A cable insulation layer defect type detection method, device and computer readable storage medium

Abstract

The application discloses a cable insulation layer defect type detection method and device and a computer readable storage medium, wherein the method comprises the following steps: obtaining reference harmonic currents corresponding to different cable insulation layer defect types of a preset sample cable; obtaining harmonic components corresponding to a to-be-detected cable; judging whether the to-be-detected cable has defects based on the harmonic components and the reference harmonic currents; performing principal component analysis on the harmonic components to obtain dimension-reduced data corresponding to the harmonic components when the to-be-detected cable has defects; determining different defect probabilities corresponding to the to-be-detected cable based on a preset Gaussian mixture model and the dimension-reduced data; and determining a defect type corresponding to the to-be-detected cable based on the different defect probabilities. The application can improve the detection efficiency of the cable insulation layer defect type.

Description

Technical Field

[0001] This invention relates to the field of cable testing technology, and specifically to a method, equipment, and computer-readable storage medium for detecting cable insulation layer defect types. Background Technology

[0002] Cross-linked polyethylene (XLPE) cables are increasingly widely used in urban power transmission and distribution systems due to their superior performance and ease of installation. However, the increasing complexity of urban underground pipe networks, the intricate structure of distribution network cable lines, diverse operating environments, growing equipment density, and the rising proportion of aging cables have led to persistently high failure rates in distribution network cable lines. This poses a growing risk of major fires or large-scale power outages, potentially severely impacting the safe operation of urban power grids.

[0003] Since cables are mainly laid underground, and the laying channels often have phenomena such as overcapacity, accumulation, water accumulation, and silt, which can easily lead to a decline in the insulation performance of the cables and cause failures, the detection and evaluation of the insulation aging and moisture condition of cables has always been a key focus for researchers and maintenance personnel.

[0004] Currently, the main methods for assessing the condition of distribution network cables are routine manual inspections and offline testing (withstand voltage, oscillating wave partial discharge, ultra-low frequency dielectric loss, etc.). Due to many limiting factors such as the construction of cable network structures, laying channels, and strict control over planned power outage maintenance time (especially in large cities with extremely high power supply reliability requirements), it is difficult to efficiently detect cable defects. Summary of the Invention

[0005] The technical problem to be solved by the embodiments of the present invention is to provide a method, device and computer-readable storage medium for detecting cable insulation layer defect types, so as to improve the efficiency of cable defect type detection.

[0006] To solve the above-mentioned technical problems, the present invention provides a method for detecting cable insulation layer defect types, comprising: Obtain the reference harmonic currents corresponding to different cable insulation defect types for the pre-set sample cable; Obtain the harmonic components corresponding to each harmonic of the cable under test, and determine whether the cable under test has defects based on the harmonic components and the reference harmonic current. When the cable under test has defects, principal component analysis is performed on each harmonic component to obtain the dimensionality reduction data corresponding to each harmonic component. Based on the pre-set Gaussian mixture model and the dimensionality reduction data, the different defect probabilities corresponding to the cable under test are determined, and the defect type corresponding to the cable under test is determined based on the different defect probabilities.

[0007] Preferably, before determining the different defect probabilities corresponding to the cable under test based on the preset Gaussian mixture model and the dimensionality-reduced data, the method further includes: Based on the pre-set Naive Bayes model and the pre-set Gaussian mixture model, the probability values ​​of different defect categories corresponding to different pre-set sample points are determined. The center point value is updated based on the probability value; Based on the updated values, the probability values ​​of the different defect categories corresponding to the different preset sample points are recalculated until the iteration is complete.

[0008] Preferably, after the iteration is completed, the process further includes: Treat each data point in the preset sample set as an independent event, and construct a product function based on the product of the probability values ​​corresponding to all data points in the preset sample set. Perform a logarithmic operation on the product function to obtain the simplified probability value function corresponding to the preset sample set; Based on the simplified probability function and the dimensionality reduction data, the different defect probabilities corresponding to the cable under test are obtained.

[0009] Preferably, after obtaining the reference harmonic currents corresponding to different cable insulation defect types for the pre-set sample cable, the method further includes: During the thermal aging and deterioration process, the harmonic diagram corresponding to the third harmonic of the reference harmonic current is determined; wherein, as the equivalent wedge-shaped pore depth increases, the harmonic diagram corresponding to the third harmonic shows two trends of first increasing and then decreasing, and the fluctuation of the first trend is greater than the fluctuation of the second trend, and the harmonic diagram corresponding to the third harmonic shows an overall upward trend. During the thermal aging and deterioration process, the harmonic diagram corresponding to the 5th harmonic of the reference harmonic current was determined; wherein, the harmonic diagram corresponding to the 5th harmonic shows a trend of first decreasing and then increasing with the increase of the equivalent wedge-shaped pore depth, and the overall trend is downward. During the thermal aging and deterioration process, a harmonic diagram corresponding to the 7th harmonic of the reference harmonic current was determined; wherein, the harmonic diagram corresponding to the 7th harmonic shows a trend of first decreasing and then increasing with the increase of the equivalent wedge-shaped pore depth, and the overall trend is downward.

[0010] Preferably, after obtaining the reference harmonic currents corresponding to different cable insulation defect types for the pre-set sample cable, the method further includes: During the hydrothermal aging process, the harmonic diagram corresponding to the third harmonic of the reference harmonic current was determined; wherein, the harmonic diagram corresponding to the third harmonic shows an overall decreasing trend with the increase of equivalent wedge pore depth and water content; During the hydrothermal aging process, the harmonic diagram corresponding to the 5th harmonic of the reference harmonic current was determined; wherein, the harmonic diagram corresponding to the 5th harmonic shows a trend of first decreasing and then increasing with the increase of equivalent wedge pore depth and water content, and then showing a decreasing trend in the later stage. During the water-thermal aging process, the harmonic diagram corresponding to the 7th harmonic of the reference harmonic current was determined; wherein, the harmonic diagram corresponding to the 7th harmonic shows a trend of first decreasing and then increasing with the increase of the equivalent wedge pore depth and water content.

[0011] Preferably, obtaining the harmonic components corresponding to the cable under test specifically includes: Obtain the distorted current waveform corresponding to the cable under test; The distorted current is expanded according to the wave using a fast Fourier transform to decompose it into the corresponding harmonic components of the cable under test.

[0012] Preferably, determining whether the cable under test has defects based on the harmonic components and the reference harmonic current specifically includes: Obtain the schematic diagram of each harmonic corresponding to the cable under test; The schematic diagrams of each harmonic are compared with multiple preset reference harmonic schematic diagrams; wherein, the reference harmonic schematic diagrams are related to the reference harmonic currents. Determine the similarity between the schematic diagrams of each harmonic and the reference harmonic schematic diagram; If the similarity is greater than a preset similarity threshold, the cable under test is determined to have a defect.

[0013] Preferably, obtaining the reference harmonic currents corresponding to different cable insulation defect types for the pre-set sample cable specifically includes: A cross-linked polyethylene cable model was built using COMSOL finite element simulation software; wherein, the cross-linked polyethylene cable model is a cable joint interface model with a pre-set conductor cross-sectional area. By constructing wedge structures of different depths using the cross-linked polyethylene cable model, the porosity generated after cable aging is simulated to simulate different defect types corresponding to the cross-linked polyethylene cable model; wherein, the wedge structure in the normally aged cross-linked polyethylene cable model does not contain moisture, while the wedge structure in the moisture-aged cross-linked polyethylene cable model contains moisture. Obtain the magnetic flux density distribution corresponding to the cross-linked polyethylene cable model; When it is determined that magnetic flux distortion occurs in the defective part of the cross-linked polyethylene cable model, the reference harmonic currents corresponding to different defect types are determined based on the magnetic flux density distribution.

[0014] The present invention also provides a cable insulation layer defect type detection device, comprising: One or more processors; Memory; One or more applications, wherein the one or more applications are stored in the memory and configured to be executed by the one or more processors, the one or more applications being configured to perform the cable insulation defect type detection method.

[0015] The present invention also provides a computer-readable storage medium comprising a stored computer program; wherein, when the computer program is executed, it controls the device containing the computer-readable storage medium to perform the cable insulation defect type detection method.

[0016] The implementation of this invention has the following beneficial effects: In this embodiment, electromagnetic simulation is used to obtain the reference harmonic currents corresponding to pre-set sample cables under different cable insulation defect types, in order to determine whether the current cable under test has defects. By introducing principal component analysis, a few variables are used to comprehensively reflect the main information of the original variables, and the final determined new variables are linear combinations of the original variables. For the dimensionality-reduced data obtained by principal component analysis, cluster analysis is further used to classify the cable defect states, thereby quickly and accurately obtaining the cable defect types. 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] Figure 1 This is a flowchart illustrating a method for detecting cable insulation layer defect types according to an embodiment of the present invention.

[0019] Figure 2 This is a first relationship diagram between magnetic flux density, porosity, and moisture content in an embodiment of the present invention.

[0020] Figure 3 This is a second relationship diagram between magnetic flux density, porosity, and moisture content in an embodiment of the present invention.

[0021] Figure 4 This is a schematic diagram of the harmonics corresponding to the thermally aged cable in an embodiment of the present invention.

[0022] Figure 5 This is a schematic diagram of the harmonics corresponding to the water-heat aging cable in an embodiment of the present invention.

[0023] Figure 6 This is a schematic diagram of the harmonics of the thermally aged cable changing over time in an embodiment of the present invention.

[0024] Figure 7 This is a schematic diagram of the harmonics of the water-heat aging cable over time in an embodiment of the present invention.

[0025] Figure 8 This is a comparison diagram of the harmonics of the thermally aged cable and the water-thermally aged cable in an embodiment of the present invention.

[0026] Figure 9 This is a schematic diagram of the clustering identification results of damp and aged cables in an embodiment of the present invention.

[0027] Figure 10 This is a schematic diagram of a cable insulation layer defect type detection device according to Embodiment 2 of the present invention. Detailed Implementation

[0028] The following description of the embodiments is taken with reference to the accompanying drawings, which illustrate specific embodiments in which the invention can be implemented.

[0029] Please refer to Figure 1 As shown, Embodiment 1 of the present invention provides a method for detecting cable insulation layer defect types, including: Step S101: Obtain the reference harmonic currents corresponding to different cable insulation layer defect types for the preset sample cable; Step S102: Obtain the harmonic components corresponding to the cable under test, and determine whether the cable under test has defects based on the harmonic components and the reference harmonic current. Step S103: When the cable under test has defects, principal component analysis is performed on each harmonic component to obtain the dimensionality reduction data corresponding to each harmonic component. Step S104: Based on the preset Gaussian mixture model and the dimensionality reduction data, determine the different defect probabilities corresponding to the cable under test, and determine the defect type corresponding to the cable under test based on the different defect probabilities.

[0030] As shown in the above steps, this embodiment of the invention obtains the reference harmonic currents corresponding to pre-set sample cables under different cable insulation defect types through electromagnetic simulation to determine whether the current cable under test has defects. By introducing principal component analysis, a few variables are used to comprehensively reflect the main information of the original variables, and the final determined new variables are linear combinations of the original variables. Cluster analysis is further used on the dimensionality-reduced data obtained by principal component analysis to classify the cable defect states, thereby quickly and accurately obtaining the cable defect type.

[0031] When power cable insulation is subjected to stress (such as moisture, thermal stress, and electric fields), it exhibits abnormal or deteriorated phenomena. When the cable is subjected to severe deterioration factors, stress aging causes nonlinearity in the cable insulation. At this time, the magnetic flux inside the cable is distorted, and a distorted current wave can be obtained by measurement.

[0032] Furthermore, by expanding the current using a Fast Fourier Transform (FFT), the harmonic components under different cable stress aging defects can be obtained. Since the thermal stress borne by the insulation material is cumulative damage stress, the insulation will undergo irreversible deterioration, leading to magnetic field distortion, which in turn causes current distortion. Therefore, cable aging defects are the main cause of higher harmonics.

[0033] In one embodiment of the present invention, a cross-linked polyethylene (XLPE) cable model is constructed using COMSOL finite element simulation software; wherein, the XLPE cable model is a cable joint interface model with a pre-defined conductor cross-sectional area. Different depth "wedge" structures are constructed using the XLPE cable model to simulate the porosity generated after cable aging, thereby simulating different defect types corresponding to the XLPE cable model; wherein, the "wedge" structure in a normally aged XLPE cable model is free of moisture, while the "wedge" structure in a moisture-aged XLPE cable model contains moisture. The magnetic flux density distribution corresponding to the XLPE cable model is obtained. When it is determined that magnetic flux distortion occurs in the defective portion of the XLPE cable model, the reference harmonic currents corresponding to different defect types are determined based on the magnetic flux density distribution.

[0034] Specifically, in this embodiment of the invention, a cross-linked polyethylene cable model was built using COMSOL finite element simulation software. The two-dimensional modeling used a cable joint cross-section model with a conductor cross-sectional area of ​​300 mm².

[0035] Specifically, this embodiment of the invention constructs cable insulation layer normal aging and water treeing cable defects, and compares and analyzes the changes in cable magnetic field strength under different defects in the cable insulation layer. Furthermore, by changing the defect type, location, and size, the magnetic flux density distribution and harmonic current ratio at different locations of the cable joint are calculated. The conductivity of the cable joints without moisture and those after one month of accelerated moisture absorption are measured using an electrometer. The dielectric constant of the materials required for the simulation is measured using the Novocontrol broadband dielectric spectroscopy system.

[0036] Furthermore, the embodiments of the present invention mainly simulate two scenarios: thermal aging and water immersion thermal aging. Different depths of "wedge" structures are used to simulate the micropores generated after cable aging, with half of the "wedge" structures in the damp cable containing moisture. The difference between water immersion thermal aging and normal thermal aging lies primarily in the presence of a large amount of moisture in the micropores, as well as the pore depth and number.

[0037] Furthermore, the local porosity caused by electrothermal aging produces a magnetic flux distortion of equal magnitude in the defective area. The magnetic flux density decreases near the outer side of the XLPE layer, while the magnetic flux density decreases significantly on the inner side of the SIR layer.

[0038] In one embodiment of the present invention, during the thermal aging and degradation process, a harmonic diagram corresponding to the third harmonic of the reference harmonic current is determined. The harmonic diagram corresponding to the third harmonic shows two trends of first increasing and then decreasing with the increase of the equivalent "wedge" pore depth, with the first trend fluctuation being greater than the second trend fluctuation, and the overall harmonic diagram corresponding to the third harmonic showing a slight upward trend. During the thermal aging and degradation process, a harmonic diagram corresponding to the fifth harmonic of the reference harmonic current is determined. The harmonic diagram corresponding to the fifth harmonic shows a trend of first decreasing and then increasing with the increase of the equivalent "wedge" pore depth, and the trend is downward. During the thermal aging and degradation process, a harmonic diagram corresponding to the seventh harmonic of the reference harmonic current is determined. The harmonic diagram corresponding to the seventh harmonic shows a trend of first decreasing and then increasing with the increase of the equivalent "wedge" pore depth, and the trend is downward.

[0039] In one embodiment of the present invention, during the hydrothermal aging process, a harmonic diagram corresponding to the third harmonic of the reference harmonic current is determined; wherein, the harmonic diagram corresponding to the third harmonic shows a slight decreasing trend overall with the increase of the equivalent "wedge" pore depth and water content. During the hydrothermal aging process, a harmonic diagram corresponding to the fifth harmonic of the reference harmonic current is determined; wherein, the harmonic diagram corresponding to the fifth harmonic shows a trend of first decreasing and then increasing with the increase of the equivalent "wedge" pore depth and water content, and then shows a decreasing trend in the later stage. During the hydrothermal aging process, a harmonic diagram corresponding to the seventh harmonic of the reference harmonic current is determined; wherein, the harmonic diagram corresponding to the seventh harmonic shows a trend of first decreasing and then increasing with the increase of the equivalent "wedge" pore depth and water content.

[0040] Figure 2 This invention provides a first relationship diagram between magnetic flux density, porosity, and moisture content. Figure 3 This invention provides a second relationship diagram between magnetic flux density, porosity, and moisture content. Figure 2 and Figure 3 It can be seen that the magnetic flux density at the cable outer sheath is distorted with the increase of porosity and moisture content. The change in magnetic flux causes a change in current, generating harmonic currents. The simulation results verify that defects in the cable insulation layer affect the magnetic field distribution. Furthermore, COMSOL was used to simulate the cable insulation layer with porosity defects, and the variation law of induced current harmonics at the outer sheath with the number of pores and moisture content was extracted.

[0041] Figure 4 This is a schematic diagram of the harmonics corresponding to a thermally aged cable provided in an embodiment of the present invention. Figure 4 It can be seen that the content of the third harmonic of the induced current initially increases and then decreases with the increase of the equivalent "wedge" pore depth, with large fluctuations, and later also shows an initial increase followed by a decrease, but with smaller fluctuations. The third harmonic generally shows an upward trend during the thermal aging process, but the increase is small. The fifth and seventh harmonics both show an initial decrease followed by an increase in the early stage of thermal aging, and their contents gradually decrease in the later stage.

[0042] Figure 5 This is a schematic diagram of the harmonics corresponding to a water-heat aging cable provided in an embodiment of the present invention. Figure 5 It can be seen that the third harmonic of the induced current generally decreases with increasing equivalent "wedge" pore depth and water content during the hydrothermal aging process. The fifth harmonic initially decreases and then increases in the early stage of aging, gradually decreasing in the later stage. The seventh harmonic generally decreases and then increases during the hydrothermal aging process.

[0043] Furthermore, harmonic current testing was conducted to obtain the harmonic characteristics of the harmonic currents of distribution cables with different degrees of thermal aging under different voltages.

[0044] Furthermore, for normal cables with different thermal aging times, data were summarized and analyzed according to the order of testing during the aging process. Figure 6 This is a schematic diagram of the harmonics of a thermally aged cable over time, provided as an embodiment of the present invention. Figure 6 It can be observed that the amplitude of the 3rd harmonic gradually increases in an oscillating manner as the aging process deepens. The amplitude of the 5th harmonic first decreases and then increases with the deterioration state. The amplitude of the 7th harmonic generally shows a downward trend, but there are abnormal sudden increases in the middle process. Figure 7 This is a schematic diagram of the harmonics of a water-heat aging cable over time, provided as an embodiment of the present invention. Figure 7 It can be seen that for water-soaked and heat-aged cables, the overall trend of the 3rd, 5th, and 7th harmonics is the same as that of heat-aged cables, but their amplitudes are slightly increased, and the degree of amplitude oscillation is significantly higher than that of heat-aged cables. Therefore, the two can be distinguished quite well.

[0045] Figure 8 This invention provides a comparison chart of the harmonics of a thermally aged cable and a water-thermally aged cable, based on an embodiment of the invention. Figure 8It can be seen that the mean values ​​of the 3rd and 4th harmonics of the water-immersed heat-aged cable are significantly higher than those of the cable aged by heat alone. The mean values ​​of the 3rd, 4th, and 7th harmonics of the water-immersed heat-aged cable are also significantly higher than those of the cable aged by heat alone. However, the mean and variance of the 5th harmonic of the water-immersed heat-aged cable are slightly lower than those of the cable aged by heat alone. The variation of the 3rd harmonic shows some consistency with the simulation results, and the 3rd harmonic can be used to distinguish between the two states.

[0046] Step S102: Obtain the harmonic components corresponding to the cable under test, and determine whether the cable under test has defects based on the harmonic components and the reference harmonic current.

[0047] In one embodiment of the present invention, the distorted current waveform corresponding to the cable under test is obtained. The distorted current waveform is expanded using a fast Fourier transform to decompose it into harmonic components corresponding to the cable under test.

[0048] Specifically, after identifying the cable to be tested, measurements are taken to obtain the corresponding distorted current waveform. By expanding the current using a Fast Fourier Transform, the harmonic components under different cable stress aging defects can be decomposed.

[0049] In one embodiment of the present invention, harmonic diagrams corresponding to each harmonic of the cable under test are obtained. Each harmonic diagram is compared with multiple preset reference harmonic diagrams, wherein the reference harmonic diagrams are related to reference harmonic currents. The similarity between each harmonic diagram and the reference harmonic diagrams is determined. If the similarity is greater than a preset similarity threshold, it is determined that the cable under test has a defect.

[0050] Specifically, after obtaining the harmonic diagrams corresponding to each order of the cable under test, these diagrams are compared with multiple preset reference harmonic diagrams. The harmonic diagrams corresponding to each order of the cable under test are used to represent the harmonic content at a certain degree of aging. The similarity between these diagrams and the preset reference harmonic diagrams is calculated. If the similarity value is greater than a preset similarity threshold, it indicates that the cable under test has a defect, allowing for further determination of the type of defect.

[0051] Step S103: When the cable under test has defects, principal component analysis is performed on each harmonic component to obtain the dimensionality reduction data corresponding to each harmonic component.

[0052] In one embodiment of the present invention, principal component analysis (PCA) is employed. PCA uses a small number of variables to comprehensively reflect the main information of the original variables, and the final determined new variables are linear combinations of the original variables. First, dimensionality-reduced data obtained from PCA is used; that is, PCA is performed on each harmonic component to obtain dimensionality-reduced data corresponding to each harmonic component. Then, cluster analysis is used to classify the cable defect status.

[0053] Step S104: Based on the preset Gaussian mixture model and the dimensionality reduction data, determine the different defect probabilities corresponding to the cable under test, and determine the defect type corresponding to the cable under test based on the different defect probabilities.

[0054] In one embodiment of the present invention, based on a pre-set Naive Bayes model and a pre-set Gaussian mixture model, the probability values ​​of different defect categories corresponding to different pre-set sample points are determined. The center point values ​​are updated based on the probability values. Based on the updated values, the probability values ​​of different defect categories corresponding to different pre-set sample points are recalculated until the iteration is complete.

[0055] In one embodiment of the present invention, each data point in a preset sample set is treated as an independent event. A product function is constructed based on the product of the probability values ​​corresponding to all data points in the preset sample set. A logarithmic operation is performed on the product function to obtain a simplified probability value function corresponding to the preset sample set. Based on the simplified probability value function and the reduced-dimensional data, the different defect probabilities corresponding to the cable under test are obtained.

[0056] Specifically, this embodiment of the invention employs a Gaussian Mixture model, where probability is used to represent the likelihood of a given data point. Belongs to a certain class ( The probability of () can be calculated by the Gaussian distribution function, as shown in equation (1):

[0057] (1)

[0058] The mean of all data points in this class is Standard deviation is .

[0059] A two-dimensional data point, if its distance from the center point is... Then this point belongs to The probability of a class is given by equation (2):

[0060] (2)

[0061] Furthermore, in statistical computation, the Expectation-Maximization (EM) algorithm is an algorithm for finding the maximum likelihood estimate of parameters in a probabilistic model. The Expectation-Maximization algorithm performs calculations in two alternating steps: the first step is to calculate the expectation (E), using a Naive Bayes model and a Gaussian mixture model to obtain the probability that all sample data points belong to each class; the second step is to maximize (M), updating the value of the centroid based on the result obtained in the E step.

[0062] The center point value obtained in step M is used in the next step E, and this process continues alternately until the iteration is complete.

[0063] Furthermore, due to the sample set Each of them Each data point in the set represents an independent event, and the probability of this sample set occurring is the product of the probabilities of all points, i.e.:

[0064]

[0065] After performing a logarithmic operation on it, the probability of the sample set can be simplified to:

[0066]

[0067] For a sample set with K classes, the probability of forming each class is: ,have: Data points belong The probability of a class can be expressed as:

[0068]

[0069] Figure 9 This is a schematic diagram illustrating the clustering identification results of damp and aged cables provided in an embodiment of the present invention. Figure 9 It can be seen that cables with moisture defects and aging defects can be identified and distinguished.

[0070] like Figure 10 As shown, corresponding to the cable insulation layer defect type detection method described in Embodiment 1 of the present invention, Embodiment 2 of the present invention also provides a cable insulation layer defect type detection device, including: One or more processors; Memory; One or more applications, wherein the one or more applications are stored in the memory and configured to be executed by the one or more processors, the one or more applications being configured to perform the cable insulation defect type detection method according to Embodiment 1 of the present invention.

[0071] Corresponding to the cable insulation layer defect type detection method described in Embodiment 1 of the present invention, Embodiment 3 of the present invention provides a computer-readable storage medium, the computer-readable storage medium including a stored computer program; wherein, when the computer program is running, it controls the device where the computer-readable storage medium is located to execute the cable insulation layer defect type detection method as described in Embodiment 1 of the present invention.

[0072] Preferably, the computer program can be divided into one or more modules / units (such as computer program 1, computer program 2, ...), and the one or more modules / units are stored in the memory and executed by the processor to complete the present invention. The one or more modules / units can be a series of computer program instruction segments capable of performing specific functions, and the instruction segments are used to describe the execution process of the computer program in the device.

[0073] The processor can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor, or the processor can be any conventional processor. The processor is the control center of the device and connects the various parts of the device using various interfaces and lines.

[0074] The memory mainly includes a program storage area and a data storage area. The program storage area can store the operating system, applications required for at least one function, etc., while the data storage area can store related data, etc. Furthermore, the memory can be a high-speed random access memory, or a non-volatile memory, such as a plug-in hard drive, a SmartMedia Card (SMC), a Secure Digital (SD) card, and a Flash Card, or other volatile solid-state storage devices.

[0075] It should be noted that the above-mentioned devices may include, but are not limited to, processors and memory, as will be understood by those skilled in the art.

[0076] For the working principle and process of the above embodiments, please refer to the description of Embodiment 1 of the present invention, which will not be repeated here.

[0077] As explained above, compared with the prior art, the beneficial effects of this invention are as follows: In this embodiment, electromagnetic simulation is used to obtain the reference harmonic currents corresponding to pre-set sample cables under different cable insulation defect types, in order to determine whether the current cable under test has defects. By introducing principal component analysis, a few variables are used to comprehensively reflect the main information of the original variables, and the final determined new variables are linear combinations of the original variables. For the dimensionality-reduced data obtained by principal component analysis, cluster analysis is further used to classify the cable defect states, thereby quickly and accurately obtaining the cable defect type.

[0078] The above description is merely a preferred embodiment of the present invention and should not be construed as limiting the scope of the invention. Therefore, any 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 defect types in cable insulation, characterized in that, include: Obtain the reference harmonic currents corresponding to different cable insulation defect types for the pre-set sample cable; Obtain the harmonic components corresponding to each harmonic of the cable under test, and determine whether the cable under test has defects based on the harmonic components and the reference harmonic current. When the cable under test has defects, principal component analysis is performed on each harmonic component to obtain the dimensionality reduction data corresponding to each harmonic component. Based on the pre-set Naive Bayes model and the pre-set Gaussian mixture model, the probability values ​​of different defect categories corresponding to different pre-set sample points are determined. The center point value is updated based on the probability value; Based on the updated values, the probability values ​​of the different defect categories corresponding to the different preset sample points are recalculated until the iteration is completed; After the iteration is completed, each data point in the preset sample set is treated as an independent event, and a product function is constructed based on the product of the probability values ​​corresponding to all data points in the preset sample set. Perform a logarithmic operation on the product function to obtain the simplified probability value function corresponding to the preset sample set; Based on the simplified probability value function and the dimensionality reduction data, the different defect probabilities corresponding to the cable under test are obtained, and the defect type corresponding to the cable under test is determined based on the different defect probabilities.

2. The method according to claim 1, characterized in that, After obtaining the reference harmonic currents corresponding to different cable insulation defect types for the pre-set sample cable, the process further includes: During the thermal aging and deterioration process, the harmonic diagram corresponding to the third harmonic of the reference harmonic current is determined; wherein, as the equivalent wedge-shaped pore depth increases, the harmonic diagram corresponding to the third harmonic shows two trends of first increasing and then decreasing, and the fluctuation of the first trend is greater than the fluctuation of the second trend, and the harmonic diagram corresponding to the third harmonic shows an overall upward trend. During the thermal aging and deterioration process, the harmonic diagram corresponding to the 5th harmonic of the reference harmonic current was determined; wherein, the harmonic diagram corresponding to the 5th harmonic shows a trend of first decreasing and then increasing with the increase of the equivalent wedge-shaped pore depth, and the overall trend is downward. During the thermal aging and deterioration process, a harmonic diagram corresponding to the 7th harmonic of the reference harmonic current was determined; wherein, the harmonic diagram corresponding to the 7th harmonic shows a trend of first decreasing and then increasing with the increase of the equivalent wedge-shaped pore depth, and the overall trend is downward.

3. The method according to claim 1, characterized in that, After obtaining the reference harmonic currents corresponding to different cable insulation defect types for the pre-set sample cable, the process further includes: During the hydrothermal aging process, the harmonic diagram corresponding to the third harmonic of the reference harmonic current was determined; wherein, the harmonic diagram corresponding to the third harmonic shows an overall decreasing trend with the increase of equivalent wedge pore depth and water content; During the hydrothermal aging process, the harmonic diagram corresponding to the 5th harmonic of the reference harmonic current was determined; wherein, the harmonic diagram corresponding to the 5th harmonic shows a trend of first decreasing and then increasing with the increase of equivalent wedge pore depth and water content, and then showing a decreasing trend in the later stage. During the water-thermal aging process, the harmonic diagram corresponding to the 7th harmonic of the reference harmonic current was determined; wherein, the harmonic diagram corresponding to the 7th harmonic shows a trend of first decreasing and then increasing with the increase of the equivalent wedge pore depth and water content.

4. The method according to claim 1, characterized in that, The acquisition of the harmonic components corresponding to the cable under test specifically includes: Obtain the distorted current waveform corresponding to the cable under test; The distorted current wave is expanded using a fast Fourier transform to decompose it into the corresponding harmonic components of the cable under test.

5. The method according to claim 1, characterized in that, The determination of whether the cable under test has defects based on the harmonic components and the reference harmonic current specifically includes: Obtain the schematic diagram of each harmonic corresponding to the cable under test; The schematic diagrams of each harmonic are compared with multiple preset reference harmonic schematic diagrams; wherein, the reference harmonic schematic diagrams are related to the reference harmonic currents. Determine the similarity between the schematic diagrams of each harmonic and the reference harmonic schematic diagram; If the similarity is greater than a preset similarity threshold, the cable under test is determined to have a defect.

6. The method according to claim 1, characterized in that, The acquisition of reference harmonic currents corresponding to different cable insulation defect types for the pre-set sample cable specifically includes: A cross-linked polyethylene cable model was built using COMSOL finite element simulation software; wherein, the cross-linked polyethylene cable model is a cable joint interface model with a pre-set conductor cross-sectional area. By constructing wedge structures of different depths using the cross-linked polyethylene cable model, the porosity generated after cable aging is simulated to simulate different defect types corresponding to the cross-linked polyethylene cable model; wherein, the wedge structure in the normally aged cross-linked polyethylene cable model does not contain moisture, while the wedge structure in the moisture-aged cross-linked polyethylene cable model contains moisture. Obtain the magnetic flux density distribution corresponding to the cross-linked polyethylene cable model; When it is determined that magnetic flux distortion occurs in the defective part of the cross-linked polyethylene cable model, the reference harmonic currents corresponding to different defect types are determined based on the magnetic flux density distribution.

7. A cable insulation layer defect type detection device, characterized in that, include: One or more processors; Memory; One or more applications, wherein the one or more applications are stored in the memory and configured to be executed by the one or more processors, the one or more applications being configured to perform the cable insulation defect type detection method as described in any one of claims 1 to 6.

8. 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, it controls the device containing the computer-readable storage medium to perform the cable insulation defect type detection method as described in any one of claims 1 to 6.

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