DCS health management data warehouse system

Abstract

The invention relates to the technical field of DCS health management, and provides a DCS health management data warehouse system, which comprises a data access and storage layer, a business logic layer and a display layer, and is characterized in that the business logic layer is used for processing DCS monitoring data, process parameter data and DCS business basic data and providing a data service interface; and a data interaction interface, a DCS field thematic base and an expert knowledge base are provided, so that the problems of data islands and unmined and utilized mass data in the DCS field are solved, unified acquisition, convergence and analysis of DCS process data and monitoring data are realized, DCS service basic data is governed, data quality is effectively improved, DCS data management efficiency and level are comprehensively improved, DCS knowledge fusion retrieval efficiency is improved, and the DCS field data management system is suitable for popularization and application. And the open sharing capability of the DCS data is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of DCS health management, and in particular to a DCS health management data warehouse system. Background Art

[0002] Data warehouses are created with the development of information technology and decision support systems (DSS), which use historical operational data for management and decision-making. Data warehouses are subject-oriented, integrated, non-volatile, time-varying data sets used to support management decisions.

[0003] In DCS health management, the following problems exist: data islands in the DCS field and a large amount of data that has not been mined and utilized; unified collection, aggregation and analysis of DCS process data and monitoring data; DCS business basic data governance; DCS data management efficiency and level; DCS knowledge fusion retrieval; and open sharing of DCS data. Summary of the invention

[0004] The main purpose of the present invention is to provide a DCS health management data warehouse system to solve the problems of data islands in the DCS field and a large amount of data not being mined and utilized.

[0005] Another object of the present invention is to provide a DCS health management data warehouse system to solve the problem of unified collection, aggregation and analysis of DCS process data and monitoring data.

[0006] Another object of the present invention is to provide a DCS health management data warehouse system to manage DCS business basic data and effectively improve data quality.

[0007] Another object of the present invention is to provide a DCS health management data warehouse system, develop a variety of DCS data tools, and comprehensively improve the efficiency and level of DCS data management.

[0008] Another object of the present invention is to provide a DCS health management data warehouse system, build a DCS expert knowledge base system, and perform DCS knowledge fusion retrieval based on artificial intelligence technology.

[0009] Another object of the present invention is to provide a DCS health management data warehouse system, publish standard data services based on the DCS health management data warehouse, and continuously improve the open sharing capabilities of DCS data.

[0010] In order to achieve the above object, the present invention provides the following technical solutions:

[0011] A DCS health management data warehouse system, comprising:

[0012] The data access and storage layer is used to store data related to DCS reliability from various business systems of different power plants into corresponding time series databases, relational databases, MPPs, big data storage systems or object storage components;

[0013] The business logic layer is used to provide data processing, data services, and business services, including: processing DCS monitoring data, process parameter data, and DCS business basic data, providing data service interfaces, data interaction interfaces, DCS domain subject libraries, and expert knowledge bases;

[0014] The presentation layer displays relevant indicators of all types of data in the data warehouse in a visual way.

[0015] In some embodiments, data related to DCS reliability in the business system includes DCS monitoring data, PI system process parameter data, operation history data, structured basic data in the information system, configuration data files, design files, equipment pictures, and on-site videos.

[0016] In some embodiments, the business logic layer includes:

[0017] Data acquisition module, used to collect DCS monitoring data, DCS process parameter data, DCS business basic data in real time, import DCS operation history data, DCS configuration data files, DCS design files and materials;

[0018] Data storage module, used to store DCS timing data, DCS business basic data, DCS configuration data, DCS design files and information;

[0019] Data processing module, used to process DCS time series data, DCS business basic data, DCS configuration data, DCS design files and information;

[0020] Data service module, used to support file synchronization, database synchronization, streaming push data publishing methods, and provide monitoring data service interface and basic data service interface;

[0021] Business service module, used to provide business system interface and build DCS subject database and expert knowledge base;

[0022] The data display module is used for data comparison, data query, and data visualization management. The data here focuses on the comprehensive integration and display of multi-source heterogeneous data.

[0023] In some embodiments, during the real-time collection of DCS monitoring data, according to the DCS system management and data access strategy of each power plant, the monitoring data is accessed from the DCS system through a gateway or an interface machine, and then received by the DCS monitoring data collection tool and sent and stored in a time series database.

[0024] In some embodiments, the benchmark data is standardized according to the needs of production data use and planning, and business-oriented subject data objects and indicators are established, including:

[0025] Data cleaning: Improve data quality by detecting errors and inconsistencies in the data, eliminating redundant data, correcting erroneous data;

[0026] Data conversion: convert according to data standard requirements;

[0027] Data association: According to the business process analysis requirements, multi-table associations are performed layer by layer for data of different dimensions and categories, and the required field data is summarized;

[0028] Data aggregation: Generate summary data based on business processing logic;

[0029] Data dimensionalization: Dimensional modeling of basic data, extraction of dimensional or dictionary information, and provision of reference data.

[0030] In some embodiments, the DCS configuration data file is converted into a data format that is highly readable and can support visualization, and the configuration data information is quickly retrieved, and the information therein is extracted for analysis; the unstructured data is marked, the content is parsed and identified, and feature extraction, content marking, analysis and identification are supported.

[0031] In some embodiments, the data service module provides a monitoring data service interface in the form of a RESTful API to implement the following data access functions:

[0032] Get the attribute information of a specified single or multiple measuring points;

[0033] Get the actual value of the latest timestamp of a specified single or multiple measurement points;

[0034] Get the interpolation value of a specified single or multiple measurement points at a specified time point;

[0035] Get all actual values ​​of a specified single or multiple measuring points within a specified time period;

[0036] Get the interpolation value of a specified single or multiple measuring points in a specified time period and time interval;

[0037] Get the aggregate query results of a specified single or multiple measurement points within a specified time period.

[0038] In some embodiments, the DCS subject library includes equipment management, simulation risk analysis, training management, maintenance management, user center, experience feedback, and digital delivery; the expert knowledge base is used to manage offline fault handling experience, manufacturer manuals, experience feedback information, and supports the association between storage data and business.

[0039] In some embodiments, the DCS health management data warehouse system further includes a DCS data tool, which includes:

[0040] DCS monitoring data collection tool, used to collect monitoring data from the power plant DCS system in real time and store it on the DHP platform;

[0041] Process parameter data collection tool, used to collect process parameter data from the PI system in real time from the power plant and store it on the DHP platform;

[0042] DCS historical data import tool, used to import the historical data files of monitoring data and process parameters in DCS into the time series database of DHP platform;

[0043] File import tool, used to collect and transfer DCS-related data documents of each pilot power plant and store them in the object storage component;

[0044] Configuration retrieval and analysis tools, used to quickly retrieve configuration data information and extract information for analysis;

[0045] Unstructured data processing tools, used to label, parse and identify DCS data files, perform feature extraction and content labeling;

[0046] Equipment configuration tools, used for access management, calculation processing and monitoring management of nuclear power equipment and its collected data;

[0047] Data configuration tool, which is used to support the configuration of time series data structure and data points, and download the data points to real-time, historical databases and calculation programs. The generated time series data configuration can be used for screen configuration, algorithm configuration and access configuration in offline environment;

[0048] Algorithm configuration tool, used to realize the configuration of computational analysis models for industrial time series data;

[0049] The screen configuration tool is used to draw, configure, download and manage various indicator-related screens of nuclear power plants, and realize real-time information monitoring and historical information display through the Web.

[0050] Compared with the prior art, the DCS health management data warehouse system provided by the present invention has the following beneficial effects:

[0051] The present invention collects, accesses, stores, processes and analyzes multi-source heterogeneous data such as DCS system data, basic equipment information, status data, maintenance data, and provides DCS-related data services to build a DCS health management data warehouse, provide data support for various application modules of DCS health management, provide data support and knowledge integration capabilities in the DCS field, provide comprehensive service support, and maintain the stability of the DCS health management platform. The DCS health management data warehouse has the functions of DCS data collection, data storage, data processing, data services, business services, etc., which is convenient for DCS application management, analysis and use of data. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] In order to more clearly illustrate the technical solution of the present invention, the following briefly introduces the drawings required for the technical description.

[0053] Figure 1 A schematic diagram of a DCS health management data warehouse system provided by the present invention;

[0054] Figure 2 A schematic diagram of the storage data model design provided by the present invention;

[0055] Figure 3 A schematic diagram of the measurement point coding design provided by the present invention;

[0056] Figure 4 This is a schematic diagram of the basic data storage layer design provided by the present invention. DETAILED DESCRIPTION

[0057] The following is further explained in detail through specific implementation methods.

[0058] like Figure 1 As shown, the present invention provides a DCS health management data warehouse system, including a data access and storage layer, a business logic layer, and a display layer. The present invention mines and utilizes a large amount of DCS data, realizes the unified collection, aggregation and analysis of DCS process data and monitoring data, manages DCS business basic data, effectively improves data quality, comprehensively improves the efficiency and level of DCS data management, improves the efficiency of DCS knowledge fusion retrieval, and enhances the open sharing capability of DCS data.

[0059] The data access and storage layer is used to store data related to DCS reliability from various business systems of different power plants into corresponding time series databases, relational databases, MPPs, big data storage systems or object storage components.

[0060] Through the data access and storage layer, DCS monitoring data related to DCS reliability from various business systems of different power plants, PI system process parameter data, operation history data, structured basic data in the information system, configuration data files, design files, equipment pictures, on-site videos and other information are collected or imported and stored in the corresponding storage components.

[0061] The business logic layer is used to provide DCS data processing, data services, and business services.

[0062] Data processing includes data interpolation and data frequency reduction for DCS monitoring data and process parameter data; data cleaning, data conversion, data association, data aggregation, data dimensionalization and other processing for DCS business basic data; content analysis, feature extraction, labeling and other processing for DCS configuration data files, DCS design materials and other related files.

[0063] The data service supports publishing data on demand to the internal or external business library specified by the DCS health management platform, and provides DCS monitoring data / process parameter data service interface, DCS business basic data service interface, and DCS file data service interface.

[0064] The business service provider provides data interaction interfaces between the power plant's ASP-1, ERMs, EAM, equipment middle platform, ERP and other business systems, a DCS field database and a DCS expert knowledge base.

[0065] The display layer provides a visual display of indicators for all types of data in the data warehouse. The displayed content includes: the overall data volume, data storage capacity, business areas to which the structured data is accessed, the distribution of the data warehouse hierarchy, the distribution of the source system, and the usage of the data interface; the data volume, data storage capacity, real-time data access, and data distribution of the time series data access; the data volume, data storage capacity, and number of different types of files of the file data.

[0066] Structured data management allows users to classify and manage data tables by business field, view a list of all data tables, retrieve and view metadata information, query data for a single data table, and support classified management of time series data by power plant / unit; time series data management allows users to view a list of measuring points, query measuring point attribute information according to power plant / unit, query single measuring point information, compare data trends of multiple measuring points, support data retrieval by time range, query method supports aggregate query and historical query, and batch export of data; file data management allows users to classify and manage files, perform batch retrieval and viewing according to file name and file format, support batch download and file preview, file list viewing, and online preview of a single file.

[0067] The DCS health management data warehouse system collects the DCS operation and equipment parameter data, configuration data, DCS-related design data, equipment pictures, etc. of each power plant that is dispersed, independent, and heterogeneous, and then performs unified and standardized processing and processing on the collected data to provide standardized result data and indicator data for the DCS health management application module. On the one hand, it uses big data processing capabilities to process massive amounts of data to reduce the data interaction pressure between each power plant system and each application module of the DCS health management platform. On the other hand, it provides high-quality data for DCS applications and provides data service capabilities to the outside world, shielding the intermediate processing links so that applications can quickly and easily obtain data. On the other hand, it provides the visualization display capability of DCS multi-source heterogeneous data to facilitate rapid viewing and retrieval of external applications.

[0068] In some embodiments, the business logic layer includes a data acquisition module, a data storage module, a data processing module, a data service module, a business service module, and a data display module.

[0069] The data acquisition module is used to collect DCS monitoring data in real time, collect DCS process parameter data in real time, collect DCS business basic data, import DCS operation history data, import DCS configuration data files, and import DCS design files and materials.

[0070] The DCS monitoring data is collected in real time through the data acquisition module. According to the DCS system control and data access strategy of each power plant, the DCS monitoring data is collected and accessed from the DCS system through a network gate or interface machine, and then received by the DCS monitoring data acquisition tool and sent and stored in the time series database.

[0071] The DCS process parameter data is collected in real time through the data acquisition module. Through the message queue method, the power plant process parameter data from the PI system of all pilot power plants is collected on demand, accessed in real time through the interface, and the protocol is parsed. The high-frequency data is down-converted, and then transmitted and stored in the time series database through the real-time transmission component and consumer program.

[0072] The basic data of DCS business is collected through the data collection module. Basic DCS business data such as basic information of DCS equipment, maintenance management data, spare parts management data, training management, configuration management, and work order data are collected from various information systems of the pilot power plant through direct database connection, collection interface, ETL tool, FTP, etc. For scenarios with low timeliness requirements, batch data access is usually T+1 days, and then transferred to the database through batch collection components. For some data with high response time requirements, real-time access is performed, such as: for Oracle's OGG method and MySQL's Binlog log parsing method, and then transferred to the database through real-time transmission components and interfaces. The collected data is stored in HDFS distributed file storage or MySQL relational database. For example, basic DCS business data such as basic DCS equipment information, maintenance management data, spare parts management data, training management, configuration management, and work order data are collected from the relational database (such as Oracle, MySQL) of the information system through the data collection module.

[0073] Import DCS operation historical data through the data acquisition module. Export the historical data of monitoring data and process parameters in DCS as files, and use the historical data import tool to collect all pilot power plant DCS historical data as needed and store them in the historical time series database. Historical data is divided into historical data in DCS and DCS archived data. Determine the storage time of historical data and the method of obtaining it from DCS; deploy the historical data import tool to collect all pilot power plant DCS historical data as needed.

[0074] Import DCS configuration data files through the data acquisition module. Collect DCS IA configuration data and TRICON configuration data, and save the configuration data in Visio, ILV, XLSX, XML, FDESEQ, RELS and other file formats. The acquisition frequency supports scheduled acquisition and irregular acquisition. The acquisition method is: import the power plant DCS configuration data file from the specified directory through the configuration data import tool and store it in the object storage component.

[0075] Import DCS design files and data through the data acquisition module. The acquisition frequency supports scheduled and irregular acquisition. The acquisition method is: various unstructured data of the power plant's DCS, such as meeting minutes, design files, equipment pictures, outline data files, fault repair data, maintenance plans, work order archives, etc., in the format of Word, PDF, pictures, videos, etc., are collected and transmitted through the file import tool and stored in the object storage component.

[0076] The data storage module is used to store DCS timing data, DCS business basic data, DCS configuration data, DCS design files and materials.

[0077] (1) DCS time series data storage

[0078] Time series data includes DCS monitoring data and DCS process parameter data from the PI system, which are stored in the time series database in the form of "measurement point name-timestamp-measurement point value". For DCS monitoring data, its quality information is stored in the time series database.

[0079] Time series data storage supports data redundant storage, and the time series database is deployed in a master-slave redundant mode. Time series data supports automatic backup and provides online data backup and recovery capabilities.

[0080] The DCS time series data model has four layers: group / company layer-power plant layer-unit layer-measurement point layer. The corresponding path consists of: root.group code (or company code).power plant code.unit code.measurement point unified code. Among them, the group / company code is the code of the enterprise group or company code, such as: CNNP. The corresponding information of power plant name and power plant code is shown in Table 1, and the corresponding information of unit name and unit code is shown in Table 2. Figure 2 For example, if the data of measuring point 10CWS-TE306A comes from Unit 1 of Sanmen Nuclear Power Plant, the path used to store the time series data is root.CNNP.ZS.01.ZS_01_10CWS-TE306A.

[0081] Table 1 Power plant name and power plant code

[0082] Power plant name Power plant code Qinshan Nuclear Power Plant Q1 Qinshan Second Nuclear Power Plant Q2 Qinshan Third Nuclear Power Plant Q3 Fangjiashan Nuclear Power Plant QF Jiangsu Nuclear Power Co., Ltd. TW Sanmen Nuclear Power Co., Ltd. ZS Fujian Fuqing Nuclear Power Co., Ltd. FQ Hainan Nuclear Power Co., Ltd. HN China National Nuclear Corporation Xiapu Nuclear Power Co., Ltd. XP China National Nuclear Corporation Zhangzhou Energy Co., Ltd. ZG

[0083] The storage group corresponds to the unit, and each unit of each power plant corresponds to a storage group. If the power plant is Sanmen Nuclear Power and the unit is Unit 1, then the storage group should be set to: root.CNNP.ZS.01. The corresponding information of the power plant name and power plant code is shown in Table 1.

[0084] The measuring point code consists of three parts. The first part is the two-character power plant code, the second part is the unit code, and the third part is the original measuring point number of the power plant. The power plant code is shown in Table 1. The measuring point code example is as follows Figure 3 .

[0085] The present invention provides measurement value encoding. In order to improve the storage efficiency of data, it is necessary to encode the data during the data writing process, thereby reducing the usage of disk space. In the process of writing data and reading data, the amount of data in I / O operation can be reduced to improve performance.

[0086] For DCS measuring point measurement values, including double-precision floating point values ​​(DOUBLE), single-precision floating point values ​​(FLOAT), and integer values ​​(INT32), GORILLA encoding is used for data encoding; for Boolean values ​​(BOOLEAN), run-length encoding (RLE) is used for data encoding.

[0087] The compression method used is: after the time series is written and encoded as binary data according to the specified type, the data is compressed using compression technology to further improve the space storage efficiency. Considering the large scale of time series data in power plants, SNAPPY compression is used for storage of time series data.

[0088] (2) DCS business basic data storage

[0089] DCS business basic data includes DCS equipment basic information, maintenance management data, spare parts management data, training management, configuration management, work order data, etc. HDFS distributed file storage is used to store raw data, process data and result data, and MySQL is used to store data distributed to various application modules of the DCS health management platform.

[0090] like Figure 4 As shown in the figure, in DCS basic data storage, the data warehouse is divided into the following 7 levels:

[0091] Data exchange layer: Exchange, stores metadata information related to data resource configuration. The metadata directory of this layer mainly includes: data resource connection, data source table information, and data warehouse resources.

[0092] Original data layer: ODS (Operational Data Store), also known as the source data layer, is used to store the source data of the business system. The original data of the business system is extracted to the ODS layer for storage, and is kept synchronously updated with the source database of the business system, serving as the basis for subsequent data processing and analysis at each layer.

[0093] Data detail layer: DWD (Data Warehouse Detail), according to the field standards, data cleaning and format conversion are performed, and data from different power plants in the business system are integrated into the corresponding data tables according to business fields and subject domains. The number of fields in the DWD layer data table is expanded according to the business conditions of different power plants, and the field types are consistent with the ODS layer. The DWD layer is used for the permanent storage of source system data on the data platform to solve the data quality problems of different power plants, data integrity problems, and inconsistent data formats.

[0094] Data standard layer: STD (Standard), according to the data standards in the nuclear power field, processes and summarizes the processed data in the DWD layer, associates the fields and attributes related to the business, and forms unified nuclear power standard data.

[0095] Data summary layer: DWS (Data Warehouse Summary) is business-oriented. It develops models based on business needs and outputs data deliverables. All summary layer data tables are bound to the business to meet business tasks. The construction of the DWS layer is based on the aggregation or multi-model processing of standardized data to form a service data model, which precipitates and processes common information together. According to business needs, the fields in the DWD and STD layers can be aggregated to form subject tables and wide tables, thereby simplifying the complex logical relationships of the business system and forming a data structure that is easy for business personnel to understand.

[0096] Data Mart layer: DM (Data Mart), oriented to applications, can process the data in the DWD, STD, and DWS layers at the row and column level and provide external services. By establishing data asset views and providing data access interfaces, data distribution services are provided to external applications, and data is provided to various applications to support business data needs; data models involved in specific or commonly used reports can be filtered or logically processed, and input parameters can be set to provide report data for applications; personalized statistical indicator data in data products can also be generated.

[0097] Public dimension table layer: DIM (Dimension), stores mapping information such as public dictionary code tables and public dimension tables used by various businesses, and is used to associate dimensions of other hierarchical data, making it convenient for business personnel to query the meaning of data fields. Too many dimensions are forcibly associated with subject tables and wide tables, which will not only cause data redundancy, but also be difficult to maintain. Therefore, dimension data needs to be placed and managed separately to ensure the integrity of the dimensions.

[0098] (3) DCS configuration data storage

[0099] The parsed content in the configuration data file is stored in the MySQL relational database, and the original configuration data file is stored in the object storage component. The object storage component supports the following common operation features for documents with readable content, such as XML and JSON type documents:

[0100] Supports full indexing, and can create indexes on any attribute;

[0101] Supports JSON query, and can query embedded objects and arrays;

[0102] Supports specifying and modifying the attribute content of document objects;

[0103] Supports batch processing and aggregation operations on data.

[0104] (4) DCS design files and data storage

[0105] Use OSS object storage components to store DCS design files and data, supporting images, videos, voice, text, and annotation files. Relying on low-cost, highly available OSS object storage, files that DCS needs to archive offline for a long time can be stored in OSS. OSS is a distributed object storage service that provides an object storage service in the form of Key-Value pairs. When storing a file (Object), you need to specify the name (Key) of this Object, and then use this Key to obtain the content of the Object.

[0106] The data processing module is used to process DCS timing data, DCS business basic data, DCS configuration data, DCS design files and information.

[0107] The DCS monitoring data and process parameter data are processed, and the processing algorithms include data interpolation and data frequency reduction.

[0108] Data interpolation: supplement missing data within a certain period of time through interpolation. Commonly used interpolation algorithms include linear interpolation and spline interpolation.

[0109] Data downscaling: Convert high-frequency time series data into low-frequency data, reduce the amount of data while maintaining data features, and simplify data analysis and modeling.

[0110] According to the needs of production data use and planning, standardize the processing of original business data, establish business-oriented subject data objects and indicators, and process them through the data governance functions provided by the data governance platform. The main processes include:

[0111] Data cleaning: Improve data quality by detecting errors and inconsistencies in the data, eliminating redundant data, correcting erroneous data, and common operations: remove duplicate values; replace null values, supplement missing values; ensure that data values ​​fall within the definition domain, and verify data logical relationships;

[0112] Data conversion: conversion according to data standard requirements, commonly used such as: date and time conversion, data encoding conversion, data item decomposition, etc.;

[0113] Data association: According to the business process analysis requirements, multi-table associations are performed layer by layer for data of different dimensions and categories, and the required field data is summarized;

[0114] Data aggregation: Generate summary data based on business processing logic;

[0115] Data dimensionalization: Dimensional modeling of basic data, extraction of dimensional or dictionary information, and provision of reference data.

[0116] The configuration data file is parsed through the configuration data processing tool to convert the configuration data file into a data format that is highly readable and can support visualization.

[0117] Unstructured data processing tools are used to perform file annotation, content parsing and identification on unstructured data such as DCS design documents and materials, supporting feature extraction, content annotation, analysis and identification.

[0118] Among them, for DCS configuration data files, they are converted into a highly readable data format that can support visualization, and the configuration data information is quickly retrieved, and the information is extracted for special analysis (for example, for IA configuration files, according to the I / A configuration file parsing specifications obtained by analysis, a parsing tool for I / A system configuration files is developed, and the actual unit I / A configuration file is used as input to realize the recognition and parsing of the reference unit I / A configuration file, and the conversion generates control logic execution code that can be downloaded to the DCS virtual controller, and the module definition file, variable definition file and initial value file are obtained at the same time; for triconf configuration files, the data structure of TRICON configuration files is analyzed, the correspondence between TRICON configuration data and DCS virtual controller logic program is sorted out, and the conversion specification between TRICON configuration language and DCS virtual controller logic program is established). For DCS design files, materials and other unstructured data, file annotation, content parsing and identification are performed, and feature extraction, content annotation, analysis and identification are supported.

[0119] The data service module is used to support file synchronization, database synchronization, and streaming data publishing methods, and provides monitoring data service interfaces and basic data service interfaces.

[0120] For DCS monitoring data, DCS process parameter real-time data, and DCS business basic data, it supports file synchronization, database synchronization, and streaming push data publishing methods, making it easier for developers to import and migrate data.

[0121] File synchronization method: Data can be stored as files and placed in the specified data directory as required.

[0122] Database synchronization method: import data directly into the specified target database.

[0123] Streaming push mode: push data to a distributed messaging system.

[0124] The data service module provides a monitoring data service interface in the form of a RESTful API, which implements the following data access functions:

[0125] Get the attribute information of a specified single or multiple measuring points;

[0126] Get the actual value (latest value) of the latest timestamp of a specified single or multiple measurement points;

[0127] Get the interpolation value of a specified single or multiple measurement points at a specified time point;

[0128] Get all actual values ​​of a specified single or multiple measuring points within a specified time period;

[0129] Get the interpolation value of a specified single or multiple measuring points in a specified time period and time interval;

[0130] Get the aggregate query results of a specified single or multiple measurement points within a specified time period.

[0131] Based on the data objects of the DCS data warehouse subject library, the data service function in the data governance tool is used to create and publish a RESTful data service interface for use by functional modules such as the DCS health management cockpit, DCS operation and maintenance management, and DCS parallel system.

[0132] The business service module is used to provide business system interfaces and build DCS subject libraries and expert knowledge bases. The DCS subject library includes equipment management, simulation risk analysis, training management, maintenance management, user center, experience feedback, and digital delivery. For example, according to the needs of DCS equipment health monitoring, maintenance management, spare parts management and other modules, the business data is analyzed and processed to build a DCS fault expert knowledge base, health status prediction analysis library, equipment reliability index library, etc.

[0133] The subject library stores the analysis result data in the form of a database and provides it to the DCS module in the form of data services, thus reducing the repeated calculation work of the business module.

[0134] The expert knowledge base is used to manage offline fault handling experience, manufacturer manuals (PDF), experience feedback information, and can support the association between storage data and business, such as: card fault association. It includes knowledge editing tools, import tools and other tools.

[0135] The business service module provides a data interaction interface with the power plant ASP-1, ERMs and other business systems, and writes the analysis results and business data of the DCS health management platform to the third-party system. Depending on the storage type of the target business system, the interface is developed in the form of RESTful API or WebService.

[0136] The data display module provides a visual display of indicators for all types of data in the data warehouse. The displayed content includes: displaying the overall data volume, data storage capacity, business areas, distribution of data warehouse levels, distribution of source systems, and usage of data interfaces for structured data access; displaying the data volume, data storage capacity, real-time data access, and data distribution of time series data access; displaying the data volume, data storage capacity, and number of different types of files for file data. It should be noted that the data here focuses on the comprehensive integration and display of multi-source heterogeneous data, and the display layer focuses on displaying the data indicators obtained after processing.

[0137] Structured data management allows users to classify and manage data tables by business field, view a list of all data tables, retrieve and view metadata information, query data for a single data table, and support classified management of time series data by power plant / unit; time series data management allows users to view a list of measuring points, query measuring point attribute information according to power plant / unit, query single measuring point information, compare data trends of multiple measuring points, support data retrieval by time range, query method supports aggregate query and historical query, and batch export of data; file data management allows users to classify and manage files, perform batch retrieval and viewing according to file name and file format, support batch download and file preview, file list viewing, and online preview of a single file.

[0138] The data tools in the DCS health management data warehouse system include DCS monitoring data acquisition tools, process parameter data acquisition tools, DCS historical data import tools, DHP data governance tools, configuration data import tools, file import tools, configuration data processing tools, configuration retrieval and analysis tools, unstructured data processing tools, data visualization management tools, equipment configuration tools, data configuration tools, algorithm configuration tools, screen configuration tools, and time series data sample management tools.

[0139] DCS monitoring data acquisition tool, used to collect monitoring data from power plant DCS systems (such as Fangjiashan, Fuqing, Hainan and other power plants) in real time and store it in a time series database.

[0140] The process parameter data collection tool is used to collect process parameter data from the PI system in real time from the power plant and store it in the time series database.

[0141] DCS historical data import tool is used to import historical data files of monitoring data and process parameters in DCS into the time series database.

[0142] The data governance tool is used to provide data collection and fusion governance capabilities for multiple heterogeneous sources. It can integrate and aggregate data from many business systems of nuclear power plants, and provide standardized multi-source heterogeneous data fusion access services for DCS health management system application modules through cross-system collection, storage, governance and sharing of multi-source heterogeneous data.

[0143] The configuration data import tool is used to transfer the collected DCS configuration data files of each pilot power plant from the specified directory to the object storage group. The configuration data files are saved in file formats such as Visio and ILV.

[0144] The file import tool is used to collect and transfer DCS-related documents of each pilot power plant and store them in the object storage component. The DCS-related documents of the power plant, such as meeting minutes, design documents, equipment pictures, outline data files, fault repair data, maintenance plans, work order archives, etc., exist in Word, PDF, pictures and other formats. They are collected and transferred through the file import tool and stored in the object storage component.

[0145] Configuration data processing tools are used to convert configuration data files into data formats or files that are highly readable or can support visualization.

[0146] Configuration retrieval and analysis tools are used to quickly retrieve configuration data information and extract the information for specialized analysis and viewing.

[0147] Unstructured data processing tool, used for data annotation, analysis and recognition of DCS data files, supporting feature extraction and content annotation.

[0148] Data visualization management tools are used to support the visualization of structured data (e.g., equipment information, instrument data, work orders), semi-structured data (e.g., configuration data), unstructured data (e.g., design documents, outline data, maintenance plans, meeting minutes, fault repair data, work order archives, equipment pictures, drawings, etc.), and time series data (e.g., DCS monitoring and process data), and can display the data in a correlated manner.

[0149] Equipment configuration tool, used for access management, calculation processing and monitoring management of nuclear power equipment and its collected data; full-cycle management of equipment data from model design, access configuration, model calculation to equipment monitoring.

[0150] Data configuration tool is a tool software used to support the configuration of time series data structure and data points, and download the data points to real-time, historical databases and calculation programs. The generated time series data configuration can be used for screen configuration, algorithm configuration and access configuration in offline environment.

[0151] The algorithm configuration tool is used to configure the calculation and analysis model of industrial time series data, helping model engineers to calculate and analyze data. The component library of the algorithm configuration tool can manage algorithms, realize the asset accumulation and sharing of algorithms, and reduce the duplication of algorithm development. The function is to calculate time series real-time data, form a calculation model through visual drag and drop in the browser, and download the model to the time series real-time logic calculation engine for operation.

[0152] The screen configuration tool is used to draw, configure, download and manage the screens related to various indicators of nuclear power plants, realize real-time information monitoring and historical information display through the Web, and support the production links such as maintenance, operation, planning, and equipment management of nuclear power plants. Various screens can be flexibly and quickly assembled through configuration, which can be used for real-time and historical information display of multiple types of data.

[0153] The time series data sample management tool is used to prepare, preprocess and label the parameter data required for the training of nuclear power machine learning algorithms and accident analysis models, build standard sample data sets that meet the model training requirements, and manage and publish sample data sets.

[0154] The DCS health management data warehouse system provided by the present invention has high performance, security, reliability and robustness.

[0155] The present invention adopts high-performance design. It supports fast storage and retrieval of real-time data, millisecond-level response; supports real-time collection and access of data of 50,000 measurement points of at least one power plant; supports concurrent calculation of at least 200 computing tasks; for general operations on the tool software interface, the response time should be within 1 second, and for complex queries on the software, the response time should be within 3 seconds.

[0156] The present invention adopts security design. The software architecture design takes security requirements into consideration and meets the security requirements of nuclear power systems; access control: supports user identity authentication, supports the setting of user permissions, has a complete database permission control function, supports network whitelist mechanism, and can further ensure the access security of instances and data by setting the list of machines allowed to access instances; operation audit: supports auditing of all database operations; encrypted communication: supports the setting of communication and storage encryption strategies.

[0157] The present invention adopts reliability design. Data storage supports multiple copies strategy; the collection and upload process needs to ensure the integrity of data, and must have automatic retransmission and breakpoint resume functions; after the calculation task fails, it is required to automatically restart the calculation task until the calculation succeeds; the tool software supports 7*24 hours operation and is developed using mature technology.

[0158] The present invention adopts a robust design. The software architecture is easy to expand, and operation and maintenance guidance is provided through the operation and maintenance manual.

[0159] The DCS health management data warehouse provided by the present invention adopts a B / S architecture. The present invention collects, accesses, stores, processes and analyzes multi-source heterogeneous data such as DCS system data, basic equipment information, status data, maintenance data, and provides DCS-related data services to build a DCS health management data warehouse, provide data support for various application modules of DCS health management, provide data support and knowledge integration capabilities in the DCS field, provide comprehensive service support, and maintain the stability of the DCS health management platform. The DCS health management data warehouse has the functions of DCS data collection, data storage, data processing, data services, business services, etc., which facilitates the DCS health management platform and other applications to analyze and use data.

[0160] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed by the present invention should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A DCS health management data warehouse system, characterized in that: include: The data access and storage layer is used to store data related to DCS reliability from various business systems of different power plants into corresponding time series databases, relational databases, MPPs, big data storage systems or object storage components; The business logic layer is used to process DCS monitoring data, process parameter data and DCS business basic data, provide data service interface, data interaction interface, DCS domain subject library and expert knowledge base; The presentation layer displays relevant indicators of all types of data in the data warehouse in a visual way.

2. The DCS health management data warehouse system according to claim 1, characterized in that: The data related to DCS reliability in the business system include DCS monitoring data, PI system process parameter data, operation history data, structured basic data in the information system, configuration data files, design files, equipment pictures, and on-site videos.

3. The DCS health management data warehouse system according to claim 1, characterized in that: The business logic layer includes: Data acquisition module, used to collect DCS monitoring data, DCS process parameter data, DCS business basic data in real time, import DCS operation history data, DCS configuration data files, DCS design files and materials; Data storage module, used to store DCS timing data, DCS business basic data, DCS configuration data, DCS design files and information; Data processing module, used to process DCS time series data, DCS business basic data, DCS configuration data, DCS design files and information; Data service module, which is used to support file synchronization, database synchronization, and streaming data publishing methods, and provides monitoring data service interface and basic data service interface; Business service module, used to provide business system interface and build DCS subject database and expert knowledge base; Data display module, used for data comparison, data query, and data visualization management.

4. The DCS health management data warehouse system according to claim 3 is characterized in that: In the process of real-time DCS monitoring data collection, according to the DCS system control and data access strategy of each power plant, the monitoring data is accessed from the DCS system through a gateway or interface machine, and then received by the DCS monitoring data collection tool and sent and stored in the time series database.

5. The DCS health management data warehouse system according to claim 3 is characterized in that: According to the needs of production data use and planning, standardize the benchmark data and establish business-oriented subject data objects and indicators, including: Data cleaning: Improve data quality by detecting errors and inconsistencies in the data, eliminating redundant data, correcting erroneous data; Data conversion: convert according to data standard requirements; Data association: According to the business process analysis requirements, multi-table associations are performed layer by layer for data of different dimensions and categories, and the required field data is summarized; Data aggregation: Generate summary data based on business processing logic; Data dimensionalization: Dimensional modeling of basic data, extraction of dimensional or dictionary information, and provision of reference data.

6. The DCS health management data warehouse system according to claim 3, characterized in that: For DCS configuration data files, they are converted into a highly readable data format that supports visualization, and the configuration data information is quickly retrieved, and the information is extracted for analysis; for unstructured data, file annotation, content parsing and identification are performed, and feature extraction, content annotation, analysis and identification are supported.

7. The DCS health management data warehouse system according to claim 3, characterized in that: The data service module provides a monitoring data service interface in the form of a RESTful API to obtain the attribute information of a specified single or multiple measuring points; obtain the actual value of the latest timestamp of a specified single or multiple measuring points; obtain the interpolated value of a specified single or multiple measuring points at a specified time point; obtain all actual values ​​of a specified single or multiple measuring points within a specified time period; obtain the interpolated value of a specified single or multiple measuring points in a specified time period and a specified time interval; obtain the aggregate query results of a specified single or multiple measuring points within a specified time period.

8. The DCS health management data warehouse system according to claim 3, characterized in that: The DCS subject database includes equipment management, simulation risk analysis, training management, maintenance management, user center, experience feedback, and digital delivery; The expert knowledge base is used to manage offline fault handling experience, manufacturer manuals, and experience feedback information, and supports the association between storage data and business.

9. The DCS health management data warehouse system according to claim 1, characterized in that: The display layer is used to display the overall data volume, data storage capacity, business areas, distribution of data warehouse levels, distribution of source systems, and usage of data interfaces for structured data access; to display the data volume, data storage capacity, real-time data access, and data distribution of time series data access; and to display the data volume, data storage capacity, and number of files of different types for file data.

10. The DCS health management data warehouse system according to claim 1, characterized in that: Also included are DCS data tools, which include: DCS monitoring data collection tool, used to collect monitoring data from the power plant DCS system in real time and store it on the DHP platform; Process parameter data collection tool, used to collect process parameter data from the PI system in real time from the power plant and store it on the DHP platform; DCS historical data import tool, used to import the historical data files of monitoring data and process parameters in DCS into the time series database of DHP platform; File import tool, used to collect and transfer DCS-related data documents of each pilot power plant and store them in the object storage component; Configuration retrieval and analysis tools, used to quickly retrieve configuration data information and extract information for analysis; Unstructured data processing tools, used to label, parse and identify DCS data files, perform feature extraction and content labeling; Equipment configuration tools, used for access management, calculation processing and monitoring management of nuclear power equipment and its collected data; Data configuration tool, which is used to support the configuration of time series data structure and data points, and download the data points to real-time, historical databases and calculation programs. The generated time series data configuration can be used for screen configuration, algorithm configuration and access configuration in offline environment; Algorithm configuration tool, used to realize the configuration of computational analysis models for industrial time series data; The screen configuration tool is used to draw, configure, download and manage various indicator-related screens of nuclear power plants, and realize real-time information monitoring and historical information display through the Web.

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