High-voltage coil turn-to-turn insulation defect detection method and system based on attenuation rate change amount, and medium

Abstract

The embodiment of the application discloses a high-voltage coil turn-to-turn insulation defect detection method and system based on attenuation rate change amount, and a medium, the method comprising: obtaining several healthy coils of the same type as the coil to be measured. A direct current high voltage is applied to each healthy coil, a first decay oscillation voltage signal is collected to determine a calibration oscillation voltage waveform and calculate a healthy decay rate, a healthy sample library is constructed from all healthy decay rates, and a calibration decay rate is selected therefrom. Kernel density estimation is performed on the healthy sample library to construct a probability density function of the healthy state decay rate, and a determination threshold is determined accordingly. The same direct current high voltage is applied to the test coil to collect a second decay oscillation voltage signal to determine a test oscillation waveform and calculate a test decay rate. The absolute value of the difference between the test decay rate and the calibration decay rate is calculated to obtain the decay rate change amount, which is compared with the determination threshold to determine whether the test coil has a turn-to-turn insulation defect, thereby effectively identifying early and slight turn-to-turn insulation degradation and ensuring that subtle faults are captured.

Description

Technical Field

[0001] This invention relates to the field of insulation testing technology for high-voltage electrical equipment, and in particular to a method, system, and medium for detecting inter-turn insulation defects in high-voltage coils based on changes in attenuation rate. Background Technology

[0002] High-voltage coils (such as air-core reactor coils, transformer windings, and motor stator coils) are prone to defects such as inter-turn insulation aging, wear, and partial discharge during long-term operation due to the influence of electric fields, thermal fields, mechanical vibrations, and environmental factors. If these defects are not detected in time, the deterioration of the inter-turn insulation may develop into inter-turn short circuits, leading to localized overheating of the coil, equipment damage, and even power grid system failures. Therefore, conducting rapid, sensitive, and non-destructive testing of inter-turn insulation defects in high-voltage coils has significant engineering implications.

[0003] Traditional inter-turn fault detection techniques mostly employ the damped oscillation method. This technique determines the presence of a short circuit by applying an impulse voltage to the system and measuring changes in the oscillation frequency. However, this method has significant drawbacks: relying solely on the oscillation frequency makes it insensitive to early and minor inter-turn insulation degradation, easily leading to misjudgments; furthermore, the oscillation frequency is greatly affected by stray circuit parameters, connection inductance, and field interference, resulting in uncertainty and poor repeatability in field assessments; more importantly, this method cannot quantify the degree of insulation degradation, relying heavily on experience or simple thresholds for subjective judgment, lacking statistically based quantitative threshold setting methods, and the judgment results are heavily influenced by operator experience, making it difficult to achieve unified and objective defect identification. Summary of the Invention

[0004] Therefore, it is necessary to propose a method, system, and medium for detecting inter-turn insulation defects in high-voltage coils based on the change in attenuation rate to address the above problems.

[0005] A method for detecting inter-turn insulation defects in high-voltage coils based on attenuation rate changes, the method comprising: Obtain a preset number of healthy coils of the same model as the coil under test. The healthy coils are those that have been confirmed to be free of inter-turn defects through a preset detection method. After applying a DC high voltage to any of the healthy coils, the healthy coils generate damped oscillations. The first damped oscillation voltage signal of the healthy coil during the damped oscillation process is collected. The calibration oscillation voltage waveform is determined based on the first damped oscillation voltage signal. The healthy attenuation rate is determined based on the calibration oscillation voltage waveform. A healthy sample library is constructed based on the healthy attenuation rates of a preset number of healthy coils. Any healthy attenuation rate in the healthy sample library is selected as the calibration attenuation rate. Kernel density estimation is performed on the data in the health sample library to construct the probability density function of the health state decay rate, and a judgment threshold is determined on the probability density function. After applying the same DC high voltage to the tested high voltage coil, the tested high voltage coil generates a damped oscillation. The second damped oscillation voltage signal of the tested high voltage coil during the damped oscillation process is collected. The test oscillation voltage waveform is determined based on the second damped oscillation voltage signal, and the test attenuation rate is determined based on the test oscillation voltage waveform. The attenuation rate change is determined based on the absolute value of the difference between the test attenuation rate and the calibrated attenuation rate. The presence of inter-turn insulation defects in the tested high-voltage coil is determined by comparing the attenuation rate change with a preset judgment threshold.

[0006] Specifically, the step of performing kernel density estimation on the data in the health sample library, constructing a probability density function for the health state decay rate, and determining a judgment threshold on the probability density function includes: Using the data in the health decay rate sample library as samples, the samples are preprocessed; A reference bandwidth is determined based on the standard deviation of the preprocessed samples, a reference interval is determined based on the reference bandwidth, cross-validation is performed within the reference interval, and the optimal bandwidth is selected. Construct a probability density function for the attenuation rate of the healthy coil based on the optimal bandwidth; On the probability density function, determine the lower quantiles that satisfy the lower area as a preset acceptable false alarm rate; The determination threshold is determined based on the lower quantile.

[0007] Specifically, the preprocessing of the data from the health decay rate sample library includes: Using the data in the health decay rate sample library as samples, the sample skewness of the data in the health decay rate sample library is determined based on the mean and standard deviation of the samples. If the sample skewness is greater than a preset threshold, then the sample data is subjected to a Box-Cox transformation; If the sample skewness is not greater than a preset threshold, the original data of the health decay rate sample library remains unchanged.

[0008] Specifically, the probability density function for constructing the attenuation rate of the healthy coil based on the optimal bandwidth includes: according to Determine the probability density function of the attenuation rate of the healthy coil, where, Let h be the Gaussian kernel function, h be the optimal bandwidth, and M be the total number of healthy coil samples. y represents the attenuation rate of the healthy coil after preprocessing, and y represents the attenuation rate of the healthy coil after current preprocessing.

[0009] Specifically, determining the judgment threshold based on the lower quantile includes: If the sample data undergoes a Box-Cox transformation, then according to Determine the judgment threshold; If the sample data has not undergone Box-Cox transformation, then according to Determine the judgment threshold.

[0010] The step of determining the judgment threshold based on the lower quantile also includes: During the testing process of the test coil using the preset detection method, the health status decay rate of each test coil that is determined to be a healthy coil is temporarily stored as a sample in the confirmation queue. When the number of samples in the queue to be confirmed reaches the preset batch size, the health decay rate sample library is updated using a sliding window method, and the judgment threshold is recalculated based on the updated health decay rate sample library.

[0011] Specifically, determining whether the tested high-voltage coil has an inter-turn insulation defect based on a comparison between the change in attenuation rate and a preset threshold includes: If the change in attenuation rate is greater than or equal to the determination threshold, then the tested high-voltage coil is determined to have an inter-turn insulation defect. If the change in attenuation rate is less than the determination threshold, then the inter-turn insulation of the tested high-voltage coil is determined to be normal.

[0012] Specifically, determining the test attenuation rate based on the test oscillation voltage waveform includes: according to Determine the test attenuation rate, where, The measured attenuation rate of the tested high-voltage coil is given by n, where n is the oscillation period. Let be the amplitude of the peak of the i-th test oscillation voltage waveform.

[0013] A high-voltage coil inter-turn insulation defect detection system based on attenuation rate change, the system comprising: A DC high-voltage power supply is used to provide a DC high voltage to charge the oscillation circuit under the action of the DC high voltage; An oscillation circuit is used to generate damped oscillations. The oscillation circuit includes a storage capacitor and a test sample interface connected in series. The storage capacitor is connected to the DC high-voltage power supply to store charging energy and release energy when the oscillation circuit is turned on to generate damped oscillations. The test sample interface is used to connect a calibration coil or a test high-voltage coil. A DC charging resistor is connected in series between the DC high-voltage power supply and the energy storage capacitor to limit the charging current to the energy storage capacitor. A high-voltage switch, connected in series with the energy storage capacitor, is used to control the on / off state of the oscillation circuit; A damping voltage divider, connected in parallel with the oscillation circuit, is used to acquire either the first attenuated oscillation voltage signal or the second attenuated oscillation voltage signal. A control and detection system, connected to the high-voltage switch and damping voltage divider, is used to execute the above-described method.

[0014] A computer-readable storage medium storing a computer program that, when executed by a processor, causes the processor to perform the steps of the method described above.

[0015] The embodiments of the present invention have the following beneficial effects: This invention uses the change in attenuation rate as the core criterion for judgment. Since the attenuation rate is more sensitive to changes in the equivalent resistance of the coil, especially for early, slight, and incomplete short-circuiting inter-turn insulation degradation, the attenuation rate change is significant while the frequency change is not obvious. Therefore, this invention accurately calculates the change in attenuation rate by testing the absolute value of the difference between the measured attenuation rate and the calibrated attenuation rate, and compares it with a judgment threshold. This effectively identifies early and slight inter-turn insulation degradation, ensuring that any subtle faults can be detected.

[0016] Furthermore, this invention employs a statistical threshold setting method based on kernel density estimation, utilizing a healthy sample database to construct a probability density function, thereby determining the judgment threshold and achieving objective quantification of the judgment standard. Compared to traditional methods relying on empirical thresholds or manual interpretation, this invention significantly reduces the impact of human factors on the judgment results, improving the consistency and reliability of the test results. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] in: Figure 1 A flowchart illustrating an embodiment of a high-voltage coil inter-turn insulation defect detection method based on attenuation rate change provided in this application; Figure 2 A flowchart illustrating another embodiment of a high-voltage coil inter-turn insulation defect detection method based on attenuation rate change provided in this application; Figure 3 A schematic diagram of an embodiment of a high-voltage coil inter-turn insulation defect detection system based on attenuation rate change provided in this application; Figure 4 A schematic diagram of the structure of an embodiment of the medium provided by the present invention. Detailed Implementation

[0019] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0020] like Figure 1 As shown, Figure 1 This is a flowchart illustrating an embodiment of a high-voltage coil inter-turn insulation defect detection method based on attenuation rate change provided in this application. The method includes: S101: Obtain a preset number of healthy coils of the same model as the coil under test. Healthy coils are coils that have been confirmed to be free of inter-turn defects through a preset detection method.

[0021] For example, M healthy coils (M≥30) of the same model as the coil under test are selected. The healthy coils are confirmed to be free of inter-turn defects through preset testing methods such as partial discharge detection, insulation resistance test, and withstand voltage test.

[0022] S102: After applying a DC high voltage to any healthy coil, the healthy coil generates a damped oscillation. The first damped oscillation voltage signal of the healthy coil during the damped oscillation process is collected. The calibration oscillation voltage waveform is determined based on the first damped oscillation voltage signal. The healthy attenuation rate is determined based on the calibration oscillation voltage waveform. A healthy sample library is constructed based on the healthy attenuation rates of a preset number of healthy coils. Any healthy attenuation rate in the healthy sample library is selected as the calibration attenuation rate.

[0023] For example, a DC high voltage (e.g., 128kV) is applied to each healthy coil to induce damped oscillations. The first damped oscillation voltage signal of each healthy coil during the damped oscillation process is acquired. The first damped oscillation voltage signal is then converted from analog to digital to determine the calibration oscillation voltage waveform. Based on the calibration oscillation voltage waveform, the healthy attenuation rate is determined. This constitutes the health sample library D = { , , ..., Select a healthy decay rate from the sample library as the calibration decay rate. .

[0024] The health decay rate is determined according to the following formula: ; in, Let n be the health decay rate of the i-th healthy coil, and n be the oscillation period. Let be the amplitude of the peak of the i-th calibration oscillation voltage waveform.

[0025] S103: Perform kernel density estimation on the data in the healthy sample library, construct the probability density function of the health status decay rate, and determine the judgment threshold on the probability density function.

[0026] For example, data from the health decay rate sample library is used as samples for preprocessing. Specifically, the sample skewness of the data in the health decay rate sample library is determined based on the mean and standard deviation of the samples. If the sample skewness is greater than a preset threshold, a Box-Cox transformation is performed on the sample data. If the sample skewness is not greater than the preset threshold, the original data in the health decay rate sample library remains unchanged.

[0027] Furthermore, a reference bandwidth is determined based on the standard deviation of the preprocessed samples, and a reference interval is determined based on the reference bandwidth. Cross-validation is then performed within the reference interval to select the optimal bandwidth. Based on the optimal bandwidth, a probability density function for the attenuation rate of the healthy coil is constructed, as shown in the following equation: ; in, Let h be the Gaussian kernel function, h be the optimal bandwidth, and M be the total number of healthy coil samples. y represents the attenuation rate of the healthy coil after preprocessing, and y represents the attenuation rate of the healthy coil after current preprocessing.

[0028] Furthermore, on the probability density function, the lower quantiles that satisfy the lower area being a preset acceptable false alarm rate are determined; and the judgment threshold is determined based on the lower quantiles.

[0029] Specifically, in the probability density function Above, based on the acceptable false alarm rate (e.g., 1%) Determine the lower quantile. : ; If a Box-Cox transformation has been performed, then the attenuation rate threshold needs to be determined by the inverse transformation. The threshold is: ;otherwise .

[0030] S104: After applying the same DC high voltage to the tested high voltage coil, the tested high voltage coil generates a damped oscillation. The second damped oscillation voltage signal of the tested high voltage coil during the damped oscillation process is collected. The test oscillation voltage waveform is determined based on the second damped oscillation voltage signal, and the test attenuation rate is determined based on the test oscillation voltage waveform.

[0031] For example, keeping the circuit parameters the same as the test voltage (i.e., DC high voltage, 128kV), the high-voltage coil under test is connected, and the second damped oscillation voltage signal of the high-voltage coil under test during the damped oscillation process is acquired. The second damped oscillation voltage signal is then converted from analog to digital to obtain the test oscillation voltage waveform, and the test attenuation rate is calculated. The attenuation rate is calculated using the following formula: ; in, The measured attenuation rate of the tested high-voltage coil is given by n, where n is the oscillation period. The amplitude of the peak of the i-th test oscillation voltage waveform It should be noted that using 3 to 5 cycles can reduce the computational load while ensuring the accuracy of the judgment.

[0032] S105: Determine the change in attenuation rate based on the absolute value of the difference between the test attenuation rate and the calibrated attenuation rate. Based on the comparison between the change in attenuation rate and the preset judgment threshold, determine whether there is an inter-turn insulation defect in the tested high-voltage coil.

[0033] For example, the change in attenuation rate is calculated according to the following formula: .

[0034] Compare With the judgment threshold : like If so, it is determined that there is an inter-turn insulation defect in the tested high-voltage coil; like If the insulation between the turns of the tested high-voltage coil is normal, it is determined that the insulation is normal.

[0035] As described above, this invention uses the change in attenuation rate as the core criterion for judgment. Since the attenuation rate is more sensitive to changes in the equivalent resistance of the coil, especially for early, slight, and incomplete short-circuiting inter-turn insulation degradation, the attenuation rate change is significant while the frequency change is not obvious. Therefore, this invention accurately calculates the change in attenuation rate by testing the absolute value of the difference between the measured attenuation rate and the calibrated attenuation rate, and compares it with a judgment threshold. This effectively identifies early and slight inter-turn insulation degradation, ensuring that any subtle faults can be accurately detected.

[0036] Furthermore, this invention employs a statistical threshold setting method based on kernel density estimation, utilizing a healthy sample database to construct a probability density function, thereby determining the judgment threshold and achieving objective quantification of the judgment standard. Compared to traditional methods relying on empirical thresholds or manual interpretation, this invention significantly reduces the impact of human factors on the judgment results, improving the consistency and reliability of the test results.

[0037] like Figure 2 As shown, Figure 2 This is a flowchart illustrating another embodiment of a high-voltage coil inter-turn insulation defect detection method based on attenuation rate change provided in this application. The method includes: S201: Obtain a preset number of healthy coils of the same model as the coil under test. Healthy coils are coils that have been confirmed to be free of inter-turn defects through a preset detection method.

[0038] S202: After applying a DC high voltage to any healthy coil, the healthy coil generates a damped oscillation. The first damped oscillation voltage signal of the healthy coil during the damped oscillation process is collected. The calibration oscillation voltage waveform is determined based on the first damped oscillation voltage signal. The healthy attenuation rate is determined based on the calibration oscillation voltage waveform. A healthy sample library is constructed based on the healthy attenuation rates of a preset number of healthy coils. Any healthy attenuation rate in the healthy sample library is selected as the calibration attenuation rate.

[0039] For example, a predetermined number of healthy coils of the same model as the coil under test are obtained. These healthy coils are those confirmed to be free of inter-turn defects through a predetermined detection method. Attenuation rate testing is performed on multiple healthy coils, with the test parameters set as follows: Test voltage (DC high voltage): 128kV; Energy storage capacitor: Selected according to coil grade; After applying a DC high voltage to any healthy coil, the healthy coil generates a damped oscillation. The first damped oscillation voltage signal of the healthy coil during the damped oscillation process is collected. The calibration oscillation voltage waveform is determined based on the first damped oscillation voltage signal, and the healthy attenuation rate is determined based on the calibration oscillation voltage waveform. A healthy sample library is constructed based on the healthy attenuation rates of a preset number of healthy coils, and any healthy attenuation rate in the healthy sample library is selected as the calibration attenuation rate.

[0040] S203: Use data from the health decay rate sample library as samples and preprocess the samples.

[0041] For example, using data from the health decay rate sample library as samples, the sample skewness of the data in the health decay rate sample library is determined based on the mean and standard deviation of the samples. Specifically, for sample data Calculate the sample mean using the formula shown below. : ; Calculate the sample standard deviation using the formula shown below. : ; The sample skewness of the data in the health decay rate sample library is determined using the following formula: .

[0042] If the sample skewness is greater than the preset threshold of 0.5, then the sample data is subjected to a Box-Cox transformation according to the formula shown below, so that the transformed data... It approximately follows a symmetrical distribution: ; If the sample skewness is not greater than the preset threshold of 0.5, the original data of the healthy decay rate sample library will remain unchanged.

[0043] S204: Determine the reference bandwidth based on the standard deviation of the preprocessed samples, determine the reference interval based on the reference bandwidth, perform cross-validation within the reference interval, and select the optimal bandwidth.

[0044] For example, for preprocessed samples The reference bandwidth is determined based on the standard deviation of the preprocessed samples, as shown in the following formula: .

[0045] Furthermore, with As the initial value, in Perform 10-fold cross-validation within the interval, and select the bandwidth that maximizes the log-likelihood function of the validation set as the optimal bandwidth. This step ensures that the probability density function is neither undersmoothed nor oversmoothed, accurately reflecting the true statistical distribution.

[0046] S205: Construct the probability density function of the attenuation rate of the healthy coil based on the optimal bandwidth.

[0047] For example, the probability density function of the attenuation rate of the healthy coil is constructed based on the optimal bandwidth, as shown in the following equation: ; in, For the kernel function, the Gaussian kernel function is preferred. h is the optimal bandwidth, and M is the total number of healthy coil samples. y represents the attenuation rate of the healthy coil after preprocessing, and y represents the attenuation rate of the healthy coil after current preprocessing.

[0048] S206: On the probability density function, determine the lower quantiles that satisfy the lower area as a preset acceptable false alarm rate.

[0049] S207: Determine the judgment threshold based on the lower quantile.

[0050] For example, based on the acceptable false alarm rate β in operations and maintenance (e.g., β=1%), in the probability density function Looking up to find the area on the lower side that satisfies the condition. quantiles As an alarm threshold: ; The solution can be obtained using numerical integration and binary search. If a Box-Cox transformation has been performed, then the attenuation rate threshold needs to be determined through an inverse transformation. (When transformed to logarithmic form), if no Box-Cox transformation is performed, then This threshold for judgment. This is the statistically significant lower tolerance boundary determined by the current sample library D. Below this value, the coil can be quantitatively determined to be a defective coil.

[0051] S208: After applying the same DC high voltage to the tested high voltage coil, the tested high voltage coil generates a damped oscillation. The second damped oscillation voltage signal of the tested high voltage coil during the damped oscillation process is collected. The test oscillation voltage waveform is determined based on the second damped oscillation voltage signal, and the test attenuation rate is determined based on the test oscillation voltage waveform.

[0052] For example, keeping the test circuit parameters and test high voltage unchanged, after applying the same DC high voltage to the high voltage coil under test, the high voltage coil under test generates a damped oscillation. The second damped oscillation voltage signal of the high voltage coil under test during the damped oscillation process is collected, the test oscillation voltage waveform is determined according to the second damped oscillation voltage signal, and the test attenuation rate is determined based on the test oscillation voltage waveform.

[0053] S209: Determine the change in attenuation rate based on the absolute value of the difference between the tested attenuation rate and the calibrated attenuation rate.

[0054] S210: If the change in attenuation rate is greater than or equal to the judgment threshold, it is determined that there is an inter-turn insulation defect in the tested high-voltage coil.

[0055] S211: If the change in attenuation rate is less than the judgment threshold, the inter-turn insulation of the tested high-voltage coil is judged to be normal.

[0056] For example, the change in attenuation rate is calculated according to the following formula: .

[0057] Compare With the judgment threshold : like If so, it is determined that there is an inter-turn insulation defect in the tested high-voltage coil; like If the insulation between the turns of the tested high-voltage coil is normal, it is determined that the insulation is normal.

[0058] S212: During the testing process of the test coil using a preset detection method, the health state decay rate of each test coil that is determined to be a healthy coil is temporarily stored as a sample in the confirmation queue.

[0059] S213: When the number of samples in the queue to be confirmed reaches the preset batch size, the health decay rate sample library is updated using a sliding window method, and the judgment threshold is recalculated based on the updated health decay rate sample library.

[0060] For example, during the testing of test coils using a preset detection method, the health status decay rate of each test coil determined to be healthy is temporarily stored in a confirmation queue. When the number of newly added healthy samples reaches a preset batch size N (e.g., N=10), a sliding incremental update of the model is triggered.

[0061] Specifically, a sliding window is used to keep the total number of samples M constant: adding new samples... Remove the earliest sample To update the health decay rate sample library, the kernel density estimate is updated based on the updated health decay rate sample library according to the following formula: ; Use the updated The judgment threshold is recalculated. This mechanism can automatically adapt to normal distribution drift caused by changes in raw material batches and production processes of the same type of coil, and maintain a consistently low false alarm rate.

[0062] like Figure 3 As shown, Figure 3 A schematic diagram of an embodiment of a high-voltage coil inter-turn insulation defect detection system based on attenuation rate change provided in this application. The high-voltage coil inter-turn insulation defect detection system 10 based on attenuation rate change includes: DC high voltage power supply 1 is used to provide DC high voltage to charge the oscillation circuit under the action of DC high voltage.

[0063] An oscillation circuit is used to generate damped oscillations. The oscillation circuit includes a storage capacitor 4 and a test sample interface 5 connected in series. The storage capacitor 4 is connected to a DC high-voltage power supply 1 to store charging energy and release energy when the oscillation circuit is turned on to generate damped oscillations. The test sample interface 5 is used to connect a calibration coil or a test high-voltage coil.

[0064] The DC charging resistor 2 is connected in series between the DC high voltage power supply 1 and the energy storage capacitor 4 to limit the charging current when charging the energy storage capacitor and protect the DC high voltage power supply and the energy storage capacitor.

[0065] High-voltage switch 3, connected in series with energy storage capacitor 4, is used to control the on / off state of the oscillation circuit.

[0066] Damping voltage divider 6 is connected in parallel with the oscillation circuit and is used to acquire the first damped oscillation voltage signal or the second damped oscillation voltage signal.

[0067] The control and detection system 8 is connected to the high-voltage switch 3 and the damping voltage divider 6 to perform the above method.

[0068] For example, the DC high voltage power supply 1 can be a high-frequency inverter DC high voltage generator to provide an adjustable DC high voltage to charge the energy storage capacitor, thereby providing initial energy for damped oscillation.

[0069] The oscillation circuit is the core energy conversion and signal generation component of the detection system. This circuit consists of a storage capacitor 4 and a test sample interface 5 connected in series. The storage capacitor 4 is connected to the DC high-voltage power supply 1 to store charging energy and releases energy when the oscillation circuit is turned on to generate damped oscillations. The test sample interface 5 is used to connect the calibration coil or the test high-voltage coil.

[0070] The DC charging resistor 2 is connected in series between the DC high voltage power supply 1 and the energy storage capacitor 4 to limit the charging current when charging the energy storage capacitor and protect the DC high voltage power supply and the energy storage capacitor.

[0071] High-voltage switch 3, connected in series with energy storage capacitor 4, is used to control the on / off state of the oscillation circuit. It closes rapidly after energy storage capacitor 4 has finished charging, thus activating the oscillation circuit and triggering the damped oscillation process. Specifically, after DC high-voltage power supply 1 charges energy storage capacitor 4 to a set voltage, high-voltage switch 3 closes, and energy storage capacitor 4 rapidly discharges through the tested high-voltage coil, generating high-frequency damped oscillation.

[0072] Damping voltage divider 6, connected in parallel with the oscillation circuit, is used to acquire the first decaying oscillation voltage signal of the calibration coil or the second decaying oscillation voltage signal of the tested high-voltage coil, providing raw waveform data for attenuation rate calculation.

[0073] The control and detection system 8, connected to the high-voltage switch 3 and the damping voltage divider 6, is used to acquire a preset number of healthy coils of the same model as the coil under test. The healthy coils are those confirmed to be free of inter-turn defects through a preset detection method. After applying a DC high voltage to any healthy coil, the coil generates a damped oscillation. The system acquires the first damped oscillation voltage signal during this oscillation process, determines the calibration oscillation voltage waveform based on the first damped oscillation voltage signal, and determines the healthy attenuation rate based on the calibration oscillation voltage waveform. A healthy sample library is constructed based on the healthy attenuation rates of the preset number of healthy coils, and any healthy attenuation rate from the healthy sample library is selected as the calibration attenuation rate. Kernel density estimation is performed on data from the healthy sample library to construct a probability density function for the decay rate of the healthy state, and a judgment threshold is determined on the probability density function. After applying the same DC high voltage to the tested high-voltage coil, the tested high-voltage coil generates decaying oscillations. The second decaying oscillation voltage signal of the tested high-voltage coil during the decaying oscillation process is collected, and the test oscillation voltage waveform is determined based on the second decaying oscillation voltage signal. The test decay rate is determined based on the absolute value of the difference between the test decay rate and the calibrated decay rate. The decay rate change is determined based on the comparison between the decay rate change and the preset judgment threshold to determine whether there is an inter-turn insulation defect in the tested high-voltage coil.

[0074] like Figure 3 As shown, a high-voltage coil inter-turn insulation defect detection system 10 based on attenuation rate change is provided. The system further includes: The current testing unit 7, which can be a Rogowski coil or a shunt, is connected to the detection and control system 8 to collect the current signal during the damping oscillation process. The data provided by the current testing unit can serve as an important aid, especially in complex field environments where the current signal is more sensitive to changes in stray parameters of the circuit, which helps to identify non-insulation faults such as poor wiring and abnormal grounding, and avoids misjudgment.

[0075] like Figure 4 As shown, Figure 4 This is a schematic diagram of the structure of an embodiment of the medium provided by the present invention. The medium 20 stores at least one computer program 21, which is executed by a processor to implement... Figure 1 and Figure 2 The method shown is detailed above and will not be repeated here. In one embodiment, the medium 20 can be a storage chip, hard disk, portable hard disk, USB flash drive, optical disk, or other read / write storage device, or even a server, etc.

[0076] Furthermore, the processes depicted in the accompanying drawings do not necessarily have to be performed in the specific or sequential order shown to achieve the desired result. In some implementations, multitasking and parallel processing are possible or may be advantageous.

[0077] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the embodiments of apparatus, devices, and non-volatile computer-readable storage media are basically similar to the method embodiments, and therefore described more simply; relevant parts can be referred to the descriptions of the method embodiments.

[0078] The apparatus, device, non-volatile computer-readable storage medium and method provided in the embodiments of this specification are corresponding. Therefore, the apparatus, device and non-volatile computer storage medium also have similar beneficial technical effects as the corresponding method. Since the beneficial technical effects of the method have been described in detail above, the beneficial technical effects of the corresponding apparatus, device and non-volatile computer storage medium will not be repeated here.

[0079] The systems, devices, modules, or units described in the above embodiments can be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, a computer can be, for example, a personal computer, laptop computer, cellular phone, camera phone, smartphone, personal digital assistant, media player, navigation device, email device, game console, tablet computer, wearable device, or any combination of these devices.

[0080] For ease of description, the above apparatus is described by dividing it into various functional units. Of course, in implementing this specification, the functions of each unit can be implemented in one or more software and / or hardware components. Those skilled in the art will understand that the embodiments of this specification can be provided as methods, systems, or computer program products. Therefore, the embodiments of this specification can take the form of entirely hardware embodiments, entirely software embodiments, or embodiments combining software and hardware aspects. Furthermore, the embodiments of this specification can take the form of computer program products 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.

[0081] This specification is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this specification. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a machine for implementing the flowchart illustrations and / or block diagrams. Figure 1One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0082] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0083] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0084] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0085] Memory may include non-persistent storage in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0086] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information by any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0087] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0088] This specification can be described in the general context of computer-executable instructions that are executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform a specific task or implement a specific abstract data type. This specification can also be practiced in distributed computing environments, where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0089] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the system embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments.

[0090] The above description discloses only preferred embodiments of the present invention and should not be construed as limiting the scope of the present invention. Therefore, equivalent variations made in accordance with the claims of the present invention are still within the scope of the present invention.

Claims

1. A method for detecting inter-turn insulation defects in high-voltage coils based on changes in attenuation rate, characterized in that, The method includes: Obtain a preset number of healthy coils of the same model as the coil under test. The healthy coils are those that have been confirmed to be free of inter-turn defects through a preset detection method. After applying a DC high voltage to any of the healthy coils, the healthy coils generate damped oscillations. The first damped oscillation voltage signal of the healthy coil during the damped oscillation process is collected. The calibration oscillation voltage waveform is determined based on the first damped oscillation voltage signal. The healthy attenuation rate is determined based on the calibration oscillation voltage waveform. A healthy sample library is constructed based on the healthy attenuation rates of a preset number of healthy coils. Any healthy attenuation rate in the healthy sample library is selected as the calibration attenuation rate. Kernel density estimation is performed on the data in the health sample library to construct the probability density function of the health state decay rate, and a judgment threshold is determined on the probability density function. After applying the same DC high voltage to the tested high voltage coil, the tested high voltage coil generates a damped oscillation. The second damped oscillation voltage signal of the tested high voltage coil during the damped oscillation process is collected. The test oscillation voltage waveform is determined based on the second damped oscillation voltage signal, and the test attenuation rate is determined based on the test oscillation voltage waveform. The attenuation rate change is determined based on the absolute value of the difference between the test attenuation rate and the calibrated attenuation rate. The presence of inter-turn insulation defects in the tested high-voltage coil is determined by comparing the attenuation rate change with a preset judgment threshold.

2. The method for detecting inter-turn insulation defects in high-voltage coils based on attenuation rate variation according to claim 1, characterized in that, The step of performing kernel density estimation on the data in the health sample library, constructing a probability density function for the health state decay rate, and determining a judgment threshold on the probability density function specifically includes: Using the data in the health decay rate sample library as samples, the samples are preprocessed; A reference bandwidth is determined based on the standard deviation of the preprocessed samples, a reference interval is determined based on the reference bandwidth, cross-validation is performed within the reference interval, and the optimal bandwidth is selected. Construct a probability density function for the attenuation rate of the healthy coil based on the optimal bandwidth; On the probability density function, determine the lower quantiles that satisfy the lower area as a preset acceptable false alarm rate; The determination threshold is determined based on the lower quantile.

3. The high-voltage coil inter-turn insulation defect detection method based on attenuation rate change according to claim 2, characterized in that, The step of using data from the health decay rate sample library as samples and preprocessing the samples specifically includes: Using the data in the health decay rate sample library as samples, the sample skewness of the data in the health decay rate sample library is determined based on the mean and standard deviation of the samples. If the sample skewness is greater than a preset threshold, then the sample data is subjected to a Box-Cox transformation; If the sample skewness is not greater than a preset threshold, the original data of the health decay rate sample library remains unchanged.

4. The high-voltage coil inter-turn insulation defect detection method based on attenuation rate change according to claim 3, characterized in that, The probability density function for constructing the attenuation rate of the healthy coil based on the optimal bandwidth specifically includes: according to Determine the probability density function of the attenuation rate of the healthy coil, where, Let h be the Gaussian kernel function, h be the optimal bandwidth, and M be the total number of healthy coil samples. y represents the attenuation rate of the healthy coil after preprocessing, and y represents the attenuation rate of the healthy coil after current preprocessing.

5. The method for detecting inter-turn insulation defects in high-voltage coils based on attenuation rate variation according to claim 3, characterized in that, The determination of the judgment threshold based on the lower quantile specifically includes: If the sample data undergoes a Box-Cox transformation, then according to Determine the judgment threshold; If the sample data has not undergone Box-Cox transformation, then according to Determine the judgment threshold.

6. The method for detecting inter-turn insulation defects in high-voltage coils based on attenuation rate variation according to claim 1, characterized in that, After determining the judgment threshold based on the lower quantile, the method further includes: During the testing process of the test coil using the preset detection method, the health status decay rate of each test coil that is determined to be a healthy coil is temporarily stored as a sample in the confirmation queue. When the number of samples in the queue to be confirmed reaches the preset batch size, the health decay rate sample library is updated using a sliding window method, and the judgment threshold is recalculated based on the updated health decay rate sample library.

7. The method for detecting inter-turn insulation defects in high-voltage coils based on attenuation rate variation according to claim 1, characterized in that, The step of determining whether the tested high-voltage coil has an inter-turn insulation defect based on a comparison of the attenuation rate change with a preset judgment threshold specifically includes: If the change in attenuation rate is greater than or equal to the determination threshold, then the tested high-voltage coil is determined to have an inter-turn insulation defect. If the change in attenuation rate is less than the determination threshold, then the inter-turn insulation of the tested high-voltage coil is determined to be normal.

8. The method for detecting inter-turn insulation defects in high-voltage coils based on attenuation rate variation according to claim 1, characterized in that, The determination of the test attenuation rate based on the test oscillation voltage waveform specifically includes: according to Determine the test attenuation rate, where, The measured attenuation rate of the tested high-voltage coil is given by n, where n is the oscillation period. Let be the amplitude of the peak of the i-th test oscillation voltage waveform.

9. A high-voltage coil inter-turn insulation defect detection system based on attenuation rate change, characterized in that, The system includes: A DC high-voltage power supply is used to provide a DC high voltage to charge the oscillation circuit under the action of the DC high voltage; An oscillation circuit is used to generate damped oscillations. The oscillation circuit includes a storage capacitor and a test sample interface connected in series. The storage capacitor is connected to the DC high-voltage power supply to store charging energy and release energy when the oscillation circuit is turned on to generate damped oscillations. The test sample interface is used to connect a calibration coil or a test high-voltage coil. A DC charging resistor is connected in series between the DC high-voltage power supply and the energy storage capacitor to limit the charging current to the energy storage capacitor. A high-voltage switch, connected in series with the energy storage capacitor, is used to control the on / off state of the oscillation circuit; A damping voltage divider, connected in parallel with the oscillation circuit, is used to acquire either the first attenuated oscillation voltage signal or the second attenuated oscillation voltage signal. A control and detection system, connected to the high-voltage switch and the damping voltage divider, is used to perform the method according to any one of claims 1-8.

10. A computer-readable storage medium storing a computer program that, when executed by a processor, causes the processor to perform the steps of the method as claimed in any one of claims 1 to 8.

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