High-low voltage power distribution cabinet discharge intelligent detection method and system based on big data

Abstract

This invention relates to the technical field of discharge detection in high and low voltage distribution cabinets, and discloses an intelligent discharge detection method and system for high and low voltage distribution cabinets based on big data. It utilizes multi-source data fusion (voltage, ultrasonic, current, electromagnetic wave, chemical gas, and temperature) combined with big data to intelligently and reliably monitor discharge faults in high and low voltage distribution cabinets. Based on multi-dimensional discharge detection results from voltage, ultrasonic, current, electromagnetic wave, chemical gas, and temperature perspectives, it performs precise digital analysis of the discharge fault occurrence level, enabling multi-parameter precise analysis of the probability of high and low voltage distribution cabinet discharge faults. Simultaneously, it integrates with a distribution cabinet safety monitoring platform and display screen to promptly and safely execute feedback operations on the discharge fault detection results, achieving highly reliable detection and visualized feedback for high and low voltage distribution cabinet discharge faults, and improving the scientific, refined monitoring and visualized intelligent management of high and low voltage distribution cabinet discharge detection.

Description

Technical Field

[0001] This invention relates to the technical field of discharge detection in high and low voltage distribution cabinets, specifically to a smart discharge detection method and system for high and low voltage distribution cabinets based on big data. Background Technology

[0002] Discharge detection in high- and low-voltage switchgear is a key technology for monitoring the insulation condition and providing early warning of faults in power equipment. With the development of smart grids, live-line detection technology, with partial discharge detection at its core, has become mainstream. It assesses insulation health by capturing various physicochemical signals generated by discharge. The main methods include transient ground voltage method for detecting electromagnetic pulses, ultrasonic method for listening to acoustic emissions, standard method for measuring pulse current, and chemical sensing method for monitoring insulation decomposition gases. These technologies can detect potential hazards such as insulation defects, loose connections, or floating potentials in the cabinet at an early stage without affecting power supply. However, existing discharge detection methods for high- and low-voltage switchgear cannot achieve accurate detection of discharge faults based on multi-source data fusion, nor can they achieve scientific analysis of the occurrence level of discharge faults, thus reducing the accuracy and efficiency of discharge detection in high- and low-voltage switchgear.

[0003] Chinese invention patent application CN121114634A discloses an intelligent monitoring method and system for power distribution cabinets. It collects multi-dimensional data signals from the busbar area, quantifies the deviation between the current signal characteristics and the health vector learned through dynamic clustering using Mahalanobis distance, and obtains an initial fault risk score. Spectrum analysis is introduced to assess signal quality, resulting in a signal data quality score. The initial fault risk score and the signal quality score are weighted to obtain a weighted fault risk score. A dynamic threshold that can adapt to drift during normal operating conditions is constructed by clustering historical weighted fault risk scores. The weighted fault risk score is compared with the dynamic threshold, and the fault status of the busbar area is assessed based on the comparison results to achieve intelligent monitoring of the power distribution cabinet. However, the above technical solution cannot reliably diagnose discharge faults in power distribution cabinets. Summary of the Invention

[0004] To address the shortcomings of existing high and low voltage switchgear discharge detection methods, which fail to achieve accurate detection of discharge faults based on multi-source data fusion and scientific analysis of the fault severity level, thus reducing the accuracy and efficiency of discharge detection, this invention provides a big data-based intelligent discharge detection method and system for high and low voltage switchgear. This system aims to achieve reliable and scientific monitoring of high and low voltage switchgear discharge faults based on the fusion of multi-source data (voltage, ultrasound, current, electromagnetic waves, chemical gases, and temperature) combined with big data; accurate digital analysis of the fault severity level; and scientific and refined monitoring of high and low voltage switchgear discharge faults, thereby improving the accuracy and efficiency of discharge detection.

[0005] This invention is achieved through the following technical solution: a smart discharge detection method for high and low voltage distribution cabinets based on big data, the method comprising the following steps:

[0006] Real-time cabinet voltage data and real-time ultrasonic frequency data inside the distribution cabinet are collected separately. Based on the discharge voltage characteristics of the distribution cabinet, the discharge fault detection and processing of the distribution cabinet is performed to obtain voltage-side distribution cabinet discharge fault detection data. Based on the discharge ultrasonic characteristics of the distribution cabinet, the discharge fault detection and processing of the distribution cabinet discharge is performed to obtain ultrasonic-side distribution cabinet discharge fault detection data.

[0007] Real-time cabinet current data and real-time electromagnetic wave frequency data inside the distribution cabinet are collected separately. Based on the discharge current characteristics of the distribution cabinet, discharge fault detection and processing are performed to obtain current-side discharge fault detection data. Based on the electromagnetic wave characteristics of the distribution cabinet discharge, discharge fault detection and processing are performed to obtain electromagnetic wave-side discharge fault detection data. Real-time chemical gas characteristic data and real-time temperature data inside the distribution cabinet are collected separately. Based on the chemical gas characteristics generated by the discharge of the distribution cabinet, discharge fault detection and processing are performed to obtain chemical gas-side discharge fault detection data. Based on the temperature characteristics of the discharge of the distribution cabinet, discharge fault detection and processing are performed to obtain temperature-side discharge fault detection data.

[0008] The probability level of discharge faults in the distribution cabinet is analyzed and processed to obtain the analysis data of the discharge fault occurrence level of the distribution cabinet, and the discharge fault detection result feedback operation of the distribution cabinet is executed.

[0009] Preferably, the following steps are taken: Real-time cabinet voltage data and real-time ultrasonic frequency data inside the distribution cabinet are collected separately; discharge fault detection and processing of the distribution cabinet based on the discharge voltage characteristics are performed to obtain voltage-side distribution cabinet discharge fault detection data; and discharge fault detection and processing of the distribution cabinet based on the ultrasonic discharge characteristics are performed to obtain ultrasonic-side distribution cabinet discharge fault detection data, including the following steps:

[0010] Voltage data on the surface of the target power distribution cabinet is collected online using a TEV sensor array, and real-time cabinet voltage data is generated, with the unit of the real-time cabinet voltage data being millivolts; ultrasonic frequency data of the ultrasonic signal inside the target power distribution cabinet is collected online using an ultrasonic sensor, and real-time internal ultrasonic frequency data is generated, with the unit of the real-time internal ultrasonic frequency data being hertz.

[0011] Based on the real-time cabinet voltage data of the distribution cabinet and the standard discharge voltage data matrix of the distribution cabinet discharge fault, the discharge fault detection processing of the distribution cabinet is performed to obtain the voltage-side distribution cabinet discharge fault detection data.

[0012] Based on the real-time ultrasonic frequency data inside the distribution cabinet and the standard discharge ultrasonic frequency data matrix of the distribution cabinet, discharge fault detection processing of the distribution cabinet is performed to obtain ultrasonic side distribution cabinet discharge fault detection data.

[0013] Preferably, the discharge fault detection processing of the distribution cabinet based on the real-time cabinet voltage data and the standard discharge voltage data matrix of the distribution cabinet discharge fault, to obtain the voltage-side distribution cabinet discharge fault detection data, includes the following steps:

[0014] Establish a standard discharge voltage data matrix for power distribution cabinet discharge faults. ,in Indicates the first The standard discharge voltage data for a power distribution cabinet discharge fault represents the induced transient voltage to ground generated on the surface of a standard power distribution cabinet when the target power distribution cabinet experiences a discharge fault; the unit of the standard discharge voltage data for a power distribution cabinet discharge fault is millivolts.

[0015] The real-time cabinet voltage data of the distribution cabinet is compared with the standard discharge voltage data matrix of the distribution cabinet for discharge faults. The standard discharge voltage data for the power distribution cabinet discharge fault described in the document Voltage data matching is performed, and discharge fault detection data for voltage-side distribution cabinets is constructed based on the voltage data matching results.

[0016] When the real-time cabinet voltage data of the distribution cabinet is different from the standard discharge voltage data of the distribution cabinet for discharge faults... When voltage data matching is successful, it indicates that a discharge fault has occurred inside the target distribution cabinet. The output of the voltage-side distribution cabinet discharge fault detection data indicates that a discharge fault has occurred.

[0017] When the real-time cabinet voltage data of the distribution cabinet is different from the standard discharge voltage data of the distribution cabinet for discharge faults... If no voltage data match is found, it indicates that no discharge fault has occurred inside the target distribution cabinet. In this case, the output of the voltage-side distribution cabinet discharge fault detection data will be "no discharge fault has occurred".

[0018] Preferably, the discharge fault detection processing of the distribution cabinet based on the real-time ultrasonic frequency data inside the distribution cabinet and the standard discharge ultrasonic frequency data matrix of the distribution cabinet includes the following steps:

[0019] Establish a standard discharge ultrasonic frequency data matrix for power distribution cabinet discharge faults. ,in Indicates the first The standard discharge ultrasonic frequency data for a power distribution cabinet discharge fault refers to the frequency data of ultrasonic signals generated inside a standard power distribution cabinet when a discharge fault occurs in the target power distribution cabinet; the unit of the standard discharge ultrasonic frequency data for a power distribution cabinet discharge fault is Hertz.

[0020] The real-time ultrasonic frequency data inside the distribution cabinet is compared with the standard discharge ultrasonic frequency data matrix of the distribution cabinet for discharge faults. The standard discharge ultrasonic frequency data for the power distribution cabinet discharge fault described in the document Perform ultrasonic frequency data matching, and construct ultrasonic side power distribution cabinet discharge fault detection data based on the ultrasonic frequency data matching results;

[0021] When the real-time ultrasonic frequency data inside the distribution cabinet matches the standard discharge ultrasonic frequency data for the discharge fault of the distribution cabinet... When the ultrasonic frequency data matching is successful, it indicates that a discharge fault has occurred inside the target power distribution cabinet. The output of the ultrasonic side power distribution cabinet discharge fault detection data is that a discharge fault has occurred.

[0022] When the real-time ultrasonic frequency data inside the distribution cabinet matches the standard discharge ultrasonic frequency data for the discharge fault of the distribution cabinet... If no matching of ultrasonic frequency data is found, it indicates that no discharge fault has occurred inside the target distribution cabinet. In this case, the output of the ultrasonic side distribution cabinet discharge fault detection data is "no discharge fault has occurred".

[0023] Preferably, the following steps are taken: Real-time cabinet current data and real-time electromagnetic wave frequency data inside the distribution cabinet are collected; discharge faults in the distribution cabinet are detected and processed based on the discharge current characteristics to obtain current-side discharge fault detection data; discharge faults in the distribution cabinet are detected and processed based on the electromagnetic wave characteristics to obtain electromagnetic wave-side discharge fault detection data; real-time chemical gas characteristic data and real-time temperature data inside the distribution cabinet are collected; discharge faults in the distribution cabinet are detected and processed based on the chemical gas characteristics generated by the discharge to obtain chemical gas-side discharge fault detection data; and discharge faults in the distribution cabinet are detected and processed based on the temperature characteristics to obtain temperature-side discharge fault detection data.

[0024] The current data on the surface of the target distribution cabinet is collected online by a high-frequency current transformer, and real-time cabinet current data is generated. The unit of the real-time cabinet current data is milliampere. The electromagnetic wave signal frequency data inside the target distribution cabinet is collected online by a UHF sensor, and real-time internal electromagnetic wave frequency data is generated. The unit of the real-time internal electromagnetic wave frequency data is hertz.

[0025] Based on the real-time cabinet current data and the standard discharge current data matrix of the distribution cabinet, discharge fault detection processing is performed to obtain current-side distribution cabinet discharge fault detection data; based on the real-time cabinet electromagnetic wave frequency data and the standard discharge electromagnetic wave frequency data matrix of the distribution cabinet, discharge fault detection processing is performed to obtain electromagnetic wave-side distribution cabinet discharge fault detection data.

[0026] The chemical gas types and concentrations inside the target distribution cabinet are collected online using chemical gas sensors, and real-time chemical gas characteristic data of the cabinet is generated. The concentration unit of the real-time chemical gas characteristic data of the distribution cabinet is microliters per liter. The chemical gas sensors include hydrogen sensors, carbon monoxide sensors, hydrogen sulfide sensors, and sulfur dioxide sensors. The temperature data of the internal space of the target distribution cabinet is collected online using an infrared thermal imager, and real-time temperature data of the distribution cabinet is generated. The unit of the real-time temperature data of the distribution cabinet is degrees Celsius.

[0027] Based on the real-time internal chemical gas characteristic data of the distribution cabinet and the standard discharge chemical gas characteristic data matrix of the distribution cabinet discharge fault, discharge fault detection processing of the distribution cabinet is performed to obtain chemical gas-side distribution cabinet discharge fault detection data; based on the real-time internal temperature data of the distribution cabinet and the standard discharge temperature data matrix of the distribution cabinet discharge fault, discharge fault detection processing of the distribution cabinet is performed to obtain temperature-side distribution cabinet discharge fault detection data.

[0028] Preferably, the discharge fault detection processing of the distribution cabinet is performed based on the real-time cabinet current data and the standard discharge current data matrix of the distribution cabinet to obtain current-side distribution cabinet discharge fault detection data; the discharge fault detection processing of the distribution cabinet based on the real-time internal electromagnetic wave frequency data and the standard discharge electromagnetic wave frequency data matrix of the distribution cabinet to obtain electromagnetic wave-side distribution cabinet discharge fault detection data includes the following steps:

[0029] Establish standard discharge current data matrices for each distribution cabinet discharge fault. and the standard discharge electromagnetic wave frequency data matrix for power distribution cabinet discharge faults ;in Indicates the first The standard discharge current data for a distribution cabinet discharge fault refers to the induced transient current data generated on the surface of a standard distribution cabinet when the target distribution cabinet experiences a discharge fault. The unit of the standard discharge current data is milliampere (mA). Indicates the first The standard discharge electromagnetic wave frequency data for a power distribution cabinet discharge fault refers to the frequency data of electromagnetic wave signals generated inside a standard power distribution cabinet when a discharge fault occurs in the target power distribution cabinet; the unit of the standard discharge electromagnetic wave frequency data for a power distribution cabinet discharge fault is Hertz.

[0030] The real-time cabinet current data of the distribution cabinet is compared with the standard discharge current data matrix of the distribution cabinet for discharge faults. The standard discharge current data for the power distribution cabinet discharge fault described in the document Perform current data matching, and construct discharge fault detection data for the current-side distribution cabinet based on the current data matching results;

[0031] When the real-time cabinet current data of the distribution cabinet is compared with the standard discharge current data of the distribution cabinet for discharge faults... When the current data matching is successful, it indicates that a discharge fault has occurred inside the target distribution cabinet. The output of the discharge fault detection data of the current-side distribution cabinet is then a discharge fault.

[0032] When the real-time cabinet current data of the distribution cabinet is compared with the standard discharge current data of the distribution cabinet for discharge faults... If no matching of current data is found, it indicates that no discharge fault has occurred inside the target distribution cabinet. In this case, the output of the current-side distribution cabinet discharge fault detection data is "no discharge fault has occurred".

[0033] The real-time electromagnetic wave frequency data inside the distribution cabinet is compared with the electromagnetic wave frequency data matrix of the standard discharge fault of the distribution cabinet. The standard discharge electromagnetic wave frequency data for the power distribution cabinet discharge fault described in the document Electromagnetic wave frequency data matching is performed, and discharge fault detection data of the electromagnetic wave side distribution cabinet is constructed based on the electromagnetic wave frequency data matching results.

[0034] When the real-time electromagnetic wave frequency data inside the distribution cabinet matches the standard discharge electromagnetic wave frequency data for the distribution cabinet's discharge fault... When electromagnetic wave frequency data matching is successful, it indicates that a discharge fault has occurred inside the target distribution cabinet. The output of the electromagnetic wave side distribution cabinet discharge fault detection data indicates that a discharge fault has occurred.

[0035] When the real-time electromagnetic wave frequency data inside the distribution cabinet matches the standard discharge electromagnetic wave frequency data for the distribution cabinet's discharge fault... If no matching of electromagnetic wave frequency data is found, it indicates that no discharge fault has occurred inside the target distribution cabinet. In this case, the output of the electromagnetic wave side distribution cabinet discharge fault detection data is "no discharge fault has occurred".

[0036] Preferably, the discharge fault detection processing of the distribution cabinet is performed based on the real-time internal chemical gas characteristic data and the standard discharge chemical gas characteristic data matrix of the distribution cabinet to obtain chemical gas-side distribution cabinet discharge fault detection data; the discharge fault detection processing of the distribution cabinet based on the real-time internal temperature data and the standard discharge temperature data matrix of the distribution cabinet to obtain temperature-side distribution cabinet discharge fault detection data includes the following steps:

[0037] Establish a standard discharge chemical gas characteristic data matrix for each distribution cabinet discharge fault. and the standard discharge temperature data matrix for electrical distribution cabinet discharge faults ;in Indicates the first The standard discharge chemical gas characteristic data for a distribution cabinet discharge fault refers to the types and concentrations of chemical gases released by the insulation material inside a standard distribution cabinet under discharge conditions when the target distribution cabinet experiences a discharge fault. The concentration unit of the standard discharge chemical gas characteristic data is microliters per liter. Indicates the first The standard discharge temperature data for a power distribution cabinet discharge fault represents the local high temperature characteristic data generated in the internal space of a standard power distribution cabinet under the action of discharge when the target power distribution cabinet experiences a discharge fault; the unit of the standard discharge temperature data for a power distribution cabinet discharge fault is degrees Celsius.

[0038] The real-time chemical gas characteristic data inside the distribution cabinet is compared with the chemical gas characteristic data matrix of the standard discharge fault of the distribution cabinet. The standard discharge chemical gas characteristic data of the distribution cabinet discharge fault described in the document Perform chemical gas characteristic information matching, and construct chemical gas-side power distribution cabinet discharge fault detection data based on the chemical gas characteristic information matching results;

[0039] When the real-time chemical gas characteristic data inside the distribution cabinet matches the standard discharge chemical gas characteristic data of the distribution cabinet for discharge faults... When the chemical gas characteristic information matching is successful, it indicates that a discharge fault has occurred inside the target distribution cabinet. Then, the discharge fault detection data of the chemical gas-side distribution cabinet is output as a discharge fault has occurred.

[0040] When the real-time chemical gas characteristic data inside the distribution cabinet matches the standard discharge chemical gas characteristic data of the distribution cabinet for discharge faults... If no matching of chemical gas characteristic information is found, it indicates that no discharge fault has occurred inside the target distribution cabinet. In this case, the output of the discharge fault detection data of the chemical gas-side distribution cabinet is "no discharge fault has occurred".

[0041] The real-time internal temperature data of the distribution cabinet is compared with the standard discharge temperature data matrix of the distribution cabinet for discharge faults. The standard discharge temperature data for the power distribution cabinet discharge fault described in the document Temperature data matching is performed, and discharge fault detection data of the temperature-side distribution cabinet is constructed based on the temperature data matching results.

[0042] When the real-time internal temperature data of the distribution cabinet is compared with the standard discharge temperature data of the distribution cabinet for discharge faults... When temperature data matching is successful, it indicates that a discharge fault has occurred inside the target distribution cabinet. The temperature-side distribution cabinet discharge fault detection data is then output as a discharge fault has occurred.

[0043] When the real-time internal temperature data of the distribution cabinet is compared with the standard discharge temperature data of the distribution cabinet for discharge faults... If no temperature data is successfully matched, it indicates that no discharge fault has occurred inside the target distribution cabinet. In this case, the output of the temperature-side distribution cabinet discharge fault detection data will be "no discharge fault has occurred".

[0044] Preferably, the analysis and processing of the probability level of the distribution cabinet discharge fault to obtain the distribution cabinet discharge fault occurrence level analysis data and the execution of the distribution cabinet discharge fault detection result feedback operation include the following steps:

[0045] Establish a standard for the occurrence level of discharge faults in distribution cabinets and a matrix of discharge fault detection information. ,in This represents the standard discharge fault detection information corresponding to the first type of discharge fault occurrence level of the distribution cabinet; where the first type of discharge fault occurrence level indicates the probability of a discharge fault occurring in the distribution cabinet. The discharge fault occurrence level standard and discharge fault detection information of the power distribution cabinet This indicates the probability level of a discharge fault detected on any one of the voltage, ultrasonic, current, electromagnetic wave, chemical gas, and temperature sides of the distribution cabinet. This indicates the standard discharge fault detection information corresponding to the second type of discharge fault occurrence level of the distribution cabinet; where the second type of discharge fault occurrence level represents the probability of a discharge fault occurring in the distribution cabinet. The discharge fault occurrence level standard and discharge fault detection information of the power distribution cabinet This indicates the probability level of a discharge fault detected on any two of the following sides of the distribution cabinet: voltage side, ultrasonic side, current side, electromagnetic wave side, chemical gas side, and temperature side. This indicates the standard discharge fault detection information corresponding to the third type of discharge fault occurrence level of the distribution cabinet; where the third type of discharge fault occurrence level represents the probability of a discharge fault occurring in the distribution cabinet. The discharge fault occurrence level standard and discharge fault detection information of the power distribution cabinet This indicates the probability level of a discharge fault detected on any three of the following three sides of the distribution cabinet: voltage side, ultrasonic side, current side, electromagnetic wave side, chemical gas side, and temperature side. This indicates the standard discharge fault detection information corresponding to the fourth type of discharge fault occurrence level of the distribution cabinet; where the fourth type of discharge fault occurrence level represents the probability of a discharge fault occurring in the distribution cabinet. The discharge fault occurrence level standard and discharge fault detection information of the power distribution cabinet This indicates the probability level of a discharge fault detected on any four of the following four sides of the distribution cabinet: voltage side, ultrasonic side, current side, electromagnetic wave side, chemical gas side, and temperature side. This indicates the standard discharge fault detection information corresponding to the fifth type of discharge fault occurrence level of the distribution cabinet; where the fifth type of discharge fault occurrence level represents the probability of a discharge fault occurring in the distribution cabinet. The discharge fault occurrence level standard and discharge fault detection information of the power distribution cabinet This indicates the probability level of a discharge fault detected on any five of the following sides of the distribution cabinet: voltage side, ultrasonic side, current side, electromagnetic wave side, chemical gas side, and temperature side. This indicates the standard discharge fault detection information corresponding to the sixth type of discharge fault occurrence level of the distribution cabinet; where the sixth type of discharge fault occurrence level represents the probability of a discharge fault occurring in the distribution cabinet. The discharge fault occurrence level standard and discharge fault detection information of the power distribution cabinet This indicates the probability level of a discharge fault in the distribution cabinet, corresponding to the detection of discharge faults on the voltage side, ultrasonic side, current side, electromagnetic wave side, chemical gas side, and temperature side.

[0046] The discharge fault detection data of the voltage-side distribution cabinet, the ultrasonic-side distribution cabinet, the current-side distribution cabinet, the electromagnetic wave-side distribution cabinet, the chemical gas-side distribution cabinet, and the temperature-side distribution cabinet are combined with the discharge fault detection information matrix based on the standard discharge fault occurrence level of the distribution cabinet. The discharge fault occurrence level standard discharge fault detection information of the power distribution cabinet described in the figure is matched with the discharge fault detection result information of the power distribution cabinet. The text information of the discharge fault occurrence level corresponding to the discharge fault detection information of the power distribution cabinet discharge fault occurrence level standard discharge fault detection information that matches the discharge fault detection data of the voltage side power distribution cabinet, the ultrasonic side power distribution cabinet, the current side power distribution cabinet, the electromagnetic wave side power distribution cabinet, the chemical gas side power distribution cabinet, and the temperature side power distribution cabinet is searched and found. The discharge fault occurrence level analysis data of the power distribution cabinet is generated after data identification.

[0047] The discharge fault detection data of the voltage-side distribution cabinet, the ultrasonic-side distribution cabinet, the current-side distribution cabinet, the electromagnetic wave-side distribution cabinet, the chemical gas-side distribution cabinet, the temperature-side distribution cabinet, and the distribution cabinet discharge fault occurrence level analysis data are transmitted to the distribution cabinet safety supervision platform through the Internet of Things communication network, and the results are output on the display screen to perform the distribution cabinet discharge fault detection result feedback operation.

[0048] A big data-based intelligent discharge detection system for high and low voltage switchgear is used to implement the big data-based intelligent discharge detection method for high and low voltage switchgear. The system includes a high and low voltage switchgear discharge fault voltage ultrasonic feature detection module, a high and low voltage switchgear discharge fault current electromagnetic wave feature detection module, a high and low voltage switchgear discharge fault chemical gas temperature feature detection module, and a high and low voltage switchgear discharge fault assessment module.

[0049] The high and low voltage distribution cabinet discharge fault voltage ultrasonic feature detection module includes a distribution cabinet real-time cabinet voltage acquisition unit, a distribution cabinet real-time cabinet internal ultrasonic frequency acquisition unit, a distribution cabinet discharge fault standard discharge voltage storage unit, a distribution cabinet discharge fault standard discharge ultrasonic frequency storage unit, a voltage-side distribution cabinet discharge fault detection unit, and an ultrasonic-side distribution cabinet discharge fault detection unit.

[0050] The real-time cabinet voltage acquisition unit of the distribution cabinet acquires real-time cabinet voltage data through a TEV sensor array; the real-time internal ultrasonic frequency acquisition unit of the distribution cabinet acquires real-time internal ultrasonic frequency data through an ultrasonic sensor; the standard discharge voltage storage unit for the distribution cabinet discharge fault stores standard discharge voltage data for the distribution cabinet discharge fault; the standard discharge ultrasonic frequency storage unit for the distribution cabinet discharge fault stores standard discharge ultrasonic frequency data for the distribution cabinet discharge fault; the voltage-side distribution cabinet discharge fault detection unit performs discharge fault detection processing based on the real-time cabinet voltage data and the standard discharge voltage data to obtain voltage-side distribution cabinet discharge fault detection data; the ultrasonic-side distribution cabinet discharge fault detection unit performs discharge fault detection processing based on the real-time internal ultrasonic frequency data and the standard discharge ultrasonic frequency data to obtain ultrasonic-side distribution cabinet discharge fault detection data.

[0051] The high and low voltage switchgear discharge fault current electromagnetic wave characteristic detection module includes a switchgear real-time cabinet current acquisition unit, a switchgear real-time cabinet internal electromagnetic wave frequency acquisition unit, a switchgear discharge fault standard discharge current storage unit, a switchgear discharge fault standard discharge electromagnetic wave frequency storage unit, a current-side switchgear discharge fault detection unit, and an electromagnetic wave-side switchgear discharge fault detection unit.

[0052] The real-time cabinet current acquisition unit of the distribution cabinet acquires real-time cabinet current data through a high-frequency current transformer; the real-time internal electromagnetic wave frequency acquisition unit of the distribution cabinet acquires real-time internal electromagnetic wave frequency data through a UHF sensor; the standard discharge current storage unit for the distribution cabinet discharge fault stores standard discharge current data for the distribution cabinet discharge fault; the standard discharge electromagnetic wave frequency storage unit for the distribution cabinet discharge fault stores standard discharge electromagnetic wave frequency data for the distribution cabinet discharge fault; the current-side distribution cabinet discharge fault detection unit performs discharge fault detection processing based on the real-time cabinet current data and the standard discharge current data of the distribution cabinet discharge fault to obtain current-side distribution cabinet discharge fault detection data; the electromagnetic wave-side distribution cabinet discharge fault detection unit performs discharge fault detection processing based on the real-time internal electromagnetic wave frequency data and the standard discharge electromagnetic wave frequency data of the distribution cabinet discharge fault to obtain electromagnetic wave-side distribution cabinet discharge fault detection data.

[0053] The high and low voltage switchgear discharge fault chemical gas temperature characteristic detection module includes a switchgear real-time cabinet internal chemical gas characteristic acquisition unit, a switchgear real-time cabinet internal temperature acquisition unit, a switchgear discharge fault standard discharge chemical gas characteristic storage unit, a switchgear discharge fault standard discharge temperature storage unit, a switchgear discharge fault detection unit on the chemical gas side, and a switchgear discharge fault detection unit on the temperature side.

[0054] The real-time internal chemical gas characteristic acquisition unit of the distribution cabinet acquires real-time internal chemical gas characteristic data through a chemical gas sensor; the real-time internal temperature acquisition unit acquires real-time internal temperature data through an infrared thermal imager; the standard discharge chemical gas characteristic storage unit for the distribution cabinet discharge fault stores standard discharge chemical gas characteristic data; the standard discharge temperature storage unit for the distribution cabinet discharge fault stores standard discharge temperature data; the chemical gas-side distribution cabinet discharge fault detection unit performs discharge fault detection processing based on the real-time internal chemical gas characteristic data and the standard discharge chemical gas characteristic data to obtain chemical gas-side distribution cabinet discharge fault detection data; the temperature-side distribution cabinet discharge fault detection unit performs discharge fault detection processing based on the real-time internal temperature data and the standard discharge temperature data to obtain temperature-side distribution cabinet discharge fault detection data.

[0055] The high and low voltage switchgear discharge fault assessment module includes a switchgear discharge fault occurrence level standard discharge fault detection information storage unit, a switchgear discharge fault occurrence level analysis unit, and a switchgear discharge fault detection feedback unit.

[0056] The distribution cabinet discharge fault occurrence level standard discharge fault detection information storage unit is used to store the distribution cabinet discharge fault occurrence level standard discharge fault detection information; the distribution cabinet discharge fault occurrence level analysis unit analyzes the distribution cabinet discharge fault based on the voltage-side distribution cabinet discharge fault detection data, the ultrasonic-side distribution cabinet discharge fault detection data, the current-side distribution cabinet discharge fault detection data, the electromagnetic wave-side distribution cabinet discharge fault detection data, the chemical gas-side distribution cabinet discharge fault detection data, the temperature-side distribution cabinet discharge fault detection data, and the distribution cabinet discharge fault occurrence level standard discharge fault detection information. The probability level analysis of electrical fault occurrence is processed to obtain the discharge fault occurrence level analysis data of the distribution cabinet. The discharge fault detection feedback unit of the distribution cabinet, based on the discharge fault detection data of the voltage side distribution cabinet, the discharge fault detection data of the ultrasonic side distribution cabinet, the discharge fault detection data of the current side distribution cabinet, the discharge fault detection data of the electromagnetic wave side distribution cabinet, the discharge fault detection data of the chemical gas side distribution cabinet, the discharge fault detection data of the temperature side distribution cabinet, and the discharge fault occurrence level analysis data of the distribution cabinet, and in conjunction with the distribution cabinet safety supervision platform and the display screen, performs the discharge fault detection result feedback operation of the distribution cabinet.

[0057] This invention provides an intelligent discharge detection method for high and low voltage switchgear based on big data. It has the following beneficial effects:

[0058] 1. Real-time and accurate acquisition of real-time cabinet voltage parameters and real-time ultrasonic signal frequency parameters within the distribution cabinet via TEV sensor array and ultrasonic sensors; based on the real-time cabinet voltage data and real-time ultrasonic signal frequency data, combined with data analysis and big data-based standard discharge voltage data and standard discharge ultrasonic frequency data of the distribution cabinet, accurate detection of discharge faults in the distribution cabinet on both the voltage and ultrasonic sides is achieved. This realizes accurate monitoring of discharge faults in high and low voltage distribution cabinets based on the fusion of multi-source voltage and ultrasonic data and combined with big data, thereby improving the accuracy of discharge detection in high and low voltage distribution cabinets.

[0059] II. Real-time dynamic acquisition of real-time cabinet current parameters and electromagnetic wave signal frequency parameters within the distribution cabinet using high-frequency current transformers and UHF sensors; precise detection of distribution cabinet discharge faults on both the current and electromagnetic wave sides based on data analysis and standard discharge current and electromagnetic wave frequency data for distribution cabinet discharge faults set using big data science, achieving multi-source data fusion of current and electromagnetic waves and scientific analysis of high and low voltage distribution cabinet discharge faults; scientific acquisition of real-time chemical gas characteristic data and real-time internal temperature data within the distribution cabinet using chemical gas sensors and infrared thermal imagers. Based on real-time chemical gas characteristic data and real-time temperature data inside the distribution cabinet, combined with data analysis and standard discharge chemical gas characteristic data and standard discharge temperature data of the distribution cabinet based on big data storage, discharge faults in the distribution cabinet on both the chemical gas and temperature sides are detected, resulting in chemical gas-side discharge fault detection data. Comprehensive discharge fault detection of the distribution cabinet is performed based on real-time temperature data inside the distribution cabinet and standard discharge temperature data. This achieves intelligent and reliable monitoring of discharge faults in high and low voltage distribution cabinets by fusing multi-source data (voltage, ultrasound, current, electromagnetic waves, chemical gases, and temperature) and combining big data, thereby improving the accuracy and quality of discharge fault detection in high and low voltage distribution cabinets.

[0060] Third, based on the discharge detection results of the distribution cabinet from multiple dimensions including voltage, ultrasonic, current, electromagnetic wave, chemical gas, and temperature, a digital and precise analysis of the discharge fault occurrence level of the distribution cabinet is performed. This enables precise multi-parameter analysis of the probability of discharge faults in high and low voltage distribution cabinets. Simultaneously, combined with the distribution cabinet safety supervision platform and display screen, timely and safe feedback of the discharge fault detection results is performed, achieving highly reliable detection and visual feedback of discharge faults in high and low voltage distribution cabinets. This improves the scientific, refined monitoring and visualized intelligent management of discharge detection in high and low voltage distribution cabinets. Attached Figure Description

[0061] Figure 1 A schematic diagram of the module of the intelligent discharge detection system for high and low voltage distribution cabinets based on big data provided by the present invention;

[0062] Figure 2 The flowchart shows the intelligent discharge detection method for high and low voltage distribution cabinets based on big data provided by this invention. Detailed Implementation

[0063] 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.

[0064] An example of the intelligent discharge detection method for high and low voltage switchgear based on big data is as follows:

[0065] Example 1: Please refer to Figures 1-2 A smart discharge detection method for high and low voltage switchgear based on big data, the method includes the following steps:

[0066] Real-time cabinet voltage data and real-time ultrasonic frequency data inside the distribution cabinet are collected separately. Based on the discharge voltage characteristics of the distribution cabinet, the discharge fault detection and processing of the distribution cabinet is performed to obtain voltage-side distribution cabinet discharge fault detection data. Based on the discharge ultrasonic characteristics of the distribution cabinet, the discharge fault detection and processing of the distribution cabinet discharge is performed to obtain ultrasonic-side distribution cabinet discharge fault detection data.

[0067] Real-time cabinet current data and real-time electromagnetic wave frequency data inside the distribution cabinet are collected separately. Based on the discharge current characteristics of the distribution cabinet, discharge fault detection and processing are performed to obtain current-side discharge fault detection data. Based on the electromagnetic wave characteristics of the distribution cabinet discharge, discharge fault detection and processing are performed to obtain electromagnetic wave-side discharge fault detection data. Real-time chemical gas characteristic data and real-time temperature data inside the distribution cabinet are collected separately. Based on the chemical gas characteristics generated by the discharge of the distribution cabinet, discharge fault detection and processing are performed to obtain chemical gas-side discharge fault detection data. Based on the temperature characteristics of the discharge of the distribution cabinet, discharge fault detection and processing are performed to obtain temperature-side discharge fault detection data.

[0068] The probability level of discharge faults in the distribution cabinet is analyzed and processed to obtain the analysis data of the discharge fault occurrence level of the distribution cabinet, and the discharge fault detection result feedback operation of the distribution cabinet is executed.

[0069] For further details, please refer to Figures 1-2 The following steps are taken: Real-time cabinet voltage data and real-time ultrasonic frequency data inside the distribution cabinet are collected; discharge fault detection and processing of the distribution cabinet based on the discharge voltage characteristics are performed to obtain voltage-side distribution cabinet discharge fault detection data; discharge fault detection and processing of the distribution cabinet based on the ultrasonic discharge characteristics are performed to obtain ultrasonic-side distribution cabinet discharge fault detection data.

[0070] Step 11: Collect voltage data on the surface of the target power distribution cabinet online using a TEV sensor array, and generate real-time cabinet voltage data in millivolts; collect ultrasonic signal frequency data inside the target power distribution cabinet online using an ultrasonic sensor, and generate real-time ultrasonic frequency data inside the cabinet in hertz.

[0071] Step 12: Based on the real-time cabinet voltage data and the standard discharge voltage data matrix of the distribution cabinet, perform the discharge fault detection processing of the distribution cabinet to obtain the voltage-side distribution cabinet discharge fault detection data.

[0072] Step 13: Based on the real-time ultrasonic frequency data inside the distribution cabinet and the standard discharge ultrasonic frequency data matrix of the distribution cabinet, perform discharge fault detection processing on the distribution cabinet to obtain ultrasonic side discharge fault detection data of the distribution cabinet.

[0073] The discharge fault detection and processing of the distribution cabinet is performed based on the real-time cabinet voltage data and the standard discharge voltage data matrix of the distribution cabinet discharge fault. The process to obtain the voltage-side distribution cabinet discharge fault detection data includes the following steps:

[0074] Step 121: Establish a standard discharge voltage data matrix for power distribution cabinet discharge faults. ,in Indicates the first The standard discharge voltage data for a distribution cabinet discharge fault represents the induced transient voltage to ground generated on the surface of the standard distribution cabinet when the target distribution cabinet experiences a discharge fault. The unit of the standard discharge voltage data for a distribution cabinet discharge fault is millivolts.

[0075] Step 122: Combine the real-time cabinet voltage data of the distribution cabinet with the standard discharge voltage data matrix for discharge faults in the distribution cabinet. Standard discharge voltage data for discharge faults in central distribution cabinets Voltage data matching is performed, and discharge fault detection data for voltage-side distribution cabinets is constructed based on the voltage data matching results.

[0076] When the real-time cabinet voltage data of the power distribution cabinet is different from the standard discharge voltage data of the power distribution cabinet for discharge faults... When voltage data matching is successful, it indicates that a discharge fault has occurred inside the target distribution cabinet, and the discharge fault detection data of the distribution cabinet on the output voltage side indicates that a discharge fault has occurred.

[0077] When the real-time cabinet voltage data of the power distribution cabinet is different from the standard discharge voltage data of the power distribution cabinet for discharge faults... If no voltage data match is found, it indicates that no discharge fault has occurred inside the target distribution cabinet, and the discharge fault detection data of the output voltage side distribution cabinet will show that no discharge fault has occurred.

[0078] Based on the real-time ultrasonic frequency data inside the distribution cabinet and the standard discharge ultrasonic frequency data matrix of the distribution cabinet, discharge fault detection processing of the distribution cabinet is performed to obtain ultrasonic side distribution cabinet discharge fault detection data, including the following steps:

[0079] Step 131: Establish a standard discharge ultrasonic frequency data matrix for power distribution cabinet discharge faults. ,in Indicates the first Standard discharge ultrasonic frequency data for a power distribution cabinet discharge fault: This data represents the frequency of ultrasonic signals generated inside a standard power distribution cabinet when a discharge fault occurs in the target power distribution cabinet. The unit of the standard discharge ultrasonic frequency data for a power distribution cabinet discharge fault is Hertz.

[0080] Step 132: Combine the real-time ultrasonic frequency data inside the distribution cabinet with the standard discharge ultrasonic frequency data matrix for discharge faults in the distribution cabinet. Standard discharge ultrasonic frequency data for electrical distribution cabinet discharge faults Perform ultrasonic frequency data matching, and construct ultrasonic side power distribution cabinet discharge fault detection data based on the ultrasonic frequency data matching results;

[0081] When the real-time ultrasonic frequency data inside the distribution cabinet matches the standard discharge ultrasonic frequency data for the distribution cabinet's discharge fault... When the ultrasonic frequency data matching is successful, it indicates that a discharge fault has occurred inside the target power distribution cabinet. The output ultrasonic side power distribution cabinet discharge fault detection data indicates that a discharge fault has occurred.

[0082] When the real-time ultrasonic frequency data inside the distribution cabinet matches the standard discharge ultrasonic frequency data for the distribution cabinet's discharge fault... If no matching of ultrasonic frequency data is found, it indicates that no discharge fault has occurred inside the target distribution cabinet, and the output ultrasonic side distribution cabinet discharge fault detection data will show that no discharge fault has occurred.

[0083] The system accurately collects real-time cabinet voltage parameters and real-time ultrasonic signal frequency parameters within the distribution cabinet using a TEV sensor array and ultrasonic sensors. Based on the real-time cabinet voltage data and the real-time ultrasonic signal frequency data, combined with data analysis and big data-based standard discharge voltage and ultrasonic frequency data for distribution cabinet discharge faults, accurate detection of discharge faults in the distribution cabinet is achieved on both the voltage and ultrasonic sides. This enables accurate monitoring of discharge faults in high and low voltage distribution cabinets by fusing multi-source voltage and ultrasonic data and combining big data, thereby improving the accuracy of discharge detection in high and low voltage distribution cabinets.

[0084] For further details, please refer to Figures 1-2The following steps are involved: Real-time cabinet current data and real-time electromagnetic wave frequency data within the distribution cabinet are collected. Based on the discharge current characteristics, discharge fault detection and processing are performed on the distribution cabinet to obtain current-side discharge fault detection data. Based on the electromagnetic wave characteristics of the discharge, discharge fault detection and processing are performed on the electromagnetic wave side to obtain electromagnetic wave side discharge fault detection data. Real-time chemical gas characteristic data and real-time temperature data within the distribution cabinet are also collected. Based on the chemical gas characteristics generated by the discharge, discharge fault detection and processing are performed on the chemical gas side to obtain chemical gas side discharge fault detection data. Finally, based on the temperature characteristics of the discharge, discharge fault detection and processing are performed on the temperature side to obtain temperature side discharge fault detection data.

[0085] Step 21: Collect current data on the surface of the target distribution cabinet online using a high-frequency current transformer, and generate real-time cabinet current data in milliamperes; collect electromagnetic wave signal frequency data inside the target distribution cabinet online using a UHF sensor, and generate real-time electromagnetic wave frequency data inside the distribution cabinet in Hertz.

[0086] Step 22: Perform discharge fault detection processing on the distribution cabinet based on the real-time cabinet current data and the standard discharge current data matrix of the distribution cabinet to obtain the current-side discharge fault detection data; perform discharge fault detection processing on the distribution cabinet based on the real-time internal electromagnetic wave frequency data and the standard discharge electromagnetic wave frequency data matrix of the distribution cabinet to obtain the electromagnetic wave-side discharge fault detection data.

[0087] Step 23: Collect online data on the types and concentrations of chemical gases inside the target distribution cabinet using chemical gas sensors, and generate real-time chemical gas characteristic data for the distribution cabinet. The concentration unit of the real-time chemical gas characteristic data for the distribution cabinet is microliters per liter. The chemical gas sensors include hydrogen sensors, carbon monoxide sensors, hydrogen sulfide sensors, and sulfur dioxide sensors. Collect online temperature data of the space inside the target distribution cabinet using an infrared thermal imager, and generate real-time temperature data for the distribution cabinet. The unit of the real-time temperature data for the distribution cabinet is degrees Celsius.

[0088] Step 24: Perform discharge fault detection processing on the distribution cabinet based on the real-time internal chemical gas characteristic data and the standard discharge chemical gas characteristic data matrix of the distribution cabinet to obtain chemical gas-side distribution cabinet discharge fault detection data; perform discharge fault detection processing on the distribution cabinet based on the real-time internal temperature data and the standard discharge temperature data matrix of the distribution cabinet to obtain temperature-side distribution cabinet discharge fault detection data.

[0089] The discharge fault detection data of the distribution cabinet is obtained by performing discharge fault detection processing based on the real-time cabinet current data and the standard discharge current data matrix of the distribution cabinet, and the electromagnetic wave side discharge fault detection data is obtained by performing discharge fault detection processing based on the real-time internal electromagnetic wave frequency data and the standard discharge electromagnetic wave frequency data matrix of the distribution cabinet, including the following steps:

[0090] Step 221: Establish standard discharge current data matrices for discharge faults in distribution cabinets. and the standard discharge electromagnetic wave frequency data matrix for power distribution cabinet discharge faults ;in Indicates the first The standard discharge current data for a distribution cabinet discharge fault represents the induced transient current data generated on the surface of a standard distribution cabinet when a discharge fault occurs in the target distribution cabinet; the unit of the standard discharge current data is milliamperes (mA). Indicates the first The standard discharge electromagnetic wave frequency data for a power distribution cabinet discharge fault represents the frequency data of electromagnetic wave signals generated inside a standard power distribution cabinet when a discharge fault occurs in the target power distribution cabinet; the unit of the standard discharge electromagnetic wave frequency data for a power distribution cabinet discharge fault is Hertz.

[0091] Step 222: Combine the real-time cabinet current data of the distribution cabinet with the standard discharge current data matrix of the distribution cabinet for discharge faults. Standard discharge current data for discharge faults in central distribution cabinets Perform current data matching, and construct discharge fault detection data for the current-side distribution cabinet based on the current data matching results;

[0092] When the real-time cabinet current data of the distribution cabinet is different from the standard discharge current data of the distribution cabinet for discharge faults When the current data matching is successful, it indicates that a discharge fault has occurred inside the target distribution cabinet, and the discharge fault detection data of the distribution cabinet on the output current side indicates that a discharge fault has occurred.

[0093] When the real-time cabinet current data of the distribution cabinet is different from the standard discharge current data of the distribution cabinet for discharge faults If the current data fails to match, it means that no discharge fault has occurred inside the target distribution cabinet, and the discharge fault detection data of the distribution cabinet on the output current side is no discharge fault.

[0094] Step 223: Combine the real-time electromagnetic wave frequency data inside the distribution cabinet with the standard discharge electromagnetic wave frequency data matrix for discharge faults in the distribution cabinet. Standard discharge electromagnetic wave frequency data for central distribution cabinet discharge fault Electromagnetic wave frequency data matching is performed, and discharge fault detection data of the electromagnetic wave side distribution cabinet is constructed based on the electromagnetic wave frequency data matching results.

[0095] When the real-time electromagnetic wave frequency data inside the distribution cabinet matches the standard discharge electromagnetic wave frequency data for the distribution cabinet's discharge fault... When electromagnetic wave frequency data matching is successful, it indicates that a discharge fault has occurred inside the target distribution cabinet. The output electromagnetic wave side distribution cabinet discharge fault detection data indicates that a discharge fault has occurred.

[0096] When the real-time electromagnetic wave frequency data inside the distribution cabinet matches the standard discharge electromagnetic wave frequency data for the distribution cabinet's discharge fault... If no matching of electromagnetic wave frequency data is found, it indicates that no discharge fault has occurred inside the target distribution cabinet. Therefore, the discharge fault detection data of the distribution cabinet on the output electromagnetic wave side will show that no discharge fault has occurred.

[0097] Discharge fault detection data for the distribution cabinet is obtained by processing real-time internal chemical gas characteristic data and standard discharge chemical gas characteristic data matrix based on the distribution cabinet discharge fault. Discharge fault detection data for the distribution cabinet on the chemical gas side is obtained by processing real-time internal temperature data and standard discharge temperature data matrix based on the distribution cabinet discharge fault. The temperature-side discharge fault detection data for the distribution cabinet is obtained through the following steps:

[0098] Step 241: Establish standard discharge chemical gas characteristic data matrices for each distribution cabinet discharge fault. and the standard discharge temperature data matrix for electrical distribution cabinet discharge faults ;in Indicates the first The standard discharge chemical gas characteristic data for a distribution cabinet discharge fault indicates the types and concentrations of chemical gases released by the insulation material inside the standard distribution cabinet under discharge conditions when the target distribution cabinet experiences a discharge fault. The concentration unit for the standard discharge chemical gas characteristic data is microliters per liter. Indicates the first Standard discharge temperature data for a power distribution cabinet discharge fault: This data represents the localized high temperature characteristics generated inside the standard power distribution cabinet under the action of discharge when the target power distribution cabinet experiences a discharge fault. The unit of the standard discharge temperature data for a power distribution cabinet discharge fault is degrees Celsius.

[0099] Step 242: Combine the real-time chemical gas characteristic data inside the distribution cabinet with the standard discharge chemical gas characteristic data matrix of the distribution cabinet for discharge faults. Standard discharge chemical gas characteristic data for electrical distribution cabinet discharge faults Perform chemical gas characteristic information matching, and construct chemical gas-side power distribution cabinet discharge fault detection data based on the chemical gas characteristic information matching results;

[0100] When the real-time chemical gas characteristic data inside the distribution cabinet matches the standard discharge chemical gas characteristic data for the distribution cabinet's discharge fault... When the chemical gas characteristic information matching is successful, it indicates that a discharge fault has occurred inside the target distribution cabinet. The output chemical gas side distribution cabinet discharge fault detection data indicates that a discharge fault has occurred.

[0101] When the real-time chemical gas characteristic data inside the distribution cabinet matches the standard discharge chemical gas characteristic data for the distribution cabinet's discharge fault... If no matching of chemical gas characteristic information is found, it indicates that no discharge fault has occurred inside the target distribution cabinet, and the output discharge fault detection data of the chemical gas side distribution cabinet is no discharge fault.

[0102] Step 243: Combine the real-time internal temperature data of the distribution cabinet with the standard discharge temperature data matrix for discharge faults in the distribution cabinet. Standard discharge temperature data for discharge faults in central distribution cabinets Temperature data matching is performed, and discharge fault detection data of the temperature-side distribution cabinet is constructed based on the temperature data matching results.

[0103] When the real-time internal temperature data of the distribution cabinet matches the standard discharge temperature data for a discharge fault in the distribution cabinet... When temperature data matching is successful, it indicates that a discharge fault has occurred inside the target distribution cabinet, and the output temperature side distribution cabinet discharge fault detection data indicates that a discharge fault has occurred.

[0104] When the real-time internal temperature data of the distribution cabinet matches the standard discharge temperature data for a discharge fault in the distribution cabinet... If no temperature data is successfully matched, it indicates that no discharge fault has occurred inside the target distribution cabinet, and the output temperature side distribution cabinet discharge fault detection data will show that no discharge fault has occurred.

[0105] Real-time dynamic acquisition of the distribution cabinet's cabinet current parameters and electromagnetic wave signal frequency parameters within the cabinet is achieved using high-frequency current transformers and UHF sensors. Based on this data, combined with data analysis and standard discharge current and electromagnetic wave frequency data for distribution cabinet discharge faults set using big data science, precise detection of discharge faults on both the current and electromagnetic wave sides is realized. This achieves multi-source data fusion of current and electromagnetic waves, combined with big data science analysis of high and low voltage distribution cabinet discharge faults. Furthermore, real-time acquisition of chemical gas characteristic data and real-time cabinet temperature data is achieved using chemical gas sensors and infrared thermal imagers. Data; based on real-time internal chemical gas characteristic data and real-time internal temperature data of the distribution cabinet, combined with data analysis and standard discharge chemical gas characteristic data and standard discharge temperature data of the distribution cabinet based on big data storage, discharge faults of the distribution cabinet on both the chemical gas side and temperature side are detected, resulting in chemical gas side discharge fault detection data; comprehensive detection of distribution cabinet discharge faults is performed based on real-time internal temperature data and standard discharge temperature data of the distribution cabinet; achieving intelligent and reliable monitoring of high and low voltage distribution cabinet discharge faults based on the fusion of multi-source data (voltage, ultrasound, current, electromagnetic waves, chemical gases, and temperature) and big data, thereby improving the accuracy and quality of discharge detection for high and low voltage distribution cabinets.

[0106] For further details, please refer to Figures 1-2 The process of analyzing and processing the probability level of discharge faults in distribution cabinets, obtaining discharge fault occurrence level analysis data, and performing discharge fault detection result feedback includes the following steps:

[0107] Step 31: Establish a standard discharge fault occurrence level and discharge fault detection information matrix for distribution cabinets. ,in This represents the standard discharge fault detection information corresponding to the first type of discharge fault occurrence level of the distribution cabinet; where the first type of discharge fault occurrence level indicates the probability of a discharge fault occurring in the distribution cabinet. Standard for Discharge Fault Occurrence Level in Distribution Cabinets; Discharge Fault Detection Information This indicates the probability level of a discharge fault detected on any one of the voltage, ultrasonic, current, electromagnetic wave, chemical gas, and temperature sides of the distribution cabinet. This indicates the standard discharge fault detection information corresponding to the second type of discharge fault occurrence level of the distribution cabinet; where the second type of discharge fault occurrence level represents the probability of a discharge fault occurring in the distribution cabinet. Standard for Discharge Fault Occurrence Level in Distribution Cabinets; Discharge Fault Detection Information This indicates the probability level of a discharge fault detected on any two of the following sides of the distribution cabinet: voltage side, ultrasonic side, current side, electromagnetic wave side, chemical gas side, and temperature side. This indicates the standard discharge fault detection information corresponding to the third type of discharge fault occurrence level of the distribution cabinet; where the third type of discharge fault occurrence level represents the probability of a discharge fault occurring in the distribution cabinet. Standard for Discharge Fault Occurrence Level in Distribution Cabinets; Discharge Fault Detection Information This indicates the probability level of a discharge fault detected on any three of the following three sides of the distribution cabinet: voltage side, ultrasonic side, current side, electromagnetic wave side, chemical gas side, and temperature side. This indicates the standard discharge fault detection information corresponding to the fourth type of discharge fault occurrence level of the distribution cabinet; where the fourth type of discharge fault occurrence level represents the probability of a discharge fault occurring in the distribution cabinet. Standard for Discharge Fault Occurrence Level in Distribution Cabinets; Discharge Fault Detection Information This indicates the probability level of a discharge fault detected on any four of the following four sides of the distribution cabinet: voltage side, ultrasonic side, current side, electromagnetic wave side, chemical gas side, and temperature side. This indicates the standard discharge fault detection information corresponding to the fifth type of discharge fault occurrence level of the distribution cabinet; where the fifth type of discharge fault occurrence level represents the probability of a discharge fault occurring in the distribution cabinet. Standard for Discharge Fault Occurrence Level in Distribution Cabinets; Discharge Fault Detection Information This indicates the probability level of a discharge fault detected on any five of the following sides of the distribution cabinet: voltage side, ultrasonic side, current side, electromagnetic wave side, chemical gas side, and temperature side. This indicates the standard discharge fault detection information corresponding to the sixth type of discharge fault occurrence level of the distribution cabinet; where the sixth type of discharge fault occurrence level represents the probability of a discharge fault occurring in the distribution cabinet. Standard for Discharge Fault Occurrence Level in Distribution Cabinets; Discharge Fault Detection Information This indicates the probability level of a discharge fault in the distribution cabinet, corresponding to the detection of discharge faults on the voltage side, ultrasonic side, current side, electromagnetic wave side, chemical gas side, and temperature side.

[0108] Step 32: Combine the discharge fault detection data from the voltage-side distribution cabinet, ultrasonic-side distribution cabinet, current-side distribution cabinet, electromagnetic wave-side distribution cabinet, chemical gas-side distribution cabinet, and temperature-side distribution cabinet with the discharge fault detection information matrix based on the standard discharge fault occurrence level of the distribution cabinet. The system matches the discharge fault detection results of the distribution cabinet with the standard discharge fault occurrence level information of the distribution cabinet. It searches for the text information of the discharge fault occurrence level corresponding to the standard discharge fault detection information of the distribution cabinet that matches the discharge fault detection data of the voltage side, ultrasonic side, current side, electromagnetic wave side, chemical gas side, and temperature side. The system then generates the discharge fault occurrence level analysis data of the distribution cabinet after data identification.

[0109] Step 33: Transmit the discharge fault detection data of the voltage-side distribution cabinet, the ultrasonic-side distribution cabinet, the current-side distribution cabinet, the electromagnetic wave-side distribution cabinet, the chemical gas-side distribution cabinet, the temperature-side distribution cabinet, and the distribution cabinet discharge fault occurrence level analysis data to the distribution cabinet safety supervision platform through the Internet of Things communication network, and output the results of the distribution cabinet discharge fault detection on the display screen to perform the feedback operation of the distribution cabinet discharge fault detection results.

[0110] Based on multi-dimensional discharge detection results from voltage, ultrasonic, current, electromagnetic wave, chemical gas, and temperature sides, this system performs digital and precise analysis of the discharge fault occurrence level of distribution cabinets. It enables accurate multi-parameter analysis of the probability of discharge faults in high and low voltage distribution cabinets. Simultaneously, by combining the distribution cabinet safety supervision platform and display screen, it promptly and safely executes the feedback of discharge fault detection results, achieving highly reliable detection and visualized feedback for high and low voltage distribution cabinet discharge faults. This improves the scientific, refined monitoring and visualized intelligent management of high and low voltage distribution cabinet discharge detection.

[0111] Example 2: Please refer to Figures 1-2 A big data-based intelligent detection system for high and low voltage switchgear discharge is used to realize a big data-based intelligent detection method for high and low voltage switchgear discharge. The system includes a high and low voltage switchgear discharge fault voltage ultrasonic feature detection module, a high and low voltage switchgear discharge fault current electromagnetic wave feature detection module, a high and low voltage switchgear discharge fault chemical gas temperature feature detection module, and a high and low voltage switchgear discharge fault assessment module.

[0112] The high and low voltage distribution cabinet discharge fault voltage ultrasonic feature detection module includes a distribution cabinet real-time cabinet voltage acquisition unit, a distribution cabinet real-time cabinet internal ultrasonic frequency acquisition unit, a distribution cabinet discharge fault standard discharge voltage storage unit, a distribution cabinet discharge fault standard discharge ultrasonic frequency storage unit, a voltage-side distribution cabinet discharge fault detection unit, and an ultrasonic-side distribution cabinet discharge fault detection unit.

[0113] The distribution cabinet comprises the following components: a real-time cabinet voltage acquisition unit, which acquires real-time cabinet voltage data via a TEV sensor array; a real-time internal ultrasonic frequency acquisition unit, which acquires real-time internal ultrasonic frequency data via an ultrasonic sensor; a standard discharge voltage storage unit, which stores standard discharge voltage data for distribution cabinet discharge faults; a standard discharge ultrasonic frequency storage unit, which stores standard discharge ultrasonic frequency data for distribution cabinet discharge faults; a voltage-side distribution cabinet discharge fault detection unit, which performs discharge fault detection processing based on the real-time cabinet voltage data and the standard discharge voltage data to obtain voltage-side distribution cabinet discharge fault detection data; and an ultrasonic-side distribution cabinet discharge fault detection unit, which performs discharge fault detection processing based on the real-time internal ultrasonic frequency data and the standard discharge ultrasonic frequency data to obtain ultrasonic-side distribution cabinet discharge fault detection data.

[0114] The high and low voltage switchgear discharge fault current electromagnetic wave characteristic detection module includes a switchgear real-time cabinet current acquisition unit, a switchgear real-time cabinet internal electromagnetic wave frequency acquisition unit, a switchgear discharge fault standard discharge current storage unit, a switchgear discharge fault standard discharge electromagnetic wave frequency storage unit, a current-side switchgear discharge fault detection unit, and an electromagnetic wave-side switchgear discharge fault detection unit.

[0115] The distribution cabinet comprises the following components: a real-time cabinet current acquisition unit, which acquires real-time cabinet current data via a high-frequency current transformer; a real-time internal electromagnetic wave frequency acquisition unit, which acquires real-time internal electromagnetic wave frequency data via a UHF sensor; a standard discharge current storage unit for standard discharge faults, which stores standard discharge current data for discharge faults; a standard discharge electromagnetic wave frequency storage unit for standard discharge faults, which stores standard discharge electromagnetic wave frequency data for discharge faults; a current-side distribution cabinet discharge fault detection unit, which performs discharge fault detection processing based on the real-time cabinet current data and the standard discharge current data to obtain current-side distribution cabinet discharge fault detection data; and an electromagnetic wave-side distribution cabinet discharge fault detection unit, which performs discharge fault detection processing based on the real-time internal electromagnetic wave frequency data and the standard discharge electromagnetic wave frequency data to obtain electromagnetic wave-side distribution cabinet discharge fault detection data.

[0116] The high and low voltage switchgear discharge fault chemical gas temperature characteristic detection module includes a switchgear real-time cabinet internal chemical gas characteristic acquisition unit, a switchgear real-time cabinet internal temperature acquisition unit, a switchgear discharge fault standard discharge chemical gas characteristic storage unit, a switchgear discharge fault standard discharge temperature storage unit, a switchgear discharge fault detection unit on the chemical gas side, and a switchgear discharge fault detection unit on the temperature side.

[0117] The system includes: a real-time internal chemical gas characteristic acquisition unit for the distribution cabinet, which acquires real-time internal chemical gas characteristic data through a chemical gas sensor; a real-time internal temperature acquisition unit for the distribution cabinet, which acquires real-time internal temperature data through an infrared thermal imager; a standard discharge chemical gas characteristic storage unit for the distribution cabinet, used to store standard discharge chemical gas characteristic data for the distribution cabinet discharge fault; a standard discharge temperature storage unit for the distribution cabinet discharge fault, used to store standard discharge temperature data for the distribution cabinet discharge fault; a chemical gas-side distribution cabinet discharge fault detection unit, which performs discharge fault detection processing based on the real-time internal chemical gas characteristic data and the standard discharge chemical gas characteristic data for the distribution cabinet discharge fault, to obtain chemical gas-side distribution cabinet discharge fault detection data; and a temperature-side distribution cabinet discharge fault detection unit, which performs discharge fault detection processing based on the real-time internal temperature data and the standard discharge temperature data for the distribution cabinet discharge fault, to obtain temperature-side distribution cabinet discharge fault detection data.

[0118] The high and low voltage switchgear discharge fault assessment module includes a switchgear discharge fault occurrence level standard discharge fault detection rule information storage unit, a switchgear discharge fault occurrence level analysis unit, and a switchgear discharge fault detection feedback unit.

[0119] The system includes: a discharge fault occurrence level standard discharge fault detection information storage unit for storing discharge fault detection information for distribution cabinets; a discharge fault occurrence level analysis unit for performing probability level analysis of discharge faults based on voltage-side, ultrasonic-side, current-side, electromagnetic-wave-side, chemical-gas-side, and temperature-side discharge fault detection data, along with the discharge fault occurrence level standard discharge fault detection information, to obtain discharge fault occurrence level analysis data; and a discharge fault detection feedback unit for performing discharge fault detection result feedback operations based on the voltage-side, ultrasonic-side, current-side, electromagnetic-wave-side, chemical-gas-side, and temperature-side discharge fault detection data, combined with the distribution cabinet safety supervision platform and display screen.

[0120] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A smart discharge detection method for high and low voltage switchgear based on big data, characterized in that, The method includes the following steps: Real-time cabinet voltage data and real-time ultrasonic frequency data inside the distribution cabinet are collected separately. Based on the discharge voltage characteristics of the distribution cabinet, the discharge fault detection and processing of the distribution cabinet is performed to obtain voltage-side distribution cabinet discharge fault detection data. Based on the discharge ultrasonic characteristics of the distribution cabinet, the discharge fault detection and processing of the distribution cabinet discharge is performed to obtain ultrasonic-side distribution cabinet discharge fault detection data. Real-time cabinet current data and real-time electromagnetic wave frequency data inside the distribution cabinet are collected separately; based on the discharge current characteristics of the distribution cabinet, discharge fault detection and processing of the distribution cabinet are performed to obtain current-side distribution cabinet discharge fault detection data. Based on the characteristics of electromagnetic waves emitted during power distribution cabinet discharge, discharge faults in the power distribution cabinet are detected and processed to obtain electromagnetic wave-side discharge fault detection data. Real-time chemical gas characteristic data and real-time temperature data inside the power distribution cabinet are collected. Based on the characteristics of the chemical gases generated by the discharge of the power distribution cabinet, discharge faults in the power distribution cabinet are detected and processed to obtain chemical gas-side discharge fault detection data. Based on the temperature characteristics of the discharge of the power distribution cabinet, discharge faults in the power distribution cabinet are detected and processed to obtain temperature-side discharge fault detection data. The probability level of discharge faults in the distribution cabinet is analyzed and processed to obtain the analysis data of the discharge fault occurrence level of the distribution cabinet, and the discharge fault detection result feedback operation of the distribution cabinet is executed.

2. The intelligent discharge detection method for high and low voltage distribution cabinets based on big data according to claim 1, characterized in that: Real-time cabinet voltage data and real-time ultrasonic frequency data inside the distribution cabinet are collected separately. Based on the discharge voltage characteristics of the distribution cabinet, discharge fault detection and processing are performed to obtain voltage-side distribution cabinet discharge fault detection data. Based on the ultrasonic discharge characteristics of the distribution cabinet, discharge fault detection and processing are performed to obtain ultrasonic-side distribution cabinet discharge fault detection data. This includes the following steps: The voltage data on the surface of the target power distribution cabinet is collected online using a TEV sensor array, and real-time cabinet voltage data is generated. The ultrasonic frequency data inside the target power distribution cabinet is collected online using an ultrasonic sensor, and real-time ultrasonic frequency data inside the cabinet is generated. Based on the real-time cabinet voltage data of the distribution cabinet and the standard discharge voltage data matrix of the distribution cabinet discharge fault, the discharge fault detection processing of the distribution cabinet is performed to obtain the voltage-side distribution cabinet discharge fault detection data. Based on the real-time ultrasonic frequency data inside the distribution cabinet and the standard discharge ultrasonic frequency data matrix of the distribution cabinet, discharge fault detection processing of the distribution cabinet is performed to obtain ultrasonic side distribution cabinet discharge fault detection data.

3. The intelligent discharge detection method for high and low voltage distribution cabinets based on big data according to claim 2, characterized in that: Based on the real-time cabinet voltage data and the standard discharge voltage data matrix of the distribution cabinet discharge fault, the discharge fault detection processing of the distribution cabinet is performed to obtain the voltage-side distribution cabinet discharge fault detection data, including the following steps: Establish a standard discharge voltage data matrix for power distribution cabinet discharge faults. The include ;in Indicates the first Standard discharge voltage data for discharge faults in individual power distribution cabinets; The real-time cabinet voltage data of the power distribution cabinet is compared with the... The above Voltage data matching is performed, and discharge fault detection data for voltage-side distribution cabinets is constructed based on the voltage data matching results. When the real-time cabinet voltage data of the power distribution cabinet is consistent with the If voltage data matching is successful, the output of the voltage-side distribution cabinet discharge fault detection data indicates that a discharge fault has occurred. When the real-time cabinet voltage data of the power distribution cabinet is consistent with the If no voltage data matching is successful, the output of the voltage-side distribution cabinet discharge fault detection data will be "no discharge fault has occurred".

4. The intelligent discharge detection method for high and low voltage distribution cabinets based on big data according to claim 3, characterized in that: Based on the real-time ultrasonic frequency data inside the distribution cabinet and the standard discharge ultrasonic frequency data matrix of the distribution cabinet, the discharge fault detection processing of the distribution cabinet is performed to obtain the ultrasonic side distribution cabinet discharge fault detection data, including the following steps: Establish a standard discharge ultrasonic frequency data matrix for power distribution cabinet discharge faults. The include ;in Indicates the first Standard discharge ultrasonic frequency data for each power distribution cabinet discharge fault. The real-time ultrasonic frequency data inside the distribution cabinet is compared with the data from the distribution cabinet. The above Perform ultrasonic frequency data matching, and construct ultrasonic side power distribution cabinet discharge fault detection data based on the ultrasonic frequency data matching results; When the real-time ultrasonic frequency data inside the distribution cabinet is consistent with the... When the ultrasonic frequency data matching is successful, the output of the ultrasonic side power distribution cabinet discharge fault detection data indicates that a discharge fault has occurred. When the real-time ultrasonic frequency data inside the distribution cabinet is consistent with the... If no matching of ultrasonic frequency data is found, the output of the ultrasonic side power distribution cabinet discharge fault detection data will be "no discharge fault has occurred".

5. The intelligent discharge detection method for high and low voltage distribution cabinets based on big data according to claim 4, characterized in that: Real-time cabinet current data and real-time electromagnetic wave frequency data inside the distribution cabinet are collected separately; based on the discharge current characteristics of the distribution cabinet, discharge fault detection and processing of the distribution cabinet are performed to obtain current-side distribution cabinet discharge fault detection data. The detection and processing of discharge faults in power distribution cabinets are performed based on the characteristics of electromagnetic waves emitted during discharge, resulting in electromagnetic wave-side discharge fault detection data. Real-time chemical gas characteristic data and real-time temperature data inside the power distribution cabinet are collected. Discharge faults are then detected and processed based on the characteristics of the chemical gases generated during discharge, resulting in chemical gas-side discharge fault detection data. Finally, discharge faults are detected and processed based on the temperature characteristics of the discharge, resulting in temperature-side discharge fault detection data. The process includes the following steps: The current data on the surface of the target distribution cabinet is collected online by a high-frequency current transformer, and real-time cabinet current data is generated; the frequency data of electromagnetic wave signals inside the target distribution cabinet is collected online by a UHF sensor, and real-time electromagnetic wave frequency data inside the cabinet is generated. Based on the real-time cabinet current data and the standard discharge current data matrix of the distribution cabinet, discharge fault detection processing is performed to obtain current-side distribution cabinet discharge fault detection data; based on the real-time cabinet electromagnetic wave frequency data and the standard discharge electromagnetic wave frequency data matrix of the distribution cabinet, discharge fault detection processing is performed to obtain electromagnetic wave-side distribution cabinet discharge fault detection data. The chemical gas type and concentration data inside the target distribution cabinet are collected online by a chemical gas sensor, and real-time chemical gas characteristic data inside the distribution cabinet are generated; the temperature data inside the target distribution cabinet is collected online by an infrared thermal imager, and real-time temperature data inside the distribution cabinet is generated. Based on the real-time internal chemical gas characteristic data of the distribution cabinet and the standard discharge chemical gas characteristic data matrix of the distribution cabinet discharge fault, discharge fault detection processing of the distribution cabinet is performed to obtain chemical gas-side distribution cabinet discharge fault detection data; based on the real-time internal temperature data of the distribution cabinet and the standard discharge temperature data matrix of the distribution cabinet discharge fault, discharge fault detection processing of the distribution cabinet is performed to obtain temperature-side distribution cabinet discharge fault detection data.

6. The intelligent discharge detection method for high and low voltage distribution cabinets based on big data according to claim 5, characterized in that: The process of detecting discharge faults in the distribution cabinet based on the real-time cabinet current data and the standard discharge current data matrix of the distribution cabinet is used to obtain current-side distribution cabinet discharge fault detection data. The process of detecting discharge faults in the distribution cabinet based on the real-time internal electromagnetic wave frequency data and the standard discharge electromagnetic wave frequency data matrix of the distribution cabinet includes the following steps: Establish standard discharge current data matrices for each distribution cabinet discharge fault. and the standard discharge electromagnetic wave frequency data matrix for power distribution cabinet discharge faults The include ;in Indicates the first Standard discharge current data for each distribution cabinet discharge fault; the aforementioned include ;in Indicates the first Standard discharge electromagnetic wave frequency data for each power distribution cabinet discharge fault; The real-time cabinet current data of the power distribution cabinet is compared with the... The above Perform current data matching, and construct discharge fault detection data for the current-side distribution cabinet based on the current data matching results; When the real-time cabinet current data of the distribution cabinet is consistent with the If the current data matching is successful, the output of the discharge fault detection data of the current-side distribution cabinet is that a discharge fault has occurred. When the real-time cabinet current data of the distribution cabinet is consistent with the If no matching of current data is found, the output of the discharge fault detection data of the current-side distribution cabinet is "no discharge fault has occurred". The real-time electromagnetic wave frequency data inside the distribution cabinet is compared with the data from the distribution cabinet. The above Electromagnetic wave frequency data matching is performed, and discharge fault detection data of the electromagnetic wave side distribution cabinet is constructed based on the electromagnetic wave frequency data matching results. When the real-time electromagnetic wave frequency data inside the distribution cabinet is consistent with the... When the electromagnetic wave frequency data matching is successful, the output of the electromagnetic wave side distribution cabinet discharge fault detection data indicates that a discharge fault has occurred. When the real-time electromagnetic wave frequency data inside the distribution cabinet is consistent with the... If no matching of electromagnetic wave frequency data is found, the output of the electromagnetic wave-side power distribution cabinet discharge fault detection data will be "no discharge fault has occurred".

7. The intelligent discharge detection method for high and low voltage distribution cabinets based on big data according to claim 6, characterized in that: Based on the real-time internal chemical gas characteristic data of the distribution cabinet and the standard discharge chemical gas characteristic data matrix of the distribution cabinet discharge fault, discharge fault detection processing of the distribution cabinet is performed to obtain chemical gas-side distribution cabinet discharge fault detection data; based on the real-time internal temperature data of the distribution cabinet and the standard discharge temperature data matrix of the distribution cabinet discharge fault, discharge fault detection processing of the distribution cabinet is performed to obtain temperature-side distribution cabinet discharge fault detection data, including the following steps: Establish a standard discharge chemical gas characteristic data matrix for each distribution cabinet discharge fault. and the standard discharge temperature data matrix for electrical distribution cabinet discharge faults The include ;in Indicates the first Standard discharge chemical gas characteristic data for each distribution cabinet discharge fault; the aforementioned include ;in Indicates the first Standard discharge temperature data for discharge faults in individual power distribution cabinets; The real-time chemical gas characteristic data inside the distribution cabinet is compared with the data from the... The above Perform chemical gas characteristic information matching, and construct chemical gas-side power distribution cabinet discharge fault detection data based on the chemical gas characteristic information matching results; When the real-time chemical gas characteristic data inside the distribution cabinet is consistent with the... When the chemical gas characteristic information matching is successful, the discharge fault detection data of the chemical gas side distribution cabinet is output as a discharge fault has occurred. When the real-time chemical gas characteristic data inside the distribution cabinet is consistent with the... If no matching of chemical gas characteristic information is found, the output of the discharge fault detection data of the chemical gas side distribution cabinet is "no discharge fault has occurred". The real-time internal temperature data of the distribution cabinet is compared with the... The above Temperature data matching is performed, and discharge fault detection data of the temperature-side distribution cabinet is constructed based on the temperature data matching results. When the real-time internal temperature data of the distribution cabinet is consistent with the... If the temperature data matching is successful, the output of the temperature-side power distribution cabinet discharge fault detection data is that a discharge fault has occurred. When the real-time internal temperature data of the distribution cabinet is consistent with the... If no matching of temperature data is found, the output of the temperature-side distribution cabinet discharge fault detection data will be "no discharge fault has occurred".

8. The intelligent discharge detection method for high and low voltage distribution cabinets based on big data according to claim 7, characterized in that: The process of analyzing and processing the probability level of discharge faults in distribution cabinets to obtain discharge fault occurrence level analysis data and performing discharge fault detection result feedback includes the following steps: Establish a standard for the occurrence level of discharge faults in distribution cabinets and a matrix of discharge fault detection information. The include , , , , and ;in This indicates the standard discharge fault detection information corresponding to the first type of discharge fault occurrence level of the distribution cabinet; where... This indicates the standard discharge fault detection information corresponding to the second type of discharge fault occurrence level of the distribution cabinet; where... This indicates the standard discharge fault detection information corresponding to the third type of discharge fault occurrence level of the distribution cabinet; among which... This indicates the standard discharge fault detection information corresponding to the fourth type of discharge fault occurrence level in the distribution cabinet; among which... This indicates the standard discharge fault detection information corresponding to the fifth level of discharge fault occurrence in the distribution cabinet; among which... This indicates the standard discharge fault detection information corresponding to the sixth type of discharge fault occurrence level of the distribution cabinet. The discharge fault detection data of the voltage-side distribution cabinet, the ultrasonic-side distribution cabinet, the current-side distribution cabinet, the electromagnetic wave-side distribution cabinet, the chemical gas-side distribution cabinet, and the temperature-side distribution cabinet are compared with the data from the above. The discharge fault occurrence level standard discharge fault detection information of the power distribution cabinet described in the figure is matched with the discharge fault detection result information of the power distribution cabinet. The text information of the discharge fault occurrence level corresponding to the discharge fault detection information of the power distribution cabinet discharge fault occurrence level standard discharge fault detection information that matches the discharge fault detection data of the voltage side power distribution cabinet, the ultrasonic side power distribution cabinet, the current side power distribution cabinet, the electromagnetic wave side power distribution cabinet, the chemical gas side power distribution cabinet, and the temperature side power distribution cabinet is searched and found. The discharge fault occurrence level analysis data of the power distribution cabinet is generated after data identification. The discharge fault detection data of the voltage-side distribution cabinet, the ultrasonic-side distribution cabinet, the current-side distribution cabinet, the electromagnetic wave-side distribution cabinet, the chemical gas-side distribution cabinet, the temperature-side distribution cabinet, and the distribution cabinet discharge fault occurrence level analysis data are transmitted to the distribution cabinet safety supervision platform through the Internet of Things communication network, and the results are output on the display screen to perform the distribution cabinet discharge fault detection result feedback operation.

9. A big data-based intelligent discharge detection system for high and low voltage distribution cabinets, used to implement the big data-based intelligent discharge detection method for high and low voltage distribution cabinets as described in any one of claims 1-8, characterized in that: The system includes a high- and low-voltage switchgear discharge fault voltage ultrasonic feature detection module, a high- and low-voltage switchgear discharge fault current electromagnetic wave feature detection module, a high- and low-voltage switchgear discharge fault chemical gas temperature feature detection module, and a high- and low-voltage switchgear discharge fault assessment module.

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