Nuclear power plant equipment data difference contrastive analysis method

Abstract

The invention belongs to the technical field of nuclear power plant equipment data processing, and particularly relates to a nuclear power plant equipment data difference comparative analysis method. Comprising the following steps: step 1, checking data integrity; 2, analyzing a comparison result; step 3, processing inconsistent data; 4, data exception processing; 5, data difference analysis is carried out; and step 6, generating a result report. The method has the advantages that compared with a traditional Excel data comparison method, the effectiveness and timeliness of data cannot be guaranteed; and through the structured processing of the data and then through the modes of extraction, comparison, analysis and arrangement, the abnormity of the data in the transmission process can be quickly found, and the data can be timely processed, so that the field working efficiency is greatly improved.

Description

Technical Field

[0001] The invention belongs to the technical field of nuclear power plant equipment data processing, and in particular relates to a method for comparing and analyzing differences in nuclear power plant equipment data. Background Art

[0002] The production management system and the enterprise asset management system play an increasingly important role in the operation of nuclear power plants. The production management system is mainly responsible for monitoring the production process, optimizing the allocation of production resources, and ensuring production efficiency and product quality; while the enterprise asset management system focuses on the tracking and management of equipment and assets to achieve the reasonable allocation and efficient use of assets. As the most important component of the operation of a nuclear power plant, the equipment is managed by the enterprise asset management system and serves the production management system. The accuracy and consistency of equipment data between the two systems are particularly important, which is of great significance to ensure the smooth operation of nuclear power plant production. Due to the lack of effective tools to verify and compare the data consistency between systems, it can only be temporarily handled when encountered in actual work, which is extremely inconvenient for production work.

[0003] To ensure the accuracy of data comparison, it is necessary to first extract the corresponding equipment data from the production management system and the enterprise asset management system. This includes but is not limited to the equipment name, model, specification, production date, commissioning date, usage status, maintenance records, etc. Data is extracted through the API interface of the production management system and the enterprise asset management system to ensure the integrity and accuracy of the data. Summary of the invention

[0004] The purpose of the present invention is to provide a method for comparing and analyzing differences in nuclear power plant equipment data, which is used to ensure the validity and uniformity of equipment data between the production system and the enterprise asset management system, so as to enable the smooth implementation of work steps, work instructions, isolation errors, risk analysis and other work in the production process, operation and maintenance work.

[0005] The technical solution of the present invention is as follows: A method for comparing and analyzing differences in nuclear power plant equipment data, comprising the following steps:

[0006] Step 1: Data integrity check;

[0007] Step 2: Comparison result analysis;

[0008] Step 3: Inconsistent data processing;

[0009] Step 4: Data exception processing;

[0010] Step 5: Data difference analysis;

[0011] Step 6: Generate result report.

[0012] The step 1 includes developing a standard template based on important equipment-related data, ensuring that the data is not missed or damaged through data cleaning, and writing a data comparison script as a data comparison tool to compare the equipment data in the production management system and the enterprise asset management system item by item.

[0013] The step 1 includes recording the data differences during the comparison process and classifying them into data inconsistency, data missing, and data errors. At the same time, the corresponding to-do items are triggered to the person responsible for the equipment through the unified to-do platform and notified by email.

[0014] The step 1 includes unifying the data format, including standardizing the coding, unit, and format of the data. The equipment coding is unified with the unit + system code + equipment code as the unique verification code; the equipment classification is unified as S key level 1 equipment, A key level 2 equipment, B important level, and C general level; ensuring that the data can be correctly compared and analyzed.

[0015] The step 2 includes the following:

[0016] Step 21: Data Extraction

[0017] Collect all tables or views in the data source and convert them into a recognizable format. Match them according to the unique code of the equipment, and then check the consistency of the equipment information. The specific check fields include power plant, unit, system, equipment type, equipment code, component type, component code, name, design, maintenance, status, revision tracking, structure, elevation, room number, column, area, specialty, notification group, equipment classification, safety level, seismic level, Q level, model, manufacturer, serial number, containment isolation boundary, containment integrity, relevant technical specifications, RWP license, specification level, warranty level, whether it is related to environmental qualification, environmental qualification remarks, CLEARANCE, E01PSA equipment, E02 equipment jurisdiction department, a total of 37 business fields;

[0018] Step 22: Data Preprocessing

[0019] After acquiring the data, pre-process the data according to the actual situation of the two systems. Some fields need to match and convert the code and description, such as status, profession, notification group, equipment classification, safety level, and earthquake resistance level fields. Some fields need to query the third-party database to obtain specific data to avoid the situation of multiple codes for one name, such as manufacturer and serial number fields. Some fields need to be intercepted and segmented, such as equipment code and component code.

[0020] Step 23: Data Verification

[0021] Merge the single device data to calculate the hash value, filter out the difference data, then take out the filtered difference device data, and then compare the fields one by one to filter out the specific difference fields.

[0022] The step 3 includes taking corresponding processing measures for inconsistent data found in the comparison results. For obvious input errors or untimely data updates, the data is directly corrected or updated according to the enterprise asset management system data; for data synchronization issues between systems, the data synchronization mechanism is optimized.

[0023] The step 4 includes cleaning, correcting or deleting abnormal data during the data comparison process to ensure the accuracy and credibility of the data.

[0024] The step 5 includes data difference analysis, including qualitative and quantitative analysis of the data differences.

[0025] The step 6 includes, after completing steps 1-5, executing a standard report template through a toolkit provided by the programming language to generate a data comparison result report.

[0026] The report includes the process, method, results and conclusions of the data comparison, and explains and analyzes the data differences.

[0027] The beneficial effect of the present invention is that compared with the traditional Excel data comparison method, the validity and timeliness of the data cannot be guaranteed; by structuring the data and then extracting, comparing, analyzing and collating the data, the abnormalities in the data transmission process can be quickly discovered and processed in time, which greatly improves the on-site work efficiency. DETAILED DESCRIPTION

[0028] The present invention is further described in detail below with reference to specific embodiments.

[0029] A method for comparing and analyzing differences in nuclear power plant equipment data, which forms a comparison model by dynamically configuring equipment attributes and automatically establishing a mapping relationship according to the attributes of two system equipment, specifically includes the following steps:

[0030] Step 1: Data integrity check

[0031] First of all, it is important to clarify that the three data items, namely equipment code, equipment classification and safety level, need to be compared.

[0032] Before comparison, the data needs to be checked for integrity, a standard template is developed based on the important data related to the equipment, and data cleaning is performed to ensure that the data is not missed or damaged. This ensures the integrity and credibility of the data.

[0033] Next, by writing a data comparison script as a data comparison tool, the equipment data in the production management system and the enterprise asset management system are compared item by item.

[0034] During the comparison process, the data differences need to be recorded and classified into categories such as inconsistent data, missing data, and data errors. At the same time, the corresponding to-do items are triggered through the unified to-do platform to the equipment responsible person, and an email is sent to notify him. Since different devices or systems may use different data formats, the data format needs to be unified before data comparison. As shown in Table 1, the data coding, unit, format, etc. are standardized. The equipment coding is unified with the unit + system code + equipment code as the only check code; the equipment classification is unified into S key level 1 equipment, A key level 2 equipment, B important level, and C general level; to ensure that the data can be correctly compared and analyzed.

[0035] Table 1 Important attributes of equipment

[0036]

[0037]

[0038] Step 2: Comparison results analysis

[0039] Comparison result analysis is the process of conducting in-depth research on the data differences found during the comparison process. By analyzing the difference data, the reasons for the data inconsistency can be found out. The specific implementation is as follows:

[0040] Step 21: Data Extraction

[0041] The unique code of equipment data is stored in both the EAM system and the ERP system. Since the databases of the two systems are not interoperable, it is necessary to extract data from the databases of the two systems through a program, collect all the tables or views in the data source, and convert them into a recognizable format. Match according to the unique code of the equipment, and then check the consistency of the equipment information. The specific check fields are power plant, unit, system, equipment type, equipment code, component type, component code, name, design, maintenance, status, revision tracking, structure, elevation, room number, column, area, specialty, notification group, equipment classification, safety level, seismic level, Q level, model, manufacturer, serial number, containment isolation boundary, containment integrity, relevant technical specifications, RWP license, specification level, warranty level, whether it is related to environmental qualification, environmental qualification remarks, CLEARANCE, E01PSA equipment, E02 equipment jurisdiction office, a total of 37 business fields.

[0042] Step 22: Data Preprocessing

[0043] After acquiring the data, the data is preprocessed. Due to the differences in the data format and form stored between the two systems, the data needs to be preprocessed according to the actual situation of the two systems. Some fields need to match and convert the code and description, such as status, major, notification group, equipment classification, safety level, and earthquake resistance level fields. Some fields need to query the third-party database to obtain specific data to avoid the situation of multiple codes for one name, such as manufacturer and serial number fields. Some fields need to be intercepted and split, such as equipment code and component code. It is also necessary to exclude the fields actually enabled by the two systems at the business level. After the data is preprocessed, the data of the two systems are unified in format and form to facilitate subsequent proofreading.

[0044] Step 23: Data Verification

[0045] Merge and calculate the hash value of a single device data, quickly filter out the difference data, then take out the filtered difference device data, and then compare the fields one by one to filter out the specific difference fields. Combining quick filtering with detailed filtering can significantly improve the efficiency of data proofreading.

[0046] Such as system input errors, untimely data updates, data synchronization issues between systems, etc. Input errors can be checked according to field rules, such as date format and code naming not in accordance with requirements; untimely data updates can be judged by the production management system timestamp being greater than the enterprise asset management system timestamp; synchronization issues can be queried through the abnormal result log returned by the system interface. In addition, the impact of inconsistent data on production management and asset management can be analyzed to provide a basis for subsequent data processing.

[0047] Step 3: Inconsistent data handling

[0048] For inconsistent data found in the comparison results, corresponding processing measures need to be taken. For obvious input errors or untimely data updates, data can be directly corrected or updated based on the enterprise asset management system data; for data synchronization issues between systems, it is necessary to optimize the data synchronization mechanism, such as checking whether data extraction adds threads, whether there will be deadlocks, or using incremental synchronization and parallel processing to optimize the data synchronization function to ensure data consistency between the two systems.

[0049] Step 4: Data anomaly handling

[0050] During the data comparison process, some abnormal data may be found, such as incomplete equipment coding, missing required fields such as equipment classification, etc. These abnormal data need to be processed to eliminate their impact on the data comparison results. This includes cleaning, correcting or deleting abnormal data to ensure the accuracy and credibility of the data.

[0051] Step 5: Data Difference Analysis

[0052] Data difference analysis is an in-depth analysis of the data comparison results. In this stage, it is necessary to analyze the data differences in detail (how to analyze them specifically) to find out the causes and influencing factors of the differences. This includes qualitative and quantitative analysis of data differences to facilitate subsequent result report generation and decision making.

[0053] Step 6: Generate result report

[0054] After completing the above steps, use the toolkit provided by the programming language to execute the standard report template and generate a data comparison result report. The report should include the process, method, results and conclusions of the data comparison, and focus on explaining and analyzing the data differences. The report should present the data comparison results in a clear and concise manner so that relevant personnel can read and understand them. At the same time, the report should also put forward targeted suggestions and improvement measures to improve the quality and reliability of the data.

Claims

1. A method for comparing and analyzing differences in nuclear power plant equipment data, characterized in that: The steps include: Step 1: Data integrity check; Step 2: Comparison result analysis; Step 3: Inconsistent data processing; Step 4: Data exception processing; Step 5: Data difference analysis; Step 6: Generate result report.

2. A method for comparing and analyzing differences in nuclear power plant equipment data according to claim 1, characterized in that: The step 1 includes developing a standard template based on important equipment-related data, ensuring that the data is not missed or damaged through data cleaning, and writing a data comparison script as a data comparison tool to compare the equipment data in the production management system and the enterprise asset management system item by item.

3. A method for comparing and analyzing differences in nuclear power plant equipment data as claimed in claim 2, characterized in that: The step 1 includes recording the data differences during the comparison process and classifying them into data inconsistency, data missing, and data errors. At the same time, the corresponding to-do items are triggered to the person responsible for the equipment through the unified to-do platform and notified by email.

4. A method for comparing and analyzing differences in nuclear power plant equipment data as claimed in claim 2, characterized in that: The step 1 includes unifying the data format, including standardizing the coding, unit, and format of the data. The equipment coding is unified with the unit + system code + equipment code as the unique verification code; the equipment classification is unified as S key level 1 equipment, A key level 2 equipment, B important level, and C general level; ensuring that the data can be correctly compared and analyzed.

5. A method for comparing and analyzing differences in nuclear power plant equipment data as claimed in claim 1, characterized in that: The step 2 includes the following: Step 21: Data Extraction Collect all tables or views in the data source and convert them into a recognizable format. Match them according to the unique code of the equipment, and then check the consistency of the equipment information. The specific check fields include power plant, unit, system, equipment type, equipment code, component type, component code, name, design, maintenance, status, revision tracking, structure, elevation, room number, column, area, specialty, notification group, equipment classification, safety level, seismic level, Q level, model, manufacturer, serial number, containment isolation boundary, containment integrity, relevant technical specifications, RWP license, specification level, warranty level, whether it is related to environmental qualification, environmental qualification remarks, CLEARANCE, E01PSA equipment, E02 equipment jurisdiction department, a total of 37 business fields; Step 22: Data Preprocessing After acquiring the data, pre-process the data according to the actual situation of the two systems. Some fields need to match and convert the code and description, such as status, profession, notification group, equipment classification, safety level, and earthquake resistance level fields. Some fields need to query the third-party database to obtain specific data to avoid the situation of multiple codes for one name, such as manufacturer and serial number fields. Some fields need to be intercepted and segmented, such as equipment code and component code. Step 23: Data Verification Merge the single device data to calculate the hash value, filter out the difference data, then take out the filtered difference device data, and then compare the fields one by one to filter out the specific difference fields.

6. A method for comparing and analyzing differences in nuclear power plant equipment data according to claim 1, characterized in that: The step 3 includes taking corresponding processing measures for inconsistent data found in the comparison results. For obvious input errors or untimely data updates, the data is directly corrected or updated according to the enterprise asset management system data; for data synchronization issues between systems, the data synchronization mechanism is optimized.

7. A method for comparing and analyzing differences in nuclear power plant equipment data according to claim 1, characterized in that: The step 4 includes cleaning, correcting or deleting abnormal data during the data comparison process to ensure the accuracy and credibility of the data.

8. A method for comparing and analyzing differences in nuclear power plant equipment data as claimed in claim 1, characterized in that: The step 5 includes data difference analysis, including qualitative and quantitative analysis of the data differences.

9. A method for comparing and analyzing differences in nuclear power plant equipment data as claimed in claim 1, characterized in that: The step 6 includes, after completing steps 1-5, executing a standard report template through a toolkit provided by the programming language to generate a data comparison result report.

10. A method for comparing and analyzing differences in nuclear power plant equipment data according to claim 9, characterized in that: The report includes the process, method, results and conclusions of the data comparison, and explains and analyzes the data differences.

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