Circuit breaker test method and system based on signal analysis, medium, equipment and product

Abstract

The invention discloses a circuit breaker testing method and system based on signal analysis, a medium, equipment and a product in the technical field of circuit breaker testing, and aims to solve the optimization problem of a circuit breaker detection technology. The method comprises the following steps: performing feature extraction on a collected multi-physical-quantity signal data set to obtain multi-physical-quantity signal features; inputting the multi-physical-quantity signal features into a constructed multi-physical-quantity signal fusion evaluation model for evaluation to obtain evaluation indexes; performing the following fault diagnosis according to the evaluation index: if an evaluation result is greater than or equal to a preset evaluation threshold value, determining that the circuit breaker operates normally; and if the evaluation result is smaller than a preset evaluation threshold value, determining that the circuit breaker operates abnormally, and inputting the multi-physical-quantity signal characteristics into a constructed signal propagation model for fault positioning to obtain a fault area of the circuit breaker. The method can provide powerful guarantee for safe operation of a power system, provides decision support for preventive maintenance and troubleshooting of the circuit breaker, and improves power supply reliability and economical efficiency.

Description

Technical Field

[0001] The present invention relates to the technical field of circuit breaker testing, and particularly relates to a circuit breaker testing method, system, medium, device and product based on signal analysis. Background Art

[0002] With the continuous development of the power system and the increasing requirement for power supply reliability, as a crucial control and protection device in the power system, the stability and reliability of the performance of the circuit breaker are directly related to the safe operation of the power system. The circuit breaker undertakes important tasks such as opening and closing the circuit and cutting off the fault current in the power system. Therefore, it is particularly important to accurately and efficiently test and evaluate its performance.

[0003] Traditional circuit breaker testing methods mainly rely on the analysis of a single physical quantity signal, such as only judging the performance state of the circuit breaker through electrical signals or vibration signals. However, this method has obvious limitations. On the one hand, a single physical quantity signal often cannot comprehensively reflect the overall performance and health status of the circuit breaker, easily leading to misdiagnosis or missed diagnosis. On the other hand, the traditional testing methods for signal preprocessing and analysis are relatively simple, and it is difficult to deeply excavate the rich information contained in the signals, thus affecting the accuracy and reliability of the testing. In addition, traditional testing methods often require manual intervention, with low testing efficiency, and it is difficult to meet the requirements of the large-scale power system for rapid and accurate evaluation of the performance of the circuit breaker. Summary of the Invention

[0004] The purpose of the present invention is to overcome the deficiencies in the prior art, and provide a circuit breaker testing method, system, medium, device and product based on signal analysis, which not only provides a strong guarantee for the safe operation of the power system, but also can provide decision-making support for the preventive maintenance and fault troubleshooting of the circuit breaker, reduce the operation and maintenance costs of the power system, and improve the power supply reliability and economy.

[0005] To solve the above technical problems, the present invention is implemented by adopting the following technical solutions:

[0006] In the first aspect, the present invention provides a circuit breaker testing method based on signal analysis, including:

[0007] Performing feature extraction on the collected multi-physical quantity signal dataset to obtain multi-physical quantity signal features;

[0008] Inputting the multi-physical quantity signal features into the constructed multi-physical quantity signal fusion evaluation model for evaluation to obtain an evaluation result that the circuit breaker is operating normally or the circuit breaker is operating abnormally;

[0009] When the evaluation result indicates that the circuit breaker is operating abnormally, an excitation signal is applied to the circuit breaker, and the arrival time and signal strength of the excitation signal are received at each monitoring point within the circuit breaker. Fault location is then performed using the arrival time, signal strength, and the constructed signal propagation model to obtain the fault area of the circuit breaker.

[0010] Optionally, it further includes signal preprocessing of the collected multi-physical quantity signal dataset. Correspondingly, the step of inputting the multi-physical quantity signal features into the constructed multi-physical quantity signal fusion evaluation model for evaluation includes: inputting the preprocessed multi-physical quantity signal features into the constructed multi-physical quantity signal fusion evaluation model for evaluation.

[0011] Optionally, the signal preprocessing includes at least one of adaptive filtering, signal amplification, linearization processing, and digital conversion.

[0012] Optionally, the multi-physical quantity signal features include electrical signal features, vibration signal features, temperature signal features, and magnetic field signal features.

[0013] The electrical signal features are obtained through the following formula:

[0014]

[0015] where represents the total number of sampling points in the electrical signal sequence, represents the th sampling point value in the electrical signal sequence, represents the time delay parameter, represents the number of sampling points in the electrical signal sequence used to calculate the change amount, represents the th sampling point value in the electrical signal sequence used to calculate the change amount;

[0016] The vibration signal features are obtained through the following formula:

[0017]

[0018] where represents the total number of sampling points in the vibration signal sequence, represents the th sampling point value in the vibration signal sequence, represents the mean value of the vibration signal sampling points, represents the number of sampling points in the vibration signal sequence used to calculate the variance, represents the th sampling point value in the vibration signal sequence used to calculate the variance;

[0019] The temperature signal feature is obtained by the following formula:

[0020]

[0021] wherein, represents the total number of sampling points in the temperature signal sequence, represents the th sampling point value in the temperature signal sequence, represents the th sampling point value in the temperature signal sequence;

[0022] The magnetic field signal feature is obtained by the following formula:

[0023]

[0024] wherein, represents the total number of sampling points in the magnetic field signal sequence, represents the th sampling point value in the magnetic field signal sequence, represents the th sampling point value in the magnetic field signal sequence.

[0025] Optionally, the data processing flow of the multi - physical quantity signal fusion evaluation model includes:

[0026] According to the multi - physical quantity signal feature, the evaluation index of the circuit breaker is obtained through the following multi - physical quantity signal fusion evaluation formula :

[0027]

[0028] wherein, represents the weight coefficient of the electrical signal feature, represents the electrical signal feature, represents the weight coefficient of the vibration signal feature, represents the vibration signal feature, represents the weight coefficient of the temperature signal feature, represents the temperature signal feature, represents the weight coefficient of the magnetic field signal feature, represents the magnetic field signal feature, represents the base of the natural logarithm, represents the bias parameter;

[0029] According to the evaluation index and the set threshold the following judgment is made:

[0030] If , the evaluation result is that the circuit breaker is operating normally;

[0031] If , the evaluation result is that the circuit breaker is operating abnormally.

[0032] Optionally, the excitation applied to the circuit breaker includes electrical pulse excitation and mechanical shock excitation, and the excitation signals include electrical pulse excitation signals and mechanical shock excitation signals.

[0033] Optionally, the data processing flow of the signal propagation model includes:

[0034] Obtain the theoretical signal strength of the excitation signal reaching each monitoring point through the following theoretical signal strength formula:

[0035]

[0036] where represents the distance from the excitation signal source to the measurement point, represents the arrival time of the excitation signal, represents the theoretical signal strength of the excitation signal at a distance and time , represents the initial strength of the excitation signal source, represents the attenuation coefficient of the excitation signal propagation medium, represents the parameter related to the excitation signal frequency, represents time when the excitation signal frequency is, represents the maximum propagation distance of the excitation signal, represents the power parameter related to the excitation signal propagation characteristics, represents the adjustment coefficient related to the excitation signal frequency, represents the initial phase parameter of the excitation signal;

[0037] According to the theoretical signal strength of the excitation signal reaching each monitoring point, obtain the fault evaluation index of each area through the following fault area analysis formula:

[0038]

[0039] where represents the fault evaluation index of the th area, represents the number of monitoring points, represents the distance from the excitation signal source to the th measurement point, represents the arrival time of the excitation signal at the th measurement point, represents at a distance and time the intensity of the excitation signal received at indicating at a distance and time the theoretical signal intensity at indicating the weight coefficient of the indicating the structural complexity index of the area where the th measurement point is located;

[0040] According to the fault evaluation indexes of the respective areas and a preset fault judgment threshold perform fault location judgment to obtain the fault area of the circuit breaker: If , then it is considered that the th area has a fault, otherwise it is considered that the th area is operating normally.

[0041] In a second aspect, the present invention provides a circuit breaker test system based on signal analysis, applicable to the circuit breaker test method based on signal analysis according to any one of the first aspects, including:

[0042] A feature extraction module, configured to: extract features from the collected multi-physical quantity signal data set to obtain multi-physical quantity signal features;

[0043] A circuit breaker evaluation module, configured to: input the multi-physical quantity signal features into the constructed multi-physical quantity signal fusion evaluation model for evaluation to obtain an evaluation result that the circuit breaker is operating normally or the circuit breaker is operating abnormally;

[0044] A circuit breaker fault diagnosis module, configured to: when the evaluation result is that the circuit breaker is operating abnormally, apply an excitation signal to the circuit breaker, and receive the arrival time and signal intensity of the excitation signal at each monitoring point in the circuit breaker, and use the arrival time, signal intensity, and the constructed signal propagation model to perform fault location to obtain the fault area of the circuit breaker.

[0045] Optionally, it further includes a preprocessing module, and the preprocessing module is configured to perform signal preprocessing on the collected multi-physical quantity signal data set; correspondingly, the inputting the multi-physical quantity signal features into the constructed multi-physical quantity signal fusion evaluation model for evaluation includes: inputting the preprocessed multi-physical quantity signal features into the constructed multi-physical quantity signal fusion evaluation model for evaluation.

[0046] Optionally, the signal preprocessing includes at least one of adaptive filtering, signal amplification, linearization processing, and digital conversion.

[0047] Optionally, the multi-physical quantity signal features include electrical signal features, vibration signal features, temperature signal features, and magnetic field signal features;

[0048] The electrical signal features are obtained through the following formula:

[0049]

[0050] where represents the total number of sampling points in the electrical signal sequence, represents the th sampling point value in the electrical signal sequence, represents the time delay parameter, represents the number of sampling points in the electrical signal sequence used to calculate the change amount, represents the th sampling point value in the electrical signal sequence used to calculate the change amount;

[0051] The vibration signal features are obtained through the following formula:

[0052]

[0053] where represents the total number of sampling points in the vibration signal sequence, represents the th sampling point value in the vibration signal sequence, represents the mean value of the vibration signal sampling points, represents the number of sampling points in the vibration signal sequence used to calculate the variance, represents the th sampling point value in the vibration signal sequence used to calculate the variance;

[0054] The temperature signal features are obtained through the following formula:

[0055]

[0056] where represents the total number of sampling points in the temperature signal sequence, represents the th sampling point value in the temperature signal sequence, represents the th sampling point value in the temperature signal sequence;

[0057] The magnetic field signal features are obtained through the following formula:

[0058]

[0059] Among them, represents the total number of sampling points in the magnetic field signal sequence, represents the th sampling point value in the magnetic field signal sequence, represents the th sampling point value in the magnetic field signal sequence.

[0060] Optionally, the data processing flow of the multi - physical quantity signal fusion evaluation model includes:

[0061] According to the multi - physical quantity signal characteristics, the evaluation index of the circuit breaker is obtained through the following multi - physical quantity signal fusion evaluation formula :

[0062]

[0063] Among them, represents the weight coefficient of the electrical signal characteristics, represents the electrical signal characteristics, represents the weight coefficient of the vibration signal characteristics, represents the vibration signal characteristics, represents the weight coefficient of the temperature signal characteristics, represents the temperature signal characteristics, represents the weight coefficient of the magnetic field signal characteristics, represents the magnetic field signal characteristics, represents the base of the natural logarithm, represents the bias parameter;

[0064] According to the evaluation index and the set threshold the following judgment is made:

[0065] If , the evaluation result is that the circuit breaker is operating normally;

[0066] If , the evaluation result is that the circuit breaker is operating abnormally.

[0067] Optionally, the excitation applied to the circuit breaker includes electrical pulse excitation and mechanical shock excitation, and the excitation signal includes electrical pulse excitation signal and mechanical shock excitation signal.

[0068] Optionally, the data processing flow of the signal propagation model includes:

[0069] The theoretical signal strength of the excitation signal reaching each monitoring point is obtained through the following theoretical signal strength formula:

[0070]

[0071] Among them, represents the distance from the excitation signal source to the measurement point, represents the arrival time of the excitation signal, represents the excitation signal at a distance of and time the theoretical signal strength at this time, represents the initial strength of the excitation signal source, represents the attenuation coefficient of the excitation signal propagation medium, represents the relevant parameter of the excitation signal frequency, represents the time the excitation signal frequency at this time, represents the maximum propagation distance of the excitation signal, represents the power parameter related to the excitation signal propagation characteristics, represents the adjustment coefficient related to the excitation signal frequency, represents the initial phase parameter of the excitation signal;

[0072] According to the theoretical signal strength of the excitation signal reaching each monitoring point, the fault evaluation index of each area is obtained through the following fault area analysis formula:

[0073]

[0074] Among them, represents the fault evaluation index of the th area, represents the number of monitoring points, represents the distance from the excitation signal source to the th measurement point, represents the th arrival time of the excitation signal at the measurement point, represents the received excitation signal strength at a distance of and time at this time, represents the theoretical signal strength at a distance of and time at this time, represents the weight coefficient of the th measurement point, represents the th structural complexity index of the area where the measurement point is located, represents the sum of the structural complexity indices of all areas where the measurement points are located;

[0075] According to the fault evaluation index of each area and the preset fault judgment threshold carry out fault location judgment to obtain the circuit breaker fault area: If , then it is considered the There is a fault in a region, otherwise it is considered that the region is operating normally.

[0076] Thirdly, the present invention provides a computer-readable storage medium, on which computer instructions are stored. When the computer instructions are executed by a processor, the steps of any one of the circuit breaker testing methods based on signal analysis in the first aspect are implemented.

[0077] Fourthly, the present invention provides a computer device, including:

[0078] A memory for storing computer instructions;

[0079] A processor for executing the computer instructions to implement the steps of any one of the circuit breaker testing methods based on signal analysis in the first aspect.

[0080] Fifthly, the present invention provides a computer program product, including computer instructions. When the computer instructions are executed by a processor, the steps of any one of the circuit breaker testing methods based on signal analysis in the first aspect are implemented.

[0081] Compared with the prior art, the beneficial effects achieved by the present invention:

[0082] 1. The circuit breaker testing method based on signal analysis provided by the present invention realizes a comprehensive and accurate evaluation of the performance of the circuit breaker through multi-physical quantity signal acquisition, preprocessing, fusion analysis, and signal propagation path modeling and real-time monitoring; by fusing multiple physical quantity information such as electrical signals, vibration signals, temperature signals, and magnetic field signals, a multi-physical quantity signal fusion evaluation model is constructed, improving the accuracy and reliability of fault diagnosis; through the signal propagation path model, the propagation law of signals inside the circuit breaker is revealed, providing a scientific basis for the accurate positioning of the fault area; it not only provides a strong guarantee for the safe operation of the power system, but also can provide decision-making support for the preventive maintenance and fault troubleshooting of the circuit breaker, reducing the operation and maintenance costs of the power system and improving the power supply reliability and economy.

[0083] 2. The circuit breaker testing system based on signal analysis provided by the present invention realizes the testing of the circuit breaker by setting a preprocessing module, a feature extraction module, a circuit breaker evaluation module, and a circuit breaker fault diagnosis module, which can comprehensively consider the internal relationship between multiple physical quantity signals, accurately evaluate the overall performance and health status of the circuit breaker, and improve the accuracy and reliability of fault diagnosis. In addition, the application of real-time monitoring and multi-physical quantity signal fusion analysis technology enables the system to detect potential faults in a timely manner, providing strong support for the preventive maintenance of the circuit breaker.

[0084] 3. The computer-readable storage medium, computer device, and computer program product provided by the present invention can execute the steps of the fault self-checking method for the breaker circuit provided by the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0085] Figure 1 FIG. is a flowchart of a breaker test method based on signal analysis according to an embodiment of the present invention;

[0086] Figure 2 FIG. is a structural diagram of a breaker test system based on signal analysis according to an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0087] The technical solution of the present invention will be described in detail below with reference to the drawings and specific embodiments. It should be understood that the specific features in the embodiments of the present invention are detailed descriptions of the technical solution of the present invention, rather than limitations on the technical solution of the present invention. Without conflict, the technical features in the embodiments of the present invention and the embodiments can be combined with each other.

[0088] It should be noted that the term "and / or" in this article is only a description of the association relationship between associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. In addition, the character " / " in this article generally represents an "or" relationship between the associated objects before and after.

[0089] Embodiment 1:

[0090] An embodiment of the present invention discloses a breaker test method based on signal analysis. Referring to Figure 1 as shown, it includes:

[0091] S1. Extract features from the collected multi-physical quantity signal dataset to obtain multi-physical quantity signal features;

[0092] S2. Input the multi-physical quantity signal features into the constructed multi-physical quantity signal fusion evaluation model for evaluation to obtain an evaluation result that the breaker is operating normally or the breaker is operating abnormally;

[0093] S3. When the evaluation result is that the breaker is operating abnormally, apply an excitation to the breaker, receive the arrival time and signal strength of the excitation signal at each monitoring point in the breaker, and use the constructed signal propagation model for fault location to obtain the breaker fault area.

[0094] Specifically,

[0095] In step S1, by arranging electrical signal sensors, vibration signal sensors, temperature signal sensors, and magnetic field signal sensors at key parts of the circuit breaker, and setting the signal acquisition frequency and sampling accuracy according to the circuit breaker characteristics and test requirements, a multi-physical quantity signal dataset is acquired; the multi-physical quantity signal dataset includes electrical signals, vibration signals, temperature signals, magnetic field signals, etc.; the positions where each sensor is arranged are as follows:

[0096] Electrical signal sensors: Arranged at the incoming line end, outgoing line end, and internal conductive circuit of the circuit breaker;

[0097] Vibration signal sensors: Arranged on the outer shell, contact system, and operating mechanism of the circuit breaker;

[0098] Temperature signal sensors: Arranged at the contacts, arc extinguishing chambers, and easily heated areas of the conductive connections;

[0099] Magnetic field signal sensors: Arranged around the conductive circuit of the circuit breaker and near the contacts.

[0100] In a substation, the high-voltage circuit breaker is crucial for the stable operation of the power system. It is in a working environment of high voltage and large current for a long time, and problems such as contact wear, insulation aging, and mechanical component failures are likely to occur, and comprehensive inspections need to be carried out regularly; therefore, in this embodiment, electrical signal sensors are installed at the incoming line end, outgoing line end, and internal conductive circuit of the high-voltage circuit breaker to accurately monitor the changes in current and voltage; vibration signal sensors are arranged on the outer shell, contact system, and operating mechanism to capture mechanical vibrations during the operation process; temperature signal sensors are set at the contacts, arc extinguishing chambers, and easily heated areas of the conductive connections to monitor abnormal temperature increases; magnetic field signal sensors are placed around the conductive circuit and near the contacts to detect fluctuations in the magnetic field. According to the characteristics of high-voltage equipment and strict test requirements, the signal acquisition frequency is set to 10 kHz, and the sampling accuracy is set to 12 bits to ensure that the acquired signals can accurately reflect the operating state of the circuit breaker.

[0101] It also includes signal preprocessing of the collected multi-physical quantity signal dataset; correspondingly, the inputting of the multi-physical quantity signal features into the constructed multi-physical quantity signal fusion evaluation model for evaluation includes: inputting the preprocessed multi-physical quantity signal features into the constructed multi-physical quantity signal fusion evaluation model for evaluation; the signal preprocessing includes: applying an adaptive filtering technique to effectively remove the power frequency interference and electromagnetic interference noise generated by the complex electromagnetic environment of the substation according to the real-time characteristics of the signal and the noise; with the help of an amplifying circuit with an automatic gain control function, automatically adjusting the amplification factor according to the input signal strength, for example, when the electrical signal is weak, amplifying it to ensure the accuracy of subsequent processing; by establishing a non-linear correction technique, performing real-time linearization processing on the non-linear signal output by the sensor to condition the signal, such as correcting the non-linear output of the temperature sensor in the high temperature section; using an analog-to-digital converter to convert the analog signal after the previous processing into a digital signal according to the signal characteristics and subsequent processing requirements, and storing it in a large-capacity storage device for subsequent analysis.

[0102] The multi-physical quantity signal features include electrical signal features, vibration signal features, temperature signal features, and magnetic field signal features; specifically, the electrical signal features are obtained through the following formula:

[0103]

[0104] where, represents the total number of sampling points in the electrical signal sequence, represents the th sampling point value in the electrical signal sequence, represents the time delay parameter, represents the number of sampling points in the electrical signal sequence used to calculate the change amount, represents the th sampling point value in the electrical signal sequence used to calculate the change amount.

[0105] The vibration signal features are obtained through the following formula:

[0106]

[0107] where, represents the total number of sampling points in the vibration signal sequence, represents the th sampling point value in the vibration signal sequence, represents the mean value of the vibration signal sampling points, represents the number of sampling points in the vibration signal sequence used to calculate the variance, represents the The values of the sampling points.

[0108] The temperature signal feature is obtained through the following formula:

[0109]

[0110] where, represents the total number of sampling points in the temperature signal sequence, represents the -th sampling point value in the temperature signal sequence, represents the -th sampling point value in the temperature signal sequence.

[0111] The magnetic field signal feature is obtained through the following formula:

[0112]

[0113] where, represents the total number of sampling points in the magnetic field signal sequence, represents the -th sampling point value in the magnetic field signal sequence, represents the -th sampling point value in the magnetic field signal sequence.

[0114] In step S2, the data processing flow of the multi-physical quantity signal fusion evaluation model includes:

[0115] Input the electrical signal feature, vibration signal feature, temperature signal feature, and magnetic field signal feature into the multi-physical quantity signal fusion evaluation model to comprehensively evaluate the overall performance and health status of the circuit breaker, and obtain the evaluation index of the circuit breaker through the following multi-physical quantity signal fusion evaluation formula :

[0116]

[0117] where, represents the weight coefficient of the electrical signal feature, represents the electrical signal feature, represents the weight coefficient of the vibration signal feature, represents the vibration signal feature, represents the weight coefficient of the temperature signal feature, represents the temperature signal feature, represents the weight coefficient of the magnetic field signal feature, represents the magnetic field signal feature, represents the base of the natural logarithm, represents the bias parameter.

[0118] According to the evaluation index of the circuit breaker and the set threshold to perform anomaly judgment; if the evaluation index of the circuit breaker value is less than the threshold , then the evaluation result is that the circuit breaker is operating abnormally and further inspection and maintenance are required, otherwise the evaluation result is that the circuit breaker is operating normally.

[0119] In step S3, the signal propagation model traces the signal propagation path through experimental measurement and numerical simulation. Based on the results of the signal propagation path tracing, combined with the characteristics of the signal source and the physical parameters of the propagation medium, it is established; the actual situation of the signal propagation path is determined through experimental measurement. According to the type and internal structure of the circuit breaker, it is divided into a conductive area, a mechanical area, an insulating area, and a heating area. Signal monitoring points are arranged in each area, an electrical pulse excitation and a mechanical shock excitation are applied to the circuit breaker, a measuring device is used to collect signals, and the relevant information on the time and intensity of the electrical pulse excitation signal and the mechanical shock excitation signal received at different monitoring points is recorded. By analyzing the time difference and intensity change of the signal reaching different monitoring points, combined with the circuit breaker structure and material characteristics, the actual situation of the signal propagation path under the actual working condition of the circuit breaker is determined.

[0120] The microscopic details and theoretical predictions of the signal propagation path are determined through numerical simulation to obtain the theoretical signal intensity formula; a three-dimensional model of the circuit breaker is constructed by means of the finite element test method. The model covers the structure of the incoming line end, outgoing line end, contact system, arc extinguishing chamber, and operating mechanism inside the circuit breaker. At the same time, the property parameters of the dielectric constant, magnetic permeability, elastic modulus, and thermal conductivity of the materials of each part are defined. The signal propagation data obtained through actual measurement is used as boundary conditions and initial conditions and input into the numerical simulation model. The phenomena of signal reflection, refraction, and scattering inside the circuit breaker are simulated in the model to determine the microscopic details and theoretical predictions of the signal propagation path inside the circuit breaker.

[0121] The data processing flow of the signal propagation model includes:

[0122] The theoretical signal intensity of the excitation signal reaching each monitoring point is obtained through the following theoretical signal intensity formula:

[0123]

[0124] Among them, represents the distance from the excitation signal source to the measurement point, represents the arrival time of the excitation signal, represents the theoretical signal intensity of the excitation signal at a distance and time , represents the initial intensity of the excitation signal source, represents the attenuation coefficient of the excitation signal propagation medium, a parameter related to the frequency of the excitation signal, represents time the frequency of the excitation signal at time represents the maximum propagation distance of the excitation signal, a power parameter related to the propagation characteristics of the excitation signal, a regulation coefficient related to the frequency of the excitation signal, represents the initial phase parameter of the excitation signal;

[0125] According to the theoretical signal strength of the excitation signal reaching each monitoring point, the fault evaluation index of each area is obtained through the following fault area analysis formula:

[0126]

[0127] where, represents the fault evaluation index of the th area, represents the number of monitoring points, represents the distance from the excitation signal source to the th measurement point, represents the arrival time of the excitation signal at the th measurement point, represents the intensity of the excitation signal received at a distance and time ; represents the theoretical signal strength at a distance and time ; represents the weight coefficient of the th measurement point, represents the structural complexity index of the area where the th measurement point is located, represents the sum of the structural complexity indices of all areas where the measurement points are located;

[0128] Based on the fault evaluation index of each area and a preset fault judgment threshold a fault location judgment is made to obtain the fault area of the circuit breaker: If , it is considered that there is a fault in the th area, otherwise it is considered that the th area is operating normally.

[0129] In this embodiment, fault diagnosis is carried out through signal propagation path analysis, revealing the propagation law of signals inside the circuit breaker. By combining experimental measurement and numerical simulation, the propagation path of signals inside the circuit breaker is traced, and a signal propagation model is established. By simulating the reflection, refraction, and scattering phenomena of signals inside the circuit breaker, the intensity change of signals at different positions and times can be accurately predicted. A fault area analysis formula is also proposed. By comparing the difference between the actually measured signal intensity and the theoretical signal intensity, the location of the fault area is determined, which not only improves the accuracy of fault location but also provides a scientific basis for fault repair of the circuit breaker, reducing the maintenance cost and time.

[0130] In summary, the circuit breaker test method based on signal analysis proposed in this embodiment plays a key role in the detection of high-voltage circuit breakers in substations. Starting from the multi-physical quantity signal acquisition stage, various sensors are accurately arranged to ensure comprehensive and key operation information can be obtained. The set acquisition frequency and accuracy meet the requirements of high-voltage equipment. The signal preprocessing effectively removes interference and corrects signals, creating good conditions for subsequent analysis. The fusion analysis uses scientific formulas and reasonable model weights to comprehensively evaluate the performance of the circuit breaker. The signal propagation path analysis explores the signal transmission law in depth through both experiments and simulations, and finally realizes accurate diagnosis and location of faults, effectively guaranteeing the safe and stable operation of the substation. This method has practicality and effectiveness in the field of high-voltage power equipment detection.

[0131] Embodiment 2:

[0132] An embodiment of the present invention discloses a circuit breaker test system based on signal analysis. Referring to Figure 2 as shown, it includes:

[0133] A feature extraction module, configured to: extract features from the acquired multi-physical quantity signal dataset to obtain multi-physical quantity signal features;

[0134] A circuit breaker evaluation module, configured to: input the multi-physical quantity signal features into the constructed multi-physical quantity signal fusion evaluation model for evaluation to obtain an evaluation result that the circuit breaker is operating normally or the circuit breaker is operating abnormally;

[0135] A circuit breaker fault diagnosis module, configured to: in the case where the evaluation result is that the circuit breaker is operating abnormally, apply an excitation signal to the circuit breaker, and receive the arrival time and signal intensity of the excitation signal at each monitoring point inside the circuit breaker, and use the arrival time, signal intensity, and the constructed signal propagation model for fault location to obtain the fault area of the circuit breaker.

[0136] Specifically, in this embodiment, electrical signal sensors, vibration signal sensors, temperature signal sensors, and magnetic field signal sensors are arranged at key parts of the circuit breaker. Meanwhile, according to the characteristics of the circuit breaker and the test requirements, the signal acquisition frequency and sampling accuracy are set to collect a multi-physical quantity signal dataset. The multi-physical quantity signal dataset includes electrical signals, vibration signals, temperature signals, magnetic field signals, etc. The positions where each sensor is arranged are as follows:

[0137] Electrical signal sensors: Arranged at the incoming line end, outgoing line end, and internal conductive circuit of the circuit breaker;

[0138] Vibration signal sensors: Arranged on the outer shell, contact system, and operating mechanism of the circuit breaker;

[0139] Temperature signal sensors: Arranged in the areas prone to heat generation at the contacts, arc extinguishing chambers, and conductive joints;

[0140] Magnetic field signal sensors: Arranged around the conductive circuit of the circuit breaker and near the contacts.

[0141] In a substation, the high-voltage circuit breaker is crucial for the stable operation of the power system. It is in a working environment of high voltage and large current for a long time, and problems such as contact wear, insulation aging, and mechanical component failures are likely to occur, and comprehensive inspections need to be carried out regularly. Therefore, in this embodiment, electrical signal sensors are installed at the incoming line end, outgoing line end, and internal conductive circuit of the high-voltage circuit breaker to accurately monitor the changes in current and voltage; vibration signal sensors are arranged on the outer shell, contact system, and operating mechanism to capture the mechanical vibrations during the operation process; temperature signal sensors are set in the areas prone to heat generation at the contacts, arc extinguishing chambers, and conductive joints to monitor abnormal temperature rises; magnetic field signal sensors are placed around the conductive circuit and near the contacts to detect the fluctuations of the magnetic field. According to the characteristics of high-voltage equipment and strict test requirements, the signal acquisition frequency is set to 10 kHz, and the sampling accuracy is set to 12 bits to ensure that the collected signals can accurately reflect the operating state of the circuit breaker.

[0142] This embodiment further includes a preprocessing module, which is used to perform signal preprocessing on the collected multi-physical quantity signal dataset; correspondingly, inputting the multi-physical quantity signal features into the constructed multi-physical quantity signal fusion evaluation model for evaluation includes: inputting the preprocessed multi-physical quantity signal features into the constructed multi-physical quantity signal fusion evaluation model for evaluation; the signal preprocessing includes: applying an adaptive filtering technique to effectively remove the power frequency interference and electromagnetic interference noise generated by the complex electromagnetic environment of the substation according to the real-time characteristics of the signal and noise; using an amplifier circuit with an automatic gain control function to automatically adjust the amplification factor according to the input signal strength. For example, when the electrical signal is weak, it is amplified to ensure the accuracy of subsequent processing; by establishing a non-linear correction technique, the non-linear signal output by the sensor is linearly processed in real time to condition the signal, such as correcting the non-linear output of the temperature sensor in the high temperature section; using an analog-to-digital converter to convert the analog signal after the previous processing into a digital signal according to the signal characteristics and subsequent processing requirements, and storing it in a large-capacity storage device for subsequent analysis.

[0143] The multi-physical quantity signal features include electrical signal features, vibration signal features, temperature signal features, and magnetic field signal features; specifically, the electrical signal features are obtained through the following formula:

[0144]

[0145] where represents the total number of sampling points in the electrical signal sequence, represents the th sampling point value in the electrical signal sequence, represents the time delay parameter, represents the number of sampling points used to calculate the change amount in the electrical signal sequence, represents the th sampling point value used to calculate the change amount in the electrical signal sequence.

[0146] The vibration signal features are obtained through the following formula:

[0147]

[0148] where represents the total number of sampling points in the vibration signal sequence, represents the th sampling point value in the vibration signal sequence, represents the mean value of the vibration signal sampling points, represents the number of sampling points used to calculate the variance in the vibration signal sequence, Indicates the th sampling point value used for calculating variance in the vibration signal sequence.

[0149] The temperature signal feature is obtained through the following formula:

[0150]

[0151] where, represents the total number of sampling points in the temperature signal sequence, represents the th sampling point value in the temperature signal sequence, represents the th sampling point value in the temperature signal sequence.

[0152] The magnetic field signal feature is obtained through the following formula:

[0153]

[0154] where, represents the total number of sampling points in the magnetic field signal sequence, represents the th sampling point value in the magnetic field signal sequence, represents the th sampling point value in the magnetic field signal sequence.

[0155] In step S3, the data processing flow of the multi - physical quantity signal fusion evaluation model includes:

[0156] Input the electrical signal feature, vibration signal feature, temperature signal feature, and magnetic field signal feature into the multi - physical quantity signal fusion evaluation model, comprehensively evaluate the overall performance and health status of the circuit breaker, and obtain the evaluation index of the circuit breaker through the following multi - physical quantity signal fusion evaluation formula :

[0157]

[0158] where, represents the weight coefficient of the electrical signal feature, represents the electrical signal feature, represents the weight coefficient of the vibration signal feature, represents the vibration signal feature, represents the weight coefficient of the temperature signal feature, represents the temperature signal feature, represents the weight coefficient of the magnetic field signal feature, represents the magnetic field signal feature, represents the base of the natural logarithm, Represents the offset parameter.

[0159] According to the evaluation index of the circuit breaker and the set threshold perform anomaly judgment; if the evaluation index of the circuit breaker value is less than the threshold , the evaluation result is that the circuit breaker is operating abnormally and further inspection and maintenance are required, otherwise the evaluation result is that the circuit breaker is operating normally.

[0160] In step S4, the signal propagation model traces the signal propagation path through experimental measurement and numerical simulation. Based on the results of the signal propagation path tracing, it is established by combining the characteristics of the signal source and the physical parameters of the propagation medium; the actual situation of the signal propagation path is determined through experimental measurement. According to the type and internal structure of the circuit breaker, it is divided into a conductive region, a mechanical region, an insulating region, and a heating region. Signal monitoring points are arranged in each region, an electrical pulse excitation and a mechanical shock excitation are applied to the circuit breaker, a measuring device is used to collect signals, and the relevant information on the time and intensity of the electrical pulse excitation signal and the mechanical shock excitation signal received at different monitoring points is recorded. By analyzing the time difference and intensity change of the signal reaching different monitoring points, combined with the circuit breaker structure and material characteristics, the actual situation of the signal propagation path under the actual working state of the circuit breaker is determined.

[0161] Determine the microscopic details and theoretical predictions of the signal propagation path through numerical simulation, and obtain the theoretical signal intensity formula; construct a three-dimensional model of the circuit breaker by means of the finite element test method. The model covers the structure of the incoming line end, outgoing line end, contact system, arc extinguishing chamber, and operating mechanism inside the circuit breaker. At the same time, define the property parameters of the dielectric constant, magnetic permeability, elastic modulus, and thermal conductivity of the materials of each part. Input the signal propagation data obtained from actual measurement as boundary conditions and initial conditions into the numerical simulation model. Simulate the phenomena of signal reflection, refraction, and scattering inside the circuit breaker in the model, and determine the microscopic details and theoretical predictions of the signal propagation path inside the circuit breaker.

[0162] The data processing flow of the signal propagation model includes:

[0163] Obtain the theoretical signal intensity of the excitation signal reaching each monitoring point through the following theoretical signal intensity formula:

[0164]

[0165] Where represents the distance from the excitation signal source to the measurement point, represents the arrival time of the excitation signal, represents the theoretical signal intensity of the excitation signal at a distance and time , represents the initial intensity of the excitation signal source, represents the attenuation coefficient of the excitation signal propagation medium, represents the relevant parameter of the excitation signal frequency, represents time the excitation signal frequency at time represents the maximum propagation distance of the excitation signal, represents the power parameter related to the propagation characteristics of the excitation signal, represents the adjustment coefficient related to the excitation signal frequency, represents the initial phase parameter of the excitation signal;

[0166] According to the theoretical signal intensity of the excitation signal reaching each monitoring point, the fault evaluation index of each area is obtained through the following fault area analysis formula:

[0167]

[0168] where, represents the fault evaluation index of the th area, represents the number of monitoring points, represents the distance from the excitation signal source to the th measurement point, represents the arrival time of the excitation signal at the th measurement point, represents at a distance and time the received excitation signal intensity at, represents at a distance and time the theoretical signal intensity at, represents the weight coefficient of the th measurement point, represents the structural complexity index of the area where the th measurement point is located, represents the sum of the structural complexity indexes of the areas where all measurement points are located;

[0169] According to the fault evaluation index of each area and the preset fault judgment threshold perform fault location judgment to obtain the circuit breaker fault area: If , then it is considered that the th area has a fault, otherwise it is considered that the th area is operating normally.

[0170] In this embodiment, it further includes a data acquisition module, a user interface and interaction module, and a data storage and management module; the data acquisition module collects a multi-physical quantity signal dataset by installing various sensors such as electrical signals, mechanical signals, thermal signals, and electromagnetic signals at key parts of the circuit breaker; the user interface and interaction module provides an operation interface for the user, supports the user to start or stop the circuit breaker test through the operation interface, presents the diagnostic results in the form of signal waveform diagrams, and can automatically generate test reports; the data storage and management module includes a storage medium and a data management system, and has functions of hierarchical storage, label classification, indexing, and backup and recovery of data.

[0171] Embodiment Three:

[0172] This embodiment provides a computer-readable storage medium, on which computer instructions are stored. When the computer instructions are executed by a processor, the steps of the circuit breaker test method based on signal analysis as described in any one of Embodiment One are implemented.

[0173] Embodiment Four:

[0174] This embodiment provides a computer device, including:

[0175] A memory for storing computer instructions;

[0176] A processor for executing the computer instructions to implement the steps of the circuit breaker test method based on signal analysis as described in any one of Embodiment One.

[0177] Embodiment Five:

[0178] This embodiment provides a computer program product, including computer instructions. When the computer instructions are executed by a processor, the steps of the circuit breaker test method based on signal analysis as described in any one of Embodiment One are implemented.

[0179] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0180] The present invention is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to embodiments of the present invention. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and combinations of flows and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to the processors of general-purpose computers, special-purpose computers, embedded processors, or other programmable data processing devices to produce a machine, such that the instructions executed by the processors of the computer or other programmable data processing devices produce means for implementing the functions specified in one flow Figure 1 one flow or multiple flows and / or blocks Figure 1 or means for implementing the functions specified in one block or multiple blocks.

[0181] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory produce a manufactured article including instruction means that implement the functions specified in one flow Figure 1 one flow or multiple flows and / or blocks Figure 1 or means for implementing the functions specified in one block or multiple blocks.

[0182] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operation steps are executed on the computer or other programmable device to produce a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one flow Figure 1 one flow or multiple flows and / or blocks Figure 1 or means for implementing the functions specified in one block or multiple blocks.

[0183] The embodiments of the present invention have been described above in conjunction with the accompanying drawings. However, the present invention is not limited to the above specific embodiments. The above specific embodiments are merely illustrative and not restrictive. Under the inspiration of the present invention, those of ordinary skill in the art can also make many forms without departing from the spirit and scope protected by the present invention and the claims. All of these fall within the protection scope of the present invention.

Claims

1. A circuit breaker testing method based on signal analysis, characterized in that, Including: Performing feature extraction on the collected multi-physical quantity signal dataset to obtain multi-physical quantity signal features; Inputting the multi-physical quantity signal features into the constructed multi-physical quantity signal fusion evaluation model for evaluation to obtain an evaluation result that the circuit breaker is operating normally or the circuit breaker is operating abnormally; In the case where the evaluation result is that the circuit breaker is operating abnormally, applying an excitation signal to the circuit breaker, and receiving the arrival time and signal strength of the excitation signal at each monitoring point within the circuit breaker, and using the arrival time, signal strength, and the constructed signal propagation model for fault location to obtain the circuit breaker fault area.

2. The circuit breaker testing method based on signal analysis according to claim 1, wherein It also includes signal preprocessing of the collected multi-physical quantity signal dataset; correspondingly, the inputting the multi-physical quantity signal features into the constructed multi-physical quantity signal fusion evaluation model for evaluation includes: inputting the preprocessed multi-physical quantity signal features into the constructed multi-physical quantity signal fusion evaluation model for evaluation.

3. The circuit breaker testing method based on signal analysis according to claim 2, characterized in that The signal preprocessing includes at least one of adaptive filtering, signal amplification, linearization processing, and digital conversion.

4. The circuit breaker testing method based on signal analysis according to claim 1, characterized in that, The multi-physical quantity signal features include electrical signal features, vibration signal features, temperature signal features, and magnetic field signal features; The electrical signal feature is obtained by the following formula: Among them, represents the total number of sampling points in the electrical signal sequence, represents the th sampling point value in the electrical signal sequence, represents the time delay parameter, represents the number of sampling points in the electrical signal sequence used to calculate the change amount, represents the th sampling point value in the electrical signal sequence used to calculate the change amount; The vibration signal characteristics are obtained by the following formula: Among them, represents the total number of sampling points in the vibration signal sequence, represents the -th sampling point value in the vibration signal sequence, represents the mean value of the vibration signal sampling points, represents the number of sampling points used to calculate the variance in the vibration signal sequence, represents the -th sampling point value used to calculate the variance in the vibration signal sequence; The temperature signal characteristics Obtained by the following formula: Among them, represents the total number of sampling points in the temperature signal sequence, represents the th sampling point value in the temperature signal sequence, represents the th sampling point value; The magnetic field signal characteristics Obtained by the following formula: Among them, represents the total number of sampling points in the magnetic field signal sequence, represents the -th sampling point value in the magnetic field signal sequence, represents the -th sampling point value in the magnetic field signal sequence.

5. The circuit breaker testing method based on signal analysis according to claim 1, characterized in that, The data processing flow of the multi-physical quantity signal fusion evaluation model includes: According to the multi-physical quantity signal characteristics, an evaluation index of the circuit breaker is obtained through the following multi-physical quantity signal fusion evaluation formula : Among them, represents the weight coefficient of the electrical signal feature, represents the electrical signal feature, represents the weight coefficient of the vibration signal feature, represents the vibration signal feature, represents the weight coefficient of the temperature signal feature, represents the temperature signal feature, represents the weight coefficient of the magnetic field signal feature, represents the magnetic field signal feature, represents the base of the natural logarithm, represents the bias parameter; According to the evaluation metrics and the set threshold make the following judgment: If , the evaluation result is that the circuit breaker is operating normally; If , the evaluation result is that the circuit breaker is operating abnormally.

6. The circuit breaker testing method based on signal analysis according to claim 1, wherein The excitation applied to the circuit breaker includes electrical pulse excitation and mechanical shock excitation, and the excitation signal includes an electrical pulse excitation signal and a mechanical shock excitation signal.

7. The circuit breaker testing method based on signal analysis according to claim 1, wherein The data processing flow of the signal propagation model includes: Obtaining the theoretical signal strength of the excitation signal reaching each monitoring point through the following theoretical signal strength formula: Among them, represents the distance from the excitation signal source to the measurement point, represents the arrival time of the excitation signal, represents the theoretical signal strength of the excitation signal at the distance and time ; represents the initial strength of the excitation signal source, represents the attenuation coefficient of the excitation signal propagation medium, represents the parameter related to the excitation signal frequency, represents the time when the excitation signal frequency is, represents the maximum propagation distance of the excitation signal, represents the power parameter related to the excitation signal propagation characteristics, represents the adjustment coefficient related to the excitation signal frequency, represents the initial phase parameter of the excitation signal; According to the theoretical signal strength of the excitation signal reaching each monitoring point, obtaining the fault evaluation index of each area through the following fault area analysis formula: Among them, represents the fault assessment index of the th area, represents the number of monitoring points, represents the distance from the excitation signal source to the th measurement point, represents the arrival time of the excitation signal at the th measurement point, represents the intensity of the excitation signal received at a distance of and time , represents the theoretical signal intensity at a distance of and time , represents the weight coefficient of the th measurement point, represents the structural complexity index of the area where the th measurement point is located, represents the sum of the structural complexity indices of the areas where all measurement points are located; Based on the fault evaluation indicators of each region and the preset fault judgment threshold perform fault location judgment to obtain the fault area of the circuit breaker: If , it is considered that there is a fault in the th region, otherwise it is considered that the th region is operating normally.

8. A circuit breaker test system based on signal analysis, characterized in that, Including: A feature extraction module for performing feature extraction on the collected multi-physical quantity signal dataset to obtain multi-physical quantity signal features; A circuit breaker evaluation module for inputting the multi-physical quantity signal features into the constructed multi-physical quantity signal fusion evaluation model for evaluation to obtain an evaluation result that the circuit breaker is operating normally or the circuit breaker is operating abnormally; A circuit breaker fault diagnosis module for, in the case where the evaluation result is that the circuit breaker is operating abnormally, applying an excitation signal to the circuit breaker, and receiving the arrival time and signal strength of the excitation signal at each monitoring point within the circuit breaker, and using the arrival time, signal strength, and the constructed signal propagation model for fault location to obtain the circuit breaker fault area.

9. The circuit breaker test system based on signal analysis according to claim 8, wherein, It also includes a preprocessing module for performing signal preprocessing on the collected multi-physical quantity signal dataset; correspondingly, the inputting the multi-physical quantity signal features into the constructed multi-physical quantity signal fusion evaluation model for evaluation includes: inputting the preprocessed multi-physical quantity signal features into the constructed multi-physical quantity signal fusion evaluation model for evaluation.

10. The circuit breaker test system based on signal analysis according to claim 9, wherein The signal preprocessing includes at least one of adaptive filtering, signal amplification, linearization processing, and digital conversion.

11. The circuit breaker test system based on signal analysis according to claim 8, wherein The multi-physical quantity signal features include electrical signal features, vibration signal features, temperature signal features, and magnetic field signal features; The electrical signal characteristics Obtained by the following formula: wherein, represents the total number of sampling points in the electrical signal sequence, represents the th sampling point value in the electrical signal sequence, represents the time delay parameter, represents the number of sampling points in the electrical signal sequence for calculating the change amount, represents the th sampling point value in the electrical signal sequence for calculating the change amount; The vibration signal characteristics are obtained by the following formula: Among them, represents the total number of sampling points in the vibration signal sequence, represents the th sampling point value in the vibration signal sequence, represents the mean value of the vibration signal sampling points, represents the number of sampling points used to calculate the variance in the vibration signal sequence, represents the th sampling point value used to calculate the variance in the vibration signal sequence; The temperature signal feature is obtained by the following formula: Among them, represents the total number of sampling points in the temperature signal sequence, represents the th sampling point value in the temperature signal sequence, represents the th sampling point value; The magnetic field signal characteristics Obtained by the following formula: Among them, represents the total number of sampling points in the magnetic field signal sequence, represents the th sampling point value in the magnetic field signal sequence, represents the th sampling point value.

12. The circuit breaker testing system based on signal analysis according to claim 8, wherein The data processing flow of the multi-physical quantity signal fusion evaluation model includes: According to the multi-physical quantity signal characteristics, an evaluation index of the circuit breaker is obtained through the following multi-physical quantity signal fusion evaluation formula :[[]]END]] Among them, represents the weight coefficient of the electrical signal feature, represents the electrical signal feature, represents the weight coefficient of the vibration signal feature, represents the vibration signal feature, represents the weight coefficient of the temperature signal feature, represents the temperature signal feature, represents the weight coefficient of the magnetic field signal feature, represents the magnetic field signal feature, represents the base of the natural logarithm, represents the bias parameter; According to the evaluation metrics and the set threshold make the following judgment: If , the evaluation result is that the circuit breaker is operating normally; If , the evaluation result is that the circuit breaker is operating abnormally.

13. The circuit breaker test system based on signal analysis according to claim 8, characterized in that, The excitations applied to the circuit breaker include electrical pulse excitation and mechanical shock excitation, and the excitation signals include electrical pulse excitation signals and mechanical shock excitation signals.

14. The circuit breaker test system based on signal analysis according to claim 8, characterized in that, The data processing flow of the signal propagation model includes: Obtain the theoretical signal intensities of the excitation signals reaching each monitoring point through the following theoretical signal intensity formula: Among them, represents the distance from the excitation signal source to the measurement point, represents the arrival time of the excitation signal, represents the theoretical signal strength of the excitation signal at a distance of and time ; represents the initial strength of the excitation signal source, represents the attenuation coefficient of the excitation signal propagation medium, represents the parameter related to the excitation signal frequency, represents time when the excitation signal frequency is represents the maximum propagation distance of the excitation signal, represents the power parameter related to the excitation signal propagation characteristics, represents the adjustment coefficient related to the excitation signal frequency, represents the initial phase parameter of the excitation signal; According to the theoretical signal intensities of the excitation signals reaching each monitoring point, obtain the fault evaluation indexes of each region through the following fault region analysis formula: Among them, represents the fault assessment index of the th area, represents the number of monitoring points, represents the distance from the excitation signal source to the th measurement point, represents the arrival time of the excitation signal at the th measurement point, represents the intensity of the excitation signal received at a distance of and time , represents the theoretical signal intensity at a distance of and time , represents the weight coefficient of the th measurement point, represents the structural complexity index of the area where the th measurement point is located, represents the sum of the structural complexity indices of the areas where all measurement points are located; Based on the fault evaluation indexes of the respective regions and the preset fault judgment thresholds perform fault location judgment to obtain the fault area of the circuit breaker: If , then it is considered that there is a fault in the th region, otherwise it is considered that the th region is operating normally.

15. A computer-readable storage medium having computer instructions stored thereon, characterized in that, When the computer instruction is executed by the processor, the steps of the circuit breaker testing method based on signal analysis according to any one of claims 1-7 are implemented.

16. A computer device, characterized in that, Including: A memory for storing computer instructions; A processor for executing the computer instructions to implement the steps of the circuit breaker testing method based on signal analysis according to any one of claims 1-7.

17. A computer program product comprising computer instructions, characterized in that, When the computer instruction is executed by the processor, the steps of the circuit breaker testing method based on signal analysis according to any one of claims 1-7 are implemented.

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