A digital industrial platform supporting model self-evolution and data consistency self-correction

Abstract

The application relates to the technical field of an industrial digital platform, in particular to a digital industrial platform supporting model self-evolution and data consistency self-correction, which comprises a digital dictionary module, an industrial internet application module, a three-dimensional visualization operation and maintenance module, a BIM model construction module, a data service module, a model self-evolution module and a data consistency self-correction module. The application can realize automatic updating of a three-dimensional model and automatic detection and repair of multi-source data differences, improve the digital management level of an industrial enterprise from a design stage to an operation and maintenance stage, and significantly enhance data consistency and system reliability.

Description

Technical Field

[0001] This invention relates to the field of industrial digitalization technology, specifically to a digital industrial platform that supports model self-evolution and data consistency self-correction. Background Technology

[0002] With the deepening of industrial digital transformation, the needs for digital manufacturing equipment, production information collection, production resource identification, on-site visualization, and digital process design have become core components of digital workshop construction in industrial enterprises. To meet these needs, information and intelligent technology companies have developed various digital application tools and systems based on technologies such as big data, the Internet of Things, artificial intelligence, and digital twins, including industrial internet platforms, digital delivery platforms, and digital twin systems. These systems provide support to enterprises at different lifecycle stages or management dimensions. For example, digital delivery platforms primarily target the design and construction phases, building digital infrastructure based on BIM models; industrial internet platforms act as a bridge between data and personnel operations during factory operation through workflow-driven processes; and digital twin systems enhance the three-dimensional effect of management by adding spatial dimensions, suitable for scenarios such as visits and demonstrations, maintenance training, and process simulation. However, these systems are typically built separately, leading to difficulties in sharing basic data resources and forming a "siloed" architecture. Furthermore, the significant differences in design depth and construction dimensions between systems result in uneven digital capabilities across enterprises, significantly increasing the difficulty of subsequent supplementary construction.

[0003] Furthermore, the construction of digital systems in industrial workshops often involves the application of 3D models. However, due to frequent additions or modifications after system delivery, existing systems suffer from significant deficiencies in 3D model sharing and deep self-editing capabilities. This deficiency not only increases the complexity of model maintenance but also limits the system's adaptability in dynamic environments. Although 3D modeling technology and industrial internet platforms have been widely used in engineering construction and production management, existing industrial digital platforms mostly focus on module integration and visualization, making it difficult to effectively address technical issues such as lagging model updates, data inconsistencies, and a lack of closed-loop control. Specifically, frequent dynamic changes in industrial sites, such as equipment additions or structural modifications, often require manual maintenance of the original 3D model, which is costly and time-consuming. Simultaneously, 3D models, operational data, and related documents come from different systems, easily leading to version mismatches, disconnected identifiers, and incorrect references, affecting data reliability and efficiency. Moreover, the platform lacks a full-process closed-loop mechanism for triggering model changes, incremental stitching, difference identification, and correction feedback, further contributing to data silos and opaque system behavior.

[0004] For example, while some existing BIM platforms have document-model binding mechanisms, they still rely on manual identification of on-site changes and manual modification of the model, lacking automated control logic from data conflict detection to the execution of error correction suggestions. These issues indicate that existing technologies are significantly inadequate in dealing with the complex and dynamic changes in industrial sites. There is an urgent need for a new industrial digital platform system that can support model self-evolution and data consistency self-correction to improve the collaborative intelligence level of models and data, and solve key problems such as lagging model updates, data inconsistencies, and opaque system behavior. Summary of the Invention

[0005] This invention addresses the shortcomings of existing industrial digital platforms in terms of model updates, data consistency, and closed-loop control, proposing a digital industrial platform that supports model self-evolution and data consistency self-correction. The platform adopts a modular design, covering the comprehensive digital application needs of industrial enterprises from design to operation and maintenance. Through a model adaptive update mechanism and a data difference detection and feedback repair mechanism, it improves data consistency and reliability among the various modules within the platform.

[0006] This invention provides a digital industrial platform that supports model self-evolution and data consistency self-correction, including a digital dictionary module, an industrial internet application module, a 3D visualization operation and maintenance module, a BIM model construction module, a data service module, a model self-evolution module, and a data consistency self-correction module. Wherein:

[0007] The digital dictionary module enables digital delivery applications based on BIM models; the industrial internet application module enables factory operation management and comprehensive safety management applications driven by two-dimensional workflows; the three-dimensional visualization operation and maintenance module enables three-dimensional digital twin applications; the BIM model construction module provides tool-based application software with in-depth self-editing capabilities for three-dimensional models; and the data service module provides three-dimensional model sharing, data sharing, and document resource sharing services for the above modules. Furthermore, the model self-evolution module is used to drive automatic updates of the three-dimensional model when structural changes or new equipment information are detected in the industrial site; and the data consistency self-correction module is used to detect and correct inconsistencies in the relationships between the three-dimensional model, operational data, and documents.

[0008] Specifically, the digital dictionary module includes a rule configuration submodule, a digital dictionary processing submodule, and a display submodule. The rule configuration submodule provides constraints to the digital dictionary processing submodule before 3D model processing, specifically including an attribute rule configuration unit, a grouping rule configuration unit, a verification rule configuration unit, a system logic configuration unit, an identifier code input unit, and a model aggregation configuration unit. The digital dictionary processing submodule couples the 3D model with model attributes, documents, and dynamic data based on the 3D engine, specifically including a 3D component model reading unit, an attribute reading unit, a document reading unit, a model lightweighting unit, an identifier code recognition unit, and a runtime data reading unit. The display submodule displays the 3D model processed by the digital dictionary processing submodule according to the constraints provided by the rule configuration submodule, specifically including a discrete display unit, a grouped display unit, a logical display unit, and a retrieval unit.

[0009] Furthermore, the industrial internet application module includes an engine support submodule and an IoT application submodule. The engine support submodule provides basic capabilities for each application within the IoT application submodule and is responsible for data interaction with the data service module. Specifically, it includes a workflow engine unit, a configuration engine unit, a data engine unit, and a WEB3D engine unit. The IoT application submodule implements specific application functions, including an equipment management application unit, a safety management application unit, a hazard management application unit, a configuration management application unit, a work order application unit, a cockpit application unit, a model application unit, and a mapping configuration application unit.

[0010] Specifically, the 3D visualization operation and maintenance module includes a 3D scene submodule and a theme management submodule. The 3D scene submodule provides a basic operation and maintenance scene based on a 3D map and spatial configuration, specifically including 3D operation and maintenance scene units and tool-based editing units. The theme management submodule implements various functional applications based on the 3D operation and maintenance scene, specifically including a safety theme management unit, an equipment theme management unit, a pipeline theme management unit, a process theme management unit, a public theme management unit, and an entry theme management unit.

[0011] Furthermore, the BIM model construction module includes a model design submodule and a model processing submodule. The model design submodule implements specific BIM model design functions, including a design tree rule definition unit, a custom shape modeling unit, a parametric equipment modeling unit, a building modeling unit, and a design attribute configuration unit. The model processing submodule performs rendering, mapping, and input / output processing on the designed model, specifically including a model rendering unit, a model mapping processing unit, and an input / output processing unit.

[0012] Specifically, the data service module includes a model service submodule, a document service submodule, and an IoT service submodule. The model service submodule provides multi-format 3D model conversion, storage, input, and output services to other modules, specifically including a model input recognition unit, a raw model data caching unit, a model data structure parsing unit, a model format conversion unit, a model storage unit, and a model output unit. The document service submodule provides document storage, input, and output services to other modules, specifically including a document verification and storage unit, a document relationship saving unit, a document version iteration processing unit, and a document retrieval processing unit. The IoT service submodule provides data acquisition, storage, and push services to other modules, specifically including a data acquisition method and interface management unit, a optimized data processing unit, a data push service management unit, and a public service processing unit.

[0013] Furthermore, the model self-evolution module includes a site perception submodule, a change analysis submodule, a model incremental generation submodule, a structural fusion submodule, and an evolution version management submodule. The site perception submodule acquires change information from sensors, user reports, or construction plans. The change analysis submodule standardizes the change information, generating structural data containing component types, spatial locations, and topological relationships. The model incremental generation submodule constructs a corresponding 3D incremental model based on the analysis results. The structural fusion submodule spatially aligns the incremental model with the original 3D model and performs structural splicing. The evolution version management submodule records the model evolution process and supports version comparison and rollback.

[0014] Specifically, the data consistency self-correction module includes a multi-source data synchronization monitoring submodule, a consistency rule library submodule, a difference detection engine submodule, a self-correction suggestion generation submodule, and a user confirmation and rollback control submodule. The multi-source data synchronization monitoring submodule monitors the key identifiers and time consistency between model data, document information, and runtime status. The consistency rule library submodule stores consistency judgment rules. The difference detection engine submodule identifies objects with discrepancies based on the rules, and the self-correction suggestion generation submodule generates correction schemes based on the detection results. The user confirmation and rollback control submodule confirms, executes, and rolls back the correction schemes.

[0015] Furthermore, the site perception submodule includes a change triggering rule unit, which determines whether to trigger the model self-evolution operation based on the magnitude of spatial coordinate changes, the addition of component identifiers, or changes in construction progress nodes. When the newly added component does not exist in the current model identifier index, the model incremental generation operation is triggered.

[0016] Specifically, the incremental model generation submodule includes a component classification generation unit, which calls the corresponding modeling template for parametric modeling based on the component type information provided by the change analysis submodule. For equipment components, templates are configured based on size, material, and mounting surface; for pipe components, sub-models are generated using rules combining straight segments, bends, and connectors.

[0017] Furthermore, the structural fusion submodule constructs the connection edge set of the current model based on the model topology graph structure, and performs spatial matching judgment on the edge set generated by the incremental components. If the matching rate exceeds a set threshold, an automatic fusion operation is performed; if there is a topological conflict, the conflict area is marked as pending confirmation and submitted to the user for confirmation.

[0018] Specifically, the evolution version management submodule includes a model evolution log unit and a version tree management unit. The former records the incremental component ID, change source, fusion strategy, and post-change topology summary information involved in each evolution operation, while the latter constructs a version tree structure with time sequence and difference markers to support multi-branch comparison and rollback.

[0019] Furthermore, the multi-source data synchronization monitoring submodule is equipped with a difference determination unit, which compares the consistency between the attribute identifier in the 3D model and the reference identifier in the document metadata, and between the device ID in the running status data and the model index ID, and uses a hash check and timestamp priority strategy to determine the conflict level.

[0020] Specifically, the consistency rule library submodule includes a rule template management unit, which stores and dynamically invokes multi-source data consistency rules in a categorized manner. The rule templates include three categories: model and document version synchronization rules, runtime data binding integrity rules, and cross-module reference logic consistency rules.

[0021] Furthermore, the difference detection engine submodule adopts a parallel detection architecture, simultaneously performing precise difference detection based on field comparison and inferential fuzzy detection based on a rule base. Difference level labels are assigned to the detection results, and the results are output to the self-correcting suggestion generation submodule for suggestion matching.

[0022] Specifically, the self-correcting suggestion generation submodule includes a suggestion construction unit and an impact assessment unit. The former generates multiple types of suggestions, including document replacement, model rebinding, and attribute repair, based on the differences and preset rules. The latter calculates the correction priority based on the scope of the difference's impact and outputs it to the user confirmation interface for interactive confirmation.

[0023] Furthermore, the user confirmation and rollback control submodule supports generating a status snapshot based on the historical execution record of the error correction suggestion, and when the user rejects the current suggestion or an execution error occurs, it calls the corresponding version tree node to implement the rollback operation, while triggering a new round of closed-loop execution of the consistency detection process.

[0024] The technical advantages of this invention are as follows: It achieves on-demand application through modular design, covering the comprehensive digital needs of industrial enterprises from design to operation and maintenance. The platform achieves adaptive updates of 3D models to cope with complex and dynamic changes in industrial environments through a model self-evolution mechanism, and improves data consistency and reliability among modules within the platform through a data consistency self-correction mechanism. Furthermore, the platform ensures the traceability of models and data through version management and rollback mechanisms, thereby significantly improving the digital management level and operational efficiency of industrial enterprises. Attached Figure Description

[0025] Figure 1 This is a schematic diagram of the overall structure of the digital industrial platform of the present invention;

[0026] Figure 2 This is a block diagram of the digital dictionary module of the present invention;

[0027] Figure 3 This is a block diagram of the industrial internet application module of the present invention;

[0028] Figure 4 This is a block diagram of the three-dimensional visualization operation and maintenance module of the present invention;

[0029] Figure 5 This is a block diagram of the BIM model construction module of the present invention;

[0030] Figure 6 This is a block diagram of the data service module of the present invention;

[0031] Figure 7 The system overall structure diagram of the present invention includes the newly added model self-evolution module and data consistency self-correction module;

[0032] Figure 8 This is a flowchart illustrating the self-evolution of the model in this invention.

[0033] Figure 9 This is a flowchart of the data consistency self-correction process of the present invention;

[0034] Figure 10 This is a diagram showing the evolution of the model version tree structure of the present invention.

[0035] Figure label:

[0036] 1. Digital Dictionary Module; 11. Rule Configuration Submodule; 111. Attribute Rule Configuration Unit; 112. Grouping Rule Configuration Unit; 113. Validation Rule Configuration Unit; 114. System Logic Configuration Unit; 115. Identifier Code Input Unit; 116. Model Aggregation Configuration Unit; 12. Digital Dictionary Processing Submodule; 121. 3D Component Model Reading Unit; 122. Attribute Reading Unit; 123. Document Reading Unit; 124. Model Lightweighting Unit; 125. Identifier Code Recognition Unit; 126. Runtime Data Reading Unit; 127. Model Coupling and Identifier Code Mapping Unit; 13. Display Submodule; 131. Discrete Display Unit; 132. Grouped Display Unit; 133. Logical Display Unit; 134. Retrieval Unit;

[0037] 2. Industrial Internet Application Module; 21. Engine Support Sub-module; 211. Workflow Engine Unit; 212. Configuration Engine Unit; 213. Data Engine Unit; 214. WEB3D Engine Unit; 22. IoT Application Sub-module; 221. Equipment Management Application Unit; 222. Safety Management Application Unit; 223. Hazard Management Application Unit; 224. Configuration Management Application Unit; 225. Work Permit Application Unit; 226. Cockpit Application Unit; 227. Model Application Unit; 228. Mapping Configuration Application Unit;

[0038] 3. 3D Visualization Operation and Maintenance Module; 31. 3D Scene Sub-module; 311. 3D Operation and Maintenance Scene Unit; 312. Tool-based Editing Unit; 32. Theme Management Sub-module; 321. Safety Theme Management Unit; 322. Equipment Theme Management Unit; 323. Pipeline Theme Management Unit; 324. Process Theme Management Unit; 325. Public Theme Management Unit; 326. Entry Theme Management Unit;

[0039] 4. BIM Model Construction Module; 41. Model Design Submodule; 411. Model Rendering Unit; 412. Model Mapping Processing Unit; 413. Input / Output Processing Unit; 42. Model Design Submodule; 421. Design Tree Rule Definition Unit; 422. Custom Shape Modeling Unit; 423. Parametric Equipment Modeling Unit; 424. Building Modeling Unit; 425. Pipeline Modeling Unit; 426. Design Attribute Configuration Unit;

[0040] 5. Data Service Module; 51. Model Service Submodule; 511. Model Input Recognition Unit; 512. Raw Model Data Caching Unit; 513. Model Data Structure Parsing Unit; 514. Model Format Conversion Unit; 515. Model Storage Unit; 516. Model Output Unit; 52. Document Service Submodule; 521. Document Verification and Storage Unit; 522. Document Association Relationship Preservation Unit; 523. Document Version Iteration Processing Unit; 524. Document Retrieval Processing Unit; 53. IoT Service Submodule; 531. Data Acquisition Method and Interface Management Unit; 532. Optimized Data Processing Unit; 533. Data Push Service Management Unit; 534. Public Service Processing Unit;

[0041] 6. Model self-evolution module; 61. On-site perception submodule; 62. Change analysis submodule; 63. Model incremental generation submodule; 64. Structure fusion submodule; 65. Evolution version management submodule;

[0042] 7. Data consistency self-correction module; 71. Multi-source data synchronization monitoring submodule; 72. Consistency rule library submodule; 73. Difference detection engine submodule; 74. Self-correction suggestion generation submodule; 75. User confirmation and rollback control submodule. Detailed Implementation

[0043] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0044] It should be noted that when a component is described as "fixed to" another component, it can be directly on the other component or may have a component in between. When a component is considered "connected to" another component, it can be directly connected to the other component or may have a component in between. When a component is considered "set on" another component, it can be directly set on the other component or may have a component in between. The terms "vertical," "horizontal," "left," "right," and similar expressions used in this document are for illustrative purposes only.

[0045] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0046] Please refer to Figure 1-10 This invention provides a digital industrial platform that supports model self-evolution and data consistency self-correction, the overall structure of which is as follows: Figure 1 As shown, the platform adopts a modular design, covering the comprehensive digital application needs of industrial enterprises from design to operation and maintenance. It also improves the data consistency and reliability between modules within the platform through a model adaptive update mechanism and a data difference detection and feedback repair mechanism.

[0047] In its implementation, the core of this platform consists of a digital dictionary module, an industrial internet application module, a 3D visualization operation and maintenance module, a BIM model building module, a data service module, a model self-evolution module, and a data consistency self-correction module. These modules work together to support complex and dynamically changing scenarios in industrial enterprises. The following will explain in detail the specific operating principles and processes of each module with reference to the accompanying diagrams.

[0048] First, the digital dictionary module 1 is one of the foundational modules of the entire platform, and its block diagram is as follows: Figure 2 As shown. The rule configuration submodule 11 provides constraints for subsequent processing. The attribute rule configuration unit 111 defines the design attribute rules, national standard attribute rules, and factory standard attribute rules for the 3D model. The grouping rule configuration unit 112 is used to group and display the model according to region, profession, or management needs. The verification rule configuration unit 113 is responsible for checking model integrity, naming standardization, etc. The system logic configuration unit 114 defines functional logic and timing logic. The identification code input unit 115 generates a unique identification code for each model. The model aggregation configuration unit 116 generates a lightweight aggregated model by deleting redundant parts and hidden surfaces. Based on the above rules, the digital dictionary processing submodule 12 obtains model data through the 3D component model reading unit 121. After reading relevant files through the attribute reading unit 122, document reading unit 123, and runtime data reading unit 126, the model lightweighting unit 124 reduces rendering pressure. Finally, the model processed by the model coupling and identification code mapping unit 127 is transferred to the display submodule 13. The display submodule 13 includes a discrete display unit 131, a grouped display unit 132, a logical display unit 133, and a retrieval unit 134, to meet the display needs in different scenarios. For example, during equipment maintenance, users can quickly locate the target model and view its associated documents and real-time status information through the identification code.

[0049] Secondly, Industrial Internet Application Module 2, such as Figure 3As shown, its core is to provide basic capability support for the IoT application submodule 22 through the engine support submodule 21. The workflow engine unit 211 is responsible for driving processes such as hazard record management and work ticket approval; the configuration engine unit 212 supports the tool-based configuration of enterprise production configuration diagrams; the data engine unit 213 realizes data transmission and filtering; and the WEB3D engine unit 214 provides customized 3D model application capabilities. The IoT application submodule 22 includes the equipment management application unit 221, the safety management application unit 222, the hazard management application unit 223, the configuration management application unit 224, the work ticket application unit 225, the cockpit application unit 226, the model application unit 227, and the mapping configuration application unit 228. For example, when a piece of equipment in the workshop malfunctions, the equipment management application unit 221 will automatically record the malfunction details and establish a connection with the corresponding 3D model through the mapping configuration application unit 228, so that managers can intuitively understand the equipment problem.

[0050] Next, the 3D visualization operation and maintenance module 3, as shown... Figure 4 As shown, the main responsibility is the management of operation and maintenance scenarios based on 3D maps and spatial configurations. The 3D operation and maintenance scenario unit 311 within the 3D scenario submodule 31 provides an operable 3D map, while the tool-based editing unit 312 allows users to dynamically adjust model parameters. The theme management submodule 32 further expands the application scenarios. The safety theme management unit 321 integrates functions such as personnel and vehicle positioning and video monitoring; the equipment theme management unit 322 displays asset information and status data; the pipeline theme management unit 323 presents complex pipeline structures through sectional views; the process theme management unit 324 simulates production process flows; the public theme management unit 325 is used for emergency drills; and the entrance theme management unit 326 serves as an access point for third-party systems. For example, in a fire drill, the public theme management unit 325 can call up a 3D map to display escape routes and verify the drill's effectiveness by combining personnel positioning information.

[0051] In addition, BIM model building module 4, such as Figure 5 As shown, the module is divided into a model design submodule 41 and a model processing submodule 42. The model design submodule 41 defines classification and naming rules through the design tree rule definition unit 421, supports the creation of irregular models through the custom shape modeling unit 422, simplifies the modeling of standard equipment through the parametric equipment modeling unit 423, and performs parametric configuration for building structures and piping systems, respectively, through the building modeling unit 424 and the piping modeling unit 425. The design attribute configuration unit 426 adds detailed descriptions to each part. The model processing submodule 42 is responsible for rendering, mapping, and input / output processing. The model rendering unit 411 adds material descriptions, the model mapping processing unit 412 categorizes new models into specified groups, and the input / output processing unit 413 completes data interaction with other modules.

[0052] Data service module 5, such as Figure 6 As shown, the system includes a model service submodule 51, a document service submodule 52, and an IoT service submodule 53. The model service submodule 51 identifies models of various formats through a model input recognition unit 511, improves parsing efficiency through a raw model data caching unit 512, extracts geometric, material, and attribute information through a model data structure parsing unit 513, adapts to different needs through a model format conversion unit 514, saves results through a model storage unit 515, and provides model output to other modules through a model output unit 516. The document service submodule 52 ensures document quality through a document verification and storage unit 521, maintains the mapping between documents and models through a document association storage unit 522, tracks version changes through a document version iteration processing unit 523, and supports keyword search through a document retrieval processing unit 524. The IoT service submodule 53 standardizes data access through a data acquisition method and interface management unit 531, cleans invalid data through a data optimization processing unit 532, distributes data on demand through a data push service management unit 533, and provides auxiliary functions such as account management through a public service processing unit 534.

[0053] Model self-evolution module 6, such as Figure 7 As shown, this system is designed to address structural changes or the addition of new equipment in industrial settings. S1, the site perception submodule 61 captures sensor data or construction plan information; the change triggering rule unit determines whether to initiate the self-evolution process. S2, the change parsing submodule 62 standardizes the captured information, generating data including component type, spatial location, and topological relationships. S3, the model incremental generation submodule 63 generates an incremental model based on the parsing results and calls the corresponding template. For example, for a newly added pump, the component classification generation unit selects templates for size, material, and mounting surface parameters for modeling. S4, the structural fusion submodule 64 spatially aligns and stitches the incremental model with the existing model. If the matching rate exceeds a threshold, automatic fusion occurs; otherwise, conflict areas are marked for user confirmation. S5, the evolution version management submodule 65 records logs of each evolution operation and generates a version tree for rollback and comparison.

[0054] Finally, the data consistency self-correction module 7, as shown in Figure 7 Figure 9As shown, the consistency issues between models, documents, and runtime data are resolved. The multi-source data synchronization monitoring submodule 71 monitors key identifiers and timestamps, and the difference determination unit uses a hash verification strategy to assess the conflict level. The consistency rule library submodule 72 stores version synchronization rules, binding integrity rules, and reference logic consistency rules. The difference detection engine submodule 73 performs precise detection and fuzzy inference, setting difference level labels. The self-correction suggestion generation submodule 74 generates repair suggestions based on the difference items, and the impact assessment unit calculates the priority before outputting them to the user interface. The user confirmation and rollback control submodule 75 records snapshots and calls version tree nodes to rollback when necessary, simultaneously triggering a new round of detection loop.

[0055] In a practical application scenario, taking an industrial enterprise as an example, this enterprise needs to manage the entire lifecycle of equipment within its factory area. First, the rule configuration submodule 11 in the digital dictionary module 1 defines the attribute rules, grouping rules, and verification rules for the factory equipment, and the digital dictionary processing submodule 9 reads the equipment model and its associated document information. Subsequently, the IoT application submodule in the industrial internet application module 2 collects equipment operation data through sensors and displays the overall equipment status in the dashboard application unit. When equipment changes, the field perception submodule in the model self-evolution module 6 acquires change information through sensors, the change parsing submodule standardizes the information, the model incremental generation submodule generates an incremental model, and the structure fusion submodule combines the incremental model with the original model. Simultaneously, the multi-source data synchronization monitoring submodule in the data consistency self-correction module 7 monitors the consistency of equipment models, document information, and operational data in real time. If inconsistencies are found, the difference detection engine submodule identifies the difference level and generates correction suggestions, which are finally executed by the user confirmation and rollback control submodule. Throughout this process, the data service module 5 acts as the core hub, undertaking data flow tasks to ensure smooth and efficient data interaction between modules.

[0056] To enable those skilled in the art to fully understand and implement this invention, the specific implementation principle of this invention is further explained below in conjunction with a specific application scenario.

[0057] In the scenario of full lifecycle management of equipment in an industrial enterprise, the attribute rules, grouping rules, and verification rules of the equipment are first defined through the rule configuration submodule 11 in the digital dictionary module 1. The attribute rule configuration unit in the rule configuration submodule 11 provides basic design attribute rules for the 3D model design, such as the geometric dimensions, material parameters, and operating status of the equipment; the grouping rule configuration unit categorizes the equipment according to its region or function, facilitating subsequent data management and display; the verification rule configuration unit sets collision check spacing, naming conventions, and version iteration rules to ensure the consistency and integrity of the model. Subsequently, the 3D component model reading unit in the digital dictionary processing submodule 12 reads component-level building and equipment models in a unified format from the data service module 5, the attribute reading unit reads the model attribute file, the document reading unit reads the document information associated with the model, and the identification code recognition unit scans the identification codes in the document content and dynamically couples them with the model. The display submodule 13, based on the constraints provided by the rule configuration submodule 8, displays the processed 3D model and related data separately, in groups, or logically according to different scenario requirements.

[0058] Next, the IoT application submodule in Industrial Internet Application Module 2 collects equipment operation data through sensors and transmits the data to the cockpit application unit for comprehensive situational awareness display. The equipment management application unit records equipment ledgers, maintenance records, document management, and fault information; the safety management application unit monitors personnel positioning, video footage, access control status, and perimeter security in real time; and the hazard management application unit, driven by the workflow engine unit, records hazard information and generates rectification tasks. When equipment changes, the field perception submodule in Model Self-Evolution Module 6 uses sensors to acquire the magnitude of spatial coordinate changes, new component identification codes, or changes in construction progress nodes to determine whether to trigger the model self-evolution operation. If the triggering conditions are met, the change analysis submodule standardizes the change information and generates structural data, and the model incremental generation submodule calls the modeling template for parametric modeling based on the component type information provided by the change analysis submodule. The structural fusion submodule judges the spatial matching rate of incremental components based on the model topology diagram. If the matching rate exceeds a set threshold, an automatic fusion operation is performed; otherwise, conflict areas are marked and submitted to the user for confirmation. The model evolution log unit in the evolution version management submodule records the incremental component ID, change source, fusion strategy, and topology summary information for each evolution operation. The version tree management unit constructs a version tree structure with time sequence and difference markers for subsequent version comparison and rollback.

[0059] Meanwhile, the multi-source data synchronization monitoring submodule in the data consistency self-correction module 7 monitors the consistency of 3D model attribute identifiers, document metadata reference identifiers, and running status device IDs in real time. The difference determination unit uses a hash check and timestamp priority strategy to determine the conflict level. If an inconsistent object is found, the difference detection engine submodule performs precise field comparison detection and rule base inference fuzzy detection, and sets a difference level label. The suggestion building unit in the self-correction suggestion generation submodule generates document replacement, model rebinding, and attribute repair suggestions. The impact assessment unit calculates the error correction priority and outputs the suggestions to the user confirmation interface. The user confirmation and rollback control submodule supports the generation of state snapshots and calls the version tree node to implement the rollback operation when the user rejects the suggestion or an execution exception occurs.

[0060] Throughout the process, Data Service Module 5 acts as the core hub, undertaking data flow tasks and ensuring smooth and efficient data interaction between modules. The Model Service submodule is responsible for the conversion, storage, and output of multi-format 3D models; the Document Service submodule provides document storage, version iteration, and retrieval services; and the IoT Service submodule is responsible for collecting, storing, and pushing operational data, and providing public data services. Through these steps, the system achieves comprehensive digital application from design to operation and maintenance, solving technical challenges such as delayed 3D model updates, significant data consistency issues, and the lack of a closed-loop control mechanism.

[0061] In summary, this platform achieves end-to-end digital coverage from design to operation and maintenance through the collaborative operation of its various modules. For example, when a new pump is added to the workshop, the model self-evolution module 6 automatically updates the 3D model, and the data consistency self-correction module 7 ensures that the ID of the new equipment matches the document references. This highly integrated design greatly improves the digital management level and operational efficiency of industrial enterprises.

Claims

1. A digitalized industrial platform supporting model self-evolution and data consistency self-correction, characterized in that It includes a digital dictionary module (1), an industrial internet application module (2), a 3D visualization operation and maintenance module (3), a BIM model construction module (4), a data service module (5), a model self-evolution module (6), and a data consistency self-correction module (7), among which: The digital dictionary module (1) realizes digital delivery applications based on BIM models; the industrial internet application module (2) realizes factory operation management and comprehensive safety management applications driven by two-dimensional workflows; the three-dimensional visualization operation and maintenance module (3) realizes three-dimensional digital twin applications; the BIM model construction module (4) provides tool-based application software with the function of deep self-editing of three-dimensional models; the data service module (5) provides three-dimensional model sharing, data sharing and document resource sharing services for the digital dictionary module (1), the industrial internet application module (2), the three-dimensional visualization operation and maintenance module (3), and the BIM model construction module (4); the model self-evolution module (6) is used to drive the three-dimensional model to automatically update when structural changes or new equipment information are detected in the industrial site; the data consistency self-correction module (7) is used to detect and correct the inconsistency of the correlation between the three-dimensional model, the running data and the document. The model self-evolution module (6) includes a site perception submodule (61), a change analysis submodule (62), a model incremental generation submodule (63), a structural fusion submodule (64), and an evolution version management submodule (65). The site perception submodule (61) includes a change triggering rule unit. When the equipment changes, the site perception submodule in the model self-evolution module (6) obtains the spatial coordinate change range, the new component identification code, or the change of construction progress node through sensors, and determines whether to trigger the model self-evolution operation. If the triggering condition is met, the change analysis submodule (62) standardizes the change information and generates structural data. The model incremental generation submodule (63) calls the modeling template to perform parametric modeling based on the component type information provided by the change analysis submodule (62). The structural fusion submodule (64) judges the spatial matching rate of the incremental component based on the model topology diagram structure. If the matching rate exceeds the set threshold, the automatic fusion operation is performed. Otherwise, the conflict area is marked and handed over to the user for confirmation. The data consistency self-correction module (7) includes a multi-source data synchronization monitoring submodule (71), a consistency rule base submodule (72), a difference detection engine submodule (73), a self-correction suggestion generation submodule (74), and a user confirmation and rollback control submodule (75). The multi-source data synchronization monitoring submodule (71) is equipped with a difference determination unit. The multi-source data synchronization monitoring submodule (71) in the data consistency self-correction module (7) monitors the consistency of the three-dimensional model attribute identifier, document metadata reference identifier and running status device ID in real time. The difference judgment unit uses hash verification and timestamp priority strategy to judge the conflict level. If an inconsistent object is found, the difference detection engine submodule (73) performs field comparison precise detection and rule base reasoning fuzzy detection and sets difference level label. The suggestion construction unit in the self-correction suggestion generation submodule (74) generates document replacement, model rebinding and attribute repair suggestions. The impact assessment unit of the self-correction suggestion generation submodule (74) calculates the error correction priority and outputs the suggestions to the user confirmation interface. The user confirmation and rollback control submodule (75) supports the generation of status snapshots. When the user rejects the suggestion or an execution exception occurs, the version tree node is called to realize the rollback operation.

2. The digital industrial platform supporting model self-evolution and data consistency self-correction as described in claim 1, characterized in that... The digital dictionary module (1) includes a rule configuration submodule (11), a digital dictionary processing submodule (12), and a display submodule (13). The rule configuration submodule (11) includes an attribute rule configuration unit (111), a grouping rule configuration unit (112), a verification rule configuration unit (113), a system logic configuration unit (114), an identifier code input unit (115), and a model aggregation configuration unit (116).

3. The digital industrial platform supporting model self-evolution and data consistency self-correction as described in claim 2, characterized in that... The digital dictionary processing submodule (12) includes a three-dimensional component model reading unit (121), an attribute reading unit (122), a document reading unit (123), a model lightweighting unit (124), an identification code recognition unit (125), and a running data reading unit (126).

4. The digital industrial platform supporting model self-evolution and data consistency self-correction as described in claim 1, characterized in that... The Industrial Internet Application Module (2) includes an Engine Support Sub-Module (21) and an Internet of Things Application Sub-Module (22), wherein the Engine Support Sub-Module (21) includes a Workflow Engine Unit (211), a Configuration Engine Unit (212), a Data Engine Unit (213), and a WEB3D Engine Unit (214).

5. The digital industrial platform supporting model self-evolution and data consistency self-correction as described in claim 4, characterized in that... The IoT application sub-module (22) includes the equipment management application unit (221), the safety management application unit (222), the hidden danger management application unit (223), the configuration management application unit (224), the work ticket application unit (225), the cockpit application unit (226), the model application unit (227), and the mapping configuration application unit (228).

6. The digital industrial platform supporting model self-evolution and data consistency self-correction as described in claim 1, characterized in that... The data service module (5) includes a model service submodule (51), a document service submodule (52) and an IoT service submodule (53). The model service submodule (51) includes a model input recognition unit (511), a raw model data caching unit (512), a model data structure parsing unit (513), a model format conversion unit (514), a model storage unit (515), and a model output unit (516).

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