Metadata-driven multi-source heterogeneous data asset intelligent fusion method

Abstract

The present application relates to the technical field of data assets, and particularly relates to a multi-source heterogeneous data asset intelligent fusion method based on metadata driving, which comprises the following steps: obtaining industrial equipment multi-source equipment data and extracting metadata such as equipment number, component number, collection measuring point, data generation time and component maintenance change information; establishing an association relationship between equipment components and collection measuring points, determining component change events according to the component maintenance change information and generating component change records; combining the data generation time to determine the component attribution corresponding to the running data, and associating and arranging the data in different stages to form a component data asset set. The present application aims at the data attribution change problem in the component replacement process of industrial equipment, drives data association adjustment through component change information, realizes accurate distinction and continuous management of historical data and current data, avoids mixing of data in different life cycles, and improves the accuracy and traceability of equipment data asset management.

Description

Technical Field

[0001] This invention relates to the field of data asset technology, and in particular to a method for intelligent fusion of multi-source heterogeneous data assets based on metadata-driven approaches. Background Technology

[0002] With the continuous advancement of digital transformation in industrial enterprises, the scale of data generated by industrial equipment during production, operation, maintenance, and equipment management is constantly growing. Equipment operation data, testing data, and maintenance data are gradually becoming important foundations for enterprises to carry out intelligent operation and maintenance and production management. However, in actual enterprise production environments, industrial equipment typically involves multiple business systems and multiple management links. Data generated at different stages suffers from problems such as scattered sources, inconsistent management methods, and difficulty in continuously maintaining data relationships, making it difficult for enterprises to fully utilize existing equipment data resources to support the entire lifecycle management of equipment. Therefore, how to improve the organization and management capabilities of industrial equipment data resources and achieve effective integration and continuous utilization of equipment data at different stages has become a technical problem that enterprises urgently need to solve in the process of promoting intelligent manufacturing and refined equipment management.

[0003] Chinese Patent Publication No. CN110704455A discloses a method, apparatus, terminal, and storage medium for generating a data asset catalog. The method includes: creating a parent catalog of business assets for a target business; adding business sub-directories at various levels to the parent catalog; adding corresponding business content to each business object sub-directory, wherein the business object sub-directory is the lowest-level business sub-directory in each business asset catalog branch; and associating each business object sub-directory with a corresponding first technical data table to obtain the business asset catalog.

[0004] Therefore, the existing technology has the following problems: it mainly constructs the data asset catalog based on the static relationship between business catalog, business objects and technical data tables, without considering the changes in data relationship caused by maintenance events such as component disassembly and replacement during the operation of industrial equipment, making it difficult to ensure the accurate correspondence between data and actual components at different stages of the equipment's life cycle; it mainly focuses on the classification, organization and catalog management of enterprise data resources, without establishing dynamic relationships based on the internal component structure of industrial equipment, data collection points and maintenance change processes, making it difficult to achieve continuous data management for specific components; it does not adjust data attribution for application scenarios where the overall equipment identification remains unchanged but internal components are replaced, making it impossible to effectively distinguish between historical operating data before and after component replacement and current operating data, and making it difficult to support the continuous utilization of data assets throughout the entire life cycle of industrial equipment. Summary of the Invention

[0005] To address this, the present invention provides a metadata-driven intelligent fusion method for multi-source heterogeneous data assets, which overcomes the problem of mismatched data relationships caused by component replacement in the prior art, thus making it difficult to continuously manage equipment data assets, by establishing component data associations based on metadata and dynamically adjusting data ownership according to component change information.

[0006] To achieve the above objectives, this invention provides a metadata-driven intelligent fusion method for multi-source heterogeneous data assets, comprising: Acquire multi-source equipment data corresponding to the target industrial equipment, wherein the multi-source equipment data includes equipment operation data, component inspection data, maintenance record data, and equipment structure data; Metadata is extracted from the multi-source device data to obtain corresponding data description information, which includes device number information, component number information, data acquisition point information, data generation time information, and component maintenance and change information. Based on the equipment number information, the component number information, and the data acquisition point information, establish the correspondence between equipment components and data acquisition points, and generate an equipment component association table; Based on the component maintenance change information, determine the equipment component replacement event, update the association between the component before replacement and the component after replacement based on the equipment component association table, and generate a component change record; Based on the component change record and the data generation time information, determine the component affiliation corresponding to each piece of running data, and divide the running data into data corresponding to the component before replacement and data corresponding to the component after replacement. Based on the component attribution determination results, the multi-source equipment data is organized, and the data corresponding to the same component are associated to form an industrial equipment component data asset set. The equipment component association table is updated based on the detected new component maintenance change information, and the component affiliation corresponding to the newly added equipment data is re-determined to achieve dynamic integration of data assets during the process of industrial equipment component changes.

[0007] Furthermore, the process of acquiring multi-source equipment data corresponding to the target industrial equipment includes: Acquire equipment operation data collected by the equipment control system. The equipment operation data includes equipment operation parameters, operation time, and data collection point identifiers. Acquire component inspection data and maintenance record data recorded by the equipment maintenance system. The maintenance record data includes component number, component disassembly time, component installation time, component replacement information, and maintenance work order information. Acquire equipment structure data from the equipment management system. The equipment structure data includes equipment number, equipment hierarchical relationship, component composition relationship, and data acquisition and measurement point configuration relationship. A multi-source device data set is established based on data identification information from different sources.

[0008] Furthermore, the process of extracting metadata from the multi-source device data includes: Extract equipment number information, data collection point information, and data generation time information from equipment operation data; Extract part number information, inspection time information, and maintenance change information from part inspection data and maintenance record data; Extract hierarchical relationship information between equipment and components from equipment structure data; Metadata records corresponding to the data of each device are generated based on the extracted information.

[0009] Furthermore, the process of generating the equipment component association table includes: The target industrial equipment is determined based on the equipment number information; The installation component corresponding to the target industrial equipment is determined based on the component number information; The installation components corresponding to each data collection point are determined based on the data collection point information. Based on the target industrial equipment, the installation components, and the collected measurement point information, a correspondence between the equipment number, component number, and collected measurement point number is established, and the equipment component association table is generated.

[0010] Furthermore, the process for identifying equipment component replacement events includes: Obtain the component disassembly and installation times from the maintenance records; The component to be replaced before being taken out of service is determined based on the component disassembly time. The replacement component to be put into operation is determined based on the installation time of the aforementioned component. A component change record is generated based on the replacement relationship between the component before and after replacement.

[0011] Furthermore, the process of determining the component affiliation corresponding to each operational data point includes: Obtain the data generation time corresponding to the running data; The data generation time is correlated with the component replacement time in the component change record; When the data generation time is earlier than the component replacement time, the corresponding operating data will be determined as the data corresponding to the component before replacement. When the data is generated later than the component replacement time, the corresponding operating data will be determined as the data corresponding to the replaced component.

[0012] Furthermore, the process of organizing the data from the multi-source devices includes: Based on the component attribution determination results, the equipment operation data, component inspection data, and maintenance record data are respectively associated with the corresponding components; Create a current component data set from the data belonging to the replaced component; Create a historical component data set from the data belonging to the component before replacement; An industrial equipment component data asset set is formed based on the current component data set and the historical component data set.

[0013] Furthermore, it also includes processing historical data after component replacement: Obtain historical maintenance records and operational data for the components; The replacement relationship between historical components and current components is determined based on the component change records; Retain data used to describe the overall operation of the target industrial equipment; Data that only reflects the state of a historical component itself is labeled as historical component data.

[0014] Furthermore, the process of updating the device component association table includes: Installation records of newly added components in the equipment maintenance system; Obtain the component number and measurement point information corresponding to the newly added component; Based on the newly added component installation record, determine the component number corresponding to the disassembled component, and remove the correspondence between the disassembled component and the corresponding data acquisition point in the equipment component association table; Based on the component number corresponding to the newly added component and the data acquisition point information, a correspondence between the newly added component and the corresponding data acquisition point is established.

[0015] Furthermore, the process of forming the data asset set of the industrial equipment components includes: Generate current device status data based on the current component data set; Generate equipment maintenance history records based on historical component data sets; Generate an industrial equipment component change process data archive based on current equipment status data and equipment maintenance history.

[0016] Compared with existing technologies, the advantages of this invention lie in its focus on application scenarios where data ownership relationships are prone to change during the maintenance and replacement of components in industrial equipment. It uses component maintenance change information as the driving basis for data asset fusion, rather than relying solely on equipment numbers or data fields. By establishing a correspondence between equipment components and data collection points, and combining this with component replacement events to form component change records, the actual component ownership corresponding to the operational data is further determined based on the data generation time. This allows for accurate differentiation and continuous management of historical and current operational data according to the component replacement process, avoiding data distortion caused by the mixed association of operational data from different stages after component replacement. Simultaneously, upon detecting new component maintenance change information, the device component association relationship can be updated synchronously, and the component ownership of the newly added data can be redefined. This achieves continuous maintenance and dynamic fusion of data assets throughout the entire process of industrial equipment component changes, thereby ensuring the accuracy, continuity, and traceability of equipment operational data throughout the entire component replacement cycle. Attached Figure Description

[0017] Figure 1 This is a flowchart of the metadata-driven intelligent fusion method for multi-source heterogeneous data assets in this embodiment; Figure 2 A flowchart for generating the device component association table in this embodiment; Figure 3 This embodiment defines a flowchart for determining equipment component replacement events; Figure 4 This is a flowchart for determining the component affiliation corresponding to each piece of operational data in this embodiment. Detailed Implementation

[0018] To make the objectives and advantages of the present invention clearer, the present invention will be further described below with reference to embodiments; it should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention.

[0019] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0020] Please see Figure 1 The diagram shown is a flowchart of the metadata-driven intelligent fusion method for multi-source heterogeneous data assets in this embodiment. The method in this embodiment includes: Acquire multi-source equipment data corresponding to the target industrial equipment. This multi-source equipment data includes equipment operation data, component inspection data, maintenance record data, and equipment structure data. Multi-source equipment data refers to equipment data from different business systems or different acquisition terminals, including equipment operation data generated by the equipment control system, component inspection data and maintenance record data recorded by the equipment maintenance system, and equipment structure data stored by the equipment management system. Data from different sources are used together to reflect the operating status and component maintenance of the target industrial equipment.

[0021] Metadata extraction is performed on the multi-source device data to obtain corresponding data description information. This data description information includes device number information, component number information, data acquisition point information, data generation time information, and component maintenance and change information. The data description information describes the source attributes and related attributes of the data of each device. It does not include the device operating parameters themselves, but includes information such as device number information, component number information, data acquisition point information, data generation time information, and component maintenance and change information to establish data relationships.

[0022] Based on the equipment number information, the component number information, and the data acquisition point information, a correspondence between equipment components and data acquisition points is established, and an equipment component association table is generated. The equipment component association table is a data record that records the correspondence between equipment number, component number, and data acquisition point number. This is used to determine the actual installed component corresponding to each data acquisition point and to provide a basis for determining the attribution of operating data before and after component replacement.

[0023] Based on the component maintenance change information, a component replacement event is determined, and the association between the component before and after replacement is updated based on the component association table, generating a component change record. The component change record records the disassembly, installation, and replacement of components, including data records of the component before replacement, the component after replacement, and the corresponding replacement time, in order to determine the replacement process of industrial equipment components.

[0024] Based on the component change records and the data generation time information, the component affiliation corresponding to each piece of operational data is determined. The operational data is then divided into data corresponding to the component before replacement and data corresponding to the component after replacement. The component attribution is determined by the actual component source corresponding to the operational data, that is, by determining whether the operational data belongs to the component before or after replacement based on the data generation time and component change records.

[0025] Based on the component attribution determination results, the multi-source equipment data is organized, and data corresponding to the same component are associated to form an industrial equipment component data asset set. The industrial equipment component data asset set is a data set organized according to component ownership, including the current component data set and the historical component data set, to completely preserve the operation and maintenance data of industrial equipment components before and after replacement.

[0026] The equipment component association table is updated based on the detected new component maintenance change information, and the component affiliation corresponding to the newly added equipment data is re-determined to achieve dynamic integration of data assets during the process of industrial equipment component changes.

[0027] Specifically, this invention addresses application scenarios where data ownership relationships are prone to change during the maintenance and replacement of components in industrial equipment. It uses component maintenance change information as the driving basis for data asset fusion, rather than relying solely on equipment numbers or data fields. By establishing a correspondence between equipment components and data collection points, and combining this with component replacement events to form component change records, the actual component ownership corresponding to the operational data is further determined based on the data generation time. This allows for accurate differentiation and continuous management of historical and current operational data according to the component replacement process, avoiding data distortion caused by the mixed association of operational data from different stages after component replacement. Simultaneously, upon detecting new component maintenance change information, the device component association relationship is updated synchronously, and the component ownership of the newly added data is redefined. This achieves continuous maintenance and dynamic fusion of data assets throughout the entire component change process of industrial equipment, thereby ensuring the accuracy, continuity, and traceability of equipment operational data throughout the entire component replacement cycle.

[0028] In this embodiment, the process of acquiring multi-source equipment data corresponding to the target industrial equipment includes: Acquire equipment operation data collected by the equipment control system. The equipment operation data includes equipment operation parameters, operation time, and acquisition point identification. The equipment operation parameters include one or more of the following: rotational speed, vibration value, temperature, pressure, and current. Acquire component inspection data and maintenance record data recorded by the equipment maintenance system. The maintenance record data includes component number, component disassembly time, component installation time, component replacement information, and maintenance work order information. Acquire equipment structure data from the equipment management system. The equipment structure data includes equipment number, equipment hierarchical relationship, component composition relationship, and data acquisition and measurement point configuration relationship. Data from different business systems is matched according to the equipment number, and data from different sources is collected according to the collection time and data source identifier to form a multi-source equipment data set corresponding to the target industrial equipment.

[0029] In this embodiment, the process of extracting metadata from the multi-source device data includes: Based on the equipment identification field, data acquisition point field, and data recording time field in the equipment operation data, the corresponding equipment number information, data acquisition point information, and data generation time information are extracted. The equipment number information identifies the target industrial equipment corresponding to the equipment operation data, the data acquisition point information identifies the data acquisition location corresponding to the equipment operation data, and the data generation time information records the time when the equipment operation data was generated.

[0030] Based on the component identification field, inspection record time field, and maintenance change record field in the component inspection data and maintenance record data, the corresponding component number information, inspection time information, and component maintenance change information are extracted. The component number information identifies the object being inspected or repaired, the inspection time information records the time when the component inspection data was generated, and the component maintenance change information records the disassembly, installation, and replacement of the component.

[0031] Based on the equipment hierarchy field and component composition field in the equipment structure data, the hierarchical relationship information between the equipment and the components is extracted, wherein the hierarchical relationship information describes the correspondence between the target industrial equipment and each component.

[0032] Based on the extracted equipment number information, component number information, data collection point information, data generation time information, and component maintenance and change information, metadata records are established according to the corresponding equipment data so that each equipment data is associated with the corresponding data description information.

[0033] Specifically, this invention extracts metadata from equipment operation data, component testing data, maintenance record data, and equipment structure data from different sources, and unifies and associates equipment number, component number, data collection point, data generation time, and component maintenance change information to form metadata records for corresponding equipment data, so that equipment data that were originally scattered in different business systems have clear data description relationships.

[0034] Please see Figure 2 The diagram shown is a flowchart for generating the equipment component association table in this embodiment. In this embodiment, the process of generating the equipment component association table includes: Based on the equipment identification content in the equipment number information, the equipment number in the equipment structure data is matched to determine the target industrial equipment corresponding to the equipment number information; Based on the component identifier content in the component number information, the component number in the equipment structure data corresponding to the target industrial equipment is matched to determine the installation component corresponding to the target industrial equipment; Based on the acquisition point identifier in the acquisition point information and the acquisition point configuration relationship in the equipment structure data, determine the component number corresponding to each acquisition point; Based on the target industrial equipment, the installation components, and the collected measurement point information, a correspondence between the equipment number, component number, and collected measurement point number is established, and the equipment component association table is generated.

[0035] Specifically, this invention establishes a correspondence between equipment number, component number, and data collection point number to generate an equipment component association table. This enables equipment data from different sources to be associated with specific industrial equipment and corresponding installed components, clarifying the data correspondence between data collection points and actual components. This provides an accurate data association basis for determining the ownership of operating data based on the component replacement process, avoiding confusion between historical operating data and current component data due to component replacement, and improving the accuracy of data fusion during industrial equipment component changes.

[0036] Please see Figure 3 As shown, this is a flowchart for determining a device component replacement event in this embodiment. In this embodiment, the process of determining a device component replacement event includes: Based on the component disassembly record field and component installation record field in the maintenance record, obtain the corresponding component disassembly time and component installation time; Based on the component disassembly time, the component to be replaced that was taken out of operation of the target industrial equipment at the corresponding time is determined from the component disassembly information in the maintenance record; Based on the component installation time, the replacement component that was put into operation at the target industrial equipment at the corresponding time is determined from the component installation information in the maintenance record; Based on the component replacement information in the maintenance record, the component before replacement and the component after replacement are matched to determine the replacement relationship between them, and a component change record containing the component before replacement information, the component after replacement information, and the component replacement time is generated.

[0037] Specifically, this invention, through correlation analysis of component disassembly information, component installation information, and component replacement information in maintenance records, can accurately identify component replacement events from equipment maintenance process records. It distinguishes between components before replacement that were taken out of service and components after replacement that were put into service based on disassembly and installation times, further establishing the replacement relationship between the two and forming a component change record. This links component change information during equipment maintenance with equipment operation data, giving industrial equipment data before and after component replacement clear time boundaries and component correspondences. This provides a reliable basis for subsequently determining the actual component ownership corresponding to the operation data based on the data generation time, avoiding the problem of confusion in the lifecycle data of different components caused by unchanged equipment numbers in traditional data fusion processes. This improves the accuracy, continuity, and traceability of data asset management in component change scenarios.

[0038] Please see Figure 4 As shown, this is a flowchart illustrating the process of determining the component affiliation corresponding to each set of operational data in this embodiment. The process of determining the component affiliation corresponding to each set of operational data in this embodiment includes: Based on the data time field in the device operation data, obtain the data generation time corresponding to the operation data; The time correspondence between the data generation time and the component replacement time in the component change record is established, and the operating data corresponding to the same target industrial equipment is matched with the corresponding component change record. When the data generation time is earlier than the component replacement time, the corresponding operating data is determined as the data corresponding to the component before replacement based on the component change record before replacement. When the data generation time is later than the component replacement time, the corresponding operating data is determined as the data corresponding to the replaced component based on the information of the replaced component in the component change record.

[0039] In this embodiment, when the data generation time is equal to the component replacement time, the corresponding component ownership is determined based on the component installation time and the component disassembly time.

[0040] Specifically, this invention maps the generation time of operational data to the replacement time of components in the component change record. This allows for accurate differentiation of the operational data based on the chronological order of the replacement components, avoiding the problem of mixed data for components at different lifecycles caused by traditional equipment data management that only aggregates data based on equipment numbers. Furthermore, this invention utilizes existing component change records to establish a correlation between operational data and actual components, ensuring continuity and clear attribution of historical operational data before and after component replacement.

[0041] In this embodiment, the process of organizing the multi-source device data includes: Based on the component attribution determination result, obtain the component number corresponding to the operating data of each device, and associate the device operating data with the corresponding component according to the component number; Based on the component number information in the component inspection data and maintenance record data, the inspection records and maintenance records of the corresponding components are associated with the corresponding components; Based on the component change records, determine the currently operating components and historically replaced components. Collect the data belonging to the replaced components to form the current component data set, and collect the data belonging to the components before replacement to form the historical component data set. Based on the current component data set and the historical component data set, the components are linked and organized according to their numbers to form an industrial equipment component data asset set.

[0042] Specifically, this invention re-associates and organizes equipment operation data, component inspection data, and maintenance record data based on component attribution determination results. This allows data from different sources and with different structures to be uniformly collected according to their actual corresponding components, avoiding the problem in traditional data asset management where data is stored only at the equipment level and cannot distinguish the lifecycle data of different components. Simultaneously, by distinguishing between the historical component data set corresponding to the component before replacement and the current component data set corresponding to the component after replacement, the historical data during the replacement process of industrial equipment components is continuously correlated with the current operating data, forming a data asset set covering both before and after the component change.

[0043] This embodiment also includes processing historical data after component replacement: Obtain the maintenance records and operating data corresponding to historical components, wherein the maintenance records include information on the maintenance process of historical components, and the operating data includes the equipment operating parameters corresponding to the operation of historical components; The replacement relationship between historical components and current components is determined based on the component change records, and the data record range corresponding to the historical components is obtained; Based on the data records corresponding to historical components, data related to the operation of the equipment and not dependent on a single historical component will be retained; Data recording the disassembly, replacement, repair, and operational changes of historical components are labeled as historical component data.

[0044] In this embodiment, the process of updating the device component association table includes: The system detects newly added component installation records based on the component installation record field in the equipment maintenance system, and obtains the corresponding component installation time and newly added component information. Based on the new component number and the data collection point information in the new component installation record, determine the component number and associated data collection point corresponding to the new component; Based on the component disassembly information in the newly added component installation record, determine the component number corresponding to the disassembled component, and search for the data acquisition point corresponding to the disassembled component in the equipment component association table, and remove the association between the disassembled component and the corresponding data acquisition point; Based on the component number corresponding to the newly added component and the data acquisition point information, a correspondence between the newly added component number and the corresponding data acquisition point number is established in the equipment component association table, thereby completing the update of the equipment component association table.

[0045] Specifically, this invention detects the installation records of newly added components in the equipment maintenance system and dynamically adjusts the relationships in the equipment component association table based on the component replacement process. This allows the correspondence between equipment components and data collection points to be updated synchronously as the actual maintenance process changes. This solves the problem that when equipment numbers remain unchanged in industrial equipment but internal components are replaced, the original data association cannot reflect the actual component status. It enables the operation data of newly added components to be accurately associated with the corresponding data collection points, while retaining the correspondence between historical components and the original data. This provides an accurate data foundation for determining the data ownership after component changes and for continuous data asset integration.

[0046] In this embodiment, the process of forming the industrial equipment component data asset set includes: Based on the equipment operation data and component testing data in the current component data set, organize the data according to the component number corresponding to the currently installed component to generate the current equipment status data; Based on the historical operation data and maintenance record data in the historical component data set, the equipment maintenance history record is generated by organizing the data according to the component number and component change record corresponding to the historical component. Based on the current equipment status data and the equipment maintenance history, the current component information, historical component information, and the corresponding data generation time are associated and organized according to the component change time to generate an industrial equipment component change process data archive.

[0047] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A metadata-driven intelligent fusion method for multi-source heterogeneous data assets, characterized in that, include: Acquire multi-source equipment data corresponding to the target industrial equipment, wherein the multi-source equipment data includes equipment operation data, component inspection data, maintenance record data, and equipment structure data; Metadata is extracted from the multi-source device data to obtain corresponding data description information, which includes device number information, component number information, data acquisition point information, data generation time information, and component maintenance and change information. Based on the equipment number information, the component number information, and the data acquisition point information, establish the correspondence between equipment components and data acquisition points, and generate an equipment component association table; Based on the component maintenance change information, determine the equipment component replacement event, update the association between the component before replacement and the component after replacement based on the equipment component association table, and generate a component change record; Based on the component change record and the data generation time information, determine the component affiliation corresponding to each piece of running data, and divide the running data into data corresponding to the component before replacement and data corresponding to the component after replacement. Based on the component attribution determination results, the multi-source equipment data is organized, and the data corresponding to the same component are associated to form an industrial equipment component data asset set. The equipment component association table is updated based on the detected new component maintenance change information, and the component affiliation corresponding to the newly added equipment data is re-determined to achieve dynamic integration of data assets during the process of industrial equipment component changes.

2. The method for intelligent fusion of multi-source heterogeneous data assets based on metadata-driven approach according to claim 1, characterized in that, The process of acquiring multi-source equipment data corresponding to the target industrial equipment includes: Acquire equipment operation data collected by the equipment control system. The equipment operation data includes equipment operation parameters, operation time, and data collection point identifiers. Acquire component inspection data and maintenance record data recorded by the equipment maintenance system. The maintenance record data includes component number, component disassembly time, component installation time, component replacement information, and maintenance work order information. Acquire equipment structure data from the equipment management system. The equipment structure data includes equipment number, equipment hierarchical relationship, component composition relationship, and data acquisition and measurement point configuration relationship. A multi-source device data set is established based on data identification information from different sources.

3. The method for intelligent fusion of multi-source heterogeneous data assets based on metadata-driven approach according to claim 1, characterized in that, The process of extracting metadata from the multi-source device data includes: Extract equipment number information, data collection point information, and data generation time information from equipment operation data; Extract part number information, inspection time information, and maintenance change information from part inspection data and maintenance record data; Extract hierarchical relationship information between equipment and components from equipment structure data; Metadata records corresponding to the data of each device are generated based on the extracted information.

4. The method for intelligent fusion of multi-source heterogeneous data assets based on metadata-driven approach according to claim 1, characterized in that, The process of generating a device component association table includes: The target industrial equipment is determined based on the equipment number information; The installation component corresponding to the target industrial equipment is determined based on the component number information; The installation components corresponding to each data collection point are determined based on the data collection point information. Based on the target industrial equipment, the installation components, and the collected measurement point information, a correspondence between the equipment number, component number, and collected measurement point number is established, and the equipment component association table is generated.

5. The method for intelligent fusion of multi-source heterogeneous data assets based on metadata-driven approach according to claim 1, characterized in that, The process for determining equipment component replacement events includes: Obtain the component disassembly and installation times from the maintenance records; The component to be replaced before being taken out of service is determined based on the component disassembly time. The replacement component to be put into operation is determined based on the installation time of the aforementioned component. A component change record is generated based on the replacement relationship between the component before and after replacement.

6. The method for intelligent fusion of multi-source heterogeneous data assets based on metadata-driven approach according to claim 1, characterized in that, The process of determining the component affiliation corresponding to each set of operational data includes: Obtain the data generation time corresponding to the running data; The data generation time is correlated with the component replacement time in the component change record; When the data generation time is earlier than the component replacement time, the corresponding operating data will be determined as the data corresponding to the component before replacement. When the data is generated later than the component replacement time, the corresponding operating data will be determined as the data corresponding to the replaced component.

7. The method for intelligent fusion of multi-source heterogeneous data assets based on metadata-driven approach according to claim 1, characterized in that, The process of organizing the data from the multi-source devices includes: Based on the component attribution determination results, the equipment operation data, component inspection data, and maintenance record data are respectively associated with the corresponding components; Create a current component data set from the data belonging to the replaced component; Create a historical component data set from the data belonging to the component before replacement; An industrial equipment component data asset set is formed based on the current component data set and the historical component data set.

8. The method for intelligent fusion of multi-source heterogeneous data assets based on metadata-driven approach according to claim 1, characterized in that, This also includes processing historical data after component replacement: Obtain historical maintenance records and operational data for the components; The replacement relationship between historical components and current components is determined based on the component change records; Retain data used to describe the overall operation of the target industrial equipment; Data that only reflects the state of a historical component itself is labeled as historical component data.

9. The method for intelligent fusion of multi-source heterogeneous data assets based on metadata-driven approach according to claim 1, characterized in that, The process of updating the device component association table includes: Installation records of newly added components in the equipment maintenance system; Obtain the component number and measurement point information corresponding to the newly added component; Based on the newly added component installation record, determine the component number corresponding to the disassembled component, and remove the correspondence between the disassembled component and the corresponding data acquisition point in the equipment component association table; Based on the component number corresponding to the newly added component and the data acquisition point information, a correspondence between the newly added component and the corresponding data acquisition point is established.

10. The method for intelligent fusion of multi-source heterogeneous data assets based on metadata-driven approach according to claim 1, characterized in that, The process of forming the data asset set of the industrial equipment components includes: Generate current device status data based on the current component data set; Generate equipment maintenance history records based on historical component data sets; Generate an industrial equipment component change process data archive based on current equipment status data and equipment maintenance history.

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