaptation module is specifically used for: parsing the component configuration and logical relationships in the composite template when the user applies the structured composite template; scanning and matching the available resources of the target project environment; and adapting the abstract definitions in the composite template to specific environmental resources based on semantic mapping or rule mapping to complete parameterized instantiation.

10. The system according to claim 9, characterized in that, When the target project environment lacks the resources specified by the composite template, the template application and context adaptation module calls the semantic understanding and interface mapping unit to find functionally equivalent alternative resources and automatically reconstruct the corresponding driver relationship or accept user manual mapping instructions to complete the adaptation.

11. The system according to claim 1, characterized in that, The visual editing environment includes a 3D scene editor and a 2D configuration editor; each editor is connected through a unified component metadata model and a state synchronization bus; in response to any modification operation of the attributes, state or linkage configuration of the digital twin component in any editor, the corresponding update message is distributed to other editors through the state synchronization bus, triggering other editors to refresh their corresponding views and logical models based on the update message.

12. The system according to claim 1, characterized in that, The system is deployed in a cloud-based microservice architecture; the digital twin construction module, simulation and control linkage configuration module, service encapsulation and template management module, and template application and context adaptation module are independent microservices that communicate and collaborate through a unified event bus and API gateway.

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