A high-voltage circuit breaker fault assessment method and device, a terminal device and a storage medium

Abstract

The application discloses a kind of high-voltage circuit breaker fault evaluation method, device, terminal equipment and storage medium, method includes: obtaining the first mechanical parameter and first model of the high-voltage circuit breaker to be evaluated;Wherein, the first mechanical parameter includes: shaft damping, circuit breaker both sides height and core gap;Shaft damping, circuit breaker both sides height and core gap are respectively used as control variable, the high-voltage circuit breaker to be evaluated is continuously regulated, and first waveform for indicating sound waveform and second waveform for indicating vibration waveform are obtained;According to first model, first mechanical parameter, first waveform and second waveform, respectively calculate energy entropy, obtain first energy entropy and second energy entropy;First energy entropy and second energy entropy are input into the preset fault category identification model and are clustered to obtain a plurality of clustering centers;Final clustering center is used as the fault evaluation result of the high-voltage circuit breaker to be evaluated.By implementing the application, the accuracy of high-voltage circuit breaker fault evaluation is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of circuit breaker evaluation, and in particular to a high-voltage circuit breaker fault evaluation method, apparatus, terminal equipment, and storage medium. Background Art

[0002] In modern power systems, circuit breakers are critical components whose reliability directly impacts the safe operation of the entire system. With the continuous advancement of circuit breaker fault assessment technology, high-precision sensors are being used to monitor critical circuit breaker parameters, providing real-time data for fault assessment. Mathematical models and simulation techniques are being used to analyze circuit breaker behavior under different operating conditions, thereby identifying abnormal patterns.

[0003] Existing circuit breaker fault diagnosis methods extract characteristic parameters reflecting the expansion and contraction process of energy storage springs from pressure signal data. These characteristic parameters are then input into an optimized SVM model for state identification, thereby determining whether the energy storage spring has failed and the type of failure. However, circuit breaker influencing factors are multidimensional, and existing methods lack multidimensional analysis of these factors and fail to conduct comprehensive simulation analysis of multiple parameters, resulting in low accuracy in high-voltage circuit breaker fault assessment. Summary of the Invention

[0004] The embodiments of the present invention provide a high-voltage circuit breaker fault assessment method, apparatus, terminal device, and storage medium, which can effectively solve the problem that the prior art lacks multi-dimensional analysis of factors affecting the circuit breaker and does not perform comprehensive simulation analysis of multiple parameters, resulting in low accuracy in high-voltage circuit breaker fault assessment.

[0005] An embodiment of the present invention provides a high-voltage circuit breaker fault assessment method, comprising:

[0006] Obtaining first mechanical parameters and a first model of a high-voltage circuit breaker to be evaluated; wherein the first mechanical parameters include: shaft damping, height of both sides of the circuit breaker, and core gap;

[0007] The shaft damping, the height of both sides of the circuit breaker, and the core gap are respectively used as control variables to continuously control the high-voltage circuit breaker to be evaluated, thereby obtaining a first waveform representing a sound waveform and a second waveform representing a vibration waveform;

[0008] Calculating the energy entropy of the first waveform according to the first model, the first mechanical parameter, and the first waveform to obtain a first energy entropy; and calculating the energy entropy of the second waveform according to the first model, the first mechanical parameter, and the second waveform to obtain a second energy entropy;

[0009] Inputting the first energy entropy and the second energy entropy into a preset fault category identification model for clustering to obtain a plurality of cluster centers;

[0010] The final cluster center is used as the fault assessment result of the high-voltage circuit breaker to be evaluated.

[0011] Furthermore, the training of the fault category identification model includes:

[0012] Obtaining second mechanical parameters, second models, and corresponding first fault categories of a plurality of high-voltage circuit breakers;

[0013] Calculating energy entropy based on the second mechanical parameter and the second model to obtain a third energy entropy for representing the energy entropy of the sound waveform and a fourth energy entropy for representing the energy entropy of the vibration waveform;

[0014] Inputting the third energy entropy and the fourth energy entropy into a fault category recognition model to be trained, and randomly generating a plurality of initial cluster centers;

[0015] According to the current cluster center and the energy entropy of the same group corresponding to the current cluster center, calculate the current distance between the current cluster center and the energy entropy of each group and the current energy entropy average value; among which, the current cluster center calculated for the first time is the initial cluster center;

[0016] Calculate the change difference based on the current energy entropy average value and the previous energy entropy average value; and update the current cluster center based on the change difference;

[0017] The current cluster center corresponding to the minimum current distance is used as the current optimal cluster center until the change difference of the average value of the energy entropy of the current cluster center is less than a preset first threshold, and the current optimal cluster center is used as the final cluster center;

[0018] According to the second fault category corresponding to the final cluster center and the first fault category, the loss function value of the fault category identification model is calculated; when the loss function value is less than a preset second threshold, a trained fault category identification model is obtained.

[0019] Furthermore, calculating energy entropy according to the second mechanical parameter and the second model to obtain a third energy entropy and a fourth energy entropy includes:

[0020] Determining, based on the second model and the corresponding parameter standard value, that the parameter standard value corresponding to the second model is the first standard value;

[0021] comparing the second mechanical parameter with the first standard value, and taking the second mechanical parameter greater than the first standard value as the first target mechanical parameter;

[0022] Signal transformation is performed according to the waveform corresponding to the first target mechanical parameter to calculate and obtain the third energy entropy and the fourth energy entropy.

[0023] Furthermore, the shaft damping, the height of both sides of the circuit breaker, and the core gap are respectively used as control variables to continuously control the high-voltage circuit breaker to be evaluated, thereby obtaining a first waveform for representing a sound waveform and a second waveform for representing a vibration waveform, including:

[0024] The shaft damping is used as a first control variable, and a first mechanical parameter other than the shaft damping is used as a first control quantity; and based on the first control variable and the first control quantity, the high-voltage circuit breaker to be evaluated is continuously controlled within a preset time period to obtain a shaft damping sound waveform and a shaft damping vibration waveform;

[0025] The height of the circuit breaker on both sides is used as a second control variable, and the first mechanical parameter other than the height of the circuit breaker on both sides is used as a second control quantity; and based on the second control variable and the second control quantity, the high-voltage circuit breaker to be evaluated is continuously controlled within a preset time period to obtain a sound waveform of the height of the circuit breaker on both sides and a vibration waveform of the height of the circuit breaker on both sides;

[0026] The core gap is used as a third control variable, and the first mechanical parameter other than the core gap is used as a third control quantity; and the high-voltage circuit breaker to be evaluated is continuously controlled within a preset time period based on the third control variable and the third control quantity to obtain a core gap sound waveform and a core gap vibration waveform;

[0027] The shaft damping sound waveform, the circuit breaker height sound waveform, and the core gap sound waveform are used as the first waveform for representing the sound waveform;

[0028] The shaft damping vibration waveform, the circuit breaker two-side height vibration waveform, and the core gap vibration waveform are used as the second waveform for representing the vibration waveform.

[0029] Further, calculating the energy entropy of the first waveform according to the first model, the first mechanical parameter, and the first waveform to obtain the first energy entropy; and calculating the energy entropy of the second waveform according to the first model, the first mechanical parameter, and the second waveform to obtain the second energy entropy, including:

[0030] According to a first model of the high-voltage circuit breaker to be evaluated and the corresponding parameter standard value, determining that the parameter standard value corresponding to the first model is a second standard value;

[0031] comparing the first mechanical parameter and the second standard value, and if both first mechanical parameters are greater than the second standard value, taking the first mechanical parameter greater than the second standard value as the second target mechanical parameter;

[0032] The first waveform and the second waveform corresponding to the second target mechanical parameter are used as the third waveform and the fourth waveform respectively;

[0033] A signal transformation is performed according to the third waveform to calculate and obtain a first energy entropy; and a signal transformation is performed according to the fourth waveform to calculate and obtain a second energy entropy.

[0034] Further, performing signal transformation according to the third waveform to calculate the first energy entropy; and performing signal transformation according to the fourth waveform to calculate the second energy entropy, including:

[0035] Performing denoising on the third waveform and the fourth waveform to obtain a first fault waveform and a second fault waveform after denoising;

[0036] Performing waveform decomposition according to the first fault waveform and preset decomposition parameters to obtain a first modal function; performing waveform decomposition according to the second fault waveform and preset decomposition parameters to obtain a second modal function;

[0037] Performing instantaneous frequency analysis on the first modal function and the second modal function respectively to obtain a first instantaneous frequency and a second instantaneous frequency;

[0038] An entropy value is calculated according to the first instantaneous frequency to obtain a first energy entropy; and an entropy value is calculated according to the second instantaneous frequency to obtain a second energy entropy.

[0039] Furthermore, the setting of the decomposition parameters includes:

[0040] Randomly select several initial decomposition mode numbers, initial smoothing parameters and initial bandwidth constraints;

[0041] Decomposing the first fault waveform and the second fault waveform according to the initial decomposition mode number, the initial smoothing parameter, and the initial bandwidth constraint to obtain a first modal function and a second modal function;

[0042] According to the first center frequency corresponding to the first modal function and the second center frequency corresponding to the second modal function, the first center frequency and the second center frequency are sorted in descending order, and the center frequency with the largest value is used as the target center frequency;

[0043] The initial decomposition mode number, initial smoothing parameter and initial bandwidth constraint corresponding to the target center frequency are used as the final decomposition parameters.

[0044] As an improvement to the above solution, another embodiment of the present invention provides a high-voltage circuit breaker fault assessment device, comprising:

[0045] A circuit breaker data acquisition module, configured to acquire first mechanical parameters and a first model of the high-voltage circuit breaker to be evaluated; wherein the first mechanical parameters include: shaft damping, height of both sides of the circuit breaker, and core gap;

[0046] a waveform control module, configured to use the shaft damping, the height of the circuit breaker on both sides, and the core gap as control variables, to continuously control the high-voltage circuit breaker to be evaluated, thereby obtaining a first waveform representing a sound waveform and a second waveform representing a vibration waveform;

[0047] an energy entropy calculation module, configured to calculate the energy entropy of the first waveform according to the first model, the first mechanical parameter, and the first waveform to obtain a first energy entropy; and to calculate the energy entropy of the second waveform according to the first model, the first mechanical parameter, and the second waveform to obtain a second energy entropy;

[0048] a fault category clustering module, configured to input the first energy entropy and the second energy entropy into a preset fault category identification model for clustering to obtain a plurality of cluster centers;

[0049] The fault assessment result determination module is used to use the final cluster center as the fault assessment result of the high-voltage circuit breaker to be assessed.

[0050] Another embodiment of the present invention provides a terminal device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, a high-voltage circuit breaker fault assessment method as described in the above embodiment is implemented.

[0051] Another embodiment of the present invention provides a computer-readable storage medium, which includes a stored computer program. When the computer program is running, the device where the computer-readable storage medium is located is controlled to execute a high-voltage circuit breaker fault assessment method described in the above embodiment.

[0052] By implementing the present invention, at least the following beneficial effects are achieved:

[0053] The present invention provides a high-voltage circuit breaker fault assessment method, device, terminal equipment and storage medium. The method can obtain first mechanical parameters and a first model of a high-voltage circuit breaker to be assessed; wherein the first mechanical parameters include: shaft damping, height on both sides of the circuit breaker and core gap; the shaft damping, the height on both sides of the circuit breaker and the core gap are respectively used as control variables to continuously control the high-voltage circuit breaker to be assessed, thereby obtaining a first waveform for representing a sound waveform and a second waveform for representing a vibration waveform; the energy entropy of the first waveform is calculated based on the first model, the first mechanical parameter and the first waveform to obtain a first energy entropy; and the energy entropy of the second waveform is calculated based on the first model, the first mechanical parameter and the second waveform to obtain a second energy entropy; the first energy entropy and the second energy entropy are input into a preset fault category identification model for clustering to obtain a plurality of cluster centers; and the final cluster center is used as the fault assessment result of the high-voltage circuit breaker to be assessed. Through multi-factor analysis of the first mechanical parameter, the shaft damping, the height on both sides of the circuit breaker, and the core gap, a comprehensive simulation analysis is performed on multiple parameters to obtain a first waveform for representing the sound waveform and a second waveform for representing the vibration waveform. The first energy entropy of the first waveform and the second energy entropy of the second waveform are input into a preset fault category identification model to cluster and obtain a fault assessment result. Combining the influence of multiple parameters can accurately identify the high-voltage circuit breaker fault assessment result, avoid the low accuracy of the assessment result due to the influence of a single factor, and multi-parameter analysis improves the accuracy of high-voltage circuit breaker fault assessment. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 This is a flow chart of a high-voltage circuit breaker fault assessment method provided by one embodiment of the present invention;

[0055] Figure 2 The figure is a structural diagram of a high-voltage circuit breaker fault assessment device provided by one embodiment of the present invention. DETAILED DESCRIPTION

[0056] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0057] See also Figure 1 , is a flow chart of a high-voltage circuit breaker fault assessment method provided by one embodiment of the present invention, comprising:

[0058] S1. Obtain first mechanical parameters and a first model of a high-voltage circuit breaker to be evaluated; wherein the first mechanical parameters include: shaft damping, height of both sides of the circuit breaker, and core gap;

[0059] S2. Continuously regulating the high-voltage circuit breaker to be evaluated by using the shaft damping, the height of both sides of the circuit breaker, and the core gap as control variables, to obtain a first waveform representing a sound waveform and a second waveform representing a vibration waveform;

[0060] S3. Calculate the energy entropy of the first waveform according to the first model, the first mechanical parameters, and the first waveform to obtain a first energy entropy; and calculate the energy entropy of the second waveform according to the first model, the first mechanical parameters, and the second waveform to obtain a second energy entropy;

[0061] S4. Inputting the first energy entropy and the second energy entropy into a preset fault category identification model for clustering to obtain a plurality of cluster centers;

[0062] S5. The final cluster center is used as the fault assessment result of the high-voltage circuit breaker to be assessed.

[0063] Specifically, the first mechanical parameter represents the mechanical parameter of the high-voltage circuit breaker to be evaluated; the first model represents the model of the high-voltage circuit breaker to be evaluated; the first waveform represents the sound waveform obtained by continuously controlling the high-voltage circuit breaker to be evaluated; the second waveform represents the vibration waveform obtained by continuously controlling the high-voltage circuit breaker to be evaluated; the first energy entropy represents the energy entropy of the first waveform; and the second energy entropy represents the energy entropy of the second waveform. Fault assessment results include circuit breaker normal, circuit breaker stuck, circuit breaker loose, and circuit breaker failure.

[0064] In a preferred embodiment of the present invention, the first mechanical parameters and the first model of the high-voltage circuit breaker to be evaluated are first obtained; wherein the first mechanical parameters include: shaft damping, height on both sides of the circuit breaker, and core gap; then the shaft damping, height on both sides of the circuit breaker, and core gap are used as control variables to continuously control the high-voltage circuit breaker to be evaluated, thereby obtaining a first waveform for representing a sound waveform and a second waveform for representing a vibration waveform; then, the energy entropy of the first waveform and the second waveform is calculated according to the first model, the first mechanical parameters, the first waveform, and the second waveform, respectively, to obtain a first energy entropy and a second energy entropy; then the first energy entropy and the second energy entropy are input into a preset fault category identification model for clustering to obtain several cluster centers; finally, the final cluster center is used as the fault evaluation result of the high-voltage circuit breaker to be evaluated. By setting and controlling multiple parameters, the status of the high-voltage circuit breaker can be systematically analyzed and monitored, thereby improving the comprehensiveness of the fault evaluation; through the calculation of energy entropy and cluster analysis, different fault modes can be clearly classified, which helps to accurately identify the fault type.

[0065] Preferably, the training of the fault category identification model includes:

[0066] Obtaining second mechanical parameters, second models, and corresponding first fault categories of a plurality of high-voltage circuit breakers;

[0067] Calculating energy entropy based on the second mechanical parameter and the second model to obtain a third energy entropy for representing the energy entropy of the sound waveform and a fourth energy entropy for representing the energy entropy of the vibration waveform;

[0068] Inputting the third energy entropy and the fourth energy entropy into a fault category recognition model to be trained, and randomly generating a plurality of initial cluster centers;

[0069] According to the current cluster center and the energy entropy of the same group corresponding to the current cluster center, calculate the current distance between the current cluster center and the energy entropy of each group and the current energy entropy average value; among which, the current cluster center calculated for the first time is the initial cluster center;

[0070] Calculate the change difference based on the current energy entropy average value and the previous energy entropy average value; and update the current cluster center based on the change difference;

[0071] The current cluster center corresponding to the minimum current distance is used as the current optimal cluster center until the change difference of the average value of the energy entropy of the current cluster center is less than a preset first threshold, and the current optimal cluster center is used as the final cluster center;

[0072] According to the second fault category corresponding to the final cluster center and the first fault category, the loss function value of the fault category identification model is calculated; when the loss function value is less than a preset second threshold, a trained fault category identification model is obtained.

[0073] Specifically, the second mechanical parameters represent the mechanical parameters of several high-voltage circuit breakers used to train the model, and the second mechanical parameters include shaft damping, height on both sides of the circuit breaker, and core gap; the second model represents the models corresponding to several high-voltage circuit breakers; the first fault category represents the fault category corresponding to several high-voltage circuit breakers; the third energy entropy represents the energy entropy corresponding to the sound waveform obtained by controlling the second mechanical parameter; the fourth energy entropy represents the energy entropy corresponding to the vibration waveform obtained by controlling the second mechanical parameter; the preset first threshold is used to evaluate the threshold of the difference in change in the average value of the energy entropy; the preset second threshold is used to evaluate the loss function value.

[0074] In a preferred embodiment of the present invention, the corresponding sound waveform and vibration waveform are determined according to the second mechanical parameter and the second model, and then the energy entropy is calculated according to the determined sound waveform and vibration waveform to obtain the third energy entropy and the fourth energy entropy; the third energy entropy and the fourth energy entropy corresponding to the same second model are numbered as the energy entropy corresponding to the same number, and the same group of energy entropies and the first fault category are used as a sample set, and the sample set is divided into a test set and a training set to train the fault category recognition model to be trained; the fault category recognition model to be trained uses the predicted second fault category as the output and the actual first fault category as the prediction target, so that the predicted second fault category and the actual first fault category are the same as the training target, and the fault category recognition model to be trained is tested according to the test set until the loss function value of the fault category recognition model to be trained is less than the preset second threshold value, and the test training is stopped to obtain a trained fault category recognition model.

[0075] The clustering logic of the fault category recognition model to be trained includes: randomly generating several initial cluster centers, for example, setting the number of clusters to 3, randomly selecting 3 initial cluster centers, then calculating the distance between the energy entropy of the same group and the initial cluster center based on the current cluster center and the energy entropy of the same group corresponding to the current cluster center, sorting the distance between the energy entropy of the same group and the initial cluster center in descending order, selecting the initial cluster center corresponding to the smallest distance, setting the initial cluster center corresponding to the smallest distance as the optimal cluster center, calculating the average energy entropy of the same group included in each initial cluster center, assigning the initial cluster center the average energy entropy value, and stopping iteration until the change difference in the assigned value of the initial cluster center is less than a preset first threshold. The current optimal cluster center is used as the final cluster center. By clustering the energy entropy, the fault categories can be accurately separated, which helps to identify and distinguish different fault types and improve the accuracy of fault assessment. The energy entropy and fault category are used as sample sets and divided into training sets and test sets. The fault category recognition model to be trained is trained based on actual faults, which can learn from actual fault data, thereby improving the practical application effect of the fault category recognition model.

[0076] Specifically, calculating the energy entropy according to the second mechanical parameter and the second model to obtain the third energy entropy and the fourth energy entropy includes:

[0077] Determining, based on the second model and the corresponding parameter standard value, that the parameter standard value corresponding to the second model is the first standard value;

[0078] comparing the second mechanical parameter with the first standard value, and taking the second mechanical parameter greater than the first standard value as the first target mechanical parameter;

[0079] Signal transformation is performed according to the waveform corresponding to the first target mechanical parameter to calculate and obtain the third energy entropy and the fourth energy entropy.

[0080] Preferably, the shaft damping, the height on both sides of the circuit breaker, and the core gap are respectively used as control variables, and the high-voltage circuit breaker to be evaluated is continuously controlled to obtain a first waveform for representing a sound waveform and a second waveform for representing a vibration waveform, including:

[0081] The shaft damping is used as a first control variable, and a first mechanical parameter other than the shaft damping is used as a first control quantity; and based on the first control variable and the first control quantity, the high-voltage circuit breaker to be evaluated is continuously controlled within a preset time period to obtain a shaft damping sound waveform and a shaft damping vibration waveform;

[0082] The height of the circuit breaker on both sides is used as a second control variable, and the first mechanical parameter other than the height of the circuit breaker on both sides is used as a second control quantity; and based on the second control variable and the second control quantity, the high-voltage circuit breaker to be evaluated is continuously controlled within a preset time period to obtain a sound waveform of the height of the circuit breaker on both sides and a vibration waveform of the height of the circuit breaker on both sides;

[0083] The core gap is used as a third control variable, and the first mechanical parameter other than the core gap is used as a third control quantity; and the high-voltage circuit breaker to be evaluated is continuously controlled within a preset time period based on the third control variable and the third control quantity to obtain a core gap sound waveform and a core gap vibration waveform;

[0084] The shaft damping sound waveform, the circuit breaker height sound waveform, and the core gap sound waveform are used as the first waveform for representing the sound waveform;

[0085] The shaft damping vibration waveform, the circuit breaker two-side height vibration waveform, and the core gap vibration waveform are used as the second waveform for representing the vibration waveform.

[0086] In a preferred embodiment of the present invention, any simulation parameter is set as a variable, while the remaining simulation parameters are set as quantitative values. For example, the shaft damping is set as a variable, while the height difference between the two sides of the circuit breaker and the core gap are set as quantitative values; the height difference between the two sides of the circuit breaker is set as a variable, while the shaft damping and the core gap are set as quantitative values; the core gap is set as a variable, while the shaft damping and the height difference between the two sides of the circuit breaker are set as quantitative values. The shaft damping is used to simulate the factor of a stuck fault, the height difference between the two sides of the circuit breaker is used to simulate the factor of a loose fault, and the core gap is used to simulate the factor of a refusal to operate fault. A preset time period is divided into Q sub-time periods, each numbered T1, T2, ..., TQ. Different variables and quantitative values ​​are set within each preset time period, for example, the variable is the shaft damping, and the quantitative values ​​are the height difference between the two sides of the circuit breaker and the core gap. A first gradient is set as an increment or decrement of the shaft damping. The shaft damping is continuously increased or decreased based on the current shaft damping and the first gradient, and the shaft damping sound waveform X1 and the shaft damping vibration waveform Y1 are recorded. The first waveform representing the sound waveform is the shaft damping sound waveform X1, the circuit breaker height difference sound waveform X2, and the core gap sound waveform X3. The second waveform representing the vibration waveform is the shaft damping vibration waveform Y1, the circuit breaker height difference vibration waveform Y2, and the core gap vibration waveform Y3. When the circuit breaker height difference and core gap are used as variables, the corresponding control steps are the same as those for the shaft damping.

[0087] By setting different simulation parameters and using them as variables and quantities, the impact of different fault factors on circuit breaker performance can be fully simulated, multiple fault modes can be fully considered, and the comprehensiveness of the assessment can be improved; the preset time period is subdivided into multiple sub-time periods, so that the behavior of the high-voltage circuit breaker under test can be analyzed on a finer time scale, which helps to capture fault characteristics in a short period of time and improve sensitivity to dynamic changes; at the same time, sound waveform and vibration waveform data are collected and their corresponding relationships at the same time point are associated, providing a multi-dimensional data source. The comprehensive analysis of sound and vibration signals can more comprehensively reflect the operating status of the circuit breaker and improve the accuracy of fault assessment.

[0088] Specifically, calculating the energy entropy of the first waveform according to the first model, the first mechanical parameter, and the first waveform to obtain the first energy entropy; and calculating the energy entropy of the second waveform according to the first model, the first mechanical parameter, and the second waveform to obtain the second energy entropy, including:

[0089] According to a first model of the high-voltage circuit breaker to be evaluated and the corresponding parameter standard value, determining that the parameter standard value corresponding to the first model is a second standard value;

[0090] comparing the first mechanical parameter and the second standard value, and if both first mechanical parameters are greater than the second standard value, taking the first mechanical parameter greater than the second standard value as the second target mechanical parameter;

[0091] The first waveform and the second waveform corresponding to the second target mechanical parameter are used as the third waveform and the fourth waveform respectively;

[0092] A signal transformation is performed according to the third waveform to calculate and obtain a first energy entropy; and a signal transformation is performed according to the fourth waveform to calculate and obtain a second energy entropy.

[0093] In a preferred embodiment of the present invention, a preset simulation database records the model of the high-voltage circuit breaker and the standard values ​​of the corresponding mechanical parameters. Based on the first model of the high-voltage circuit breaker to be evaluated and the parameter standard value corresponding to the first mechanical parameter, the parameter standard value corresponding to the first model is determined to be a second standard value. Based on the first mechanical parameter and the second standard value, a comparison is performed, and the first mechanical parameter greater than the second standard value is used as the second target mechanical parameter; the first waveform and the second waveform corresponding to the second target mechanical parameter are used as the third waveform and the fourth waveform, respectively (the first waveform and the second waveform corresponding to the first mechanical parameter less than or equal to the second standard value are deleted); finally, signal transformation is performed based on the third waveform and the fourth waveform, respectively, to calculate the first energy entropy and the second energy entropy.

[0094] In another preferred embodiment of the present invention, the third waveform and the corresponding fourth waveform are set as waveforms in the same group, and the waveforms in the same group are numbered. The number of the third waveform is represented by X. P B n , the corresponding fourth waveform number is represented by Y P B nm , where n and m are both natural numbers, P∈[1,3] and P is an integer. The waveforms are grouped according to the standard value comparison results and numbered. The test data is systematically managed to facilitate tracking and analysis of the test results of different waveforms, which is helpful for data organization and subsequent analysis. Setting the waveform number facilitates waveform management. By entering the number, the corresponding waveform can be queried, which improves the data management effect. The first mechanical parameter is set as a variable and quantitative in order to observe the impact of a single mechanical parameter on the circuit breaker fault by changing it. The variables set in different orders are compared with the corresponding standard values, which makes it easier to screen the fault waveforms corresponding to different variables. By deleting invalid waveforms, the amount of data is simplified and the amount of subsequent calculations is reduced.

[0095] Preferably, performing signal transformation according to the third waveform to calculate the first energy entropy; and performing signal transformation according to the fourth waveform to calculate the second energy entropy, including:

[0096] Performing denoising on the third waveform and the fourth waveform to obtain a first fault waveform and a second fault waveform after denoising;

[0097] Performing waveform decomposition according to the first fault waveform and preset decomposition parameters to obtain a first modal function; performing waveform decomposition according to the second fault waveform and preset decomposition parameters to obtain a second modal function;

[0098] Performing instantaneous frequency analysis on the first modal function and the second modal function respectively to obtain a first instantaneous frequency and a second instantaneous frequency;

[0099] An entropy value is calculated according to the first instantaneous frequency to obtain a first energy entropy; and an entropy value is calculated according to the second instantaneous frequency to obtain a second energy entropy.

[0100] In a preferred embodiment of the present invention, denoising is performed on the third waveform and the fourth waveform respectively to obtain the first fault waveform and the second fault waveform after denoising, and the denoising is performed using wavelet packet soft threshold denoising. The modal function is obtained by the empirical mode decomposition (EMD) method, and the implementation steps are as follows: (1) Parameter setting: setting the number of decomposed modes (N), the number of modal functions extracted from the waveform; setting the smoothing parameter (S) to control the smoothness in the decomposition process to reduce the influence of noise; setting the bandwidth constraint (B) to limit the frequency range of the modal function to better capture the fault characteristics; (2) Denoising: denoising is performed on the first fault waveform and the second fault waveform, and wavelet transform or filter technology can be used to reduce the influence of noise on subsequent decomposition; (3) Modal decomposition: using empirical mode decomposition (EMD), the first fault waveform and the second fault waveform after denoising are used as input; by repeatedly extracting local extreme points, calculating the envelope, and then extracting the intrinsic modal function (I MF); set conditions and check whether the number of extracted modal functions reaches the preset number of decomposition modes (N); (4) smoothing and constraint: for the extracted modal functions, apply the smoothing parameter (S) for post-processing to reduce high-frequency noise; according to the bandwidth constraint (B), perform frequency domain analysis on the modal function to ensure that the extracted modal function is within the specified bandwidth range; (5) result output: output the modal function of the first fault waveform and the modal function of the second fault waveform, that is, the first modal function and the second modal function.

[0101] The first modal function and the second modal function are subjected to instantaneous frequency analysis respectively to obtain the first instantaneous frequency and the second instantaneous frequency, that is, the first instantaneous frequency and the corresponding second instantaneous frequency are obtained by H i bert transform (Hilbert transform). Then, the entropy values ​​are calculated according to the first instantaneous frequency and the second instantaneous frequency respectively to obtain the first energy entropy and the second energy entropy. In mechanical and electrical equipment, the sudden change of frequency may be closely related to the occurrence of faults. Analyzing the change of instantaneous frequency can provide a basis for fault identification, capture the frequency change of the signal in time, and help to understand the dynamic characteristics of the signal; the change of energy entropy indicates the change of system state. When the entropy value changes significantly, it indicates that the system has a fault or abnormal state; the instantaneous frequency extracted by applying Hilbert transform is combined with energy entropy to provide richer information for signal analysis, which helps to identify and quantify important features in the signal to support fault detection and early warning. The same group of energy entropies can set the first energy entropy and the corresponding second energy entropy as the same group of energy entropies, compare the energy characteristics of different signals in the same time period, and thus perform more effective fault analysis and pattern recognition. The energy entropies in the same group are numbered, and the number of the first energy entropy is represented as EX P B n , the second number of the corresponding second energy entropy is represented by EYP B nm , where E represents the sign of energy entropy, and energy entropy is calculated using the Hilbert marginal energy entropy formula.

[0102] Schematically, the setting of the decomposition parameters includes:

[0103] Randomly select several initial decomposition mode numbers, initial smoothing parameters and initial bandwidth constraints;

[0104] Decomposing the first fault waveform and the second fault waveform according to the initial decomposition mode number, the initial smoothing parameter, and the initial bandwidth constraint to obtain a first modal function and a second modal function;

[0105] According to the first center frequency corresponding to the first modal function and the second center frequency corresponding to the second modal function, the first center frequency and the second center frequency are sorted in descending order, and the center frequency with the largest value is used as the target center frequency;

[0106] The initial decomposition mode number, initial smoothing parameter and initial bandwidth constraint corresponding to the target center frequency are used as the final decomposition parameters.

[0107] In a preferred embodiment of the present invention, the initial number of decomposition modes, the initial smoothing parameter and the initial bandwidth constraint are preset, and according to the center frequencies of the first modal function and the second modal function, the center frequencies are traversed and sorted in descending order; the center frequency with the largest value is selected, and the number of decomposition modes, the smoothing parameter and the bandwidth constraint corresponding to the center frequency with the largest value are set as the target number of decomposition modes, the target smoothing parameter and the target bandwidth constraint, respectively; the value of the target number of decomposition modes is a first value, the value of the target smoothing parameter is a second value, and the value of the target bandwidth constraint is a third value, and the initial number of decomposition modes, the initial smoothing parameter and the initial bandwidth constraint corresponding to the target center frequency are used as the final decomposition parameters.

[0108] Wavelet packet soft threshold denoising can effectively reduce noise in the signal, improve the signal quality of the data, and thus improve the accuracy of the analysis results; by decomposing the modal function, the waveform data is decomposed into multiple levels of detail, which helps to more deeply analyze and understand the waveform characteristics; Hibert transform provides instantaneous frequency calculation, which helps to capture the frequency changes of the waveform at different time points and enhance the understanding of the dynamic behavior of the signal.

[0109] By implementing this embodiment, the first mechanical parameters and the first model of the high-voltage circuit breaker to be evaluated are obtained; wherein the first mechanical parameters include: shaft damping, height on both sides of the circuit breaker, and core gap; the shaft damping, the height on both sides of the circuit breaker, and the core gap are respectively used as control variables, and the high-voltage circuit breaker to be evaluated is continuously controlled to obtain a first waveform for representing a sound waveform and a second waveform for representing a vibration waveform; the energy entropy of the first waveform and the second waveform are respectively calculated according to the first model, the first mechanical parameters, the first waveform, and the second waveform to obtain a first energy entropy and a second energy entropy; the first energy entropy and the second energy entropy are input into a preset fault category identification model for clustering to obtain several cluster centers; and the final cluster center is used as the fault assessment result of the high-voltage circuit breaker to be evaluated. Through multi-factor analysis of the first mechanical parameter, the shaft damping, the height on both sides of the circuit breaker, and the core gap, a comprehensive simulation analysis is performed on multiple parameters to obtain a first waveform for representing the sound waveform and a second waveform for representing the vibration waveform. The first energy entropy of the first waveform and the second energy entropy of the second waveform are input into a preset fault category identification model to cluster and obtain a fault assessment result. Combining the influence of multiple parameters can accurately identify the high-voltage circuit breaker fault assessment result, avoid the low accuracy of the assessment result due to the influence of a single factor, and multi-parameter analysis improves the accuracy of high-voltage circuit breaker fault assessment.

[0110] See also Figure 2 , is a structural diagram of a high-voltage circuit breaker fault assessment device provided by one embodiment of the present invention, comprising:

[0111] A circuit breaker data acquisition module, configured to acquire first mechanical parameters and a first model of the high-voltage circuit breaker to be evaluated; wherein the first mechanical parameters include: shaft damping, height of both sides of the circuit breaker, and core gap;

[0112] a waveform control module, configured to use the shaft damping, the height of the circuit breaker on both sides, and the core gap as control variables, to continuously control the high-voltage circuit breaker to be evaluated, thereby obtaining a first waveform representing a sound waveform and a second waveform representing a vibration waveform;

[0113] an energy entropy calculation module, configured to calculate the energy entropy of the first waveform according to the first model, the first mechanical parameter, and the first waveform to obtain a first energy entropy; and to calculate the energy entropy of the second waveform according to the first model, the first mechanical parameter, and the second waveform to obtain a second energy entropy;

[0114] a fault category clustering module, configured to input the first energy entropy and the second energy entropy into a preset fault category identification model for clustering to obtain a plurality of cluster centers;

[0115] The fault assessment result determination module is used to use the final cluster center as the fault assessment result of the high-voltage circuit breaker to be assessed.

[0116] The present invention provides a high-voltage circuit breaker fault assessment device, which obtains first mechanical parameters and a first model of a high-voltage circuit breaker to be assessed according to a circuit breaker data acquisition module; wherein the first mechanical parameters include: shaft damping, height on both sides of the circuit breaker, and core gap; through a waveform control module, the shaft damping, the height on both sides of the circuit breaker, and the core gap are respectively used as control variables to continuously control the high-voltage circuit breaker to be assessed, thereby obtaining a first waveform for representing a sound waveform and a second waveform for representing a vibration waveform; in an energy entropy calculation module, the energy entropy of the first waveform and the second waveform is respectively calculated according to the first model, the first mechanical parameters, the first waveform, and the second waveform, thereby obtaining a first energy entropy and a second energy entropy; through a fault category clustering module, the first energy entropy and the second energy entropy are input into a preset fault category identification model for clustering, thereby obtaining a plurality of cluster centers; finally, according to a fault assessment result determination module, the final cluster center is used as the fault assessment result of the high-voltage circuit breaker to be assessed. Through multi-factor analysis of the first mechanical parameter, the shaft damping, the height on both sides of the circuit breaker, and the core gap, a comprehensive simulation analysis is performed on multiple parameters to obtain a first waveform for representing the sound waveform and a second waveform for representing the vibration waveform. The first energy entropy of the first waveform and the second energy entropy of the second waveform are input into a preset fault category identification model to cluster and obtain a fault assessment result. Combining the influence of multiple parameters can accurately identify the high-voltage circuit breaker fault assessment result, avoid the low accuracy of the assessment result due to the influence of a single factor, and multi-parameter analysis improves the accuracy of high-voltage circuit breaker fault assessment.

[0117] It should be noted that the device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed across multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the present embodiment. In addition, in the drawings of the device embodiments provided by the present invention, the connection relationship between the modules indicates that there is a communication connection between them, which may be specifically implemented as one or more communication buses or signal lines. A person of ordinary skill in the art can understand and implement the present invention without inventive effort.

[0118] Those skilled in the art can clearly understand that, for the sake of convenience and brevity, the specific working process of the device described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0119] Another embodiment of the present invention provides a terminal device comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements a high-voltage circuit breaker fault assessment method as described in the above embodiment. The terminal device can be a computing device such as a desktop computer, a notebook, a PDA, or a cloud server. The terminal device can include, but is not limited to, a processor and a memory.

[0120] The processor may be a central processing unit (CPU), or other general-purpose processors, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the terminal device, and connects various parts of the entire terminal device using various interfaces and lines.

[0121] The memory can be used to store the computer program, and the processor realizes various functions of the terminal device by running or executing the computer program stored in the memory and calling the data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, at least one application required for a function, etc.; the data storage area can store data created according to the use of the mobile phone, etc. In addition, the memory can include a high-speed random access memory, and can also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart Med i aCard, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device or other volatile solid-state storage device.

[0122] Another embodiment of the present invention provides a computer-readable storage medium, which includes a stored computer program. When the computer program is running, the device where the computer-readable storage medium is located is controlled to execute a high-voltage circuit breaker fault assessment method described in the above embodiment.

[0123] The storage medium is a computer-readable storage medium, and the computer program is stored in the computer-readable storage medium. When the computer program is executed by the processor, the steps of the above-mentioned method embodiments can be implemented. The computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device that can carry the computer program code, a recording medium, a USB flash drive, a mobile hard disk, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunications signal, and a software distribution medium.

[0124] The above is a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A high voltage circuit breaker fault assessment method, characterized in that: include: Obtaining first mechanical parameters and a first model of a high-voltage circuit breaker to be evaluated; wherein the first mechanical parameters include: shaft damping, height of both sides of the circuit breaker, and core gap; The shaft damping, the height of both sides of the circuit breaker, and the core gap are respectively used as control variables to continuously control the high-voltage circuit breaker to be evaluated, thereby obtaining a first waveform representing a sound waveform and a second waveform representing a vibration waveform; Calculating the energy entropy of the first waveform according to the first model, the first mechanical parameter, and the first waveform to obtain a first energy entropy; and calculating the energy entropy of the second waveform according to the first model, the first mechanical parameter, and the second waveform to obtain a second energy entropy; Inputting the first energy entropy and the second energy entropy into a preset fault category identification model for clustering to obtain a plurality of cluster centers; The final cluster center is used as the fault assessment result of the high-voltage circuit breaker to be assessed; The shaft damping, the height of both sides of the circuit breaker, and the core gap are respectively used as control variables to continuously control the high-voltage circuit breaker to be evaluated, thereby obtaining a first waveform for representing a sound waveform and a second waveform for representing a vibration waveform, including: The shaft damping is used as a first control variable, and a first mechanical parameter other than the shaft damping is used as a first control quantity; and based on the first control variable and the first control quantity, the high-voltage circuit breaker to be evaluated is continuously controlled within a preset time period to obtain a shaft damping sound waveform and a shaft damping vibration waveform; The height of the circuit breaker on both sides is used as a second control variable, and the first mechanical parameter other than the height of the circuit breaker on both sides is used as a second control quantity; and based on the second control variable and the second control quantity, the high-voltage circuit breaker to be evaluated is continuously controlled within a preset time period to obtain a sound waveform of the height of the circuit breaker on both sides and a vibration waveform of the height of the circuit breaker on both sides; The core gap is used as a third control variable, and the first mechanical parameter other than the core gap is used as a third control quantity; and the high-voltage circuit breaker to be evaluated is continuously controlled within a preset time period based on the third control variable and the third control quantity to obtain a core gap sound waveform and a core gap vibration waveform; The shaft damping sound waveform, the circuit breaker height sound waveform, and the core gap sound waveform are used as the first waveform for representing the sound waveform; The shaft damping vibration waveform, the circuit breaker two-side height vibration waveform, and the core gap vibration waveform are used as the second waveform for representing the vibration waveform.

2. A high-voltage circuit breaker fault assessment method according to claim 1, characterized in that: The training of the fault category identification model includes: Obtaining second mechanical parameters, second models, and corresponding first fault categories of a plurality of high-voltage circuit breakers; Calculating energy entropy based on the second mechanical parameter and the second model to obtain a third energy entropy for representing the energy entropy of the sound waveform and a fourth energy entropy for representing the energy entropy of the vibration waveform; Inputting the third energy entropy and the fourth energy entropy into a fault category recognition model to be trained, and randomly generating a plurality of initial cluster centers; According to the current cluster center and the energy entropy of the same group corresponding to the current cluster center, calculate the current distance between the current cluster center and the energy entropy of each group and the current energy entropy average value; among which, the current cluster center calculated for the first time is the initial cluster center; Calculate the change difference based on the current energy entropy average value and the previous energy entropy average value; and update the current cluster center based on the change difference; The current cluster center corresponding to the minimum current distance is used as the current optimal cluster center until the change difference of the average value of the energy entropy of the current cluster center is less than a preset first threshold, and the current optimal cluster center is used as the final cluster center; According to the second fault category corresponding to the final cluster center and the first fault category, the loss function value of the fault category identification model is calculated; when the loss function value is less than a preset second threshold, a trained fault category identification model is obtained.

3. A high-voltage circuit breaker fault assessment method according to claim 2, characterized in that: Calculating energy entropy according to the second mechanical parameter and the second model to obtain a third energy entropy and a fourth energy entropy includes: Determining, based on the second model and the corresponding parameter standard value, that the parameter standard value corresponding to the second model is the first standard value; comparing the second mechanical parameter with the first standard value, and taking the second mechanical parameter greater than the first standard value as the first target mechanical parameter; Signal transformation is performed according to the waveform corresponding to the first target mechanical parameter to calculate and obtain the third energy entropy and the fourth energy entropy.

4. A high-voltage circuit breaker fault assessment method according to claim 1, characterized in that: Calculating the energy entropy of the first waveform according to the first model, the first mechanical parameter, and the first waveform to obtain a first energy entropy; and calculating the energy entropy of the second waveform according to the first model, the first mechanical parameter, and the second waveform to obtain the second energy entropy, including: According to a first model of the high-voltage circuit breaker to be evaluated and the corresponding parameter standard value, determining that the parameter standard value corresponding to the first model is a second standard value; comparing the first mechanical parameter and the second standard value, and if both first mechanical parameters are greater than the second standard value, taking the first mechanical parameter greater than the second standard value as the second target mechanical parameter; The first waveform and the second waveform corresponding to the second target mechanical parameter are used as the third waveform and the fourth waveform respectively; A signal transformation is performed according to the third waveform to calculate and obtain a first energy entropy; and a signal transformation is performed according to the fourth waveform to calculate and obtain a second energy entropy.

5. A high-voltage circuit breaker fault assessment method according to claim 4, characterized in that: Performing signal transformation according to the third waveform to calculate and obtain a first energy entropy; Performing signal transformation according to the fourth waveform to calculate a second energy entropy includes: Performing denoising on the third waveform and the fourth waveform to obtain a first fault waveform and a second fault waveform after denoising; Performing waveform decomposition according to the first fault waveform and preset decomposition parameters to obtain a first modal function; performing waveform decomposition according to the second fault waveform and preset decomposition parameters to obtain a second modal function; Performing instantaneous frequency analysis on the first modal function and the second modal function respectively to obtain a first instantaneous frequency and a second instantaneous frequency; An entropy value is calculated according to the first instantaneous frequency to obtain a first energy entropy; and an entropy value is calculated according to the second instantaneous frequency to obtain a second energy entropy.

6. A high-voltage circuit breaker fault assessment method according to claim 5, characterized in that: The setting of the decomposition parameters includes: Randomly select several initial decomposition mode numbers, initial smoothing parameters and initial bandwidth constraints; Decomposing the first fault waveform and the second fault waveform according to the initial decomposition mode number, the initial smoothing parameter, and the initial bandwidth constraint to obtain a first modal function and a second modal function; According to the first center frequency corresponding to the first modal function and the second center frequency corresponding to the second modal function, the first center frequency and the second center frequency are sorted in descending order, and the center frequency with the largest value is used as the target center frequency; The initial decomposition mode number, initial smoothing parameter and initial bandwidth constraint corresponding to the target center frequency are used as the final decomposition parameters.

7. A high voltage circuit breaker fault assessment device, characterized in that: include: A circuit breaker data acquisition module, configured to acquire first mechanical parameters and a first model of the high-voltage circuit breaker to be evaluated; wherein the first mechanical parameters include: shaft damping, height of both sides of the circuit breaker, and core gap; a waveform control module, configured to use the shaft damping, the height of the circuit breaker on both sides, and the core gap as control variables, to continuously control the high-voltage circuit breaker to be evaluated, thereby obtaining a first waveform representing a sound waveform and a second waveform representing a vibration waveform; an energy entropy calculation module, configured to calculate the energy entropy of the first waveform according to the first model, the first mechanical parameter, and the first waveform to obtain a first energy entropy; and to calculate the energy entropy of the second waveform according to the first model, the first mechanical parameter, and the second waveform to obtain a second energy entropy; a fault category clustering module, configured to input the first energy entropy and the second energy entropy into a preset fault category identification model for clustering to obtain a plurality of cluster centers; A fault assessment result determination module is used to use the final cluster center as the fault assessment result of the high-voltage circuit breaker to be assessed; The waveform control module is configured to use the shaft damping, the height of the circuit breaker on both sides, and the core gap as control variables to continuously control the high-voltage circuit breaker to be evaluated, thereby obtaining a first waveform representing a sound waveform and a second waveform representing a vibration waveform, including: The shaft damping is used as a first control variable, and a first mechanical parameter other than the shaft damping is used as a first control quantity; and based on the first control variable and the first control quantity, the high-voltage circuit breaker to be evaluated is continuously controlled within a preset time period to obtain a shaft damping sound waveform and a shaft damping vibration waveform; The height of the circuit breaker on both sides is used as a second control variable, and the first mechanical parameter other than the height of the circuit breaker on both sides is used as a second control quantity; and based on the second control variable and the second control quantity, the high-voltage circuit breaker to be evaluated is continuously controlled within a preset time period to obtain a sound waveform of the height of the circuit breaker on both sides and a vibration waveform of the height of the circuit breaker on both sides; The core gap is used as a third control variable, and the first mechanical parameter other than the core gap is used as a third control quantity; and the high-voltage circuit breaker to be evaluated is continuously controlled within a preset time period based on the third control variable and the third control quantity to obtain a core gap sound waveform and a core gap vibration waveform; The shaft damping sound waveform, the circuit breaker height sound waveform, and the core gap sound waveform are used as the first waveform for representing the sound waveform; The shaft damping vibration waveform, the circuit breaker two-side height vibration waveform, and the core gap vibration waveform are used as the second waveform for representing the vibration waveform.

8. A terminal device, characterized in that: The method comprises a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, a high-voltage circuit breaker fault assessment method according to any one of claims 1 to 6 is implemented.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium includes a stored computer program, wherein when the computer program is executed, the device where the computer-readable storage medium is located is controlled to execute a high-voltage circuit breaker fault assessment method according to any one of claims 1 to 6.

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