A digital-twin-based substation noise distribution state monitoring system

Abstract

The application relates to the technical field of noise monitoring, and particularly discloses a substation noise distribution state monitoring system based on digital twinning, which comprises a digital twinning modeling and dividing module, which is used for establishing a platform model of a substation through digital twinning, dividing the platform model into multiple areas, and ensuring that each area has only one set of substation equipment; a data processing module is used for calculating corrected actual noise values in different time periods by combining information data of a data acquisition module and a data recording module, in the process, the reliability of the calculation result is improved by eliminating external interference factors after combining surrounding environment information of the substation and maintenance and repair records and overhaul information of the substation equipment, so that the noise distribution state can be accurately judged, the accuracy of noise monitoring is improved, the running state of the substation equipment can be accurately judged, and the substation equipment can be maintained in time to improve the service life.

Description

Technical Field

[0001] This invention relates to the field of noise monitoring technology, specifically to a substation noise distribution status monitoring system based on digital twins. Background Technology

[0002] A substation is a location in a power system that transforms voltage and current, receives electrical energy, and distributes it. Substations within power plants are step-up substations, whose function is to step up the voltage of the electricity generated by generators before feeding it into the high-voltage power grid. The construction and operation of substations not only help solve current energy problems but also lay a solid foundation for future sustainable development.

[0003] During the operation of a substation, the internal electrical equipment may experience abnormalities after prolonged use. These abnormalities generate significant noise. Therefore, a substation noise distribution monitoring system is used to monitor the noise levels within the substation. Based on changes in noise levels, the operating status of the electrical equipment can be determined quickly and easily.

[0004] In existing technologies, when monitoring noise in substations, since substations are usually located in relatively open outdoor areas, some external interference factors still need to be considered. These external interference factors may prevent the accurate judgment of the noise distribution, thereby reducing the accuracy of noise monitoring and making it impossible to make accurate judgments on the operating status of the substation equipment. Summary of the Invention

[0005] The purpose of this invention is to provide a substation noise distribution status monitoring system based on digital twins, solving the following technical problems:

[0006] How to improve the accuracy of noise monitoring and the accuracy of the judgment results on the operating status of power equipment.

[0007] The objective of this invention can be achieved through the following technical solutions:

[0008] A substation noise distribution status monitoring system based on digital twin, the system comprising:

[0009] The digital twin modeling and partitioning module is used to build a platform model of a substation using digital twins and divide it into multiple regions, with each region having one and only one set of substation equipment.

[0010] The data acquisition module is used to collect noise values ​​in different areas and environmental information around the substation.

[0011] The data logging module is used to record all maintenance and repair records of substation equipment, as well as inspection information;

[0012] The data processing module is used to calculate the corrected actual noise values ​​for different time periods based on the information data from the data acquisition module and the data recording module, and to judge whether the noise distribution status of different areas is qualified by combining the preset noise value threshold.

[0013] The analysis and early warning module is used to analyze the abnormal operating status of the substation equipment in a certain area when the noise distribution status of a certain area is deemed unqualified, and to issue an early warning.

[0014] Furthermore, the environmental information collected by the data acquisition module includes the current air humidity, wind speed, and rainfall, while the information recorded by the data recording module includes the maintenance frequency of different power equipment, the duration of each maintenance, the time elapsed since the last maintenance, and the number of abnormal states.

[0015] Furthermore, the processing procedure of the data processing module includes:

[0016] Through formula Calculate the corrected actual noise value in the a-th region during a single data acquisition. ;

[0017] Where 'a' represents any region in the platform model of the substation built using digital twins. Let be the monitoring noise value in the a-th region during a single data acquisition. To adjust the coefficient lookup table function, based on empirical data... The extent to which the range of numerical values ​​affects the noise level is based on test data. Let be the environmental impact coefficient for the a-th region in a single data collection. Let be the usage impact coefficient of the equipment in region a. and 2 is the weighting coefficient. This is the error influence coefficient.

[0018] Furthermore, the processing procedure of the data processing module also includes:

[0019] Corrected actual noise values ​​across all regions in a single data acquisition Compared with the preset noise threshold Perform a comparison;

[0020] If all All less than The system determines that the corrected actual noise values ​​in all areas are within acceptable levels during this data collection, which means that the operating status of the power equipment in all areas is good.

[0021] If any Greater than The system determines that the corrected actual noise values ​​in this area did not reach the qualified level during the data collection, which means that the operating status of the substation equipment in this area may be abnormal, and issues an early warning.

[0022] Furthermore, the processing procedure of the data processing module also includes:

[0023] Through formula Calculate the environmental impact coefficient for the a-th region in a single data collection. ;

[0024] in, Let be the humidity in the a-th region during a single data collection. The preset humidity, Let be the wind speed in the a-th region during a single data collection. The preset wind speed, The rainfall impact coefficient in a single data collection session is set based on empirical fitting. Let be the area of ​​the obstruction in the a-th region during a single data collection. for The standard value.

[0025] Furthermore, the processing procedure of the data processing module also includes:

[0026] Through formula Calculate the usage impact coefficient of equipment in region a. ;

[0027] in, Let be the maintenance frequency of the equipment in region a. This is the preset maintenance frequency. Let be the number of days since the last maintenance of the equipment in region a. for The standard value, Let n be the time spent on any single maintenance of the equipment, and n be the total number of maintenance operations. Let be the time spent on the i-th maintenance of equipment in region a. For all The average value, Let a be the number of abnormal states of the equipment in region a. for The standard value.

[0028] Furthermore, the early warning process of the analysis and early warning module includes:

[0029] When it is determined that the operating status of the substation equipment in the a-th area is abnormal, the operating status of the substation equipment in the adjacent areas is detected.

[0030] If the operating status of the power equipment in the adjacent areas is normal, then only the current area will be given an early warning and location.

[0031] If the operating status of the substation equipment in the adjacent area is abnormal, the corrected actual noise value in this area is compared with the corrected actual noise value in the adjacent area, and further judgment is made based on the comparison result.

[0032] Furthermore, the monitoring process of the substation noise distribution status monitoring system includes:

[0033] S1: First, a platform model of the substation is established by dividing the modules through digital twin modeling, and it is divided into multiple areas, with each area having one and only one set of substation equipment.

[0034] S2: Collect noise levels in different areas and environmental information around the substation through the data acquisition module;

[0035] S3: Records all maintenance and repair records of all substation equipment, as well as inspection information, through the data logging module;

[0036] S4: The data processing module calculates the corrected actual noise values ​​for different time periods and, in conjunction with the preset noise value threshold, judges whether the noise distribution status in different areas is qualified.

[0037] S5: When the noise distribution status of a certain area is determined to be unqualified, the analysis and early warning module analyzes the abnormal operation status of the substation equipment in that area and issues an early warning.

[0038] The beneficial effects of this invention are:

[0039] (1) The present invention calculates the corrected actual noise value for different time periods by combining the information data of the data processing module, the data acquisition module and the data recording module. In this process, by combining the environmental information around the substation and the maintenance and repair records and inspection information of the substation equipment, external interference factors can be eliminated to improve the reliability of the calculation results, thereby accurately judging the noise distribution status and improving the accuracy of noise monitoring. This enables accurate judgment of the operating status of the substation equipment and timely early warning to maintain the substation equipment and improve its service life.

[0040] (2) By combining the environmental impact coefficient and the equipment usage impact coefficient in the a-th region of a single data acquisition, the present invention can eliminate external interference factors and improve the reliability of the calculation results, thereby obtaining the corrected actual noise value in the a-th region of a single data acquisition. The system can accurately determine the noise distribution status based on the corrected actual noise value, thereby improving the accuracy of noise monitoring and enabling accurate judgment of the operating status of power equipment in the future.

[0041] (3) The present invention corrects the actual noise values ​​in all regions during a single data acquisition. Compared with the preset noise threshold By comparing the actual noise values, since the corrected actual noise values ​​have eliminated external interference factors, the reliability of the data is relatively high. Based on this comparison, it is possible to accurately determine whether the actual noise values ​​in different areas are at a qualified level, and further determine whether there are any abnormalities in the operating status of the substation equipment in different areas, thereby improving the accuracy of noise monitoring and the accuracy of the judgment results on the operating status of the substation equipment.

[0042] (4) The present invention obtains the environmental impact coefficient of the a-th region in a data acquisition by calculation. As the humidity in the air increases, the corona discharge formed by air ionization will be enhanced, which will lead to an increase in corona audible noise. When the wind speed increases, broadband noise similar to cracking sound may be generated. In addition, the size of the area of ​​the obstruction will also affect the diffusion of noise. Therefore, by combining environmental information to calculate the environmental impact coefficient of the a-th region in a data acquisition, the accuracy and reliability of the calculation of the corrected actual noise value can be improved, thereby improving the accuracy of noise monitoring. Attached Figure Description

[0043] The invention will now be further described with reference to the accompanying drawings.

[0044] Figure 1 This is a schematic block diagram of a substation noise distribution status monitoring system based on digital twins in this invention;

[0045] Figure 2 This is a flowchart of the substation noise distribution status monitoring process in this invention. Detailed Implementation

[0046] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0047] Please see Figure 1 As shown, in one embodiment, this application provides a substation noise distribution status monitoring system based on digital twin, the system comprising:

[0048] The digital twin modeling and partitioning module is used to build a platform model of a substation using digital twins and divide it into multiple regions, with each region having one and only one set of substation equipment.

[0049] The data acquisition module is used to collect noise values ​​in different areas and environmental information around the substation.

[0050] The data logging module is used to record all maintenance and repair records of substation equipment, as well as inspection information;

[0051] The data processing module is used to calculate the corrected actual noise values ​​for different time periods based on the information data from the data acquisition module and the data recording module, and to judge whether the noise distribution status of different areas is qualified by combining the preset noise value threshold.

[0052] The analysis and early warning module is used to analyze the abnormal operating status of the substation equipment in a certain area when the noise distribution status of a certain area is deemed unqualified, and to issue an early warning.

[0053] Through the above technical solution, this embodiment provides a digital twin modeling and partitioning module for establishing a platform model of a substation and dividing it into multiple areas. Each area has one and only one set of substation equipment. In daily use, the noise values ​​and environmental information of the substation surrounding area are first collected by the data acquisition module, and the maintenance and repair records and inspection information of all substation equipment are recorded and updated by the data recording module. Then, the data processing module calculates the corrected actual noise values ​​for different time periods based on the information data from the data acquisition module and the data recording module, and judges whether the noise distribution status of different areas is qualified by combining the preset noise value threshold. When the noise distribution status of a certain area is judged to be unqualified, the analysis and early warning module can analyze the abnormality of the substation equipment operation status in that area and issue an early warning.

[0054] By combining the information from the data processing module with that from the data acquisition and data recording modules, the corrected actual noise values ​​for different time periods are calculated. In this process, by incorporating information about the substation's surrounding environment, as well as maintenance and repair records and inspection information of the substation equipment, external interference factors can be eliminated, thus improving the reliability of the calculation results. This allows for an accurate assessment of the noise distribution and enhances the accuracy of noise monitoring. Consequently, it enables accurate assessment of the substation equipment's operating status, timely early warnings, and timely maintenance to extend its service life.

[0055] The environmental information collected by the data acquisition module includes the current air humidity, wind speed and rainfall. The information recorded by the data recording module includes the maintenance frequency of different power equipment, the duration of each maintenance, the time since the last maintenance and the number of abnormal states.

[0056] Through the above technical solution, this embodiment provides environmental information collected by the data acquisition module, including current air humidity, wind speed, and rainfall, as well as information recorded by the data recording module, including the maintenance frequency of different power equipment, the duration of each maintenance, the time elapsed since the last maintenance, and the number of abnormal states. By collecting diverse data, not only can the accuracy of subsequent calculation results be improved, but external interference factors can also be minimized, thereby ensuring the reliability of subsequent calculation results. This makes the corrected actual noise value obtained from the calculation closer to the true value, thus improving the accuracy of noise monitoring and the accuracy of the judgment results on the operating status of power equipment.

[0057] The data processing module's processing procedure includes:

[0058] Through formula Calculate the corrected actual noise value in the a-th region during a single data acquisition. ;

[0059] Where 'a' represents any region in the platform model of the substation built using digital twins. Let be the monitoring noise value in the a-th region during a single data acquisition. To adjust the coefficient lookup table function, based on empirical data... The extent to which the range of numerical values ​​affects the noise level is based on test data. Let be the environmental impact coefficient for the a-th region in a single data collection. Let be the usage impact coefficient of the equipment in region a. and 2 represents the weighting coefficient, which can be set based on empirical data. This is the error influence coefficient, which can be set based on empirical data fitting.

[0060] Through the above technical solution, this embodiment provides the corrected actual noise value in the a-th region during a single data acquisition. It can be done through the formula By combining the environmental impact coefficient and the equipment usage impact coefficient within the a-th region of a single data acquisition, external interference factors can be eliminated, thus improving the reliability of the calculation results and obtaining the corrected actual noise value within the a-th region of a single data acquisition. The system can accurately determine the noise distribution status based on the corrected actual noise value, thereby improving the accuracy of noise monitoring and enabling accurate judgment of the operating status of power equipment in the future.

[0061] The data processing module's processing procedure also includes:

[0062] Corrected actual noise values ​​across all regions in a single data acquisition Compared with the preset noise threshold Perform a comparison;

[0063] If all All less than The system determines that the corrected actual noise values ​​in all areas are within acceptable levels during this data collection, which means that the operating status of the power equipment in all areas is good.

[0064] If any Greater than The system determines that the corrected actual noise values ​​in this area did not reach the qualified level during the data collection, which means that the operating status of the substation equipment in this area may be abnormal, and issues an early warning.

[0065] Through the above technical solution, this embodiment corrects the actual noise values ​​in all areas during a single data acquisition. Compared with the preset noise threshold By comparing the actual noise values, since the corrected actual noise values ​​have eliminated external interference factors, the reliability of the data is relatively high. Based on this comparison, it is possible to accurately determine whether the actual noise values ​​in different areas are at a qualified level, and further determine whether there are any abnormalities in the operating status of the substation equipment in different areas, thereby improving the accuracy of noise monitoring and the accuracy of the judgment results on the operating status of the substation equipment.

[0066] The data processing module's processing procedure also includes:

[0067] Through formula Calculate the environmental impact coefficient for the a-th region in a single data collection. ;

[0068] in, Let be the humidity in the a-th region during a single data collection. The preset humidity, Let be the wind speed in the a-th region during a single data collection. The preset wind speed, The rainfall impact coefficient in a single data collection session is set based on empirical fitting. Let be the area of ​​the obstruction in the a-th region during a single data collection. for Standard value;

[0069] Through the above technical solution, this embodiment provides the environmental impact coefficient for the a-th region in a single data collection. It can be done through the formula Calculations show that increased humidity enhances corona discharge from air ionization, leading to increased audible corona noise. Increased wind speed may generate broadband noise similar to crackling sounds, and the size of obstructions also affects noise diffusion. Therefore, in a single data collection period, higher humidity and wind speed, along with larger obstruction areas, result in a higher environmental impact coefficient for region a. The larger the value, the greater the interference with the actual noise level. Conversely, the smaller the humidity and wind speed in region a during a data collection, and the smaller the area of ​​the obstruction, the greater the environmental impact coefficient in region a during a data collection. The smaller the value, the less interference it causes to the actual noise value. By setting it in this way, the environmental impact coefficient of the a-th region in a data acquisition is obtained by combining environmental information. This can improve the accuracy and reliability of the calculation of the corrected actual noise value, thereby improving the accuracy of noise monitoring.

[0070] The data processing module's processing procedure also includes:

[0071] Through formula Calculate the usage impact coefficient of equipment in region a. ;

[0072] in, Let be the maintenance frequency of the equipment in region a. This is the preset maintenance frequency. Let be the number of days since the last maintenance of the equipment in region a. for The standard value, Let n be the time spent on any single maintenance of the equipment, and n be the total number of maintenance operations. Let be the time spent on the i-th maintenance of equipment in region a. For all The average value, Let a be the number of abnormal states of the equipment in region a. for Standard value;

[0073] Through the above technical solution, this embodiment provides the usage impact coefficient of equipment in the a-th region. It can be done through the formula Calculations show that the more frequent the maintenance of equipment in region a, and the greater the number of days since the last maintenance and the more frequent the abnormal conditions, the higher the usage impact coefficient of equipment in region a. The larger the value, the more severe the aging of the equipment in that area, which may increase noise during operation. Conversely, the less frequent the maintenance of the equipment in area a, and the fewer the days since the last maintenance and the fewer the number of abnormal conditions, the lower the usage impact coefficient of the equipment in area a. The smaller the value, the less the equipment in that area is aging and the less noise it generates during operation. This setting improves the accuracy and reliability of the corrected actual noise value calculation, thereby enhancing the accuracy of noise monitoring.

[0074] The early warning process of the analysis and early warning module includes:

[0075] When it is determined that the operating status of the substation equipment in the a-th area is abnormal, the operating status of the substation equipment in the adjacent areas is detected.

[0076] If the operating status of the power equipment in the adjacent areas is normal, then only the current area will be given an early warning and location.

[0077] If the operating status of the substation equipment in the adjacent area is abnormal, the corrected actual noise value in this area is compared with the corrected actual noise value in the adjacent area, and further judgment is made based on the comparison result.

[0078] Through the above technical solution, when it is determined that the operating status of the substation equipment in the a-th area is abnormal, the operating status of the substation equipment in the adjacent areas is detected. If the operating status of the substation equipment in the adjacent areas is not abnormal, only the current area is given an early warning. If the operating status of the substation equipment in the adjacent areas is abnormal, the corrected actual noise value in this area is compared with the corrected actual noise value in the adjacent areas, and multi-level alarms are issued according to the order of the magnitude of the corrected actual noise values. By setting it up in this way, when the noise distribution status of a certain area is determined to be unqualified, the abnormality of the operating status of the substation equipment in that area can be analyzed and different levels of alarms can be issued. This allows maintenance personnel to make priority maintenance decisions based on different levels of alarms, thereby facilitating the maintenance work.

[0079] Please see Figure 2 As shown, the monitoring process of the substation noise distribution status monitoring system includes:

[0080] S1: First, a platform model of the substation is established by dividing the modules through digital twin modeling, and it is divided into multiple areas, with each area having one and only one set of substation equipment.

[0081] S2: Collect noise levels in different areas and environmental information around the substation through the data acquisition module;

[0082] S3: Records all maintenance and repair records of all substation equipment, as well as inspection information, through the data logging module;

[0083] S4: The data processing module calculates the corrected actual noise values ​​for different time periods and, in conjunction with the preset noise value threshold, judges whether the noise distribution status in different areas is qualified.

[0084] S5: When the noise distribution status of a certain area is determined to be unqualified, the analysis and early warning module analyzes the abnormal operation status of the substation equipment in that area and issues an early warning.

[0085] Through the above technical solution, this embodiment provides the monitoring process of a substation noise distribution status monitoring system. First, a platform model of the substation is established through a digital twin modeling and partitioning module, and it is divided into multiple areas, with each area having one and only one set of substation equipment. Then, the noise values ​​in different areas and the surrounding environment information of the substation are collected through a data acquisition module, and the maintenance and repair records and inspection information of all substation equipment are recorded through a data recording module. Afterwards, the corrected actual noise values ​​for different time periods are calculated through a data processing module, and combined with a preset noise value threshold, the noise distribution status of different areas is judged to be qualified. When the noise distribution status of a certain area is judged to be unqualified, the analysis and early warning module analyzes the abnormality of the substation equipment operation status in that area and issues an early warning.

[0086] By combining the data from the data processing module with the data acquisition and recording modules, the corrected actual noise values ​​for different time periods are calculated. In this process, by incorporating information about the substation's surrounding environment, maintenance records, and inspection information of the substation equipment, external interference factors can be eliminated, thus improving the reliability of the calculation results. This allows for an accurate assessment of the noise distribution and enhances the accuracy of noise monitoring. Consequently, it enables accurate assessment of the substation equipment's operating status, timely early warnings, and timely maintenance to extend its service life.

[0087] The foregoing has provided a detailed description of one embodiment of the present invention, but this description is merely a preferred embodiment and should not be construed as limiting the scope of the invention. All equivalent variations and modifications made within the scope of the claims of this invention should still fall within the patent coverage of this invention.

Claims

1. A substation noise distribution status monitoring system based on digital twin, characterized in that, The system includes: The digital twin modeling and partitioning module is used to build a platform model of a substation using digital twins and divide it into multiple regions, with each region having one and only one set of substation equipment. The data acquisition module is used to collect noise values ​​in different areas and environmental information around the substation. The data logging module is used to record all maintenance and repair records of substation equipment, as well as inspection information; The data processing module is used to calculate the corrected actual noise values ​​for different time periods based on the information data from the data acquisition module and the data recording module, and to judge whether the noise distribution status of different areas is qualified by combining the preset noise value threshold. The analysis and early warning module is used to analyze the abnormal operating status of the substation equipment in a certain area when the noise distribution status of a certain area is deemed unqualified, and to issue an early warning. The data processing module's processing procedure includes: Through formula Calculate the corrected actual noise value in the a-th region during a single data acquisition. ; Where 'a' represents any region in the platform model of the substation built using digital twins. Let be the monitoring noise value in the a-th region during a single data acquisition. To adjust the coefficient lookup table function, based on empirical data... The extent to which the range of numerical values ​​affects the noise level is based on test data. Let be the environmental impact coefficient for the a-th region in a single data collection. Let be the usage impact coefficient of the equipment in region a. and 2 is the weighting coefficient. This is the error influence coefficient.

2. The substation noise distribution status monitoring system based on digital twin according to claim 1, characterized in that, The environmental information collected by the data acquisition module includes the current air humidity, wind speed, and rainfall. The information recorded by the data recording module includes the maintenance frequency of different power equipment, the duration of each maintenance, the time elapsed since the last maintenance, and the number of abnormal states.

3. The substation noise distribution status monitoring system based on digital twin according to claim 1, characterized in that, The data processing module's processing procedure also includes: Corrected actual noise values ​​across all regions in a single data acquisition Compared with the preset noise threshold Perform a comparison; If all All less than The system determines that the corrected actual noise values ​​in all areas are within acceptable levels during this data collection, which means that the operating status of the power equipment in all areas is good. If any Greater than The system determines that the corrected actual noise values ​​in this area did not reach the qualified level during the data collection, which means that the operating status of the substation equipment in this area may be abnormal, and issues an early warning.

4. The substation noise distribution status monitoring system based on digital twin according to claim 3, characterized in that, The data processing module's processing procedure also includes: Through formula Calculate the environmental impact coefficient for the a-th region in a single data collection. ; in, Let be the humidity in the a-th region during a single data collection. The preset humidity, Let be the wind speed in the a-th region during a single data collection. The preset wind speed, The rainfall impact coefficient in a single data collection session is set based on empirical fitting. Let be the area of ​​the obstruction in the a-th region during a single data collection. for The standard value.

5. A substation noise distribution monitoring system based on digital twin according to claim 4, characterized in that, The data processing module's processing procedure also includes: Through formula Calculate the usage impact coefficient of equipment in region a. ; in, Let be the maintenance frequency of the equipment in the a-th region. This is the preset maintenance frequency. Let be the number of days since the last maintenance of the equipment in region a. for The standard value, Let n be the time spent on any single maintenance of the equipment, and n be the total number of maintenance operations. Let be the time spent on the i-th maintenance of equipment in region a. For all The average value, Let a be the number of abnormal states of the equipment in region a. for The standard value.

6. The substation noise distribution status monitoring system based on digital twin according to claim 1, characterized in that, The early warning process of the analysis and early warning module includes: When it is determined that the operating status of the substation equipment in the a-th area is abnormal, the operating status of the substation equipment in the adjacent areas is detected. If the operating status of the power equipment in the adjacent areas is normal, then only the current area will be given an early warning and location. If the operating status of the substation equipment in the adjacent area is abnormal, the corrected actual noise value in this area is compared with the corrected actual noise value in the adjacent area, and further judgment is made based on the comparison result.

7. A substation noise distribution monitoring system based on digital twin according to claim 1, characterized in that, The monitoring process of the substation noise distribution status monitoring system includes: S1: First, a platform model of the substation is established by dividing the modules through digital twin modeling, and it is divided into multiple areas, with each area having one and only one set of substation equipment. S2: Collect noise levels in different areas and environmental information around the substation through the data acquisition module; S3: Records all maintenance and repair records of all substation equipment, as well as inspection information, through the data logging module; S4: The data processing module calculates the corrected actual noise values ​​for different time periods and, in conjunction with the preset noise value threshold, judges whether the noise distribution status in different areas is qualified. S5: When the noise distribution status of a certain area is determined to be unqualified, the analysis and early warning module analyzes the abnormal operation status of the substation equipment in that area and issues an early warning.

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