Equipment fault detection method and device and positioning system

Abstract

The invention discloses an equipment fault detection method and device and a positioning system, and relates to the field of fault detection, and the method comprises the steps: determining a noise suppression capability evaluation value of the positioning system according to the operation data of the positioning system and the environment data of a transformer substation; determining a positioning precision evaluation index of the positioning system according to the result data of the positioning system and the equipment state data of the positioning system; performing performance evaluation on the positioning system according to the operation process data, the noise suppression capability evaluation value and the positioning precision evaluation index of the positioning system; according to the invention, the operation state of the positioning system and the multi-source data of the environment can be automatically acquired and analyzed, then the working performance of the positioning system is evaluated and determined, if the performance meets the requirements, the system can accurately detect whether the gas insulated switchgear has a fault or not, the detection abnormity caused by the fault of the positioning system is avoided, and the reliability of the system is improved. And finally, the safety and the efficiency of the power system are improved.

Description

Technical Field

[0001] The present invention relates to the field of fault detection, and in particular to a method, a device and a positioning system for detecting equipment faults. Background Art

[0002] With the rapid development of my country's economy, the demand for electricity is growing, and the number and scale of substations are also expanding. In the operation of substations, GIS (gas insulated switchgear) is a key equipment, and its safe and stable operation is crucial to the reliability of the power system. However, GIS may produce partial discharge during operation, and the acoustic wave signal generated by this discharge contains rich equipment status information. Through acoustic imaging positioning technology, the operating status of GIS equipment can be effectively monitored, potential faults can be discovered in advance, and accidents can be prevented. However, if the acoustic positioning system of the GIS equipment fails, the positioning of the GIS equipment will be problematic, which will affect the status monitoring of the substation and make it impossible to determine the fault of the substation in time. Summary of the invention

[0003] The purpose of the present invention is to provide a method, device and positioning system for detecting equipment failure, which can automatically acquire and analyze multi-source data of the operating status and environment of the positioning system, and then evaluate and determine the working performance of the positioning system. If the performance meets the requirements, the system can accurately detect whether the gas-insulated switchgear has a fault, avoid abnormal detection due to positioning system failure, affect the stability of the substation, and ultimately improve the safety and efficiency of the power system.

[0004] In order to solve the above technical problems, the present invention provides a method for detecting equipment failure, comprising:

[0005] Determine a noise suppression capability evaluation value of the positioning system according to operation data of the positioning system and environmental data of the substation, wherein the operation data is data characterizing the anti-interference capability of the positioning system, and the environmental data is data characterizing the noise of the environment in which the substation is located;

[0006] Determine the positioning accuracy evaluation index of the positioning system according to the result data of the positioning system and the device status data of the positioning system, wherein the result data is data characterizing the accuracy of the result output by the positioning system;

[0007] Performing a performance evaluation on the positioning system according to the operation process data of the positioning system, the noise suppression capability evaluation value and the positioning accuracy evaluation index, wherein the operation process data is data characterizing the computing capability of the positioning system;

[0008] After the performance evaluation of the positioning system is passed, the positioning system is used to perform acoustic imaging positioning on the gas insulated switchgear, and whether the gas insulated switchgear fails is determined based on the result of the acoustic imaging positioning.

[0009] On the other hand, before determining the noise suppression capability evaluation value of the positioning system according to the operation data of the positioning system and the environmental data of the substation, the method further includes:

[0010] Acquire operation data of the positioning system, wherein the operation data includes a combination of one or more of a signal-to-noise ratio of the positioning system, a sidelobe suppression ratio of the positioning system, and a noise type recognition accuracy rate of the positioning system;

[0011] The signal-to-noise ratio represents the ratio of the power of the target sound source signal to the power of the background noise signal, the sidelobe suppression ratio represents the ratio of the main lobe peak to the first sidelobe peak, and the system noise type recognition accuracy represents the percentage of correctly identifying different types of noise;

[0012] Acquire environmental data of the substation, the environmental data including one or more combinations of electromagnetic field strength of the environment in which the substation is located, electromagnetic interference frequency of each environmental monitoring point, number of radio frequency interference sources, power of each interference signal and background noise level;

[0013] Determining a noise suppression capability evaluation value of the positioning system according to operation data of the positioning system and environmental data of the substation includes:

[0014] Determine an environmental interference characteristic value of the area where the substation is located according to the environmental data of the substation, wherein the environmental interference characteristic value is positively correlated with the environmental data;

[0015] A noise suppression capability evaluation value of the positioning system is determined according to the environmental interference characteristic value and the operating data of the positioning system.

[0016] On the other hand, determining the environmental interference characteristic value of the area where the substation is located according to the environmental data of the substation includes:

[0017] The environmental interference characteristic value of the area where the substation is located is determined according to the environmental data of the substation, and the expression of the environmental interference characteristic value is:

[0018] ;

[0019] in, is the environmental interference characteristic value, is the regional environmental interference influence factor corresponding to the preset electromagnetic field strength, is the regional environmental interference impact factor corresponding to the preset electromagnetic interference frequency, is the regional environmental interference impact factor corresponding to the preset number of interference sources, is the regional environmental interference impact factor corresponding to the preset interference signal power, is the regional environmental interference influencing factor corresponding to the preset background noise level, i is the number of each environmental monitoring point, h is the total number of the environmental monitoring points, CG is the electromagnetic field strength, GRi is the electromagnetic interference frequency of the i-th environmental monitoring point, GS is the number of radio frequency interference sources, GLn is the n-th interference signal power, SP is the background noise level, △CG is the critical electromagnetic field strength, △GR is the critical electromagnetic interference frequency, △GS is the critical number of interference sources, △GL is the critical interference signal power, and △SP is the critical noise level.

[0020] On the other hand, determining a noise suppression capability evaluation value of the positioning system according to the environmental interference characteristic value and the operation data of the positioning system includes:

[0021] Obtain a critical signal-to-noise ratio, a critical sidelobe suppression ratio, and a critical noise type recognition accuracy rate, and determine a noise suppression capability evaluation value of the positioning system according to the environmental interference characteristic value and the operating data of the positioning system, wherein the expression of the noise suppression capability evaluation value is:

[0022] ;

[0023] Among them, μXN represents the system noise suppression capability evaluation value, represents the regional environmental interference characteristic value, SNR represents the system signal-to-noise ratio, SIR represents the system sidelobe suppression ratio, SBZ represents the system noise type recognition accuracy, △SNR represents the critical signal-to-noise ratio, △SIR represents the critical sidelobe suppression ratio, △SBZ represents the critical noise type recognition accuracy, Indicates the influence factor of the system noise suppression capability corresponding to the preset signal-to-noise ratio, Indicates the system noise suppression capability impact factor corresponding to the preset sidelobe suppression ratio, Indicates the system noise suppression capability influencing factor corresponding to the preset noise type recognition accuracy, Indicates the system noise suppression capability impact factor corresponding to the preset regional environmental interference characteristic value.

[0024] On the other hand, the positioning accuracy evaluation index of the positioning system is determined according to the result data of the positioning system and the device status data of the positioning system, wherein the result data represents the accuracy of the result output by the positioning system, including:

[0025] Determine an abnormal device status evaluation value of the positioning system according to the rated device status data of the positioning system and the device status data of the positioning system;

[0026] Obtaining a positioning accuracy evaluation index of the positioning system according to the critical result data, the result data of the positioning system and the abnormal equipment status evaluation value;

[0027] Among them, the result data of the positioning system includes a combination of one or more of the sound source positioning error, the sound source identification accuracy and the spatial resolution; the equipment status data of the positioning system includes a combination of one or more of the voltage, temperature, vibration intensity and data transmission rate at each time monitoring point; the rated equipment status data includes a combination of one or more of the rated voltage, rated vibration intensity, reference standard temperature, allowable deviation voltage, allowable deviation vibration intensity, allowable deviation temperature and critical data transmission rate; the critical result data includes a combination of one or more of the critical positioning error, critical identification accuracy and critical spatial resolution.

[0028] On the other hand, determining the device status abnormality assessment value of the positioning system according to the rated device status data of the positioning system and the device status data of the positioning system includes:

[0029] The device status abnormality evaluation value of the positioning system is determined according to the rated device status data of the positioning system and the device status data of the positioning system. The expression of the device status abnormality evaluation value is:

[0030] ;

[0031] in, is the abnormal evaluation value of the system equipment status, t is the number of each time monitoring point, s is the total number of time monitoring points, τDY t is the voltage at the tth time monitoring point, τWD t is the temperature of the monitoring point at time t, τZD t is the vibration intensity at the tth time monitoring point, τCS t is the data transmission rate at the tth time monitoring point, τDY 0 is the rated voltage, τZD 0 is the rated vibration intensity, τWD 0 is the reference standard temperature, △τDY is the allowable deviation voltage, △τZD is the allowable deviation vibration intensity, △τWD is the allowable deviation temperature, △τCS is the critical data transmission rate, ρ1 is the system equipment state abnormal interference characteristic factor corresponding to the preset voltage, ρ2 is the system equipment state abnormal interference characteristic factor corresponding to the preset temperature, ρ3 is the system equipment state abnormal interference characteristic factor corresponding to the preset vibration intensity, ρ4 is the system equipment state abnormal interference characteristic factor corresponding to the preset data transmission rate.

[0032] On the other hand, the positioning accuracy evaluation index of the positioning system is obtained according to the critical result data, the result data of the positioning system and the abnormal equipment status evaluation value, including:

[0033] The positioning accuracy evaluation index of the positioning system is obtained according to the critical result data, the result data of the positioning system and the abnormal equipment status evaluation value. The relationship formula of the positioning accuracy evaluation index is:

[0034] ;

[0035] Among them, μDJ represents the system positioning accuracy evaluation index, represents the abnormal evaluation value of the system equipment status, WC represents the sound source positioning error, SQ represents the sound source recognition accuracy, JL represents the spatial resolution, △WC represents the critical positioning error, △SQ represents the critical recognition accuracy, △JL represents the critical spatial resolution, Indicates the system positioning accuracy influencing factor corresponding to the preset positioning error, Indicates the system positioning accuracy influencing factor corresponding to the preset recognition accuracy rate, Indicates the system positioning accuracy impact factor corresponding to the preset spatial resolution, Indicates the system positioning accuracy impact factor corresponding to the preset system equipment status abnormality assessment value.

[0036] On the other hand, the performance of the positioning system is evaluated according to the operation process data of the positioning system, the noise suppression capability evaluation value and the positioning accuracy evaluation index, including:

[0037] Acquire the operation process data of the positioning system, wherein the operation process data includes the calculation time and the utilization rate of each calculation resource;

[0038] The value of the comprehensive energy efficiency evaluation index of the positioning system is obtained according to the operation process data of the positioning system, the noise suppression capability evaluation value and the positioning accuracy evaluation index. The relationship formula of the value of the comprehensive energy efficiency evaluation index is:

[0039] ;

[0040] Among them, μZX represents the system comprehensive energy efficiency evaluation index, μXN represents the system noise suppression capability evaluation value, μDJ represents the system positioning accuracy evaluation index, μJT represents the system calculation time, r represents the number of each computing resource, g represents the total number of computing resources, and μJY represents the total number of computing resources. r represents the utilization rate of the rth computing resource in the system, △μJT represents the critical computing time, △μJY represents the critical computing resource utilization rate, Indicates the system comprehensive energy efficiency correction factor corresponding to the preset system noise suppression capability evaluation value, Indicates the system comprehensive energy efficiency correction factor corresponding to the preset system positioning accuracy evaluation index, Indicates the system comprehensive energy efficiency correction factor corresponding to the preset calculation time, Indicates the system comprehensive energy efficiency correction factor corresponding to the preset computing resources.

[0041] In order to solve the above technical problems, the present invention also provides a device for detecting equipment failure, comprising:

[0042] Memory for storing computer programs;

[0043] A processor is used to implement the steps of the above-mentioned device failure detection method when executing the computer program.

[0044] In order to solve the above technical problem, the present invention also provides a positioning system, including the above-mentioned device failure detection apparatus.

[0045] The present invention discloses a detection method, device and positioning system for equipment failure, which relates to the field of fault detection, including determining the noise suppression capability evaluation value of the positioning system according to the operation data of the positioning system and the environmental data of the substation; determining the positioning accuracy evaluation index of the positioning system according to the result data of the positioning system and the equipment status data of the positioning system; evaluating the performance of the positioning system according to the operation process data of the positioning system, the noise suppression capability evaluation value and the positioning accuracy evaluation index; after passing, using the positioning system to perform acoustic imaging positioning on the gas insulated switchgear, and determining whether the gas insulated switchgear fails. The present invention can automatically acquire and analyze the multi-source data of the operation status and environment of the positioning system, and then evaluate and determine the working performance of the positioning system. If the performance meets the requirements, the system can accurately detect whether the gas insulated switchgear fails, avoid detection abnormality due to the failure of the positioning system, affect the stability of the substation, and ultimately improve the safety and efficiency of the power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the prior art and the drawings required for use in the embodiments are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0047] Figure 1 A flow chart of a method for detecting equipment failure provided by the present invention;

[0048] FIG2 (a) is a main lobe width error curve diagram of a conventional beamforming method and a DW-GIB method under different signal-to-noise ratios under a noise of 5 dB provided by the present invention;

[0049] FIG2( b ) is a main lobe width error curve diagram of a conventional beamforming method and a DW-GIB method under different signal-to-noise ratios under a noise of 10 dB provided by the present invention;

[0050] FIG2( c ) is a main lobe width error curve diagram of a conventional beamforming method and a DW-GIB method under different signal-to-noise ratios under a noise of 20 dB provided by the present invention;

[0051] FIG2( d ) is a main lobe width error curve diagram of a conventional beamforming method and a DW-GIB method under different signal-to-noise ratios under a noise of 30 dB provided by the present invention;

[0052] FIG3 (a) is a positioning error curve diagram of a conventional beamforming method and a DW-GIB method under different signal-to-noise ratios provided by the present invention when the noise is 5 dB;

[0053] FIG3( b ) is a positioning error curve diagram of a conventional beamforming method and a DW-GIB method under different signal-to-noise ratios provided by the present invention when the noise is 10 dB;

[0054] FIG3 (c) is a positioning error curve diagram of a conventional beamforming method and a DW-GIB method under different signal-to-noise ratios provided by the present invention when the noise is 30 dB;

[0055] FIG3( d ) is a positioning error curve diagram of a conventional beamforming method and a DW-GIB method under different signal-to-noise ratios under a noise of 30 dB provided by the present invention;

[0056] Figure 4 A schematic structural diagram of a device for detecting equipment failure provided by the present invention. DETAILED DESCRIPTION

[0057] The core of the present invention is to provide a method, device and positioning system for detecting equipment failure, which automatically obtains data on the operating status and environment of the positioning system, and then determines the working performance of the positioning system. Normally, the positioning system can accurately detect whether the gas-insulated switchgear has a fault, avoiding detection abnormalities due to positioning system failures, which affects the stability of the substation.

[0058] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0059] Figure 1 A flow chart of a device failure detection method provided by the present invention, the device failure detection method comprising:

[0060] S11: determining a noise suppression capability evaluation value of the positioning system according to operation data of the positioning system and environmental data of the substation, wherein the operation data is data characterizing the anti-interference capability of the positioning system, and the environmental data is data characterizing the noise of the environment in which the substation is located;

[0061] S12: determining a positioning accuracy evaluation index of the positioning system according to result data of the positioning system and device status data of the positioning system, wherein the result data is data representing the accuracy of the result output by the positioning system;

[0062] S13: Evaluate the performance of the positioning system according to the operation process data of the positioning system, the noise suppression capability evaluation value and the positioning accuracy evaluation index, where the operation process data is data representing the computing capability of the positioning system;

[0063] S14: After the performance evaluation of the positioning system is passed, the positioning system is used to perform acoustic imaging positioning on the gas-insulated switchgear, and whether the gas-insulated switchgear fails is determined based on the results of the acoustic imaging positioning.

[0064] With the rapid development of my country's economy, the demand for electricity is growing, and the number and scale of substations are also expanding. In the operation of substations, GIS (gas insulated switchgear) is a key equipment, and its safe and stable operation is crucial to the reliability of the power system. However, GIS may produce partial discharge during operation, and the sound wave signal generated by this discharge contains rich equipment status information. Through acoustic imaging positioning technology, the operating status of GIS equipment can be effectively monitored, potential faults can be discovered in advance, and accidents can be prevented.

[0065] It needs to be explained that electromagnetic fields and electromagnetic interference will modulate the propagation of sound waves, causing distortion of sound wave signals. Background noise will reduce the detection and identification capabilities of sound source signals, affecting the accuracy of sound source positioning. Radio frequency interference signals will interfere with sound wave signals, resulting in sound source positioning errors. Through comprehensive analysis of substation environmental data, the interference of the environment on the acoustic imaging positioning system can be more effectively evaluated, and corresponding measures can be taken to compensate and suppress it, thereby improving the performance and robustness of the positioning system and enabling it to adapt to complex substation environments.

[0066] It needs to be explained that the higher the spatial resolution, the smaller the sound source localization error. Because high spatial resolution means that the system can more accurately determine the location of the sound source. High spatial resolution helps improve the accuracy of sound source recognition because it can provide more accurate sound source location information, which is helpful for feature extraction and pattern recognition. The localization error will affect the accuracy of sound source recognition. If the localization error is large, the extracted sound source features may be inaccurate, thereby reducing the recognition accuracy.

[0067] It needs to be explained that comprehensive analysis of the positioning system's sound source localization error, sound source identification accuracy and spatial resolution, as well as the system equipment status abnormality assessment value, can comprehensively evaluate the system positioning accuracy, help guide system design and optimization, and improve system performance, thereby directly improving the system's positioning accuracy and reliability, helping to improve user experience and system practicality, and also enhancing the system's adaptability in complex environments, reducing false alarm rates, and improving system safety and efficiency.

[0068] It needs to be explained that by monitoring and responding to abnormal equipment status in a timely manner, system failures and downtime can be reduced and system reliability can be improved. Through preventive maintenance, equipment wear can be reduced and the service life of the equipment can be extended. It can also help maintain the positioning accuracy of the system.

[0069] Provide fault warning for system equipment based on abnormal evaluation value of system equipment status.

[0070] Specifically, fault warning is performed on system equipment according to the system equipment status abnormal evaluation value. The specific warning process is: extract the system equipment status abnormal evaluation threshold from the system database, compare the system equipment status abnormal evaluation value with the system equipment status abnormal evaluation threshold, if the system equipment status abnormal evaluation value is greater than or equal to the system equipment status abnormal evaluation threshold, then the device is marked as an abnormal device and a warning feedback is performed; if the system equipment status abnormal evaluation value is less than the system equipment status abnormal evaluation threshold, then the device is marked as a normal device and a display output is performed.

[0071] The critical positioning error, critical recognition accuracy and critical spatial resolution are extracted from the system database, and based on the positioning system result data and the abnormal evaluation value of the system equipment status, a comprehensive analysis is performed to obtain the system positioning accuracy evaluation index. The system positioning accuracy evaluation index is used to quantitatively evaluate the positioning accuracy of the positioning system and provide a basis for evaluating the comprehensive energy efficiency of the positioning system.

[0072] It should be explained that the improvement of noise suppression capability helps to reduce the interference of noise on positioning signals, thereby improving positioning accuracy. In order to improve positioning accuracy, it may be necessary to increase computing time and complexity. Complex noise suppression algorithms may require higher computing power and larger storage space to support. The length of computing time usually depends on the sufficiency of computing resources. Comprehensively analyzing the positioning accuracy, noise suppression capability, computing time and computing resource utilization of the system can make the evaluation of the comprehensive energy efficiency of the positioning system more comprehensive and accurate. The positioning accuracy and noise suppression capability can be improved by adopting advanced positioning algorithms and noise suppression technologies. At the same time, the consumption of computing time and computing resources can be reduced by optimizing the algorithm and code structure. The comprehensive performance of the positioning system can be effectively improved.

[0073] Specifically, the positioning system is performance evaluated and feedback is given based on the system comprehensive energy efficiency evaluation index. The specific evaluation process is: extracting the system comprehensive energy efficiency evaluation index threshold from the system database, comparing the system comprehensive energy efficiency evaluation index with the system comprehensive energy efficiency evaluation index threshold; if the system comprehensive energy efficiency evaluation index is higher than or equal to the system comprehensive energy efficiency evaluation index threshold, the system performance is evaluated as qualified; if the system comprehensive energy efficiency evaluation index is lower than the system comprehensive energy efficiency evaluation index threshold, the system performance is evaluated as unqualified, and the system is analyzed for problems and the results are fed back.

[0074] The present invention discloses a method for detecting equipment failure, which relates to the field of fault detection, including determining the noise suppression capability evaluation value of the positioning system according to the operation data of the positioning system and the environmental data of the substation; determining the positioning accuracy evaluation index of the positioning system according to the result data of the positioning system and the equipment status data of the positioning system; evaluating the performance of the positioning system according to the operation process data of the positioning system, the noise suppression capability evaluation value and the positioning accuracy evaluation index; after passing, using the positioning system to perform acoustic imaging positioning on the gas insulated switchgear, and determining whether the gas insulated switchgear fails. The present invention can automatically acquire and analyze the multi-source data of the operation status and environment of the positioning system, and then evaluate and determine the working performance of the positioning system. If the performance meets the requirements, the system can accurately detect whether the gas insulated switchgear fails, avoid detection abnormality due to the failure of the positioning system, affect the stability of the substation, and ultimately improve the safety and efficiency of the power system.

[0075] Based on the above embodiments:

[0076] In some embodiments, before determining the noise suppression capability evaluation value of the positioning system according to the operation data of the positioning system and the environmental data of the substation, the method further includes:

[0077] Acquire operation data of the positioning system, the operation data including a combination of one or more of a signal-to-noise ratio of the positioning system, a sidelobe suppression ratio of the positioning system, and a noise type recognition accuracy rate of the positioning system;

[0078] Among them, the signal-to-noise ratio represents the ratio of the power of the target sound source signal to the power of the background noise signal, the sidelobe suppression ratio represents the ratio of the main lobe peak to the first sidelobe peak, and the system noise type recognition accuracy represents the percentage of correctly identifying different types of noise;

[0079] Obtaining environmental data of the substation, the environmental data including one or more combinations of the electromagnetic field strength of the substation environment, the electromagnetic interference frequency of each environmental monitoring point, the number of radio frequency interference sources, the power of each interference signal and the background noise level;

[0080] The noise suppression capability evaluation value of the positioning system is determined based on the operating data of the positioning system and the environmental data of the substation, including:

[0081] Determine the environmental interference characteristic value of the area where the substation is located according to the environmental data of the substation, and the environmental interference characteristic value is positively correlated with the environmental data;

[0082] The noise suppression capability evaluation value of the positioning system is determined based on the environmental interference characteristic value and the operating data of the positioning system.

[0083] Specifically, the positioning system operation data includes: system signal-to-noise ratio, system sidelobe suppression ratio and system noise type recognition accuracy.

[0084] It should be explained that the system signal-to-noise ratio refers to the ratio of the power of the target sound source signal to the power of the background noise signal, the system sidelobe suppression ratio refers to the ratio of the main lobe peak to the first sidelobe peak, and the system noise type recognition accuracy refers to the percentage of the system correctly identifying different types of noise. Professional acoustic test instruments, such as sound level meters and spectrum analyzers, can be used to directly measure the system signal-to-noise ratio and system sidelobe suppression ratio. Acoustic signal processing software can be used to extract and classify the features of the collected sound pressure signals and compare them with the manually labeled noise types to obtain the noise type recognition accuracy.

[0085] Substation environmental data, including: electromagnetic field strength, electromagnetic interference frequency of each environmental monitoring point, number of radio frequency interference sources, power of each interference signal and background noise level.

[0086] It should be explained that an electromagnetic field strength meter can be used to measure the electromagnetic field strength inside and around the substation. A spectrum analyzer can be used to perform spectrum analysis on the electromagnetic interference signal inside the substation to determine the frequency of the interference signal. Through spectrum analysis, interference signals in different frequency ranges are identified and the number of interference signals is counted. Then, a spectrum analyzer is used to perform spectrum analysis on the interference signal and measure the power of each interference signal. A sound level meter can be used to measure the background noise inside the substation and record the noise level.

[0087] The system noise suppression capability evaluation value is used to quantitatively evaluate the noise suppression capability of the positioning system and provide a basis for evaluating the comprehensive energy efficiency of the positioning system.

[0088] The critical electromagnetic field strength, critical electromagnetic interference frequency, critical number of interference sources, critical interference signal power and critical noise level are extracted from the system database, and based on the substation environmental data, a comprehensive analysis is performed to obtain the regional environmental interference characteristic value. The regional environmental interference characteristic value is used to quantitatively evaluate the degree of interference of the substation environment on the accuracy of the positioning system, providing a basis for evaluating the noise suppression capability of the positioning system.

[0089] In some embodiments, determining the environmental interference characteristic value of the area where the substation is located according to the environmental data of the substation includes:

[0090] The environmental interference characteristic value of the area where the substation is located is determined based on the environmental data of the substation. The expression of the environmental interference characteristic value is:

[0091] ;

[0092] in, is the environmental interference characteristic value, is the regional environmental interference influence factor corresponding to the preset electromagnetic field strength, is the regional environmental interference impact factor corresponding to the preset electromagnetic interference frequency, is the regional environmental interference impact factor corresponding to the preset number of interference sources, is the regional environmental interference impact factor corresponding to the preset interference signal power, is the regional environmental interference influencing factor corresponding to the preset background noise level, i is the number of each environmental monitoring point, h is the total number of environmental monitoring points, CG is the electromagnetic field strength, GRi is the electromagnetic interference frequency of the i-th environmental monitoring point, GS is the number of radio frequency interference sources, GLn is the n-th interference signal power, SP is the background noise level, △CG is the critical electromagnetic field strength, △GR is the critical electromagnetic interference frequency, △GS is the critical number of interference sources, △GL is the critical interference signal power, and △SP is the critical noise level.

[0093] It needs to be explained that when the electromagnetic field strength, electromagnetic interference frequency, number of radio frequency interference sources, power of each interference signal and background noise level are greater, the corresponding regional environmental interference characteristic value will be greater, indicating that the substation environment will interfere with the accuracy of the positioning system to a greater extent.

[0094] It should be added that, in this embodiment Indicates the regional environmental interference impact factor corresponding to the preset electromagnetic field strength, Indicates the regional environmental interference impact factor corresponding to the preset electromagnetic interference frequency. Indicates the regional environmental interference impact factor corresponding to the preset number of interference sources, Indicates the regional environmental interference impact factor corresponding to the preset interference signal power, It indicates the regional environmental interference impact factor corresponding to the preset background noise level. The values ​​of these impact factors respectively indicate the interference degree of the electromagnetic field strength, electromagnetic interference frequency, number of interference sources, interference signal power and background noise level unit value on the positioning accuracy of the positioning system. When used, these impact factors can be directly obtained from the system database. The values ​​of these impact factors are preset in the system database. For example, the electromagnetic field strength, the electromagnetic interference frequency of each environmental monitoring point, the number of radio frequency interference sources, the interference signal power and the background noise level are respectively mapped with the preset impact factors in the system database to form a mapping set. The real-time electromagnetic field strength, electromagnetic interference frequency, number of interference sources, interference signal power and background noise level are input into the mapping set to obtain the corresponding environmental interference impact factor. These mapping relationships can be one-to-one or many-to-one. The value range of all impact factors is between 0 and 1, indicating the degree from no impact to maximum impact. The higher the electromagnetic field strength, the higher the electromagnetic interference frequency. Electromagnetic field and radio frequency interference may cause distortion of sound wave signals, thereby increasing the background noise level.

[0095] In some embodiments, determining a noise suppression capability evaluation value of a positioning system according to an environmental interference characteristic value and operation data of the positioning system includes:

[0096] The critical signal-to-noise ratio, critical sidelobe suppression ratio and critical noise type recognition accuracy are obtained, and the noise suppression capability evaluation value of the positioning system is determined according to the environmental interference characteristic value and the operating data of the positioning system. The expression of the noise suppression capability evaluation value is:

[0097] ;

[0098] Among them, μXN represents the system noise suppression capability evaluation value, represents the regional environmental interference characteristic value, SNR represents the system signal-to-noise ratio, SIR represents the system sidelobe suppression ratio, SBZ represents the system noise type recognition accuracy, △SNR represents the critical signal-to-noise ratio, △SIR represents the critical sidelobe suppression ratio, △SBZ represents the critical noise type recognition accuracy, Indicates the influence factor of the system noise suppression capability corresponding to the preset signal-to-noise ratio, Indicates the system noise suppression capability impact factor corresponding to the preset sidelobe suppression ratio, Indicates the system noise suppression capability influencing factor corresponding to the preset noise type recognition accuracy, Indicates the system noise suppression capability impact factor corresponding to the preset regional environmental interference characteristic value.

[0099] When the system signal-to-noise ratio, sidelobe suppression ratio and system noise type recognition accuracy are larger, and the regional environmental interference characteristic value is smaller, the corresponding system noise suppression capability evaluation value is larger, indicating that the positioning system has a stronger noise suppression capability.

[0100] It should be added that, in this embodiment Indicates the influence factor of the system noise suppression capability corresponding to the preset signal-to-noise ratio, Indicates the system noise suppression capability impact factor corresponding to the preset sidelobe suppression ratio, Indicates the system noise suppression capability influencing factor corresponding to the preset noise type recognition accuracy, Indicates the system noise suppression capability influencing factors corresponding to the preset regional environmental interference characteristic values. The values ​​of these influencing factors respectively represent the degree of influence of the system signal-to-noise ratio, sidelobe suppression ratio, system noise type identification accuracy and regional environmental interference characteristic value unit values ​​on the positioning system noise suppression capability. When used, these influencing factors can be directly obtained from the system database. The values ​​of these influencing factors are preset in the system database. For example, the system signal-to-noise ratio, sidelobe suppression ratio, system noise type identification accuracy and regional environmental interference characteristic values ​​form a mapping set with the preset influencing factors in the system database respectively. The real-time system signal-to-noise ratio, sidelobe suppression ratio, system noise type identification accuracy and regional environmental interference characteristic values ​​are input into the mapping set to obtain the corresponding system noise suppression capability influencing factors. These mapping relationships can be one-to-one or many-to-one. The value range of all influencing factors is between 0 and 1, indicating the degree from no influence to maximum influence.

[0101] In the acoustic imaging positioning system, the signal-to-noise ratio is an indicator to measure the noise reduction effect of the system. If the signal-to-noise ratio is high, it means that the target sound source signal is stronger than the noise signal, and the system's noise reduction effect is better, which can improve the detection and identification ability of the sound source signal. In acoustic imaging, side lobes refer to other beam parts except the main lobe (directly pointing in the direction of the sound source). Side lobes may capture noise or other interfering signals, resulting in positioning errors. The higher the sidelobe suppression ratio, the stronger the system's ability to suppress side lobes, and the higher the distinction between the main lobe and the side lobe, so that the sound source can be located more accurately. In complex environments such as substations, there may be many types of noise, such as corona noise, mechanical vibration noise, etc. The stronger the system's ability to identify the type of noise, the more targeted noise reduction measures can be taken to improve the extraction quality of the sound source signal. The higher the accuracy rate, the better the system's performance in noise type identification, which helps to improve the accuracy of the overall acoustic imaging positioning.

[0102] FIG2 (a) is a main lobe width error curve diagram of a conventional beamforming method and a DW-GIB method under different signal-to-noise ratios under a noise of 5 dB provided by the present invention;

[0103] FIG2( b ) is a main lobe width error curve diagram of a conventional beamforming method and a DW-GIB method under different signal-to-noise ratios under a noise of 10 dB provided by the present invention;

[0104] FIG2( c ) is a main lobe width error curve diagram of a conventional beamforming method and a DW-GIB method under different signal-to-noise ratios under a noise of 20 dB provided by the present invention;

[0105] FIG2( d ) is a main lobe width error curve diagram of a conventional beamforming method and a DW-GIB method under different signal-to-noise ratios under a noise of 30 dB provided by the present invention;

[0106] It should be added that in actual engineering measurements, due to the limitations of experimental facilities, it is difficult for us to control the level of interference noise in the measurement environment, and these noises often have some impact on the measurement results. In order to explore the impact of interference noise, the figure examines the performance of sound field reconstruction under 5dB, 10dB, 20dB and 30dB signal-to-noise ratios of the weighted noise reduction generalized inverse beamforming sound source identification method (Denoising weightinggeneralized inverse beamforming, referred to as DW-GIB) and the traditional beamforming method. In Figure 2 (a), at a higher noise level, the DW-GIB method has better noise resistance than the traditional method. The main lobe width can be obtained at around 100Hz, and the main lobe width decreases as the frequency increases. Finally, the signal-to-noise ratio remains at around 15dB, while the traditional method only forms a measurable main lobe width at 700Hz, and the main lobe width is much larger than the DW-GIB method. As the signal-to-noise ratio increases, the advantages of the DW-GIB method become more obvious. In Figure 2 (d), the signal-to-noise ratio value is reduced to the grid width, while the traditional method is 17dB. Therefore, the signal-to-noise ratio has a significant impact on the sound source recognition algorithm, especially at 5dB, the performance of the algorithm drops significantly, the reconstruction resolution is relatively low, and it is not conducive to sound source recognition. Therefore, although the DW-GIB algorithm has good anti-noise performance, the signal-to-noise ratio is kept above 10dB as much as possible to ensure the spatial resolution of the sound field reconstruction.

[0107] It should be added that the DW-GIB method first denoises and reconstructs the cross-spectral matrix of the actual sound field signal, and then uses the known source strength distribution information to construct a regularization matrix related to the beamforming output result. This regularization matrix is ​​then used as a constraint on the L2 norm regularization term, and ultimately an improved L2 norm minimization problem is formed. The regularization matrix is ​​optimized through an iterative method, which further improves the performance of this method.

[0108] FIG3 (a) is a positioning error curve diagram of a conventional beamforming method and a DW-GIB method under different signal-to-noise ratios provided by the present invention when the noise is 5 dB;

[0109] FIG3( b ) is a positioning error curve diagram of a conventional beamforming method and a DW-GIB method under different signal-to-noise ratios provided by the present invention when the noise is 10 dB;

[0110] FIG3 (c) is a positioning error curve diagram of a conventional beamforming method and a DW-GIB method under different signal-to-noise ratios provided by the present invention when the noise is 30 dB;

[0111] FIG3( d ) is a positioning error curve diagram of a conventional beamforming method and a DW-GIB method under different signal-to-noise ratios under a noise of 30 dB provided by the present invention;

[0112] In Figure 3, when the signal-to-noise ratio is equal to 5dB (Figure 3 (a)), both algorithms have positioning errors at low frequencies, especially the traditional method has a deviation of 0.1m at 100Hz. As the signal-to-noise ratio increases, the DW-GIB method has almost no positioning error. When SNR=30dB, as shown in Figure 3 (d), both methods can accurately locate the position of the noise source.

[0113] In general, the signal-to-noise ratio has a significant impact on the sound source reconstruction performance, especially at a lower signal-to-noise ratio. Although the DW-GIB method has improved noise immunity, when the noise level is too high, it is still easy to cause sound source identification errors, affecting the accuracy of the test results. Therefore, it is recommended to try to keep the signal-to-noise ratio above 10dB in actual engineering measurements.

[0114] In some embodiments, the positioning accuracy evaluation index of the positioning system is determined according to the result data of the positioning system and the device status data of the positioning system, and the result data represents the accuracy of the result output by the positioning system, including:

[0115] Determine an abnormal equipment status evaluation value of the positioning system according to the rated equipment status data of the positioning system and the equipment status data of the positioning system;

[0116] The positioning accuracy evaluation index of the positioning system is obtained based on the critical result data, the result data of the positioning system and the abnormal evaluation value of the equipment status;

[0117] Among them, the result data of the positioning system includes a combination of one or more of the sound source positioning error, the sound source identification accuracy and the spatial resolution; the equipment status data of the positioning system includes a combination of one or more of the voltage, temperature, vibration intensity and data transmission rate at each time monitoring point; the rated equipment status data includes a combination of one or more of the rated voltage, rated vibration intensity, reference standard temperature, allowable deviation voltage, allowable deviation vibration intensity, allowable deviation temperature and critical data transmission rate; the critical result data includes a combination of one or more of the critical positioning error, the critical identification accuracy and the critical spatial resolution.

[0118] Specifically, the positioning system result data includes: sound source positioning error, sound source identification accuracy and spatial resolution.

[0119] It should be explained that the sound source localization error in this embodiment refers to the deviation between the sound source position determined by the acoustic imaging positioning system and the actual position of the sound source. This deviation is specifically the distance in three-dimensional space. Sound source recognition accuracy refers to the percentage of the system correctly identifying a specific sound source (such as the sound of a certain device). Spatial resolution refers to the minimum distance between two adjacent sound sources that the system can distinguish. High spatial resolution means that the positioning system can distinguish two sound sources at a closer distance, which is crucial for accurate sound source positioning in a dense sound source environment.

[0120] It needs to be explained that by conducting on-site sound source localization tests, statistical methods can be used to analyze the error between the positioning result and the actual sound source position, and the sound source localization error and spatial resolution can be quantified. At the same time, through multiple sound source localization tests, the system sound source recognition accuracy can be calculated.

[0121] Positioning system equipment status data, including: voltage, temperature, vibration intensity and data transmission rate at each monitoring point at each time.

[0122] It should be explained that the positioning system device in this embodiment specifically refers to an acoustic imager, and the acoustic imager based on a sensor array is used to collect sound wave information with sound source characteristics and perform acoustic analysis. The data transmission rate refers to the serial port communication rate, which is expressed in baud rate.

[0123] It should be explained that the built-in voltage sensor and temperature sensor can be used to directly measure the device voltage and temperature. A special vibration sensor can be used to connect to the data acquisition system to convert the vibration signal into an electrical signal, and then the vibration intensity can be obtained through data analysis. The serial port debugging tool can be used to test the baud rate setting and data transmission rate.

[0124] It needs to be explained that the greater the absolute difference between the voltage, temperature, vibration intensity and the rated voltage, temperature, vibration intensity, and the smaller the data transmission rate, the greater the corresponding system equipment status abnormality assessment value, indicating that the degree of abnormality of the positioning system equipment status is higher.

[0125] It should be explained that when the device is running, voltage stability may cause the temperature to rise. If the voltage is too high or too low, it may cause the device to work unstably and the temperature to rise or fall abnormally. Unstable voltage may cause the vibration of motors or other moving parts to increase. Increased temperature may cause mechanical parts to expand, change the gap between them, and thus increase vibration. Voltage stability is the basis for the normal operation of electronic equipment, and voltage fluctuations may affect the data transmission rate. High temperature may cause the performance of electronic components to deteriorate, thereby reducing the data transmission rate. Strong vibrations may interfere with the transmission of signals, resulting in a decrease in data transmission rate or transmission errors.

[0126] In some embodiments, determining the device status abnormality assessment value of the positioning system according to the rated device status data of the positioning system and the device status data of the positioning system includes:

[0127] The device status abnormality evaluation value of the positioning system is determined according to the rated device status data of the positioning system and the device status data of the positioning system. The expression of the device status abnormality evaluation value is: ;

[0128] in, is the abnormal evaluation value of the system equipment status, t is the number of each time monitoring point, s is the total number of time monitoring points, τDY t is the voltage at the tth time monitoring point, τWD t is the temperature of the monitoring point at time t, τZD t is the vibration intensity at the tth time monitoring point, τCS t is the data transmission rate at the tth time monitoring point, τDY 0 is the rated voltage, τZD 0 is the rated vibration intensity, τWD 0 is the reference standard temperature, △τDY is the allowable deviation voltage, △τZD is the allowable deviation vibration intensity, △τWD is the allowable deviation temperature, △τCS is the critical data transmission rate, ρ1 is the system equipment state abnormal interference characteristic factor corresponding to the preset voltage, ρ2 is the system equipment state abnormal interference characteristic factor corresponding to the preset temperature, ρ3 is the system equipment state abnormal interference characteristic factor corresponding to the preset vibration intensity, ρ4 is the system equipment state abnormal interference characteristic factor corresponding to the preset data transmission rate.

[0129] It should be added that, in this embodiment, ρ1 is the abnormal interference characteristic factor of the system equipment state corresponding to the preset voltage, ρ2 is the abnormal interference characteristic factor of the system equipment state corresponding to the preset temperature, ρ3 is the abnormal interference characteristic factor of the system equipment state corresponding to the preset vibration intensity, and ρ4 is the abnormal interference characteristic factor of the system equipment state corresponding to the preset data transmission rate. The values ​​of these interference characteristic factors respectively represent the interference degree of the unit values ​​of voltage, temperature, vibration intensity and data transmission rate on the positioning system equipment state. When used, these influencing factors can be directly obtained from the system database. The values ​​of these interference characteristic factors are preset in the system database. For example, the voltage, temperature, vibration intensity and data transmission rate form a mapping set with the interference characteristic factors preset in the system database respectively. The real-time voltage, temperature, vibration intensity and data transmission rate are input into the mapping set to obtain the corresponding abnormal interference characteristic factor of the system equipment state. These mapping relationships can be one-to-one or many-to-one. The value range of all interference characteristic factors is between 0 and 1, indicating the degree from no influence to maximum influence.

[0130] In some embodiments, the positioning accuracy evaluation index of the positioning system is obtained according to the critical result data, the result data of the positioning system and the abnormal evaluation value of the device status, including:

[0131] The positioning accuracy evaluation index of the positioning system is obtained based on the critical result data, the result data of the positioning system and the abnormal equipment status evaluation value. The relationship between the positioning accuracy evaluation index is:

[0132] ;

[0133] Among them, μDJ represents the system positioning accuracy evaluation index, represents the abnormal evaluation value of the system equipment status, WC represents the sound source positioning error, SQ represents the sound source recognition accuracy, JL represents the spatial resolution, △WC represents the critical positioning error, △SQ represents the critical recognition accuracy, △JL represents the critical spatial resolution, Indicates the system positioning accuracy influencing factor corresponding to the preset positioning error, Indicates the system positioning accuracy influencing factor corresponding to the preset recognition accuracy rate, Indicates the system positioning accuracy impact factor corresponding to the preset spatial resolution, Indicates the system positioning accuracy impact factor corresponding to the preset system equipment status abnormality assessment value.

[0134] It needs to be explained that when the system sound source localization error and the system equipment status abnormality evaluation value are smaller, the sound source identification accuracy and the spatial resolution are greater, the corresponding system positioning accuracy evaluation index is larger, indicating that the positioning accuracy of the positioning system is higher.

[0135] It should be added that, in this embodiment Indicates the system positioning accuracy influencing factor corresponding to the preset positioning error, Indicates the system positioning accuracy influencing factor corresponding to the preset recognition accuracy rate, Indicates the system positioning accuracy impact factor corresponding to the preset spatial resolution, It represents the system positioning accuracy influencing factors corresponding to the preset system equipment status abnormal evaluation values. The values ​​of these influencing factors respectively represent the degree of influence of the system positioning error, recognition accuracy, spatial resolution and system equipment status abnormal evaluation value unit values ​​on the positioning accuracy of the positioning system. When used, these influencing factors can be directly obtained from the system database. The values ​​of these influencing factors are preset in the system database. For example, the system positioning error, recognition accuracy, spatial resolution and system equipment status abnormal evaluation value form a mapping set with the preset influencing factors in the system database respectively. The real-time system positioning error, recognition accuracy, spatial resolution and system equipment status abnormal evaluation value are input into the mapping set to obtain the corresponding system positioning accuracy influencing factors. These mapping relationships can be one-to-one or many-to-one. The value range of all influencing factors is between 0 and 1, indicating the degree from no influence to maximum influence.

[0136] In some embodiments, the performance of the positioning system is evaluated based on the operation process data of the positioning system, the noise suppression capability evaluation value, and the positioning accuracy evaluation index, including:

[0137] Obtaining the operation process data of the positioning system, the operation process data including the calculation time and the utilization rate of each calculation resource;

[0138] According to the operation process data of the positioning system, the noise suppression capability evaluation value and the positioning accuracy evaluation index, the value of the comprehensive energy efficiency evaluation index of the positioning system is obtained. The relationship between the values ​​of the comprehensive energy efficiency evaluation index is:

[0139] ;

[0140] Among them, μZX represents the system comprehensive energy efficiency evaluation index, μXN represents the system noise suppression capability evaluation value, μDJ represents the system positioning accuracy evaluation index, μJT represents the system calculation time, r represents the number of each computing resource, g represents the total number of computing resources, and μJY represents the total number of computing resources. r represents the utilization rate of the rth computing resource in the system, △μJT represents the critical computing time, △μJY represents the critical computing resource utilization rate, Indicates the system comprehensive energy efficiency correction factor corresponding to the preset system noise suppression capability evaluation value, Indicates the system comprehensive energy efficiency correction factor corresponding to the preset system positioning accuracy evaluation index, Indicates the system comprehensive energy efficiency correction factor corresponding to the preset calculation time, Indicates the system comprehensive energy efficiency correction factor corresponding to the preset computing resources.

[0141] Locate system operation process data, including system computing time and system computing resource utilization.

[0142] System computing time refers to the time required for the system to process data and is used to evaluate computing efficiency.

[0143] The utilization of various computing resources in the system refers to the utilization of various computing resources required by the system, including CPU utilization, memory utilization, and disk utilization, which is used to evaluate the consumption of computing resources.

[0144] It should be explained that the system's built-in high-precision clock can be used to record the start and end time of the task, thereby calculating the total computing time. Resource monitoring tools can be used to monitor and record computing resource consumption in real time. The shorter the computing time, the higher the computing efficiency. The fewer computing resources, the higher the computing efficiency.

[0145] Furthermore, a comprehensive analysis is performed to obtain a system comprehensive energy efficiency evaluation index. The specific analysis process is as follows: the critical computing time and critical computing resource utilization are extracted from the system database, and based on the positioning system operation process data, the system noise suppression capability evaluation value and the system positioning accuracy evaluation index, a comprehensive analysis is performed to obtain the system comprehensive energy efficiency evaluation index. The system comprehensive energy efficiency evaluation index is used to quantitatively evaluate the performance of the comprehensive energy efficiency of the positioning system, and to provide a basis for evaluating the system performance.

[0146] It needs to be explained that when the system noise suppression capability evaluation value, the system positioning accuracy evaluation index and the system computing resource utilization rate are larger, and the system calculation time is smaller, the corresponding system comprehensive energy efficiency evaluation index is larger, indicating that the comprehensive energy efficiency performance of the positioning system is better.

[0147] It should be added that, in this embodiment Indicates the system comprehensive energy efficiency correction factor corresponding to the preset system noise suppression capability evaluation value, Indicates the system comprehensive energy efficiency correction factor corresponding to the preset system positioning accuracy evaluation index, Indicates the system comprehensive energy efficiency correction factor corresponding to the preset calculation time, It represents the system comprehensive energy efficiency correction factor corresponding to the preset computing resources. The values ​​of these correction factors respectively represent the influence of the system noise suppression capability evaluation value, the system positioning accuracy evaluation index, the computing time and the computing resource utilization unit value on the comprehensive energy efficiency of the positioning system. When used, these correction factors can be directly obtained from the system database. The values ​​of these correction factors are preset in the system database. For example, the system noise suppression capability evaluation value, the system positioning accuracy evaluation index, the computing time and the computing resource utilization form a mapping set with the preset influencing factors in the system database. The real-time system noise suppression capability evaluation value, the system positioning accuracy evaluation index, the computing time and the computing resource utilization are input into the mapping set to obtain the corresponding system comprehensive energy efficiency correction factor. These mapping relationships can be one-to-one or many-to-one. The value range of all correction factors is between 0 and 1, indicating the degree from no influence to maximum influence.

[0148] Furthermore, for positioning accuracy problems, by comparing the system positioning accuracy evaluation index with the critical positioning accuracy threshold, if the evaluation index is significantly lower than the threshold, it may be due to excessive sound source positioning error. The source of the error can be determined by analyzing the statistical data of the positioning error, such as whether it is due to environmental noise interference, insufficient sensor accuracy, or algorithm problems. For noise suppression problems, check the system noise suppression capability evaluation value. If the evaluation value is lower than expected, it may be due to the noise suppression algorithm not being advanced enough or the environmental noise changing greatly. The problem can be determined by analyzing the parameter settings of the noise suppression algorithm and the changes in environmental noise. The calculation time is too long. Monitor the system calculation time. If the calculation time exceeds the preset critical calculation time, it may be due to high algorithm complexity or insufficient computing resources. The problem can be determined by analyzing the load and resource utilization of the computing task. The computing resource utilization is too low. Check the utilization of computing resources such as CPU, memory, and disk. If the utilization is lower than expected, it may be due to unreasonable system design or improper resource allocation. It can be solved by optimizing resource allocation and system architecture.

[0149] Display and output the system performance evaluation results (qualified or unqualified). Display the system performance evaluation results through the user interface or log system to ensure that managers can view the system status in a timely manner. Provide detailed problem diagnosis reports, including problem types, cause analysis, and recommended solutions. Generate reports containing problem types, cause analysis, and recommended solutions. Reports can be generated through automated tools and sent to relevant personnel via email or system notifications. For unqualified systems, issue early warning information to prompt managers to take timely measures for maintenance or repair. Notify managers through alarm systems or text messages to ensure that timely measures are taken for maintenance or repair. IoT devices or integrated platforms can be used to achieve real-time early warnings. Provide optimization suggestions, such as improving algorithms, replacing hardware, and adjusting system parameters, to improve system performance. Based on the problem diagnosis report, provide specific optimization suggestions, such as improving algorithms, replacing hardware, or adjusting system parameters. Optimization suggestions can be provided through expert systems or knowledge bases. Maintain or upgrade the system based on the problem diagnosis report and optimization suggestions to solve existing problems. Based on the problem diagnosis report and optimization suggestions, develop a detailed maintenance or upgrade plan and implement it through automated tools or manual operations. A version control system can be used to manage updates. Continuously monitor system performance to ensure stable system operation. Ensure stable system operation by monitoring system performance indicators in real time. Use monitoring tools and data analysis platforms to continuously track system status.

[0150] Figure 4 A schematic diagram of the structure of a device for detecting equipment failure provided by the present invention, the device for detecting equipment failure comprises:

[0151] A memory 41, used for storing computer programs;

[0152] The processor 42 is used to implement the steps of the above-mentioned device failure detection method when executing the computer program.

[0153] For an introduction to the device failure detection apparatus provided in the present application, please refer to the above-mentioned embodiments, which will not be described in detail here.

[0154] The present application also provides a positioning system, including the above-mentioned device failure detection apparatus.

[0155] For an introduction to the positioning system provided in this application, please refer to the above embodiments, which will not be repeated here.

[0156] In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part.

[0157] It should also be noted that, in this specification, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "comprise", "include" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the statement "comprises a ..." does not exclude the presence of other identical elements in the process, method, article or device including the element.

[0158] Professionals may further appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in the above description according to function. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians may use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0159] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for detecting equipment failure, characterized in that: include: Determine a noise suppression capability evaluation value of the positioning system according to operation data of the positioning system and environmental data of the substation, wherein the operation data is data characterizing the anti-interference capability of the positioning system, and the environmental data is data characterizing the noise of the environment in which the substation is located; Determine the positioning accuracy evaluation index of the positioning system according to the result data of the positioning system and the device status data of the positioning system, wherein the result data is data characterizing the accuracy of the result output by the positioning system; Performing a performance evaluation on the positioning system according to the operation process data of the positioning system, the noise suppression capability evaluation value and the positioning accuracy evaluation index, wherein the operation process data is data characterizing the computing capability of the positioning system; After the performance evaluation of the positioning system is passed, the positioning system is used to perform acoustic imaging positioning on the gas insulated switchgear, and whether the gas insulated switchgear fails is determined based on the result of the acoustic imaging positioning.

2. The method for detecting equipment failure according to claim 1, characterized in that: Before determining the noise suppression capability evaluation value of the positioning system according to the operation data of the positioning system and the environmental data of the substation, the method further includes: Acquire operation data of the positioning system, wherein the operation data includes a combination of one or more of a signal-to-noise ratio of the positioning system, a sidelobe suppression ratio of the positioning system, and a noise type recognition accuracy rate of the positioning system; The signal-to-noise ratio represents the ratio of the power of the target sound source signal to the power of the background noise signal, the sidelobe suppression ratio represents the ratio of the main lobe peak to the first sidelobe peak, and the system noise type recognition accuracy represents the percentage of correctly identifying different types of noise; Acquire environmental data of the substation, the environmental data including one or more combinations of electromagnetic field strength of the environment in which the substation is located, electromagnetic interference frequency of each environmental monitoring point, number of radio frequency interference sources, power of each interference signal and background noise level; Determining a noise suppression capability evaluation value of the positioning system according to operation data of the positioning system and environmental data of the substation includes: Determine an environmental interference characteristic value of the area where the substation is located according to the environmental data of the substation, wherein the environmental interference characteristic value is positively correlated with the environmental data; A noise suppression capability evaluation value of the positioning system is determined according to the environmental interference characteristic value and the operating data of the positioning system.

3. The method for detecting equipment failure according to claim 2, characterized in that: Determining the environmental interference characteristic value of the area where the substation is located according to the environmental data of the substation includes: The environmental interference characteristic value of the area where the substation is located is determined according to the environmental data of the substation, and the expression of the environmental interference characteristic value is: ； in, is the environmental interference characteristic value, is the regional environmental interference influence factor corresponding to the preset electromagnetic field strength, is the regional environmental interference impact factor corresponding to the preset electromagnetic interference frequency, is the regional environmental interference impact factor corresponding to the preset number of interference sources, is the regional environmental interference impact factor corresponding to the preset interference signal power, is the regional environmental interference influencing factor corresponding to the preset background noise level, i is the number of each environmental monitoring point, h is the total number of the environmental monitoring points, CG is the electromagnetic field strength, GRi is the electromagnetic interference frequency of the i-th environmental monitoring point, GS is the number of radio frequency interference sources, GLn is the n-th interference signal power, SP is the background noise level, △CG is the critical electromagnetic field strength, △GR is the critical electromagnetic interference frequency, △GS is the critical number of interference sources, △GL is the critical interference signal power, and △SP is the critical noise level.

4. The method for detecting equipment failure according to claim 2, characterized in that: Determining a noise suppression capability evaluation value of the positioning system according to the environmental interference characteristic value and the operation data of the positioning system includes: Obtain a critical signal-to-noise ratio, a critical sidelobe suppression ratio, and a critical noise type recognition accuracy rate, and determine a noise suppression capability evaluation value of the positioning system according to the environmental interference characteristic value and the operating data of the positioning system, wherein the expression of the noise suppression capability evaluation value is: ； Among them, μXN represents the system noise suppression capability evaluation value, represents the regional environmental interference characteristic value, SNR represents the system signal-to-noise ratio, SIR represents the system sidelobe suppression ratio, SBZ represents the system noise type recognition accuracy, △SNR represents the critical signal-to-noise ratio, △SIR represents the critical sidelobe suppression ratio, △SBZ represents the critical noise type recognition accuracy, Indicates the influence factor of the system noise suppression capability corresponding to the preset signal-to-noise ratio, Indicates the system noise suppression capability impact factor corresponding to the preset sidelobe suppression ratio, Indicates the system noise suppression capability influencing factor corresponding to the preset noise type recognition accuracy, Indicates the system noise suppression capability impact factor corresponding to the preset regional environmental interference characteristic value.

5. The method for detecting equipment failure according to claim 1, characterized in that: Determining a positioning accuracy evaluation index of the positioning system according to result data of the positioning system and device status data of the positioning system, wherein the result data represents the accuracy of a result output by the positioning system, includes: Determine an abnormal device status evaluation value of the positioning system according to the rated device status data of the positioning system and the device status data of the positioning system; Obtaining a positioning accuracy evaluation index of the positioning system according to the critical result data, the result data of the positioning system and the abnormal equipment status evaluation value; Among them, the result data of the positioning system includes a combination of one or more of the sound source positioning error, the sound source identification accuracy and the spatial resolution; the equipment status data of the positioning system includes a combination of one or more of the voltage, temperature, vibration intensity and data transmission rate at each time monitoring point; the rated equipment status data includes a combination of one or more of the rated voltage, rated vibration intensity, reference standard temperature, allowable deviation voltage, allowable deviation vibration intensity, allowable deviation temperature and critical data transmission rate; the critical result data includes a combination of one or more of the critical positioning error, critical identification accuracy and critical spatial resolution.

6. The method for detecting equipment failure according to claim 5, characterized in that: Determining the device status abnormality assessment value of the positioning system according to the rated device status data of the positioning system and the device status data of the positioning system includes: The device status abnormality evaluation value of the positioning system is determined according to the rated device status data of the positioning system and the device status data of the positioning system. The expression of the device status abnormality evaluation value is: ； in, is the abnormal evaluation value of the system equipment status, t is the number of each time monitoring point, s is the total number of time monitoring points, τDY t is the voltage at the tth time monitoring point, τWD t is the temperature of the monitoring point at time t, τZD t is the vibration intensity at the tth time monitoring point, τCS t is the data transmission rate at the tth time monitoring point, τDY 0 is the rated voltage, τZD 0 is the rated vibration intensity, τWD 0 is the reference standard temperature, △τDY is the allowable deviation voltage, △τZD is the allowable deviation vibration intensity, △τWD is the allowable deviation temperature, △τCS is the critical data transmission rate, ρ1 is the system equipment state abnormal interference characteristic factor corresponding to the preset voltage, ρ2 is the system equipment state abnormal interference characteristic factor corresponding to the preset temperature, ρ3 is the system equipment state abnormal interference characteristic factor corresponding to the preset vibration intensity, ρ4 is the system equipment state abnormal interference characteristic factor corresponding to the preset data transmission rate.

7. The method for detecting equipment failure according to claim 5, characterized in that: The positioning accuracy evaluation index of the positioning system is obtained according to the critical result data, the result data of the positioning system and the abnormal equipment status evaluation value, including: The positioning accuracy evaluation index of the positioning system is obtained according to the critical result data, the result data of the positioning system and the abnormal equipment status evaluation value. The relationship formula of the positioning accuracy evaluation index is: ； Among them, μDJ represents the system positioning accuracy evaluation index, represents the abnormal evaluation value of the system equipment status, WC represents the sound source positioning error, SQ represents the sound source recognition accuracy, JL represents the spatial resolution, △WC represents the critical positioning error, △SQ represents the critical recognition accuracy, △JL represents the critical spatial resolution, Indicates the system positioning accuracy influencing factor corresponding to the preset positioning error, Indicates the system positioning accuracy influencing factor corresponding to the preset recognition accuracy rate, Indicates the system positioning accuracy impact factor corresponding to the preset spatial resolution, Indicates the system positioning accuracy impact factor corresponding to the preset system equipment status abnormality assessment value.

8. The method for detecting equipment failure according to any one of claims 1 to 7, characterized in that: The performance of the positioning system is evaluated according to the operation process data of the positioning system, the noise suppression capability evaluation value and the positioning accuracy evaluation index, including: Acquire the operation process data of the positioning system, wherein the operation process data includes the calculation time and the utilization rate of each calculation resource; The value of the comprehensive energy efficiency evaluation index of the positioning system is obtained according to the operation process data of the positioning system, the noise suppression capability evaluation value and the positioning accuracy evaluation index. The relationship formula of the value of the comprehensive energy efficiency evaluation index is: ； Among them, μZX represents the system comprehensive energy efficiency evaluation index, μXN represents the system noise suppression capability evaluation value, μDJ represents the system positioning accuracy evaluation index, μJT represents the system calculation time, r represents the number of each computing resource, g represents the total number of computing resources, and μJY represents the total number of computing resources. r represents the utilization rate of the rth computing resource in the system, △μJT represents the critical computing time, △μJY represents the critical computing resource utilization rate, Indicates the system comprehensive energy efficiency correction factor corresponding to the preset system noise suppression capability evaluation value, Indicates the system comprehensive energy efficiency correction factor corresponding to the preset system positioning accuracy evaluation index, Indicates the system comprehensive energy efficiency correction factor corresponding to the preset calculation time, Indicates the system comprehensive energy efficiency correction factor corresponding to the preset computing resources.

9. A device for detecting equipment failure, characterized in that: include: Memory for storing computer programs; A processor, configured to implement the steps of the device failure detection method as claimed in any one of claims 1 to 8 when executing the computer program.

10. A positioning system, characterized in that: The device comprises the device for detecting equipment failure as claimed in claim 9.

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