A process industry data fusion method and device based on a star model

Abstract

This invention discloses a method and apparatus for data fusion in process industries based on a star schema. The method includes the following steps: Step S1: Obtain a digitized process industry flowchart, identify objects, object attributes, and connection relationships in the flowchart using primitive recognition technology, and construct a graph structure model; Step S2: Assign a unique equipment code to each equipment node corresponding to each equipment object in the graph structure model, construct a star schema data association model centered on the equipment code, and perform data fusion by using different types of industrial data as association branches of the star schema data association model; Step S3: Based on the fused data of each equipment node in the star schema data association model, mark the status of each equipment node on the digitized flowchart to generate a holographic data view with status identifiers. This invention enables the fusion and display of different process industry data on a flowchart.

Description

Technical Field

[0001] This invention relates to the field of process industry data processing technology, and in particular to a process industry data fusion method and apparatus based on a star schema. Background Technology

[0002] With the deepening of industrial digital transformation, process industries such as petrochemicals, chemicals, power, and metallurgy have accumulated a large amount of data resources during production and operation. Based on their sources and uses, these data can be divided into three main categories: information technology data, operational technology data, and engineering technology data, namely IT data, OT data, and ET data.

[0003] IT data primarily originates from business management platforms such as Enterprise Resource Planning (ERP) systems, Manufacturing Execution Systems (MES), and Supply Chain Management (SLM) systems. It includes structured business data such as work order information, inventory information, and cost information, as well as unstructured document data such as design drawings and process documents. OT data mainly comes from field equipment and industrial control systems, collected in real-time by field devices such as sensors, controllers, and actuators. It reflects equipment operating status, environmental parameters, and production process information, including real-time time-series data and equipment status signals. ET data includes various industrial drawings, operating procedures, 3D models, and other engineering and technical documents, carrying core knowledge of factory design and operation.

[0004] For process industries to achieve digital transformation, they must recognize the value of ET data and its synergistic relationship with IT and OT data. ET data serves as a bridge for the deep integration of IT and OT data. Existing technologies have explored the integration of IT and OT data extensively, achieving a certain degree of correlation between business and operational data through data platforms and industrial internet platforms. However, existing solutions generally suffer from the following shortcomings: First, the value of ET data has not been fully explored, engineering drawings are still stored in the form of static files, and have not been effectively linked with IT and OT data. Maintenance personnel need to frequently switch between multiple systems to obtain complete information about the equipment. Second, there is a lack of equipment-level data fusion models based on engineering drawings. Equipment-related multi-source heterogeneous data are scattered in different systems, making it difficult to form a unified holographic view. Third, existing data association methods mainly rely on table joins in relational databases, which are difficult to express the complex topological connections between equipment, pipelines, and instruments in the process industry, and are even less capable of intelligent analysis such as automatic isolation boundary identification based on topological relationships; Fourth, the development of equipment isolation schemes still relies on manual drawing and experience-based judgment, making it easy to overlook the identification of isolation boundaries, and there is a lack of visual linkage between the isolation status and the flowchart. Fifth, the execution process of the operating procedures is disconnected from the flowchart, and maintenance personnel cannot intuitively see the impact of the procedure steps on the equipment status on the drawings, resulting in insufficient visibility and traceability of the procedure execution. Sixth, the real-time data access and refresh mechanism is imperfect, and there is a lack of a unified data subscription and caching update strategy, which makes it difficult to guarantee the timeliness of data; Seventh, graph traversal algorithms lack parameterized control and boundary verification mechanisms, which can easily lead to problems such as excessive traversal depth or incomplete isolation boundaries in complex flowcharts.

[0005] Therefore, there is an urgent need for a technical solution that can use digital engineering drawings as a bridge to integrate IT business data, OT operation data and ET engineering data, and present the multi-dimensional status of equipment in a graphical way on the flowchart, while having a complete real-time data processing mechanism and intelligent algorithms. Summary of the Invention

[0006] In view of this, it is necessary to provide a method and apparatus for data fusion in the process industry based on a star schema, so as to effectively solve the technical problem that it is difficult to achieve data fusion in the process industry on the flowchart.

[0007] This invention provides a data fusion method for process industries based on a star schema, comprising the following steps: Step S1: Obtain the digitized process flow diagram of the process industry, use graph element recognition technology to identify the objects, object attributes and connection relationships in the process flow diagram, and construct a graph structure model; Step S2: Assign a unique device code to the device node corresponding to each device object in the graph structure model, construct a star-shaped data association model with the device code as the center, and use different types of industrial data as the association branches of the star-shaped data association model to perform data fusion. Step S3: Based on the fused data of each device node in the star-shaped data association model, mark the status of each device node on the digital flowchart to generate a holographic data view with status identifiers.

[0008] Preferably, in step S1, primitive recognition technology is used to identify objects, object attributes, and connection relationships in the engineering flowchart, specifically as follows: Graphical symbols in the engineering flowchart are identified using primitive recognition technology. Equipment objects, pipeline objects, and instrument objects are extracted. The equipment type attribute and equipment parameter attribute of the equipment object are extracted, the pipe diameter attribute and medium type attribute of the pipeline object are extracted, the measurement type attribute of the instrument object is extracted, and the connection relationship between the objects is extracted.

[0009] Preferably, the construction of the graph structure model in step S1 specifically involves: The graph structure model is represented by a directed graph, with equipment objects and instrument objects as nodes and pipeline objects as edges. The edges represent the topological connections between the nodes, and the edges are associated with the medium flow direction attribute, while the nodes are associated with functional attributes.

[0010] Preferably, step S2 specifically comprises: A unique device code is assigned to the device node corresponding to each device object in the graph structure model. A device code registry is established. The device code registry stores the correspondence between the device code and the node identifier of each device node. Based on the correspondence, the star-shaped data association model is constructed with the device code as the center. By connecting various data source systems through data adapters, a mapping relationship is established between the device code and related data in each data source system. A star-shaped index structure is constructed with the device code as the index key. Based on the star-shaped index structure, different types of industrial data are obtained as the association branches of the star-shaped data association model.

[0011] Preferably, the different types of industrial data specifically include information technology data, operational technology data, and engineering technology data; For the information technology data association branch, work order information, spare parts inventory information, and cost information are associated through the equipment code; For the operational technology data association branch, the timing operation parameter data and equipment status signal data are associated through the equipment code, and the updated data of the operational technology data are obtained in real time through the data subscription mechanism; For the engineering and technical data association branch, the equipment node is associated with the graphical representation, operation procedure document and three-dimensional model data in the engineering flowchart through the equipment code.

[0012] Preferably, the data subscription mechanism adopts a publish-subscribe model, which establishes a connection with the data source system through an industrial communication protocol and subscribes to change events of the operating parameter data and status signal data associated with the device node; The data subscription mechanism also includes a data caching and update strategy and a data anomaly handling mechanism.

[0013] Preferably, step S3 specifically comprises: Based on the fused data of each device node in the star-shaped data association model, the status of each device node is marked on the digital flowchart using preset graphical identification rules, thereby generating a holographic data view with graphical status identification.

[0014] Preferably, the graphical identification rules are as follows: The isolation status of the equipment is identified by a first preset geometric shape, and different isolation types are distinguished by a first color coding scheme; the work order status and defect status of the equipment are identified by a second preset geometric shape, and the severity level of the work order is distinguished by a second color coding scheme; the real-time operating parameters of the equipment are identified by dynamic numerical labels; the graphical labels are displayed in an overlay form at preset positions of the corresponding equipment nodes on the digital flowchart.

[0015] Preferably, step S4 further includes: In response to a user’s first type of interactive operation on a device node in the digital flowchart, a main data information panel of the device node is displayed in a preset area of ​​the digital flowchart. The main data information panel includes device name, device code, device type and design parameters. In response to the second type of user interaction with the device node, a shortcut menu containing multiple data dimension entries is displayed in a preset area next to the device node. Each data dimension entry in the shortcut menu corresponds one-to-one with each association branch in the star-shaped data association model. The system receives the user's selection of a data dimension entry in the shortcut menu, retrieves and aggregates data from the corresponding related branch in the star-shaped data association model based on the device code, and generates a device digital screen containing the selected data dimension.

[0016] The present invention also provides a process industry data fusion device based on a star schema, including a memory and a processor. The memory stores a computer program, which, when executed by the processor, implements the process industry data fusion method based on a star schema.

[0017] Compared with existing technologies, the beneficial effects of this invention are as follows: This invention uses a graph structure to perform topological modeling of devices, pipelines, and instruments in the flowchart. It accurately stores topological relationships and attribute information through node attribute tables and edge attribute tables, accurately expressing complex device connection relationships. Based on the device coding registry mechanism and star-structured index, it achieves on-demand aggregation and penetrating query of multi-source heterogeneous data based on device coding, centrally displaying device information scattered across multiple systems to form a complete digital profile of the devices. This invention combines a graph structure model with a digital engineering flowchart as the link with a star-structure model centered on device coding, achieving unified integration of IT business data, OT operation data, and ET engineering data at the device level. This data is then intuitively presented on the flowchart through graphical status indicators, realizing "one-map perception" of device status. Maintenance personnel can grasp the complete status information of the devices without switching between multiple systems. Attached Figure Description

[0018] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, illustrate exemplary embodiments of the invention and, together with their description, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings: Figure 1 is a flowchart of an embodiment of a process industry data fusion method based on a star schema provided by the present invention; Figure 2 yes Figure 1 A detailed flowchart of an embodiment of the process industry data fusion method based on a star schema is shown in the example. Figure 3 yes Figure 1 The diagram shown is a modeling schematic diagram of one embodiment of the diagram structure model. Figure 4a yes Figure 1 The diagram shown is a schematic representation of one embodiment of the star-shaped data association model. Figure 4b yes Figure 1 The diagram shown illustrates a data classification scheme for one embodiment of process industry data. Figure 5 yes Figure 1 A schematic diagram of an embodiment of the graphical state identification rules shown in the example; Figure 6 yes Figure 1 The illustrated embodiment is a schematic diagram of the interactive operation of a device digital portrait. Detailed Implementation

[0019] Preferred embodiments of the present invention will now be described in detail with reference to the accompanying drawings, which form part of this application and are used together with the embodiments of the present invention to illustrate the principles of the present invention, but are not intended to limit the scope of the present invention.

[0020] Example 1 Please see Figure 1 The process industry data fusion method based on a star schema in this embodiment specifically includes the following steps: Step S1: Obtain the digitized process flow diagram of the process industry, use graph element recognition technology to identify objects, object attributes and connection relationships in the process flow diagram, and construct a graph structure model; Step S2: Assign a unique device code to the device node corresponding to each device object in the graph structure model, construct a star-shaped data association model with the device code as the center, and use different types of industrial data as association branches of the star-shaped data association model to perform data fusion. Step S3: Based on the fused data of each device node in the star-shaped data association model, mark the status of each device node on the digital flowchart to generate a holographic data view with status identifiers.

[0021] This embodiment addresses the technical problems in existing process industries where IT, OT, and ET data are isolated and lack a unified data fusion and visualization model linked by engineering drawings. This results in difficulties in achieving holographic perception of equipment-level information, automatic identification of isolation boundaries, and linkage between operating procedure execution and equipment status. It provides a method and system for process industry data fusion and visualization based on a star-map model, which is a combination of a star-shaped data association model and a structured graph model of a flowchart. Each step is described in detail below.

[0022] S1: Obtain the engineering flow diagram of the process industry, digitize the engineering flow diagram, use graphic element recognition technology to identify graphic symbols in the engineering flow diagram, extract equipment objects, pipeline objects and instrument objects, and extract the equipment type attributes and equipment parameter attributes of equipment objects, the pipe diameter attributes and media type attributes of pipeline objects, the measurement type attributes of instrument objects, and the connection relationships between objects.

[0023] Graphical primitive recognition technology, based on computer vision and pattern recognition algorithms, can automatically identify standard graphic symbols in engineering flowcharts, such as equipment symbols, valve symbols, and instrument symbols, and extract their attribute information. Equipment type attributes include equipment types such as pumps, valves, heat exchangers, reactors, and storage tanks; equipment parameter attributes include technical parameters such as design temperature, design pressure, volume, and power; pipe diameter attributes include nominal diameter DN and pipe specifications; media type attributes include media name, such as steam, water, oil, and gas, as well as media state, such as liquid and gas; and measurement type attributes include temperature measurement, pressure measurement, flow measurement, and level measurement.

[0024] A graph structure model is constructed based on the equipment objects, pipeline objects, and instrument objects obtained from primitive recognition. The equipment objects and instrument objects are respectively used as nodes in the graph structure model, and the pipeline objects are used as edges in the graph structure model. The edges are used to represent the topological connection relationship between the nodes. The graph structure model adopts a directed graph representation, with edges carrying the medium flow direction attribute and nodes carrying the equipment function attribute.

[0025] The graph structure model also includes a node attribute table and an edge attribute table. The node attribute table stores the node identifier, equipment code, equipment functional attributes, and location attributes of each node; the edge attribute table stores the edge identifier, starting node identifier, ending node identifier, medium flow direction attribute, and pipeline specification attribute of each edge. Equipment functional attributes describe the functional role of the equipment in the process flow, such as heat exchange, drive, pressure regulation, separation, reaction, etc.; location attributes include the spatial location information of the equipment in the plant, such as its area, elevation, and three-dimensional coordinates.

[0026] S2: Assign a unique device code to each device node in the graph structure model, and construct a star-shaped data association model with the device code as the center. Information technology data, operational technology data, and engineering technology data are respectively used as the association branches of the star-shaped data association model. Among them, the enterprise resource planning system, manufacturing execution system, distributed control system, and real-time database are connected through data adapters to establish the mapping relationship between the device code and the device-related data in each system, and construct a star-shaped index structure with the device code as the index key.

[0027] The construction of the star-shaped data association model also includes: establishing an equipment code registry, which stores the correspondence between the equipment code and node identifier of each equipment node in the graph structure model; for the information technology data association branch, linking work order information, spare parts inventory information, and cost information through equipment codes; for the operation technology data association branch, linking time-series operating parameter data and equipment status signal data through equipment codes, and obtaining updated operation technology data in real time through a data subscription mechanism; for the engineering technology data association branch, linking the graphical representation of equipment nodes in the engineering flowchart, operating procedure documents, and 3D model data through equipment codes.

[0028] The data subscription mechanism adopts a publish-subscribe model, establishing connections with distributed control systems and real-time databases through industrial communication protocols, and subscribing to changes in operating parameter data and status signal data associated with device nodes.

[0029] The data subscription mechanism also includes a data caching update strategy: a local cache is established for operational technical data, which stores the latest operating parameter data and status signal data of each device node; when a data change event is received, the data of the corresponding device node in the local cache is updated; the holographic data view reads data from the local cache for display, and the refresh frequency is a preset refresh cycle.

[0030] The data subscription mechanism also includes a data anomaly handling mechanism: monitoring the update timestamps of operational technical data, and determining that the data of a device node is abnormal when the data update timestamp of a certain device node exceeds a preset timeout threshold; marking the abnormal device nodes on the digital flowchart with anomaly markers, which use preset anomaly marker elements, such as a gray question mark icon or a flashing warning symbol.

[0031] S3: On the digital flowchart, based on the fused data of each device node in the star-shaped data association model, the status of each device node is marked using preset graphical identification rules, generating a holographic data view with graphical status identification.

[0032] The graphical identification rules include: using a first preset geometric shape to identify the isolation status of the equipment and using a first color coding scheme to distinguish different isolation types; using a second preset geometric shape to identify the work order status and defect status of the equipment and using a second color coding scheme to distinguish the severity level of the work order; using dynamic numerical labels to identify the real-time operating parameters of the equipment; and displaying the graphical identification in an overlay form at the preset position of the corresponding equipment node on the digital flowchart.

[0033] Specifically, the first preset geometric shape is a hexagon, and the first color coding scheme includes: red for temporary isolation, green for no isolation sign, and blue for permanent isolation. The second preset geometric shape is a triangle, and the second color coding scheme includes: yellow for pending work orders, red for unresolved defects, and orange for urgent work orders. Dynamic numerical annotations are obtained from a real-time database and automatically refreshed according to a preset sampling period. The overlay format refers to the graphical identifiers being displayed as independent layers overlaid on or near the device graphic symbols in the digital flowchart, without altering the original flowchart's graphical structure, allowing users to obtain device status information while maintaining flowchart clarity. The preset position can be the upper right corner, upper left corner, or other positions that do not obscure key information from the device graphic symbol.

[0034] Furthermore, step S3 is followed by a step of generating a digital profile of the device: In response to the user's first type of interactive operation on the device nodes on the digital flowchart, the main data information panel of the device node is displayed in the preset area of ​​the digital flowchart. The main data information panel includes the device name, device code, device type and design parameters. In response to the user's second type of interactive operation on the device node, a shortcut menu containing multiple data dimension entries is displayed near the device node. Each data dimension entry in the shortcut menu corresponds to a related branch in the star data association model. The system receives the user's selection of a data dimension entry in the shortcut menu, retrieves and aggregates data from the corresponding related branches in the star-shaped data association model based on the device code, and generates and displays a digital profile of the device containing the selected data dimension.

[0035] The first type of interactive operation is a left-click operation, and the second type is a right-click operation. The data dimension entry points in the shortcut menu include spare parts information, inspection records, historical work orders, related documents, experience feedback, equipment monitoring information, and instrumentation information. Through this two-tiered interactive mechanism, users can quickly view basic equipment information, and by clicking the left mouse button, they can delve deeper into detailed, multi-dimensional equipment data. Clicking the right mouse button enables hierarchical information display and on-demand access.

[0036] The following uses the primary loop system of a nuclear power plant as an example to illustrate the implementation method in specific application objects and scenarios, such as... Figure 2 As shown, the specific steps include: Step S1: Digital processing of engineering flowchart Obtain the piping and instrumentation diagram (P&ID) of the primary loop system of the nuclear power plant and digitize the P&ID. Use graphic element recognition technology to automatically identify and classify the graphic symbols in the P&ID, and extract the following object information: Equipment objects: Identify equipment such as steam generator SG-001, main pump RCP-001, and pressure regulator PZR-001, and extract attribute information such as equipment type and equipment parameters. Equipment parameters include design temperature, design pressure, and volume. Pipeline objects: Identify the process pipelines connecting various equipment, and extract attribute information such as pipe diameter (e.g., DN850), medium type (e.g., borate water), and pipeline number; Instrument objects: Identify instruments such as temperature transmitters, pressure transmitters, and level gauges, and extract attribute information such as measurement type and range information; Connection relationships: Identify the topological connections between equipment and pipelines, and the installation locations of pipelines and instruments.

[0037] like Figure 3 As shown, a graph structure model is constructed based on object information extracted using primitive recognition technology. The graph structure model is represented using a directed graph: The steam generator SG-001, main pump RCP-001, and pressure regulator PZR-001 are treated as equipment nodes. Each equipment node carries equipment functional attributes, such as heat exchange, drive, pressure regulation, and location attributes, such as plant area, elevation, and coordinates. Instrument objects such as temperature transmitters and pressure transmitters are treated as instrument nodes, carrying measurement function attributes and installation location attributes; The process pipelines are used as directed edges to connect the nodes. The direction of the edge indicates the direction of coolant flow. Each edge carries medium flow direction attributes and pipeline specification attributes, such as pipe diameter, material, and pressure rating.

[0038] Step S2: Construction of Star-shaped Data Association Model like Figure 4a As shown, a unique device code is assigned to each device node in the graph structure model, using the KKS encoding system. A star-shaped data association model is constructed centered around these device codes. Figure 4b As shown, this embodiment divides process industry data into three main categories: information technology data, operational technology data, and engineering technology data, namely IT data, OT data, and ET data. Three related branches are constructed for these three types of data, including: IT data association branch: Associate equipment codes with work order information in the ERP system, such as repair work orders, maintenance work orders, and spare parts inventory information, such as inventory quantity, delivery cycle, and cost information; associate equipment codes with production plans and quality data in the MES system; OT data association branch: The operation data in the distributed control system (DCS) and PI real-time database are associated through equipment coding, including time-series parameters such as steam generator outlet temperature and main pump speed. The sampling period for outlet temperature and main pump speed is 1 second, as well as signal data such as equipment start-up and shutdown status and alarm status. ET Data Association Branch: Associates the device with its graphical representation in P&ID, operating procedure documents, 3D model data, design calculation sheets and other engineering and technical information through the device code.

[0039] Step S3: Generation of graphical status indicators and holographic views like Figure 5 As shown, on the digital flowchart, based on the fused data of each device node in the star-shaped data association model, the status is labeled using preset graphical identification rules: Isolation Status Identifier: A hexagon is used as the primary geometric shape to identify the isolation status of the device. A red hexagon indicates temporary isolation, while a green hexagon indicates no isolation tag. The isolation status is updated in real-time, linked to isolation command data from the isolation management system.

[0040] Work order / defect status identification: Triangles are used as the secondary geometric shape to identify the work order and defect status of the equipment. Yellow triangles indicate pending work orders, and red triangles indicate unresolved defects. Work order / defect number information is attached next to the identification and linked to the work management system data.

[0041] Operating parameter labeling: Key operating parameters, such as temperature, pressure, and flow rate, are displayed with dynamic numerical labels next to the equipment graphic symbol. The values ​​are obtained from the PI real-time database and are automatically refreshed according to the sampling period. The real-time nature of the parameters is ensured through a data subscription mechanism.

[0042] By using the above identification rules, maintenance personnel can open the digital flowchart and simultaneously see the isolation status of each device (hexagonal identification part), the work order / defect status (triangle identification part), and the real-time operating parameters (numerical identification part) on one diagram, thus achieving "one-diagram perception" of device status.

[0043] This embodiment establishes a data subscription mechanism through an industrial communication protocol, adopts a publish-subscribe model to obtain real-time updates of operational technical data, and ensures data real-time performance and access efficiency through a local caching update strategy. At the same time, a data anomaly monitoring unit monitors data update timestamps and identifies abnormal data, thus ensuring the data quality of the holographic data view.

[0044] Following step S3, device digital profiling and interactive queries are also performed, such as... Figure 6 As shown, maintenance personnel can interact with the steam generator SG-001 in the holographic data view generated in step S3: The first type of operation, in this embodiment, is a left-click: In response to the user's left-click operation, the system automatically displays the main data information panel of SG-001 on the right side of the flowchart, including basic information such as equipment name: No. 1 steam generator, equipment code: 10JNA01AC001, equipment type: U-tube steam generator, design parameters: primary side design pressure 17.23MPa, design temperature 343.3℃, ​​commissioning date, and manufacturer.

[0045] The second type of operation, in this embodiment, is a right-click: In response to the user's right-click operation, the system displays a shortcut menu containing the following data dimension entries: Spare parts information: View the inventory quantity and status of spare parts associated with this equipment, such as heat transfer tube bundles, water chamber gaskets, and tube sheets; Inspection Records: View the equipment's periodic inspection data, including vibration values, temperature, and visual inspection records; Oil usage information: View the type, quantity, and replacement records of the lubricating oil associated with this equipment; Historical work orders and reports: View the equipment's maintenance work order list, periodic inspection reports, and full maintenance process traceability records; Related documents / experience feedback: View the associated operating procedures, design drawings, and experience feedback documents for similar equipment at home and abroad; Equipment monitoring information: View the real-time monitoring screen and historical trend curves of this equipment in the DCS / PI system; Instrumentation and control information: View the list of instruments associated with this device, instrument calibration records, and control logic diagram; Chemical Information: View the water chemical parameters associated with this device, such as pH value, boron content, oxygen content and other monitoring data.

[0046] Each data dimension entry in the shortcut menu corresponds to a related branch in the star-shaped data association model. After clicking any entry, the system retrieves and aggregates data from the corresponding data source in real time based on the device code for display.

[0047] Example 2 This embodiment provides a process industry data fusion device based on a star schema, including a memory and a processor. The memory stores a computer program, and when the computer program is executed by the processor, it implements the process industry data fusion method based on a star schema of Embodiment 1.

[0048] The star-based process industry data fusion device provided in this embodiment is used to implement the star-based process industry data fusion method. Therefore, the star-based process industry data fusion device also possesses the technical effects of the star-based process industry data fusion method, and will not be elaborated here.

[0049] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of the present invention.

Claims

1. A data fusion method for process industries based on a star schema, characterized in that, Includes the following steps: Step S1: Obtain the digitized process flow diagram of the process industry, use graph element recognition technology to identify the objects, object attributes and connection relationships in the process flow diagram, and construct a graph structure model; Step S2: Assign a unique device code to the device node corresponding to each device object in the graph structure model, construct a star-shaped data association model with the device code as the center, and use different types of industrial data as the association branches of the star-shaped data association model to perform data fusion. Step S3: Based on the fused data of each device node in the star-shaped data association model, mark the status of each device node on the digital flowchart to generate a holographic data view with status identifiers.

2. The process industry data fusion method based on a star schema according to claim 1, characterized in that, In step S1, primitive recognition technology is used to identify objects, object attributes, and connection relationships in the engineering flowchart, specifically as follows: Graphical symbols in the engineering flowchart are identified using primitive recognition technology. Equipment objects, pipeline objects, and instrument objects are extracted. The equipment type attribute and equipment parameter attribute of the equipment object are extracted, the pipe diameter attribute and medium type attribute of the pipeline object are extracted, the measurement type attribute of the instrument object is extracted, and the connection relationship between the objects is extracted.

3. The process industry data fusion method based on a star schema according to claim 1, characterized in that, The construction of the graph structure model in step S1 is specifically as follows: The graph structure model is represented by a directed graph, with equipment objects and instrument objects as nodes and pipeline objects as edges. The edges represent the topological connections between the nodes, and the edges are associated with the medium flow direction attribute, while the nodes are associated with functional attributes.

4. The process industry data fusion method based on a star schema according to claim 1, characterized in that, Step S2 specifically involves: A unique device code is assigned to the device node corresponding to each device object in the graph structure model. A device code registry is established. The device code registry stores the correspondence between the device code and the node identifier of each device node. Based on the correspondence, the star-shaped data association model is constructed with the device code as the center. By connecting various data source systems through data adapters, a mapping relationship is established between the device code and related data in each data source system. A star-shaped index structure is constructed with the device code as the index key. Based on the star-shaped index structure, different types of industrial data are obtained as the association branches of the star-shaped data association model.

5. The process industry data fusion method based on a star schema according to claim 1, characterized in that, The different types of industrial data specifically include information technology data, operational technology data, and engineering technology data; For the information technology data association branch, work order information, spare parts inventory information, and cost information are associated through the equipment code; For the operational technology data association branch, the timing operation parameter data and equipment status signal data are associated through the equipment code, and the updated data of the operational technology data are obtained in real time through the data subscription mechanism; For the engineering and technical data association branch, the equipment node is associated with the graphical representation, operation procedure document and three-dimensional model data in the engineering flowchart through the equipment code.

6. The process industry data fusion method based on a star schema according to claim 5, characterized in that, The data subscription mechanism adopts a publish-subscribe model, establishes a connection with the data source system through an industrial communication protocol, and subscribes to change events of the operating parameter data and status signal data associated with the device nodes; The data subscription mechanism also includes a data caching and update strategy and a data anomaly handling mechanism.

7. The process industry data fusion method based on a star schema according to claim 1, characterized in that, Step S3 specifically involves: Based on the fused data of each device node in the star-shaped data association model, the status of each device node is marked on the digital flowchart using preset graphical identification rules, thereby generating a holographic data view with graphical status identification.

8. The process industry data fusion method based on a star schema according to claim 7, characterized in that, The specific rules for graphical identification are as follows: The isolation status of the equipment is identified by a first preset geometric shape, and different isolation types are distinguished by a first color coding scheme; the work order status and defect status of the equipment are identified by a second preset geometric shape, and the severity level of the work order is distinguished by a second color coding scheme. The real-time operating parameters of the equipment are marked by dynamic numerical labels; the graphical labels are displayed in an overlay form at the preset positions of the corresponding equipment nodes on the digital flowchart.

9. The process industry data fusion method based on a star schema according to claim 1, characterized in that, Step S4 further includes: In response to a user’s first type of interactive operation on a device node in the digital flowchart, a main data information panel of the device node is displayed in a preset area of ​​the digital flowchart. The main data information panel includes device name, device code, device type and design parameters. In response to the second type of user interaction with the device node, a shortcut menu containing multiple data dimension entries is displayed in a preset area next to the device node. Each data dimension entry in the shortcut menu corresponds one-to-one with each association branch in the star-shaped data association model. The system receives the user's selection of a data dimension entry in the shortcut menu, retrieves and aggregates data from the corresponding related branch in the star-shaped data association model based on the device code, and generates a device digital screen containing the selected data dimension.

10. A process industry data fusion device based on a star schema, characterized in that, It includes a memory and a processor, wherein the memory stores a computer program, which, when executed by the processor, implements the process industry data fusion method based on a star schema as described in any one of claims 1-9.

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