GIS equipment wireless sensing monitoring system based on edge calculation

Abstract

The invention discloses a GIS equipment wireless sensing monitoring system based on edge computing, and relates to the technical field of GIS equipment intelligent monitoring, the system collects the operation parameters of gas insulated switchgear in real time through an integrated sensor group and a monitor, preprocesses the data, locally computes and analyzes the preprocessed data, and obtains the real-time monitoring result of the GIS equipment. The method comprises the following steps: acquiring a gas quality index Qpz, a gas state dynamic index Qdz and an insulation state dynamic index Jzz, carrying out nondimensionalization on the indexes, calculating to obtain an equipment stability index SWDZ, comparing a preset threshold value with the dynamic indexes, providing primary and secondary evaluation, generating early warning information, and carrying out graphical display through an equipment operation state and an analysis result. Real-time data, historical trends and early warning information are provided, and a user is helped to identify problems and take measures; according to the system, real-time monitoring and fault early warning of the gas insulated switchgear can be realized, and the operation safety and reliability of the switchgear are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of GIS equipment intelligent monitoring, and in particular to a GIS equipment wireless sensor monitoring system based on edge computing. Background Art

[0002] In modern high-voltage power transmission systems, gas-insulated switchgear (GIS) has become the first choice for many power companies due to its high reliability, compactness and low maintenance requirements. GIS equipment uses gas as the insulating medium, replacing the traditional air or oil medium, which greatly improves the insulation performance and operation stability of the equipment. As a key equipment for high-voltage power transmission systems, GIS plays a vital role in power systems. However, with the continuous development and complexity of power systems, higher requirements are placed on the monitoring and maintenance of GIS equipment.

[0003] At present, the traditional gas-insulated switchgear GIS also has some shortcomings and potential problems in the operation process. Due to the closed nature of the gas-insulated switchgear GIS, its internal operating status is difficult to monitor in real time, especially the quality and state changes of the insulating gas, which often rely on regular manual inspection and maintenance. This traditional monitoring method is not only inefficient, but may also lead to the failure to discover hidden faults in time, thereby affecting the stable operation of the equipment. In addition, the existing monitoring systems generally lack intelligent and automated functions, and cannot comprehensively analyze and evaluate complex operating parameters, thereby limiting the accuracy of fault warning and status assessment. Summary of the invention

[0004] In view of the shortcomings of the prior art, the present invention provides a wireless sensor monitoring system for GIS equipment based on edge computing, which solves the problems mentioned in the background technology.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: a wireless sensor monitoring system for GIS equipment based on edge computing, including a data acquisition module, an edge computing module, a comprehensive analysis module, a monitoring and early warning module, and a visualization module;

[0006] The data acquisition module is used to install a sensor group and a monitor on the gas-insulated switchgear, collect the operating parameters of the gas-insulated switchgear in real time, and pre-process the acquired parameters;

[0007] The edge computing module is used to receive sensor data and use the processing power of edge computing to perform calculations and analyses locally to obtain the gas quality index Qpz, the gas state dynamic index Qdz and the insulation state dynamic index Jzz;

[0008] The comprehensive evaluation module is used to correlate the obtained gas quality index Qpz, gas state dynamic index Qdz and insulation state dynamic index Jzz to obtain the equipment stability index SWDZ;

[0009] The monitoring and early warning module is used to perform a preliminary evaluation based on the historical standard insulation state interval of the gas-insulated switchgear operation, the preset insulation state dynamic evaluation threshold A and the obtained insulation state dynamic index Jzz, perform an initial adjustment on the equipment according to the evaluation result, and start a second evaluation mechanism, the second evaluation mechanism is used to compare and evaluate the preset first equipment stability threshold M and the preset second equipment stability threshold N with the obtained equipment stability index SWDZ, and generate early warning information according to the evaluation result;

[0010] The visualization module is used to present the operating status and analysis results of the gas-insulated switchgear in a graphical manner, provide real-time data display, historical data trend analysis, early warning information display and equipment stability index display, intuitively understand the operating status of the equipment, identify potential problems, and take corresponding measures in a timely manner.

[0011] Preferably, the data acquisition module includes a data acquisition unit and a data preprocessing unit;

[0012] The data acquisition unit is used to collect the operation data of the gas-insulated switchgear in real time from the integrated sensor group and monitor installed in the gas-insulated switchgear, and classify and summarize to generate a gas quality data group, a gas state data group and an insulation state data group; the integrated sensor group includes a pressure sensor, a temperature sensor, a gas density sensor, a humidity sensor, a corona discharge intensity sensor, a gas particle sensor, a light scattering sensor and a sound velocity sensor; the monitor includes a gas composition analyzer, an insulation resistance tester and a leakage detector;

[0013] The gas pressure P is obtained by a pressure sensor;

[0014] The gas temperature T is obtained through the temperature sensor;

[0015] The gas density ρ is obtained through a gas density sensor;

[0016] Humidity H is obtained through a humidity sensor;

[0017] Insulating gas composition C i Obtained through a gas composition analyzer;

[0018] The insulation resistance R is obtained by an insulation resistance tester;

[0019] The corona discharge intensity D is obtained by a corona discharge intensity sensor;

[0020] The gas leakage rate L is obtained through a leak detector;

[0021] The gas particle concentration wl is measured by a gas particle sensor;

[0022] The gas light scattering coefficient S is measured by a light scattering sensor;

[0023] The gas sound velocity C is measured by a sound velocity sensor;

[0024] The data preprocessing unit is used to perform preliminary data noise filtering, data cleaning, outlier detection, correction and dimensionless processing on the insulation state data group, the gas quality data group and the gas state data group through the edge node, and convert the data format to obtain the insulation state data set, the gas quality data set and the gas state data set;

[0025] The insulation status data set includes corona discharge intensity D, insulation resistance R and gas leakage rate L;

[0026] The gas quality data set includes gas particle concentration wl, gas light scattering coefficient S and gas sound velocity C;

[0027] The gas state data set includes gas pressure P, gas temperature T, humidity H, gas density ρ and insulating gas composition C i ;

[0028] The preprocessed data is transmitted to the edge computing module via the wireless network.

[0029] Preferably, the edge computing module includes an insulation state analysis unit, a gas quality analysis unit and a gas state analysis unit;

[0030] The insulation state analysis unit is used to perform dimensionless processing on the obtained insulation state data set, and then perform analysis and calculation to obtain the insulation state dynamic index Jzz;

[0031] The insulation state dynamic index Jzz is obtained by the following formula:

[0032]

[0033] Where k represents the correction constant and ln represents the logarithmic function.

[0034] Preferably, the gas quality analysis unit is used to perform dimensionless processing on the acquired gas quality data set, and then perform analysis and calculation to obtain the gas quality index Qpz;

[0035] The gas quality index Qpz is obtained by the following formula:

[0036]

[0037] Wherein, ln represents the logarithmic function.

[0038] Preferably, the gas state analysis unit is used to perform dimensionless processing on the acquired gas state data set, and then perform analysis and calculation to obtain the gas state dynamic index Qdz;

[0039] The gas state dynamic index Qdz is obtained by the following formula:

[0040]

[0041] In the formula, ln represents the logarithmic function, ∑ i ln(1+C i ) represents the insulating gas composition C i The logarithm sum of each component, e represents the exponential function, e H It means that the effect of humidity on the gas state is exponential.

[0042] Preferably, the comprehensive analysis module is used to perform dimensionless processing on the obtained gas quality index Qpz, gas state dynamic index Qdz and insulation state dynamic index Jzz, and then perform summary calculation to obtain the equipment stability index SWDZ;

[0043] The equipment stability index SWDZ is obtained by the following formula:

[0044]

[0045] Wherein, log represents the logarithmic function.

[0046] Preferably, the monitoring and early warning module includes a first early warning unit and a second early warning unit;

[0047] The first early warning unit is used to compare and analyze the insulation state dynamic index Jzz with the preset insulation state dynamic assessment threshold A to determine whether the current insulation state of the gas insulated switchgear is normal. The specific assessment scheme is as follows;

[0048] When the insulation state dynamic index Jzz> the preset insulation state dynamic assessment threshold A, it means that the insulation state is normal;

[0049] When the insulation state dynamic index Jzz≤the preset insulation state dynamic assessment threshold A, it indicates that the insulation state is abnormal, and the first warning signal is obtained. At this time, the secondary assessment mechanism is executed.

[0050] Preferably, the second early warning unit presets the first equipment stability threshold M and the second equipment stability threshold N based on the upper limit and the lower limit of the historical gas-insulated switchgear stability index, and then performs a secondary comparative evaluation with the obtained equipment stability index SWDZ to analyze the stability of the current gas-insulated switchgear during operation. The specific evaluation scheme is as follows;

[0051] When the equipment stability index SWDZ> the first equipment stability threshold M, it means that the gas stability inside the equipment is normal and there is no need to detect the insulating gas;

[0052] When the second equipment stability threshold N≤equipment stability index SWDZ≤first equipment stability threshold M, it indicates that the equipment has a potential failure risk, and a second warning signal is obtained;

[0053] The equipment stability index SWDZ is less than the second equipment stability threshold N, indicating that the equipment stability is in a dangerous state, and a third warning signal is obtained.

[0054] Preferably, the monitoring and early warning module is used to receive a first early warning signal, a second early warning signal and a third early warning signal;

[0055] When receiving the first warning signal, notify the relevant staff to shut down the equipment, check the corona discharge of each part of the equipment, measure the insulation resistance and replace the contaminated or aged insulation parts, repair the gas leakage point, and ensure the gas pressure in the gas-insulated switchgear is normal;

[0056] When receiving the second warning signal, notify relevant staff to detect the insulating gas in the equipment;

[0057] When the third warning signal is received, the relevant staff will be notified to immediately shut down the equipment, conduct a comprehensive internal inspection and test, replace the insulating gas in the gas-insulated switchgear and conduct an electrical performance test.

[0058] Preferably, the visualization module includes a data identification unit, a data storage unit and a data aggregation unit;

[0059] The data storage unit is used to store the data and analysis results processed by the edge computing module and the comprehensive analysis module in a local database;

[0060] The data identification unit is used to distinguish normal data from risk data, and forward risk and abnormal data to the cloud or central server for further analysis and long-term storage;

[0061] The data summary unit is used to summarize the operating status and analysis results of the gas-insulated switchgear, present them in a graphical form, and synchronize the summarized charts to the cloud or central server, providing real-time data display, historical data trend analysis, early warning information display and equipment stability index display functions, so that users can intuitively understand the operating status of the equipment, identify potential problems, and take corresponding measures in a timely manner;

[0062] Display the changing trend of historical data through line charts and bar charts to help users identify potential problems and failure trends;

[0063] Different levels of warning information are displayed through eye-catching colors and icons to ensure that relevant staff pay attention and handle them in a timely manner;

[0064] Displays the real-time value and historical changes of the equipment stability index SWDZ, compares it with the preset threshold, and provides a detailed analysis report.

[0065] The present invention provides a wireless sensor monitoring system for GIS equipment based on edge computing. It has the following beneficial effects:

[0066] (1) The GIS equipment wireless sensor monitoring system based on edge computing realizes comprehensive real-time monitoring and analysis of gas-insulated switchgear. The system can collect and pre-process various operating parameters of gas-insulated equipment in real time, and use edge computing technology to perform data analysis locally to obtain the gas quality index Qpz, gas state dynamic index Qdz and insulation state dynamic index Jzz. This localized processing greatly reduces data transmission delays, improves the timeliness and accuracy of monitoring, and provides a scientific basis for the stability and safety of the equipment.

[0067] (2) The edge computing-based GIS equipment wireless sensor monitoring system obtains the equipment stability index by converting the gas quality index, gas state dynamic index and insulation state dynamic index into dimensionless ones and then summarizing them. This comprehensive analysis not only improves the overall understanding of the equipment operation status, but also realizes accurate stability assessment. The monitoring and early warning module conducts preliminary and secondary assessments of the equipment status through the set threshold mechanism, and can issue early warning signals in a timely manner. Compared with traditional equipment monitoring methods, this system provides a more comprehensive and detailed fault early warning method through a multi-level early warning mechanism, which significantly improves the prevention capability and handling efficiency of equipment failures.

[0068] (3) The edge computing-based GIS equipment wireless sensor monitoring system optimizes the data processing process and improves the response speed by performing real-time data analysis on the edge computing nodes. In addition, the system's visualization module graphically displays the equipment operating status, historical data trends, and warning information, allowing users to intuitively understand the equipment status and potential problems, making it easier to take timely measures. These improvements not only enhance the ability to monitor the equipment operating status, but also improve the efficiency and accuracy of equipment maintenance. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] Figure 1 It is a schematic diagram of the process of the wireless sensor monitoring system for GIS equipment based on edge computing of the present invention. DETAILED DESCRIPTION

[0070] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0071] Example 1

[0072] See also Figure 1 , the present invention provides a GIS equipment wireless sensor monitoring system based on edge computing. To achieve the above purpose, the present invention is implemented through the following technical solutions: including a data acquisition module, an edge computing module, a comprehensive analysis module, a monitoring and early warning module and a visualization module;

[0073] The data acquisition module is used to install a sensor group and a monitor on the gas-insulated switchgear, collect the operating parameters of the gas-insulated switchgear in real time, and pre-process the acquired parameters;

[0074] The edge computing module is used to receive sensor data and use the processing power of edge computing to perform calculations and analyses locally to obtain the gas quality index Qpz, the gas state dynamic index Qdz and the insulation state dynamic index Jzz;

[0075] The comprehensive evaluation module is used to correlate the obtained gas quality index Qpz, gas state dynamic index Qdz and insulation state dynamic index Jzz to obtain the equipment stability index SWDZ;

[0076] The monitoring and early warning module is used to perform a preliminary evaluation based on the historical standard insulation state interval of the gas-insulated switchgear operation, the preset insulation state dynamic evaluation threshold A and the obtained insulation state dynamic index Jzz, perform an initial adjustment on the equipment according to the evaluation result, and start a second evaluation mechanism, the second evaluation mechanism is used to compare and evaluate the preset first equipment stability threshold M and the preset second equipment stability threshold N with the obtained equipment stability index SWDZ, and generate early warning information according to the evaluation result;

[0077] The visualization module is used to present the operating status and analysis results of the gas-insulated switchgear in a graphical manner, provide real-time data display, historical data trend analysis, early warning information display and equipment stability index display, intuitively understand the operating status of the equipment, identify potential problems, and take corresponding measures in a timely manner.

[0078] In this embodiment, the wireless sensor monitoring system for GIS equipment based on edge computing realizes comprehensive, real-time and efficient monitoring and management through the collaborative work of its five modules; the data acquisition module can collect equipment operating parameters in real time and perform preprocessing through the sensor group and monitor installed on the gas insulated switchgear to ensure the accuracy and consistency of the data; the edge computing module uses local computing power to analyze the data instantly at the equipment site to obtain the gas quality index Qpz, the gas state dynamic index Qdz and the insulation state dynamic index Jzz, which greatly reduces the delay of data transmission; the comprehensive evaluation module uses correlation calculation to integrate various indexes to obtain the equipment stability index SWDZ, which provides a scientific quantitative evaluation for the stability of the equipment; the monitoring and early warning module combines historical data and preset thresholds to perform multi-level evaluation of the equipment status, and issues early warning information in time to help users prevent and deal with potential faults; finally, the visualization module graphically displays the equipment operation status and analysis results, so that users can intuitively understand the equipment situation, identify potential problems and take timely measures; the system significantly improves the monitoring capability of the equipment operation status, the real-time and accuracy of data processing, and improves the efficiency of fault prevention and maintenance through early warning mechanism and visualization display.

[0079] Example 2

[0080] This embodiment is explained in Example 1, please refer to Figure 1 ,Specifically: the data acquisition module includes a data acquisition unit and a data preprocessing unit;

[0081] The data acquisition unit is used to collect the operation data of the gas-insulated switchgear in real time from the integrated sensor group and monitor installed in the gas-insulated switchgear, and classify and summarize to generate a gas quality data group, a gas state data group and an insulation state data group; the integrated sensor group includes a pressure sensor, a temperature sensor, a gas density sensor, a humidity sensor, a corona discharge intensity sensor, a gas particle sensor, a light scattering sensor and a sound velocity sensor; the monitor includes a gas composition analyzer, an insulation resistance tester and a leakage detector;

[0082] The data preprocessing unit is used to perform preliminary data noise filtering, data cleaning, outlier detection, correction and dimensionless processing on the insulation state data group, the gas quality data group and the gas state data group through the edge node, and convert the data format to obtain the insulation state data set, the gas quality data set and the gas state data set;

[0083] The insulation status data set includes corona discharge intensity D, insulation resistance R and gas leakage rate L;

[0084] The gas quality data set includes gas particle concentration wl, gas light scattering coefficient S and gas sound velocity C;

[0085] The gas state data set includes gas pressure P, gas temperature T, humidity H, gas density ρ and insulating gas composition C i ;

[0086] The preprocessed data is transmitted to the edge computing module via the wireless network.

[0087] In this embodiment, the data acquisition module can collect and classify the operating data of the gas-insulated switchgear in real time by integrating multiple sensors and monitors, and generate gas quality data groups, gas state data groups and insulation state data groups; the data preprocessing unit uses edge nodes to perform data noise filtering, data cleaning, outlier detection, correction and dimensionless processing to ensure data consistency and accuracy; this preprocessing mechanism greatly improves the quality and reliability of the data and reduces the errors that may occur during the transmission process; in addition, by transmitting the preprocessed data to the edge computing module, real-time analysis and processing can be achieved locally, reducing data transmission delays, improving the response speed and real-time performance of the monitoring system, and providing a solid foundation for equipment operation status evaluation and fault warning; this comprehensive data acquisition and preprocessing solution significantly enhances the monitoring effect of gas-insulated switchgear and ensures the stability and safety of the equipment.

[0088] Example 3

[0089] This embodiment is explained in Example 2. Please refer to Figure 1, specifically: the edge computing module includes an insulation state analysis unit, a gas quality analysis unit and a gas state analysis unit;

[0090] The insulation state analysis unit is used to perform dimensionless processing on the obtained insulation state data set, and then perform analysis and calculation to obtain the insulation state dynamic index Jzz;

[0091] The insulation state dynamic index Jzz is obtained by the following formula:

[0092]

[0093] Where k represents the correction constant and ln represents the logarithmic function.

[0094] The gas quality analysis unit is used to perform dimensionless processing on the acquired gas quality data set, and then perform analysis and calculation to obtain the gas quality index Qpz;

[0095] The gas quality index Qpz is obtained by the following formula:

[0096]

[0097] Wherein, ln represents the logarithmic function.

[0098] The gas state analysis unit is used to perform dimensionless processing on the acquired gas state data set, and then perform analysis and calculation to obtain the gas state dynamic index Qdz;

[0099] The gas state dynamic index Qdz is obtained by the following formula:

[0100]

[0101] In the formula, ln represents the logarithmic function, ∑ i ln(1+C i ) represents the insulating gas composition C i The logarithm sum of each component, e represents the exponential function.

[0102] The comprehensive analysis module is used to perform dimensionless processing on the obtained gas quality index Qpz, gas state dynamic index Qdz and insulation state dynamic index Jzz, and then perform summary calculation to obtain the equipment stability index SWDZ;

[0103] The equipment stability index SWDZ is obtained by the following formula:

[0104]

[0105] Wherein, log represents the logarithmic function.

[0106] In this embodiment, by integrating the insulation state analysis unit, the gas quality analysis unit and the gas state analysis unit, multi-dimensional and real-time monitoring of the gas insulated switchgear is realized; the system calculates the insulation state dynamic index Jzz, the gas quality index Qpz and the gas state dynamic index Qdz respectively by dimensionlessly processing the insulation state data set, the gas quality data set and the gas state data set; the comprehensive analysis module summarizes these indexes to calculate the equipment stability index SWDZ; the local processing capability of edge computing is utilized to greatly reduce the delay of data transmission, and through real-time analysis of multi-dimensional data, an accurate assessment of the equipment operating status is provided; compared with the traditional central server processing method, the system significantly improves the real-time, accuracy and stability of monitoring, can promptly discover potential problems of equipment, improve the safety and operation efficiency of equipment, and brings significant technical improvements and effect improvements.

[0107] Example 4

[0108] This embodiment is explained in Example 3, please refer to Figure 1 , specifically: the monitoring and early warning module includes a first early warning unit, a second early warning unit and a third early warning unit;

[0109] The first early warning unit is used to compare and analyze the insulation state dynamic index Jzz with the preset insulation state dynamic assessment threshold A to determine whether the current insulation state of the gas insulated switchgear is normal. The specific assessment scheme is as follows;

[0110] When the insulation state dynamic index Jzz> the preset insulation state dynamic assessment threshold A, it means that the insulation state is normal;

[0111] When the insulation state dynamic index Jzz≤the preset insulation state dynamic assessment threshold A, it indicates that the insulation state is abnormal, and the first warning signal is obtained. At this time, the secondary assessment mechanism is executed.

[0112] The second early warning unit performs a secondary comparative evaluation by presetting the first equipment stability threshold M and the second equipment stability threshold N based on the upper and lower limits of the historical gas-insulated switchgear stability index, and then compares the obtained equipment stability index SWDZ to analyze the stability of the current gas-insulated switchgear during operation. The specific evaluation scheme is as follows;

[0113] When the equipment stability index SWDZ> the first equipment stability threshold M, it means that the gas stability inside the equipment is normal and there is no need to detect the insulating gas;

[0114] When the second equipment stability threshold N≤equipment stability index SWDZ≤first equipment stability threshold M, it indicates that the equipment has a potential failure risk, and a second warning signal is obtained;

[0115] The equipment stability index SWDZ is less than the second equipment stability threshold N, indicating that the equipment stability is in a dangerous state, and a third warning signal is obtained.

[0116] The third warning unit is used to receive the first warning signal, the second warning signal and the third warning signal;

[0117] When receiving the first warning signal, notify the relevant staff to shut down the equipment, check the corona discharge of each part of the equipment, measure the insulation resistance and replace the contaminated or aged insulation parts, repair the gas leakage point, and ensure the gas pressure in the gas-insulated switchgear is normal;

[0118] When receiving the second warning signal, notify relevant staff to detect the insulating gas in the equipment;

[0119] When the third warning signal is received, the relevant staff will be notified to immediately shut down the equipment, conduct a comprehensive internal inspection and test, replace the insulating gas in the gas-insulated switchgear and conduct an electrical performance test.

[0120] In this embodiment, the insulation state of the equipment is preliminarily judged by comparing the insulation state dynamic index Jzz with the preset threshold value A, and the secondary evaluation mechanism is started when necessary; the secondary evaluation mechanism further analyzes the operating stability of the equipment by comparing the equipment stability index SWDZ with the preset threshold values ​​M and N, and promptly discovers potential fault risks or dangerous conditions; after receiving warning signals of different levels, the system can quickly notify relevant staff to take corresponding measures, such as shutting down the equipment for inspection, replacing insulating components, or conducting comprehensive internal inspections and tests; compared with traditional monitoring methods, the multi-level warning mechanism of the system not only improves the accuracy and timeliness of fault detection, but also significantly enhances the predictability and response efficiency of equipment maintenance, ensuring the safe and stable operation of gas insulated switchgear.

[0121] Example 5

[0122] This embodiment is explained in Example 1, please refer to Figure 1 ,Specifically: the visualization module includes a data recognition unit, a data storage unit and a data aggregation unit;

[0123] The data storage unit is used to store the data and analysis results processed by the edge computing module and the comprehensive analysis module in a local database;

[0124] The data identification unit is used to distinguish normal data from risk data, and forward risk and abnormal data to the cloud or central server for further analysis and long-term storage;

[0125] The data summary unit is used to summarize the operating status and analysis results of the gas-insulated switchgear, present them in a graphical form, and synchronize the summarized charts to the cloud or central server, providing real-time data display, historical data trend analysis, early warning information display and equipment stability index display functions, so that users can intuitively understand the operating status of the equipment, identify potential problems, and take corresponding measures in a timely manner;

[0126] Display the changing trend of historical data through line charts and bar charts to help users identify potential problems and failure trends;

[0127] Different levels of warning information are displayed through eye-catching colors and icons to ensure that relevant staff pay attention and handle them in a timely manner;

[0128] Displays the real-time value and historical changes of the equipment stability index SWDZ, compares it with the preset threshold, and provides a detailed analysis report.

[0129] In this embodiment, the data storage unit stores the processed data and analysis results in a local database to ensure the reliability and traceability of the data; the data identification unit can effectively distinguish between normal data and risk data, and forward the risk and abnormal data to the cloud or central server for further analysis and long-term storage, thereby improving the efficiency and security of data processing; the data aggregation unit presents the operating status and analysis results of the equipment to the user in a graphical manner, providing real-time data display, historical data trend analysis, early warning information display and equipment stability index display functions, so that users can intuitively understand the operation of the equipment, identify potential problems and take corresponding measures in time; these improvements not only improve the accuracy and real-time performance of equipment operation status monitoring, but also help users respond quickly through intuitive charts and eye-catching early warning information to ensure the stability and safety of the equipment.

[0130] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. GIS equipment wireless sensor monitoring system based on edge computing, characterized by: It includes data acquisition module, edge computing module, comprehensive analysis module, monitoring and early warning module and visualization module; The data acquisition module is used to install a sensor group and a monitor on the gas-insulated switchgear, collect the operating parameters of the gas-insulated switchgear in real time, and pre-process the acquired parameters; The edge computing module is used to receive sensor data and use the processing power of edge computing to perform calculations and analyses locally to obtain the gas quality index Qpz, the gas state dynamic index Qdz and the insulation state dynamic index Jzz; The comprehensive analysis module is used to correlate the obtained gas quality index Qpz, gas state dynamic index Qdz and insulation state dynamic index Jzz to obtain the equipment stability index SWDZ; The monitoring and early warning module is used to perform a preliminary evaluation based on the historical standard insulation state interval of the gas-insulated switchgear operation, the preset insulation state dynamic evaluation threshold A and the obtained insulation state dynamic index Jzz, perform an initial adjustment on the equipment according to the evaluation result, and start a second evaluation mechanism, the second evaluation mechanism is used to compare and evaluate the preset first equipment stability threshold M and the preset second equipment stability threshold N with the obtained equipment stability index SWDZ, and generate early warning information according to the evaluation result; The visualization module is used to present the operating status and analysis results of the gas-insulated switchgear in a graphical manner, provide real-time data display, historical data trend analysis, early warning information display and equipment stability index display, intuitively understand the operating status of the equipment, identify potential problems, and take corresponding measures in a timely manner.

2. The GIS equipment wireless sensor monitoring system based on edge computing according to claim 1 is characterized in that: The data acquisition module includes a data acquisition unit and a data preprocessing unit; The data acquisition unit is used to collect the operation data of the gas-insulated switchgear in real time from the integrated sensor group and monitor installed in the gas-insulated switchgear, and classify and summarize to generate a gas quality data group, a gas state data group and an insulation state data group; the integrated sensor group includes a pressure sensor, a temperature sensor, a gas density sensor, a humidity sensor, a corona discharge intensity sensor, a gas particle sensor, a light scattering sensor and a sound velocity sensor; the monitor includes a gas composition analyzer, an insulation resistance tester and a leakage detector; The data preprocessing unit is used to perform preliminary data noise filtering, data cleaning, outlier detection, correction and dimensionless processing on the insulation state data group, the gas quality data group and the gas state data group through the edge node, and convert the data format to obtain the insulation state data set, the gas quality data set and the gas state data set; The insulation status data set includes corona discharge intensity D, insulation resistance R and gas leakage rate L; The gas quality data set includes gas particle concentration wl, gas light scattering coefficient S and gas sound velocity C; The gas state data set includes gas pressure P, gas temperature T, humidity H, gas density ρ and insulating gas composition C i ; The preprocessed data is transmitted to the edge computing module via the wireless network.

3. The GIS equipment wireless sensor monitoring system based on edge computing according to claim 2 is characterized in that: The edge computing module includes an insulation state analysis unit, a gas quality analysis unit and a gas state analysis unit; The insulation state analysis unit is used to perform dimensionless processing on the obtained insulation state data set, and then perform analysis and calculation to obtain the insulation state dynamic index Jzz; The insulation state dynamic index Jzz is obtained by the following formula: Where k represents the correction constant and ln represents the logarithmic function.

4. The GIS equipment wireless sensor monitoring system based on edge computing according to claim 3 is characterized in that: The gas quality analysis unit is used to perform dimensionless processing on the acquired gas quality data set, and then perform analysis and calculation to obtain the gas quality index Qpz; The gas quality index Qpz is obtained by the following formula: Wherein, ln represents the logarithmic function.

5. The GIS equipment wireless sensor monitoring system based on edge computing according to claim 3 is characterized in that: The gas state analysis unit is used to perform dimensionless processing on the acquired gas state data set, and then perform analysis and calculation to obtain the gas state dynamic index Qdz; The gas state dynamic index Qdz is obtained by the following formula: In the formula, ln represents the logarithmic function, ∑ i ln(1+C i ) represents the insulating gas composition C i The logarithm sum of each component, e represents the exponential function, e H It means that the effect of humidity on the gas state is exponential.

6. The GIS equipment wireless sensor monitoring system based on edge computing according to claim 1 is characterized in that: The comprehensive analysis module is used to perform dimensionless processing on the obtained gas quality index Qpz, gas state dynamic index Qdz and insulation state dynamic index Jzz, and then perform summary calculation to obtain the equipment stability index SWDZ; The equipment stability index SWDZ is obtained by the following formula: Wherein, log represents the logarithmic function.

7. The GIS equipment wireless sensor monitoring system based on edge computing according to claim 1 is characterized in that: The monitoring and early warning module includes a first early warning unit, a second early warning unit and a third early warning unit; The first early warning unit is used to compare and analyze the insulation state dynamic index Jzz with the preset insulation state dynamic assessment threshold A to determine whether the current insulation state of the gas insulated switchgear is normal. The specific assessment scheme is as follows; When the insulation state dynamic index Jzz> the preset insulation state dynamic assessment threshold A, it means that the insulation state is normal; When the insulation state dynamic index Jzz≤the preset insulation state dynamic assessment threshold A, it indicates that the insulation state is abnormal, and the first warning signal is obtained. At this time, the secondary assessment mechanism is executed.

8. The GIS equipment wireless sensor monitoring system based on edge computing according to claim 7 is characterized in that: The second early warning unit performs a secondary comparative evaluation by presetting the first equipment stability threshold M and the second equipment stability threshold N based on the upper and lower limits of the historical gas-insulated switchgear stability index, and then compares the obtained equipment stability index SWDZ to analyze the stability of the current gas-insulated switchgear during operation. The specific evaluation scheme is as follows; When the equipment stability index SWDZ> the first equipment stability threshold M, it means that the gas stability inside the equipment is normal and there is no need to detect the insulating gas; When the second equipment stability threshold N≤equipment stability index SWDZ≤first equipment stability threshold M, it indicates that the equipment has a potential failure risk, and a second warning signal is obtained; The equipment stability index SWDZ is less than the second equipment stability threshold N, indicating that the equipment stability is in a dangerous state, and a third warning signal is obtained.

9. The GIS equipment wireless sensor monitoring system based on edge computing according to claim 7 is characterized in that: The third warning unit is used to receive the first warning signal, the second warning signal and the third warning signal; When receiving the first warning signal, notify the relevant staff to shut down the equipment, check the corona discharge of each part of the equipment, measure the insulation resistance and replace the contaminated or aged insulation parts, repair the gas leakage point, and ensure the gas pressure in the gas-insulated switchgear is normal; When receiving the second warning signal, notify relevant staff to detect the insulating gas in the equipment; When the third warning signal is received, the relevant staff will be notified to immediately shut down the equipment, conduct a comprehensive internal inspection and test, replace the insulating gas in the gas-insulated switchgear and conduct an electrical performance test.

10. The GIS equipment wireless sensor monitoring system based on edge computing according to claim 1 is characterized in that: The visualization module includes a data identification unit, a data storage unit and a data aggregation unit; The data identification unit is used to distinguish normal data from risk data, and forward risk and abnormal data to the cloud or central server for further analysis and long-term storage; The data storage unit is used to store the data and analysis results processed by the edge computing module and the comprehensive analysis module in a local database; The data summary unit is used to summarize the operating status and analysis results of the gas-insulated switchgear, present them in a graphical form, and synchronize the summarized charts to the cloud or central server, providing real-time data display, historical data trend analysis, early warning information display and equipment stability index display functions, so that users can intuitively understand the operating status of the equipment, identify potential problems, and take corresponding measures in a timely manner; Display the changing trend of historical data through line charts and bar charts to help users identify potential problems and failure trends; Different levels of warning information are displayed through eye-catching colors and icons to ensure that relevant staff pay attention and handle them in a timely manner; Displays the real-time value and historical changes of the equipment stability index SWDZ, compares it with the preset threshold, and provides a detailed analysis report.

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