Coal mine enterprise power data processing method and system based on metadata architecture

Abstract

The invention discloses a coal mine enterprise power data processing method and system based on a metadata architecture, and relates to the technical field of data center cloud platform communication, and the method comprises the steps: obtaining coal mine enterprise power metadata, extracting power data elements, and generating a power data asset directory. Embedded micro-service governance and data asset management are realized by constructing a power meta-model and a metadata governance knowledge graph. And estimating the number of storage layer nodes according to the meta-model, and carrying out dispersed storage on the power data according to data element description of the power data so as to expand a metadata management architecture and realize load balancing. Meanwhile, a full-link data map is constructed, metadata traceability tracing and analysis are carried out, and data quality hidden dangers are early warned. According to the method, a comprehensive data asset catalog is formed through an extended acquisition adaptation engine in combination with a centralized and dispersed combined architecture, and data standards and rules are automatically generated by utilizing an intelligent technology, so that effective management and dynamic monitoring of multi-source heterogeneous power data are realized.

Description

Technical Field

[0001] The present invention relates to the field of data center cloud platform communication technology, and in particular to a coal mine enterprise power data processing method and system based on metadata architecture. Background Art

[0002] At present, with the rapid development of data center networks, there are still many problems to be solved, such as how to create a data center network environment to build a network management layer, how to control the traffic between cloud hosts, how to build a virtual extended local area network multi-layer tunnel protocol, how to monitor the routing status of cloud host network cards, reasonably allocate bandwidth within the cloud, and perform quality control management of cloud host storage services.

[0003] At present, the existing technologies for the management and processing of power data of coal mining enterprises mainly include the following methods: Through a centralized data management system, the power data of various coal mining enterprises are aggregated and uniformly managed. This method can realize the centralized storage and processing of data, but it has low flexibility and efficiency when facing a large number of heterogeneous data sources; by formulating unified data standards and specifications, the consistency of data from different sources is ensured. This method often relies on manual intervention, resulting in a long processing cycle and low efficiency; using distributed storage and computing frameworks (such as Hadoop and Spark) to process large-scale power data. Although this method improves data processing capabilities, it still has deficiencies in metadata management and resource coordination, making it difficult to achieve optimal performance; some enterprises have introduced real-time monitoring systems to dynamically monitor and warn power data. Most of these systems are independently built, lack integrity and systematization, and have limited comprehensive analysis capabilities for data. Summary of the invention

[0004] In view of the above-mentioned problems, the present invention is proposed.

[0005] Therefore, the technical problem solved by the present invention is: how to effectively manage and process multi-source heterogeneous power data of coal mining enterprises to improve data integration, quality control and resource utilization efficiency.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0007] In a first aspect, an embodiment of the present invention provides a method for processing power data of a coal mining enterprise based on a metadata architecture, comprising:

[0008] Obtain coal mine enterprise power metadata, extract coal mine enterprise power data elements, and generate coal mine enterprise power data asset catalog;

[0009] According to the power metadata of coal mining enterprises, the power meta-model and metadata governance knowledge graph of coal mining enterprises are constructed to carry out metadata governance and data asset management of embedded microservices;

[0010] According to the coal mine enterprise power meta-model, the number of storage layer nodes is estimated, and the coal mine enterprise power data is dispersed and stored on multiple storage layer nodes according to its data meta description, so as to expand the metadata management architecture;

[0011] Build a full-link data map, conduct full-link metadata traceability and full-link metadata analysis, and issue early warnings for enterprise data quality risks.

[0012] As a preferred solution for coal mining enterprise power data processing method based on metadata architecture, the following is the solution:

[0013] The coal mining enterprise power metadata includes: technical metadata, business metadata, operation metadata and management metadata; the data element description includes: electricity type or transmission frequency.

[0014] As a preferred solution for coal mining enterprise power data processing method based on metadata architecture, the following is the solution:

[0015] The coal mining enterprise power meta-model includes: a technical metadata model, a business metadata model, an operation metadata model and a management metadata model.

[0016] As a preferred solution for coal mining enterprise power data processing method based on metadata architecture, the following is the solution:

[0017] The construction of the coal mining enterprise power meta-model includes:

[0018] According to the coal mine enterprise power metadata, the model is configured and the metamodel modeling tool is set; through the metamodel modeling tool, the coal mine enterprise power metamodel is constructed.

[0019] As a preferred solution for coal mining enterprise power data processing method based on metadata architecture, the following is the solution:

[0020] The model configuration includes:

[0021] Suspected overcapacity production: When the production status specified by the coal mine is normal, and the daily electricity consumption index is greater than the maximum electricity consumption index;

[0022] Suspected suspension of production and illegal mining: When the production status of the coal mine is suspended, the power consumption index of the previous day is less than the minimum power consumption, and the power consumption of the current day is greater than the minimum power consumption;

[0023] Suspected unplanned power outage: When the production status specified by the coal mine is normal production, the power consumption on the previous day is greater than the minimum power consumption, and the power consumption on the current day is less than the minimum power consumption; it is judged as a sudden power outage, that is, an unplanned power outage;

[0024] Suspected resumption of work and production: When the production status specified by the coal mine is normal production, the power consumption on the previous day is less than the minimum power consumption, and the power consumption on the current day is greater than the minimum power consumption; it is judged that the coal mine has resumed normal production, that is, resumption of work and production.

[0025] As a preferred solution for coal mining enterprise power data processing method based on metadata architecture, the following is the solution:

[0026] The construction of the full-link data map includes:

[0027] Graphically display all metadata node data processing and related nodes to build a full-link data map.

[0028] As a preferred solution for coal mining enterprise power data processing method based on metadata architecture, the following is the solution:

[0029] The metadata full-link tracing and metadata full-link analysis includes:

[0030] Through the full-link data map, with the current metadata node, the data flow is traced and the metadata traceability impact analysis is performed. Starting from the current metadata node, the current metadata node is traced and any nodes associated with it are traced upwards and the data flow is traced upwards and the processing process is traced and analyzed. The data flow is traced downwards and the processing link impact analysis is performed. A three-dimensional diagram is used to display the metadata node traceability data flow and processing process traceability analysis information. A cluster link diagram is used to display the metadata node traceability data flow and processing link impact analysis information; any nodes associated with it include: data table nodes, model nodes, indicator nodes, data application nodes or business application nodes.

[0031] In a second aspect, an embodiment of the present invention provides a coal mining enterprise power data processing system based on a metadata architecture, comprising:

[0032] The coal mine power metadata collection layer is used to obtain coal mine enterprise power metadata, extract coal mine enterprise power data elements, and generate a coal mine enterprise power data asset directory;

[0033] The power metadata model data governance layer is used to build the power meta-model and metadata governance knowledge graph of coal mining enterprises based on the power metadata of coal mining enterprises, and to perform metadata governance and data asset management for embedded microservices;

[0034] The data processing resource expansion migration layer is used to estimate the number of storage layer nodes according to the coal mining enterprise power meta-model, and disperse the coal mining enterprise power data to multiple storage layer nodes according to its data meta description, so as to expand the metadata management architecture;

[0035] The meta-model full-link management layer is used to build a full-link data map, conduct full-link metadata traceability and metadata full-link analysis, and provide early warning of enterprise data quality risks.

[0036] In a third aspect, an embodiment of the present invention provides a computing device, including:

[0037] Memory and processor;

[0038] The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the one or more programs are executed by the one or more processors, the one or more processors implement the coal mining enterprise power data processing method based on metadata architecture as described in any embodiment of the present invention.

[0039] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the coal mine enterprise power data processing method based on metadata architecture.

[0040] The beneficial effects of the present invention are as follows: the present invention obtains the power metadata of coal mine enterprises and extracts the power data elements of coal mine enterprises through an extended collection adaptation metadata automatic collection engine according to the multi-source heterogeneous power data of each coal mine enterprise, and generates a power data asset directory of coal mine enterprises through a centralized and decentralized combination architecture; constructs a coal mine enterprise power meta-model and a metadata governance knowledge graph according to the power metadata of coal mine enterprises, and performs embedded microservice metadata governance and data asset management; estimates the number of storage layer nodes, and according to the power data elements of coal mine enterprises, stores them in a dispersed manner on multiple storage layer nodes according to the data element description of the power data elements of coal mine enterprises, and performs metadata management architecture expansion and Load balancing; build a full-link data map, conduct full-link metadata traceability and full-link metadata analysis; sort out enterprise data assets and warn of enterprise data quality risks; be able to build a unified metadata model to achieve effective management and utilization of multi-source, heterogeneous power data; through automatic collection of technical metadata, business metadata and management metadata, form a comprehensive data asset catalog and build a metadata governance knowledge graph; use intelligent technology to automatically generate data standards and rules for coal industry enterprise power data, basic information and safety monitoring intelligent assessment and analysis based on the coal mine enterprise power data asset catalog, to support dynamic monitoring and evaluation of data quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative labor.

[0042] Figure 1 It is an overall flow chart of the coal mining enterprise power data processing method based on metadata architecture described in the first embodiment of the present invention;

[0043] Figure 2 It is an overall schematic diagram of a coal mining enterprise power data processing system based on metadata architecture according to a second embodiment of the present invention;

[0044] Figure 3 It is a schematic diagram of power metadata and metadata description of a coal mining enterprise power data processing system based on metadata architecture according to a second embodiment of the present invention;

[0045] Figure 4 It is a model configuration simulation diagram of a coal mining enterprise power data processing system based on metadata architecture described in the second embodiment of the present invention. DETAILED DESCRIPTION

[0046] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0047] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0048] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0049] Example 1

[0050] Reference Figure 1, which is the first embodiment of the present invention, and provides a method for processing power data of a coal mining enterprise based on a metadata architecture, comprising:

[0051] S1: Obtain coal mine enterprise power metadata, extract coal mine enterprise power data elements, and generate coal mine enterprise power data asset directory;

[0052] In the embodiment of the present application, the coal mining enterprise power metadata includes: technical metadata, business metadata, operation metadata and management metadata; the data element description includes: electricity type or transmission frequency.

[0053] Specifically, based on the multi-source heterogeneous power data of each coal mining enterprise, the power metadata of the coal mining enterprise is obtained through the extended collection and adaptation metadata automatic collection engine; based on the power metadata of the coal mining enterprise, a subset of the power metadata of the coal mining enterprise is extracted to obtain the power data elements of the coal mining enterprise; based on the power metadata of the coal mining enterprise and the power data elements of the coal mining enterprise, a centralized and decentralized combination architecture is used to generate a catalog of power data assets of the coal mining enterprise.

[0054] S2: Based on the power metadata of coal mining enterprises, build the power meta-model and metadata governance knowledge graph of coal mining enterprises, and carry out metadata governance and data asset management of embedded microservices;

[0055] In the embodiment of the present application, the coal mining enterprise power meta-model includes: a technical metadata model, a business metadata model, an operation metadata model, and a management metadata model;

[0056] In the embodiment of the present application, constructing the coal mining enterprise power meta-model includes:

[0057] According to the coal mine enterprise power metadata, the model is configured and the metamodel modeling tool is set; through the metamodel modeling tool, the coal mine enterprise power metamodel is constructed;

[0058] In the embodiment of the present application, the model configuration includes:

[0059] Suspected overcapacity production: When the production status specified by the coal mine is normal, and the daily electricity consumption index is greater than the maximum electricity consumption index;

[0060] Suspected suspension of production and illegal mining: When the production status of the coal mine is suspended, the power consumption index of the previous day is less than the minimum power consumption, and the power consumption of the current day is greater than the minimum power consumption;

[0061] Suspected unplanned power outage: When the production status specified by the coal mine is normal production, the power consumption on the previous day is greater than the minimum power consumption, and the power consumption on the current day is less than the minimum power consumption; it is judged as a sudden power outage, that is, an unplanned power outage;

[0062] Suspected resumption of work and production: When the production status specified by the coal mine is normal production, the power consumption on the previous day is less than the minimum power consumption, and the power consumption on the current day is greater than the minimum power consumption; it is judged that the coal mine has resumed normal production, that is, resumption of work and production.

[0063] Specifically, based on the coal mine enterprise power metadata, a coal mine enterprise power metamodel is constructed through the metamodel modeling tool to process the coal mine enterprise power metadata; a metadata governance knowledge graph is constructed to conduct embedded microservice metadata governance, and data asset management is performed through a distributed extended computing framework. New metadata information is obtained through the coal mine enterprise power metamodel in combination with the data source target address; relying on metadata entity information and metadata relationship services, the metadata governance knowledge graph decouples the complex relationships between data, business, and management in layers to form a multi-layer knowledge graph, and uses data feedback business capabilities to assist the coal mine enterprise power metamodel in business management goals, operation monitoring, model sharing, data experience, and asset value assessment;

[0064] S3: Estimate the number of storage layer nodes based on the coal mining enterprise power meta-model, store the coal mining enterprise power data in multiple storage layer nodes according to its data meta description, and expand the metadata management architecture;

[0065] Specifically, the number of storage layer nodes is estimated based on the amount of metadata processing information and data processing computing resources of the coal mining enterprise power meta-model; the coal mining enterprise power data elements are distributed and stored on multiple storage layer nodes according to the data element description of the coal mining enterprise power data elements, and the metadata management architecture is expanded; the coal mining enterprise power data elements are dynamically migrated between the storage layer nodes to achieve load balancing.

[0066] S4: Build a full-link data map, conduct full-link metadata traceability and metadata analysis, and issue early warnings for enterprise data quality risks.

[0067] In the embodiment of the present application, constructing a full-link data map includes:

[0068] Use graphics to display data processing and associated nodes of all metadata nodes, and build a full-link data map;

[0069] In the embodiment of the present application, performing metadata full-link source tracing and metadata full-link analysis includes:

[0070] Through the full-link data map, with the current metadata node, the data flow is traced and the metadata traceability impact analysis is performed. Starting from the current metadata node, the current metadata node is traced and any nodes associated with it are traced upwards and the data flow is traced upwards and the processing process is traced and analyzed. The data flow is traced downwards and the processing link impact analysis is performed. A three-dimensional diagram is used to display the metadata node traceability data flow and processing process traceability analysis information. A cluster link diagram is used to display the metadata node traceability data flow and processing link impact analysis information; any nodes associated with it include: data table nodes, model nodes, indicator nodes, data application nodes or business application nodes.

[0071] Specifically, based on the expansion foundation of the metadata management architecture, a full-link data map is constructed to conduct full-link metadata traceability and metadata analysis. Intelligent technology is used to automatically generate data standards and rules for intelligent assessment and analysis of coal industry enterprise power data, basic information and safety monitoring based on the coal mine enterprise power data asset directory, to support dynamic monitoring and evaluation of data quality. Enterprise data assets are sorted out to warn of potential risks in enterprise data quality.

[0072] It should be noted that the present invention constructs a unified metadata model to achieve effective management and utilization of multi-source, heterogeneous power data; forms a comprehensive data asset catalog by automatically collecting technical metadata, business metadata and management metadata, and constructs a metadata governance knowledge graph; uses intelligent technology to automatically generate data standards and rules for intelligent evaluation and analysis of power data, basic information and safety monitoring of coal industry enterprises based on the power data asset catalog of coal mining enterprises, and supports dynamic monitoring and evaluation of data quality; according to the power data collection specifications and data access solutions of coal mining enterprises, jointly with the data source management unit to carry out data access work such as data push, data analysis, and data warehousing storage to ensure the consistency, timeliness, authenticity and security of data and data sources; adopts a big data distributed network storage architecture to disperse and store a large number of data elements on multiple nodes according to the type of data, transmission frequency, etc., so as to improve the scalability of the metadata management architecture; estimates the number of nodes required based on the amount of data and the workload of calculation. The data is collected and dynamically migrated between nodes to achieve load balancing; the basic data of the coal mining enterprise power report is established through data collection and statistics; the map information is entered into the map database; the coal mining enterprise power map data type is selected in the map database; the coal mining enterprise power map data source is set through data association; the coal mining enterprise power map style is set and various interactive effects are set, and the modular query object constructs all data link relationships above and below the modular query object, conducts full-link data analysis, and constructs a full-link data map; conducts metadata full-link traceability and metadata full-link analysis; traces back the lineage analysis layer by layer to find the source of the coal mining enterprise power data; correspondingly, finds the downstream sub-data of any data module downward, and conducts the coal mining enterprise power data impact analysis; sorts out the enterprise data assets and warns of the enterprise data quality risks; at the same time, when the node fails, the data can be restored through the copy mechanism, which has less impact on the upper-level application; conducts coal mining enterprise power data asset management collaboration.

[0073] The above is a schematic scheme of the coal mine enterprise power data processing method based on the metadata architecture of this embodiment. It should be noted that the technical scheme of the coal mine enterprise power data processing system based on the metadata architecture and the technical scheme of the coal mine enterprise power data processing method based on the metadata architecture above belong to the same concept, and the details of the technical scheme of the coal mine enterprise power data processing system based on the metadata architecture in this embodiment that are not described in detail can all be referred to the description of the technical scheme of the coal mine enterprise power data processing method based on the metadata architecture above.

[0074] The coal mine enterprise power data processing system based on metadata architecture in this embodiment includes:

[0075] The coal mine power metadata collection layer is used to obtain coal mine enterprise power metadata, extract coal mine enterprise power data elements, and generate a coal mine enterprise power data asset directory;

[0076] The power metadata model data governance layer is used to build the power meta-model and metadata governance knowledge graph of coal mining enterprises based on the power metadata of coal mining enterprises, and to perform metadata governance and data asset management for embedded microservices;

[0077] The data processing resource expansion migration layer is used to estimate the number of storage layer nodes according to the coal mining enterprise power meta-model, and disperse the coal mining enterprise power data to multiple storage layer nodes according to its data meta description, so as to expand the metadata management architecture;

[0078] The meta-model full-link management layer is used to build a full-link data map, conduct full-link metadata traceability and metadata full-link analysis, and provide early warning of enterprise data quality risks.

[0079] This embodiment also provides a computing device, which is applicable to the case of a coal mine enterprise power data processing method based on a metadata architecture, including:

[0080] Memory and processor; the memory is used to store computer executable instructions, and the processor is used to execute computer executable instructions to implement the coal mining enterprise power data processing method based on metadata architecture as proposed in the above embodiment.

[0081] This embodiment also provides a storage medium on which a computer program is stored. When the program is executed by a processor, the method for processing power data of a coal mining enterprise based on a metadata architecture as proposed in the above embodiment is implemented.

[0082] The storage medium proposed in this embodiment and the coal mine enterprise power data processing method based on metadata architecture proposed in the above embodiment belong to the same inventive concept. The technical details not described in detail in this embodiment can be referred to the above embodiment, and this embodiment has the same beneficial effects as the above embodiment.

[0083] Example 2

[0084] Reference Figure 2-Figure 4 , which is an embodiment of the present invention, provides a coal mine enterprise power data processing system based on metadata architecture. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through simulation experiments.

[0085] like Figure 2 As shown, the present invention provides a coal mine enterprise power data processing system based on metadata architecture, including:

[0086] The coal mine power metadata collection layer, based on the multi-source heterogeneous power data of each coal mine enterprise, obtains the coal mine enterprise power metadata through the extended collection adaptation metadata automatic collection engine, extracts the coal mine enterprise power data elements, and generates the coal mine enterprise power data asset directory through the centralized and decentralized combination architecture;

[0087] In the embodiment of the present application, the coal mine power metadata collection layer includes:

[0088] The extended adaptation automatic collection engine can obtain the power metadata of coal mining enterprises through the extended collection and adaptation metadata automatic collection engine according to the multi-source heterogeneous power data of each coal mining enterprise;

[0089] The power data element extraction unit extracts the power data element subset of the coal mine enterprise according to the power data element of the coal mine enterprise, and obtains the power data element of the coal mine enterprise;

[0090] The centralized and decentralized combined architecture unit generates a coal mine enterprise power data asset catalog based on the coal mine enterprise power metadata and coal mine enterprise power data elements through the centralized and decentralized combined architecture;

[0091] like Figure 3 As shown, the power metadata of coal mining enterprises include: technical metadata, business metadata, operation metadata and management metadata; the data element description includes: electricity type or transmission frequency.

[0092] Specifically, the coal mine power metadata collection layer includes: an extended adaptive automatic collection engine, which acquires the coal mine enterprise power metadata through an extended collection adaptive metadata automatic collection engine according to the multi-source heterogeneous power data of each coal mine enterprise; a power data element extraction unit, which extracts a subset of the coal mine enterprise power metadata according to the coal mine enterprise power metadata and acquires the coal mine enterprise power data element; a centralized and decentralized combined architecture unit, which generates a coal mine enterprise power data asset directory through a centralized and decentralized combined architecture according to the coal mine enterprise power metadata and the coal mine enterprise power data element; the coal mine enterprise power metadata includes: technical metadata, business metadata, operation metadata and management metadata; the data element description includes: electricity consumption type or transmission frequency.

[0093] The power metadata model data governance layer builds the power meta-model and metadata governance knowledge graph of coal mining enterprises based on the power metadata of coal mining enterprises, and performs metadata governance and data asset management for embedded microservices;

[0094] In the embodiment of the present application, the power metadata model data governance layer includes:

[0095] The coal mine power meta-model processing unit constructs the coal mine enterprise power meta-model based on the coal mine enterprise power metadata through the meta-model modeling tool, and processes the coal mine enterprise power metadata;

[0096] The knowledge graph metadata governance unit builds a metadata governance knowledge graph, performs embedded microservice metadata governance, and manages data assets through a distributed extended computing framework.

[0097] Specifically, the data governance layer of the power metadata model includes: a coal mine power metamodel processing unit, which builds a coal mine enterprise power metamodel based on the coal mine enterprise power metadata through the metamodel modeling tool, and processes the coal mine enterprise power metadata; a knowledge graph metadata governance unit, which builds a metadata governance knowledge graph, performs embedded microservice metadata governance, and manages data assets through a distributed extended computing framework; the coal mine enterprise power metamodel includes: a technical metadata model, a business metadata model, an operation metadata model, and a management metadata model; through the coal mine enterprise power metamodel, in combination with the data source target address, newly added metadata information is obtained; relying on metadata entity information and metadata relationship services, the metadata governance knowledge graph decouples the complex relationships between data, business, and management in layers to form a multi-layer knowledge graph, and uses data feedback business capabilities to assist the coal mine enterprise power metamodel in business management goals, operation monitoring, model sharing, data experience, and asset value assessment;

[0098] According to the coal mine enterprise power metadata, the model is configured and the metamodel modeling tool is set; the coal mine enterprise power metamodel is constructed through the metamodel modeling tool; Figure 4 As shown, the model configuration simulation includes: suspected overcapacity production: when the production status specified by the coal mine is normal, and the daily electricity consumption index is greater than the maximum electricity consumption index; suspected suspension of production and illegal mining: when the production status specified by the coal mine is suspension of production, there is a power consumption index of the previous day that is less than the minimum power consumption, and the power consumption on the current day is greater than the minimum power consumption; suspected unplanned power outage: when the production status specified by the coal mine is normal production, there is a power consumption of the previous day that is greater than the minimum power consumption, and the power consumption on the current day is less than the minimum power consumption; it is judged to be a sudden power outage, that is, an unplanned power outage; suspected resumption of work and production: when the production status specified by the coal mine is normal production, there is a power consumption of the previous day that is less than the minimum power consumption, and the power consumption on the current day is greater than the minimum power consumption; it is judged that the coal mine has resumed production normally, that is, resumption of work and production.

[0099] The data processing resource expansion migration layer estimates the number of storage layer nodes, and according to the coal mine enterprise power data element, stores it in multiple storage layer nodes according to the data element description of the coal mine enterprise power data element, and expands the metadata management architecture and load balances;

[0100] In an embodiment of the present application, the data processing resource extension migration layer includes:

[0101] The information volume calculation resource operation unit estimates the number of storage layer nodes based on the metadata processing information volume and data processing calculation resource volume of the coal mining enterprise power meta-model;

[0102] The storage layer node expansion unit is configured to disperse and store the coal mine enterprise power data elements on multiple storage layer nodes according to the data element description of the coal mine enterprise power data elements, and to expand the metadata management architecture;

[0103] The dynamic migration unit between nodes dynamically migrates the power data elements of coal mining enterprises between the nodes of the storage layer to achieve load balancing.

[0104] Specifically, the data processing resource expansion and migration layer includes: an information volume calculation resource operation unit, which estimates the number of storage layer nodes according to the amount of metadata processing information and the amount of data processing calculation resources based on the coal mine enterprise power meta-model; a storage layer node expansion unit, which expands the metadata management architecture according to the coal mine enterprise power data element and the data element description of the coal mine enterprise power data element, and disperses the storage to multiple storage layer nodes; an inter-node dynamic migration unit, which dynamically migrates the coal mine enterprise power data element between the storage layer nodes to achieve load balancing.

[0105] The meta-model full-link management layer builds a full-link data map, conducts full-link metadata traceability and metadata full-link analysis; supports dynamic monitoring and evaluation of data quality, sorts out enterprise data assets, and warns of potential risks in enterprise data quality.

[0106] In the embodiment of the present application, the meta-model full-link management layer includes:

[0107] The full-link data map analysis unit builds a full-link data map based on the metadata management architecture expansion foundation, and conducts metadata full-link source tracing and metadata full-link analysis;

[0108] The data quality dynamic monitoring and evaluation unit uses intelligent technology to automatically generate data standards and rules for intelligent evaluation and analysis of coal industry enterprise power data, basic information and safety monitoring based on the coal mine enterprise power data asset catalog, supports dynamic monitoring and evaluation of data quality, sorts out enterprise data assets, and warns of potential risks in enterprise data quality.

[0109] Specifically, the full-link management layer of the meta-model includes: a full-link data map analysis unit, which expands the foundation of the metadata management architecture, builds a full-link data map, and conducts full-link metadata traceability and full-link metadata analysis; a data quality dynamic monitoring and evaluation unit, which uses intelligent technology to automatically generate data standards and rules for intelligent evaluation and analysis of coal industry enterprise power data, basic information and safety monitoring based on the coal mine enterprise power data asset directory, supports dynamic monitoring and evaluation of data quality; sorts out enterprise data assets, and warns of enterprise data quality risks; builds a full-link data map, conducts full-link metadata traceability and full-link metadata analysis, including: using graphics to display all metadata node data processing and Associate nodes and build a full-link data map; through the full-link data map, use the current metadata node to trace the data flow and perform metadata traceability impact analysis. Starting from the current metadata node, trace the current metadata node to any node associated with it, trace the data flow upward and conduct processing traceability analysis, trace the data flow downward and conduct processing link impact analysis, use a three-dimensional stereogram to display the metadata node traceability data flow and processing traceability analysis information, and use a cluster link diagram to display the metadata node traceability data flow and processing link impact analysis information; any nodes associated with it include: data table nodes, model nodes, indicator nodes, data application nodes or business application nodes.

[0110] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for processing power data of coal mining enterprises based on metadata architecture, characterized in that: include: Obtain coal mine enterprise power metadata, extract coal mine enterprise power data elements, and generate coal mine enterprise power data asset catalog; According to the power metadata of coal mining enterprises, the power meta-model and metadata governance knowledge graph of coal mining enterprises are constructed to carry out metadata governance and data asset management of embedded microservices; According to the coal mine enterprise power meta-model, the number of storage layer nodes is estimated, and the coal mine enterprise power data is dispersed and stored on multiple storage layer nodes according to its data meta description, so as to expand the metadata management architecture; Build a full-link data map, conduct full-link metadata traceability and full-link metadata analysis, and issue early warnings for enterprise data quality risks.

2. The method for processing power data of coal mining enterprises based on metadata architecture according to claim 1, characterized in that: The coal mining enterprise power metadata includes: technical metadata, business metadata, operation metadata and management metadata; the data element description includes: electricity type or transmission frequency.

3. The method for processing coal mine enterprise power data based on metadata architecture according to claim 2, characterized in that: The coal mining enterprise power meta-model includes: a technical metadata model, a business metadata model, an operation metadata model and a management metadata model.

4. The method for processing coal mine enterprise power data based on metadata architecture according to claim 3, characterized in that: The construction of the coal mining enterprise power meta-model includes: According to the coal mine enterprise power metadata, the model is configured and the metamodel modeling tool is set; through the metamodel modeling tool, the coal mine enterprise power metamodel is constructed.

5. The method for processing power data of coal mining enterprises based on metadata architecture according to claim 4, characterized in that: The model configuration includes: Suspected overcapacity production: When the production status specified by the coal mine is normal, and the daily electricity consumption index is greater than the maximum electricity consumption index; Suspected suspension of production and illegal mining: When the production status of the coal mine is suspended, the power consumption index of the previous day is less than the minimum power consumption, and the power consumption of the current day is greater than the minimum power consumption; Suspected unplanned power outage: When the production status specified by the coal mine is normal production, the power consumption on the previous day is greater than the minimum power consumption, and the power consumption on the current day is less than the minimum power consumption; it is judged as a sudden power outage, that is, an unplanned power outage; Suspected resumption of work and production: When the production status specified by the coal mine is normal production, the power consumption on the previous day is less than the minimum power consumption, and the power consumption on the current day is greater than the minimum power consumption; it is judged that the coal mine has resumed normal production, that is, resumption of work and production.

6. The method for processing power data of coal mining enterprises based on metadata architecture according to claim 5, characterized in that: The construction of the full-link data map includes: Graphically display all metadata node data processing and related nodes to build a full-link data map.

7. The method for processing coal mine enterprise power data based on metadata architecture according to claim 6, characterized in that: The metadata full-link tracing and metadata full-link analysis includes: Through the full-link data map, with the current metadata node, the data flow is traced and the metadata traceability impact analysis is performed. Starting from the current metadata node, the current metadata node is traced and any nodes associated with it are traced upwards and the data flow is traced upwards and the processing process is traced and analyzed. The data flow is traced downwards and the processing link impact analysis is performed. A three-dimensional diagram is used to display the metadata node traceability data flow and processing process traceability analysis information. A cluster link diagram is used to display the metadata node traceability data flow and processing link impact analysis information; any nodes associated with it include: data table nodes, model nodes, indicator nodes, data application nodes or business application nodes.

8. A system using the coal mining enterprise power data processing method based on metadata architecture as described in any one of claims 1 to 7, characterized in that: include: The coal mine power metadata collection layer is used to obtain coal mine enterprise power metadata, extract coal mine enterprise power data elements, and generate a coal mine enterprise power data asset directory; The power metadata model data governance layer is used to build the power meta-model and metadata governance knowledge graph of coal mining enterprises based on the power metadata of coal mining enterprises, and to perform metadata governance and data asset management for embedded microservices; The data processing resource expansion migration layer is used to estimate the number of storage layer nodes according to the coal mining enterprise power meta-model, and disperse the coal mining enterprise power data to multiple storage layer nodes according to its data meta description, so as to expand the metadata management architecture; The meta-model full-link management layer is used to build a full-link data map, conduct full-link metadata traceability and metadata full-link analysis, and provide early warning of enterprise data quality risks.

9. A computing device comprising: Memory and processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, the steps of the coal mining enterprise power data processing method based on metadata architecture as described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the steps of the coal mine enterprise power data processing method based on metadata architecture as described in any one of claims 1 to 7.

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