A safety management method for PBD test system

Abstract

The present invention discloses a safety management method for a PBD test system, and relates to the technical field of safety management of a PBD test system. Potential discharge risks are identified by analyzing the waveform characteristic change trend of the discharge signal of the power test equipment. Analyzing the fatigue characteristics and strain rate of the power test equipment in the mechanical stress test helps to identify whether the power test equipment has excessive wear or potential mechanical failure during the test process, avoid equipment failure due to mechanical stress, analyze the impact of electromagnetic interference and electromagnetic sensitivity on the power test equipment, evaluate the performance of the equipment in the electromagnetic environment, reduce equipment failure or test data distortion caused by electromagnetic interference, and ensure the accuracy of the test results and the reliability of the equipment. Comprehensively evaluate the risk factors of each test to generate the abnormal coefficient of the PBD test system, which can comprehensively identify the potential risks in the system, reduce the occurrence of equipment failures and accidents, and ensure the safe operation of the equipment.

Description

Technical Field

[0001] The invention relates to the technical field of PBD test system safety management, in particular to a PBD test system safety management method. Background Art

[0002] The PBD (Position Based Dynamics) test system is an advanced system for precise position control and dynamic simulation. It is widely used in electrical equipment, automation systems, and robot control. With the increasing complexity of electrical equipment and systems, such as high-voltage power transmission, smart grids, and automated control systems, more accurate and efficient test systems are required to ensure the reliability and safety of the equipment.

[0003] Electrical equipment plays a critical role in various applications, such as energy supply, industrial automation, etc., and has strict requirements on its reliability and safety. The PBD test system can effectively identify and manage potential safety hazards through precise dynamic simulation and position control technology, thereby improving the operational safety of equipment.

[0004] However, during the PBD test system testing process, there are deficiencies in the comprehensive assessment and management of various risks such as partial discharge, mechanical stress and electromagnetic compatibility of power test equipment, which may lead to potential safety hazards in the actual operation of the test system and electrical equipment. Summary of the invention

[0005] In view of the deficiencies in the prior art, the present invention provides a safety management method for a PBD test system, which solves the problems of the above-mentioned background technology.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: a safety management method for a PBD test system, comprising the following steps: S1. collecting test parameters of the PBD test system, the test parameters including: partial discharge test parameters, mechanical stress test parameters, and electromagnetic compatibility test parameters; S2. based on the partial discharge test parameters, analyzing the waveform characteristic change trend of the discharge signal of the power test equipment in the partial discharge test, identifying the partial discharge test risk, and evaluating the partial discharge test risk coefficient; S3. based on the mechanical stress test parameters, analyzing the fatigue characteristics and strain rate of the power test equipment in the mechanical stress test, identifying the degree of mechanical stress abnormality of the power test equipment, and evaluating the mechanical stress test risk coefficient; S4. based on the electromagnetic compatibility test parameters, analyzing the degree of influence of the electromagnetic interference and electromagnetic sensitivity of the power test equipment on the electrical equipment in the electromagnetic compatibility test, and evaluating the electromagnetic compatibility test risk coefficient; S5. by comprehensively evaluating the partial discharge test risk coefficient, the mechanical stress test risk coefficient and the electromagnetic compatibility test risk coefficient, obtaining the abnormal coefficient of the PBD test system, comparing the abnormal coefficient of the PBD test system with the set abnormal coefficient threshold of the PBD test system, identifying the test risk in the PBD test system, and having maintenance personnel repair the corresponding power test equipment.

[0007] Furthermore, based on the local discharge test parameters, the waveform characteristic change trend of the discharge signal of the power test equipment in the local discharge test is analyzed, and the specific process of identifying the local discharge test risk is as follows: based on the local discharge test parameters, the local discharge test parameters are preprocessed to obtain the local discharge signal, and the waveform characteristics of the signal are extracted, including the discharge amplitude, discharge phase, discharge duration and discharge interval; the local discharge signal is decomposed by wavelet to obtain signal representations of different scales and times, the wavelet coefficients are extracted, and compared with the set threshold, the change trend at different scales is analyzed, and abnormal discharge signals are identified.

[0008] Furthermore, the specific process of evaluating the partial discharge test risk coefficient is as follows: extract statistical features from the wavelet coefficients and calculate the eigenvalues ​​of the wavelet coefficients at each scale; define fuzzy sets and membership functions based on the extracted statistical features, and construct fuzzy logic rules; convert the input statistical eigenvalues ​​into fuzzy membership values, apply fuzzy logic rules, calculate the fuzzified eigenvalues ​​through the fuzzy reasoning mechanism, obtain the fuzzy output, and obtain the partial discharge test risk coefficient through defuzzification.

[0009] Furthermore, based on the mechanical stress test parameters, the fatigue characteristics and strain rate of the power test equipment in the mechanical stress test are analyzed, and the specific process of identifying the abnormal degree of mechanical stress of the power test equipment is as follows: based on the partial discharge test parameters, the fatigue life of the power test equipment under a specific stress level is predicted through the stress-life curve, the cumulative damage of the power test equipment under different stress levels is evaluated, and the cumulative damage coefficient of the power test equipment is obtained; the strain rate of the power test equipment under different operating conditions is calculated, and the strain rate is comprehensively processed with the set strain rate standard value to obtain the high strain rate coefficient of the power test equipment; based on the cumulative damage coefficient of the power test equipment and the high strain rate coefficient of the power test equipment, the mechanical stress risk of the power test equipment is identified.

[0010] Furthermore, the specific process of evaluating the mechanical stress test risk coefficient is as follows: weights are assigned to the cumulative damage coefficient and the high strain rate coefficient of the power testing equipment through the tomography analysis method to obtain the cumulative damage coefficient weight coefficient and the high strain rate coefficient weight coefficient; the cumulative damage coefficient weight coefficient and the high strain rate coefficient weight coefficient are respectively comprehensively calculated with the cumulative damage coefficient of the power testing equipment and the high strain rate coefficient of the power testing equipment to obtain the mechanical stress test risk coefficient.

[0011] Furthermore, based on the electromagnetic compatibility test parameters, the specific process of analyzing the influence of the electromagnetic interference and electromagnetic sensitivity of the power test equipment on the electrical equipment in the electromagnetic compatibility test is as follows: based on the electromagnetic compatibility test parameters, extract the spectrum characteristics and response characteristics of the electromagnetic interference signal of the power test equipment, obtain the electromagnetic interference tolerance coefficient and the electromagnetic sensitivity tolerance coefficient, and divide the interference level; respectively determine whether the electromagnetic interference tolerance threshold and the electromagnetic sensitivity tolerance threshold of the power test equipment are exceeded, and identify the electromagnetic compatibility test risks;

[0012] Furthermore, the specific process of evaluating the electromagnetic compatibility test risk coefficient is as follows: based on the electromagnetic interference tolerance coefficient and the electromagnetic sensitivity tolerance coefficient, comprehensive calculations are performed with the electromagnetic interference tolerance threshold and the electromagnetic sensitivity tolerance threshold respectively to obtain the electromagnetic compatibility test risk coefficient.

[0013] Furthermore, the specific process of obtaining the abnormality coefficient of the PBD test system is as follows: the partial discharge test risk coefficient, the mechanical stress test risk coefficient and the electromagnetic compatibility test risk coefficient are respectively comprehensively calculated with the set partial discharge test risk coefficient threshold, the mechanical stress test risk coefficient threshold and the electromagnetic compatibility test risk coefficient threshold to obtain the abnormality coefficient of the PBD test system.

[0014] The present invention has the following beneficial effects:

[0015] (1) This safety management method for a PBD test system can identify potential discharge risks and detect abnormal discharge conditions in a timely manner by analyzing the waveform characteristic change trend of the discharge signal, thereby preventing possible equipment failures or safety accidents and improving the overall safety of the system. Analyzing the fatigue characteristics and strain rate in mechanical stress testing helps to identify whether the equipment has excessive wear or potential mechanical failures during the test process, avoid equipment failure due to mechanical stress, and thus ensure the stable operation of the test system.

[0016] (2) This safety management method for a PBD test system analyzes the impact of electromagnetic interference and electromagnetic sensitivity on power test equipment, evaluates the performance of the equipment in an electromagnetic environment, identifies possible electromagnetic compatibility issues, reduces equipment failures or test data distortion caused by electromagnetic interference, and ensures the accuracy of test results and the reliability of equipment. By comprehensively evaluating the risk factors of each test, generating an abnormality coefficient for the PBD test system, and comparing it with the preset threshold, potential risks in the system can be fully identified. Through timely maintenance and adjustment, safety hazards can be reduced and the overall safety and reliability of the system can be improved.

[0017] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 This is a flow chart of a safety management method for a PBD test system of the present invention.

[0019] Figure 2 The present invention obtains the abnormal coefficient flow chart of the PBD test system. DETAILED DESCRIPTION

[0020] The embodiment of the present application adopts a safety management method for a PBD test system, which solves the problem of insufficient risk assessment of partial discharge, mechanical stress and electromagnetic interference by systematically collecting and analyzing partial discharge, mechanical stress and electromagnetic compatibility test parameters, identifies potential safety hazards in the system, and ensures the overall safety and reliability of the test system.

[0021] The overall idea of ​​the problem in the embodiments of the present application is as follows: collect test parameters of the PBD test system, and the test parameters include: partial discharge test parameters, mechanical stress test parameters, and electromagnetic compatibility test parameters.

[0022] Based on the partial discharge test parameters, the waveform characteristic change trend of the discharge signal of the power test equipment in the partial discharge test is analyzed, the partial discharge test risk is identified, and the partial discharge test risk coefficient is evaluated.

[0023] Based on the mechanical stress test parameters, the fatigue characteristics and strain rate of the power test equipment in the mechanical stress test are analyzed, the abnormal degree of mechanical stress of the power test equipment is identified, and the risk factor of the mechanical stress test is evaluated.

[0024] Based on the electromagnetic compatibility test parameters, the influence of electromagnetic interference and electromagnetic sensitivity of power test equipment on electrical equipment in electromagnetic compatibility test is analyzed, and the risk factor of electromagnetic compatibility test is evaluated.

[0025] By comprehensively evaluating the partial discharge test risk factor, mechanical stress test risk factor and electromagnetic compatibility test risk factor, the abnormality coefficient of the PBD test system is obtained, and the abnormality coefficient of the PBD test system is compared with the set abnormality coefficient threshold of the PBD test system to identify the test risks in the PBD test system, and the corresponding power test equipment is repaired by maintenance personnel.

[0026] See also Figure 1 , an embodiment of the present invention provides a technical solution: a safety management method for a PBD test system, comprising the following steps: S1. collecting test parameters of the PBD test system, the test parameters including: partial discharge test parameters, mechanical stress test parameters, and electromagnetic compatibility test parameters; S2. based on the partial discharge test parameters, analyzing the waveform characteristic change trend of the discharge signal of the power test equipment in the partial discharge test, identifying the partial discharge test risk, and evaluating the partial discharge test risk coefficient; S3. based on the mechanical stress test parameters, analyzing the fatigue characteristics and strain rate of the power test equipment in the mechanical stress test, identifying the abnormal degree of mechanical stress of the power test equipment, and evaluating the mechanical stress test risk coefficient; S4. based on the electromagnetic compatibility test parameters, analyzing the influence of the electromagnetic interference and electromagnetic sensitivity of the power test equipment on the electrical equipment in the electromagnetic compatibility test, and evaluating the electromagnetic compatibility test risk coefficient; S5. by comprehensively evaluating the partial discharge test risk coefficient, the mechanical stress test risk coefficient and the electromagnetic compatibility test risk coefficient, obtaining the abnormal coefficient of the PBD test system, comparing the abnormal coefficient of the PBD test system with the set abnormal coefficient threshold of the PBD test system, identifying the test risk in the PBD test system, and having maintenance personnel repair the corresponding power test equipment.

[0027] In this embodiment, test parameters of the PBD test system are collected, and the test parameters include: partial discharge test parameters, mechanical stress test parameters, and electromagnetic compatibility test parameters. The partial discharge test parameters include the discharge amplitude, which is used to measure the intensity of the partial discharge signal and represents the energy of the discharge phenomenon.

[0028] The discharge phase indicates the specific position of the partial discharge phenomenon in the AC voltage cycle and is used to analyze the discharge characteristics. The discharge duration indicates the duration of a single partial discharge event and reflects the stability of the discharge phenomenon. The discharge interval refers to the time interval between two consecutive partial discharge events and is used to identify the periodicity and regularity of the discharge. The mechanical stress test parameters include, and the electromagnetic compatibility test parameters include;

[0029] Partial discharge refers to the discharge phenomenon caused by the incomplete penetration of some charges in the insulating materials inside the electrical equipment. It often occurs at the insulation defects of the power equipment. Mechanical stress refers to the internal stress of the power equipment under the action of external force. It usually affects the structural integrity and operational reliability of the equipment. Electromagnetic compatibility refers to the ability of electrical equipment to operate normally in its working environment without interfering with other equipment. EMC testing is designed to evaluate the anti-interference ability of the equipment in the electromagnetic environment and the impact on other equipment. Spectral characteristics refer to the distribution of signals in the frequency domain. By analyzing the spectral characteristics of electromagnetic signals, the frequency components and interference sources of the signal can be understood. Strain rate refers to the degree of deformation that occurs per unit time. In mechanical stress testing, strain rate is used to evaluate the dynamic response of the equipment under stress.

[0030] Specifically, based on the local discharge test parameters, the waveform characteristic change trend of the discharge signal of the power test equipment in the local discharge test is analyzed, and the specific process of identifying the local discharge test risk is as follows: based on the local discharge test parameters, the local discharge test parameters are preprocessed to obtain the local discharge signal, and the waveform characteristics of the signal are extracted, including the discharge amplitude, discharge phase, discharge duration and discharge interval; the local discharge signal is decomposed by wavelet to obtain signal representations of different scales and times, the wavelet coefficients are extracted, and compared with the set threshold, the change trend at different scales is analyzed, and abnormal discharge signals are identified.

[0031] In this embodiment, filtering, denoising and other operations are performed during the signal preprocessing process. The filtering methods include low-pass filtering, high-pass filtering and band-pass filtering. Characteristic parameters are extracted from the local discharge signal, including discharge amplitude, discharge phase, discharge duration and discharge interval. The extraction of these features is usually achieved through statistical methods and signal processing methods. Wavelet decomposition involves the following formula, and the wavelet transform formula for a discrete signal is expressed as: in, Representation scale and location The wavelet coefficients at represents the wavelet basis function, Represents the original signal at time point The value, scale Control the width and position of the wavelet Controls the position of the wavelet in the signal. After wavelet decomposition, the obtained wavelet coefficients It reflects the characteristics of the signal at different scales and times. The extracted wavelet coefficients are compared with the preset threshold Make comparisons and identify abnormal signals. ; Indicates that there is an abnormality at this point. Adaptive threshold ;in is a constant, is the standard deviation of the signal.

[0032] Specifically, the specific process of evaluating the partial discharge test risk coefficient is as follows: extract statistical features from the wavelet coefficients and calculate the eigenvalues ​​of the wavelet coefficients at each scale; define fuzzy sets and membership functions based on the extracted statistical features, and construct fuzzy logic rules; convert the input statistical eigenvalues ​​into fuzzy membership values, apply fuzzy logic rules, calculate the fuzzified eigenvalues ​​through the fuzzy reasoning mechanism, obtain the fuzzy output, and obtain the partial discharge test risk coefficient through defuzzification.

[0033] In this implementation, the statistical feature extraction process is to extract statistical features from the wavelet coefficients obtained by wavelet transformation. These features usually include the mean and standard deviation of the wavelet coefficients, which are used to describe the basic properties of the signal. The mean formula of the wavelet coefficients is: ;in, Represents the mean of the wavelet coefficients, indicating the average level of the coefficients. Represents the total number of wavelet coefficients. Indicates wavelet coefficients. Standard deviation: ;in, The standard deviation of the wavelet coefficients indicates the degree of dispersion of the coefficients. Define fuzzy sets and membership functions. According to the extracted statistical features, define fuzzy sets and membership functions: Fuzzy sets of the mean of wavelet coefficients: low mean (less than 6), medium mean (6 to 8), high mean (greater than 8) Triangular membership function example: low mean: ; Mean ; ; Fuzzy set of standard deviation of wavelet coefficients: low standard deviation (less than 1.5), medium standard deviation (1.5 to 2.5), high standard deviation (greater than 2.5) Membership function example: low standard deviation: ; Mean standard deviation: ; High standard deviation: . Construct fuzzy logic rules: Construct fuzzy logic rules based on fuzzy sets of mean and standard deviation. For example: if the mean is a high mean and the standard deviation is a high standard deviation, then the overall risk is a high risk; if the mean is a medium mean and the standard deviation is a medium standard deviation, then the overall risk is a medium risk; if the mean is a low mean and the standard deviation is a low standard deviation, then the overall risk is a low risk. The formula for calculating the final risk coefficient by weighted average is used to convert the results of fuzzy logic reasoning into specific values. For the mean and standard deviation on each scale, calculate its membership value in the fuzzy set, and the specific process of obtaining the partial discharge test risk coefficient by defuzzification is as follows: ;in, Represents the partial discharge test risk factor after defuzzification. Indicates The membership value of a fuzzy rule is the membership obtained in fuzzy logic reasoning. Indicates The output value corresponding to a fuzzy rule is usually a risk level or score. Represents the total number of fuzzy rules.

[0034] Specifically, based on the mechanical stress test parameters, the fatigue characteristics and strain rate of the power test equipment in the mechanical stress test are analyzed, and the specific process of identifying the abnormal degree of mechanical stress of the power test equipment is as follows: based on the partial discharge test parameters, the fatigue life of the power test equipment under a specific stress level is predicted through the stress-life curve, the cumulative damage of the power test equipment under different stress levels is evaluated, and the cumulative damage coefficient of the power test equipment is obtained; the strain rate of the power test equipment under different operating conditions is calculated, and the strain rate is comprehensively processed with the set strain rate standard value to obtain the high strain rate coefficient of the power test equipment; based on the cumulative damage coefficient of the power test equipment and the high strain rate coefficient of the power test equipment, the mechanical stress risk of the power test equipment is identified.

[0035] In this embodiment, the stress-life curve (SN curve) is used to predict the fatigue life of materials or equipment at different stress levels. The steps include obtaining the stress-life curve: the stress-life curve is obtained through experimental data, showing the fatigue life of materials or equipment at different stress levels (i.e., how many cycles of loading can be sustained without fatigue failure), and applying the curve: based on the actual stress level of the power test equipment, it is substituted into the stress-life curve to predict the fatigue life of the equipment at these stress levels. The Basquin formula of the stress-life curve is: ; Q represents the number of fatigue life cycles. represents the stress amplitude, and Represents a material constant, determined experimentally. The cumulative damage is used to describe the overall fatigue damage of the equipment at different stress levels: ; In the formula Indicates the cumulative damage coefficient of power test equipment, represents the actual number of cycles under the i-th stress level. It represents the fatigue life under the i-th stress level. If D reaches 1, it means that the cumulative damage of the equipment under all stress levels has reached the fatigue limit of the equipment. The calculation formula of the high strain rate coefficient of power test equipment is as follows: ; Where K represents the high strain rate coefficient of the power test equipment, represents the number of measurement points, Indicates The actual strain rate at each measuring point is Indicates the set standard value of strain rate. The strain rate reflects the deformation speed of the equipment under different operating conditions and indicates the change of equipment strain per unit time. The standard strain rate is used as a benchmark for evaluating the working status of the equipment. The high strain rate coefficient evaluates whether the strain rate of the equipment under different operating conditions exceeds the normal range by comprehensively comparing the actual strain rate with the standard strain rate.

[0036] Specifically, the specific process of evaluating the mechanical stress test risk coefficient is as follows: weights are assigned to the cumulative damage coefficient and the high strain rate coefficient of the power testing equipment through the tomography analysis method to obtain the cumulative damage coefficient weight coefficient and the high strain rate coefficient weight coefficient; the cumulative damage coefficient weight coefficient and the high strain rate coefficient weight coefficient are respectively comprehensively calculated with the cumulative damage coefficient of the power testing equipment and the high strain rate coefficient of the power testing equipment to obtain the mechanical stress test risk coefficient.

[0037] In this implementation, a hierarchical model is established: the decision target (mechanical stress test risk factor), criteria (cumulative damage coefficient and high strain rate coefficient) and sub-criteria (respective weights) are determined. A judgment matrix is ​​constructed: the importance of the cumulative damage coefficient and the high strain rate coefficient is compared, and a pairwise comparison matrix is ​​constructed. The example comparison results are as follows: ;in, Indicates the importance of the cumulative damage coefficient relative to the high strain rate coefficient. Calculate the weight vector: Perform eigenvalue decomposition on the judgment matrix to obtain the maximum eigenvalue and the corresponding eigenvector. The normalized eigenvector is the weight vector, and the weight obtained is ; The calculation formula of the mechanical stress test risk coefficient obtained by comprehensive calculation is as follows: ;in, Indicates the mechanical stress test risk factor, represents the weight coefficient of the cumulative damage coefficient, D represents the cumulative damage coefficient, It represents the weight coefficient of high strain rate coefficient, and K represents the high strain rate coefficient of power test equipment.

[0038] Specifically, based on the electromagnetic compatibility test parameters, the specific process of analyzing the influence of the electromagnetic interference and electromagnetic sensitivity of the power test equipment on the electrical equipment in the electromagnetic compatibility test is as follows: based on the electromagnetic compatibility test parameters, extract the spectrum characteristics and response characteristics of the electromagnetic interference signal of the power test equipment, obtain the electromagnetic interference tolerance coefficient and the electromagnetic sensitivity tolerance coefficient, and divide the interference level; respectively determine whether the electromagnetic interference tolerance threshold and the electromagnetic sensitivity tolerance threshold of the power test equipment are exceeded, and identify the electromagnetic compatibility test risks;

[0039] In this embodiment, the spectrum characteristics refer to the amplitude distribution of the electromagnetic interference signal at different frequencies, which can be extracted from the time domain signal by Fourier transform and other methods. The response characteristics refer to the response of the power test equipment when subjected to electromagnetic interference, including changes in parameters such as voltage and current. The electromagnetic interference tolerance coefficient indicates the maximum electromagnetic interference intensity that the power test equipment can withstand without affecting normal operation. Through experimental measurement or standard provisions, the tolerance limit of the power test equipment at different frequencies and intensities is determined. The sensitivity of the power test equipment to electromagnetic interference indicates the stability of the equipment in a specific electromagnetic environment. Through experiments or simulations, the working stability of the power test equipment under different electromagnetic interference conditions is evaluated to determine its sensitivity tolerance coefficient. According to the tolerance of the power test equipment to electromagnetic interference of different intensities and frequencies, the interference signal is divided into different levels, such as slight interference, medium interference, severe interference, etc. According to the spectrum characteristics of the electromagnetic interference signal and the tolerance coefficient of the equipment, the interference level classification standard is formulated to assign specific interference signals to the corresponding levels. The electromagnetic interference tolerance threshold represents the maximum acceptable value of the power test equipment at a specific electromagnetic interference intensity and frequency. The electromagnetic sensitivity tolerance threshold represents the critical value of the stability of the power test equipment in a specific electromagnetic environment. Compare whether the response characteristics of the equipment under specific electromagnetic interference conditions exceed the electromagnetic sensitivity tolerance factor.

[0040] Specifically, the specific process of evaluating the electromagnetic compatibility test risk coefficient is as follows: based on the electromagnetic interference tolerance coefficient and the electromagnetic sensitivity tolerance coefficient, comprehensive calculations are performed with the electromagnetic interference tolerance threshold and the electromagnetic sensitivity tolerance threshold respectively to obtain the electromagnetic compatibility test risk coefficient.

[0041] In this implementation plan, the calculation formula for the electromagnetic compatibility test risk coefficient is as follows: ; In the formula, Indicates the electromagnetic compatibility test risk factor, represents the electromagnetic interference tolerance coefficient, DCV represents the electromagnetic interference tolerance threshold, represents the electromagnetic sensitivity tolerance coefficient, and FGB represents the electromagnetic sensitivity tolerance threshold.

[0042] See also Figure 2Specifically, the specific process of obtaining the abnormality coefficient of the PBD test system is as follows: the partial discharge test risk coefficient, the mechanical stress test risk coefficient and the electromagnetic compatibility test risk coefficient are respectively comprehensively calculated with the set partial discharge test risk coefficient threshold, the mechanical stress test risk coefficient threshold and the electromagnetic compatibility test risk coefficient threshold to obtain the abnormality coefficient of the PBD test system.

[0043] In this implementation scheme, the calculation formula of the abnormal coefficient of the PBD test system is as follows: ; In the formula, represents the abnormal coefficient of the PBD test system, R represents the partial discharge test risk factor, RTF represents the partial discharge test risk factor threshold, represents the mechanical stress test risk factor, er represents the mechanical stress test risk factor threshold, represents the electromagnetic compatibility test risk factor, and fv represents the electromagnetic compatibility test risk factor threshold. The partial discharge test risk factor threshold represents the critical value of the risk in the partial discharge test. Exceeding this value indicates that the test has an abnormal risk. The mechanical stress test risk factor threshold represents the critical value of the risk in the mechanical stress test. Exceeding this value indicates that the test has an abnormal risk. The electromagnetic compatibility test risk factor threshold represents the critical value of the risk in the electromagnetic compatibility test. Exceeding this value indicates that the test has an abnormal risk.

[0044] In summary, this application has at least the following effects:

[0045] A safety management method for a PBD test system identifies potential discharge risks by analyzing the waveform characteristic change trend of the discharge signal of the power test equipment. Analyzing the fatigue characteristics and strain rate of the power test equipment in the mechanical stress test helps to identify whether the power test equipment has excessive wear or potential mechanical failure during the test process, avoid equipment failure due to mechanical stress, analyze the impact of electromagnetic interference and electromagnetic sensitivity on the power test equipment, evaluate the performance of the equipment in the electromagnetic environment, reduce equipment failure or test data distortion caused by electromagnetic interference, and ensure the accuracy of the test results and the reliability of the equipment. Comprehensively evaluating the risk factors of each test to generate the abnormality coefficient of the PBD test system can comprehensively identify potential risks in the system, reduce the occurrence of equipment failures and accidents, and ensure the safe operation of the equipment.

[0046] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may 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.

[0047] The present invention is described with reference to flowcharts and / or block diagrams of systems, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0048] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0049] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0050] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0051] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A safety management method for a PBD test system, characterized in that: The following steps are involved: S1. Collect the test parameters of the PBD test system, including: partial discharge test parameters, mechanical stress test parameters, and electromagnetic compatibility test parameters; S2. Based on the partial discharge test parameters, analyze the waveform characteristic change trend of the discharge signal of the power test equipment in the partial discharge test, identify the partial discharge test risk, and evaluate the partial discharge test risk factor; S3. Based on the mechanical stress test parameters, analyze the fatigue characteristics and strain rate of the power test equipment in the mechanical stress test, identify the abnormal degree of mechanical stress of the power test equipment, and evaluate the risk factor of the mechanical stress test; S4. Based on the electromagnetic compatibility test parameters, analyze the impact of electromagnetic interference and electromagnetic sensitivity of power test equipment on electrical equipment during electromagnetic compatibility testing, and evaluate the risk factor of electromagnetic compatibility testing; S5. Obtain the abnormal coefficient of the PBD test system by comprehensively evaluating the partial discharge test risk factor, the mechanical stress test risk factor, and the electromagnetic compatibility test risk factor, compare the abnormal coefficient of the PBD test system with the set abnormal coefficient threshold of the PBD test system, identify the test risk in the PBD test system, and have maintenance personnel repair the corresponding power test equipment; The calculation formula of the abnormal coefficient of the PBD test system is as follows: ; In the formula, represents the abnormal coefficient of the PBD test system, R represents the partial discharge test risk factor, RTF represents the partial discharge test risk factor threshold, represents the mechanical stress test risk factor, er represents the mechanical stress test risk factor threshold, represents the electromagnetic compatibility test risk factor, and fv represents the electromagnetic compatibility test risk factor threshold.

2. The safety management method of a PBD test system according to claim 1, characterized in that: Based on the partial discharge test parameters, the waveform characteristic change trend of the discharge signal of the power test equipment in the partial discharge test is analyzed, and the specific process of identifying the partial discharge test risk is as follows: Based on the partial discharge test parameters, the partial discharge test parameters are preprocessed to obtain the partial discharge signal and extract the waveform characteristics of the signal, including the discharge amplitude, discharge phase, discharge duration and discharge interval; The local discharge signal is decomposed by wavelet to obtain signal representations of different scales and time. The wavelet coefficients are extracted and compared with the set thresholds to analyze their changing trends at different scales and identify abnormal discharge signals.

3. The safety management method of a PBD test system according to claim 2, characterized in that: The specific process of evaluating the risk factor of partial discharge testing is as follows: Extract statistical features from wavelet coefficients and calculate the eigenvalues ​​of wavelet coefficients at each scale; Based on the extracted statistical features, fuzzy sets and membership functions are defined, and fuzzy logic rules are constructed; The input statistical eigenvalues ​​are converted into fuzzy membership values, and the fuzzy logic rules are applied to calculate the fuzzified eigenvalues ​​through the fuzzy reasoning mechanism to obtain the fuzzy output. The partial discharge test risk coefficient is obtained through defuzzification.

4. The safety management method of a PBD test system according to claim 3, characterized in that: Based on the mechanical stress test parameters, the fatigue characteristics and strain rate of the power test equipment in the mechanical stress test are analyzed, and the specific process of identifying the abnormal degree of mechanical stress of the power test equipment is as follows: Based on the partial discharge test parameters, the fatigue life of the power test equipment at a specific stress level is predicted through the stress-life curve, the cumulative damage of the power test equipment at different stress levels is evaluated, and the cumulative damage coefficient of the power test equipment is obtained; Calculate the strain rate of the power test equipment under different operating conditions, and perform comprehensive processing with the set strain rate standard value to obtain the high strain rate coefficient of the power test equipment; Identify the mechanical stress risk of power test equipment based on the cumulative damage coefficient and high strain rate coefficient of power test equipment.

5. The safety management method of a PBD test system according to claim 4, characterized in that: The specific process of evaluating the risk factor of mechanical stress testing is as follows: The cumulative damage coefficient and the high strain rate coefficient of the power test equipment are assigned weights by a tomographic analysis method to obtain a weight coefficient of the cumulative damage coefficient and a weight coefficient of the high strain rate coefficient; The cumulative damage coefficient weight coefficient and the high strain rate coefficient weight coefficient are respectively comprehensively calculated with the cumulative damage coefficient of the power test equipment and the high strain rate coefficient of the power test equipment to obtain the mechanical stress test risk coefficient.

6. The safety management method of a PBD test system according to claim 5, characterized in that: Based on the electromagnetic compatibility test parameters, the specific process of analyzing the impact of electromagnetic interference and electromagnetic susceptibility of power test equipment on electrical equipment in electromagnetic compatibility testing is as follows: Based on the electromagnetic compatibility test parameters, extract the spectrum characteristics and response characteristics of the electromagnetic interference signal of the power test equipment, obtain the electromagnetic interference tolerance coefficient and electromagnetic sensitivity tolerance coefficient, and divide the interference level; Determine whether the electromagnetic interference tolerance threshold and electromagnetic sensitivity tolerance threshold of the power test equipment are exceeded respectively, and identify the electromagnetic compatibility test risks.

7. The safety management method of a PBD test system according to claim 6, characterized in that: The specific process of evaluating the risk factor of electromagnetic compatibility testing is as follows: Based on the electromagnetic interference tolerance coefficient and the electromagnetic sensitivity tolerance coefficient, comprehensive calculations are performed with the electromagnetic interference tolerance threshold and the electromagnetic sensitivity tolerance threshold to obtain the electromagnetic compatibility test risk coefficient.

8. The safety management method of a PBD test system according to claim 7, characterized in that: The specific process of obtaining the abnormal coefficient of the PBD test system is as follows: The partial discharge test risk factor, mechanical stress test risk factor and electromagnetic compatibility test risk factor are respectively comprehensively calculated with the set partial discharge test risk factor threshold, mechanical stress test risk factor threshold and electromagnetic compatibility test risk factor threshold to obtain the abnormality coefficient of the PBD test system.

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