A cable degradation degree detection method, device and computer readable storage medium

Abstract

The application discloses a cable deterioration degree detection method, equipment and a computer readable storage medium, wherein the method comprises the following steps: acquiring the magnetic field distribution of a preset sample cable under different deterioration degrees, determining the reference harmonic current corresponding to the cable with deterioration based on the magnetic field distribution; acquiring each harmonic component corresponding to the cable to be detected, determining whether the cable to be detected has a deterioration condition based on each harmonic component and the reference harmonic current; when the cable to be detected has a deterioration condition, cross-validation and data fitting are performed on a preset Lasso regression objective function based on each harmonic component corresponding to the cable to be detected, and a harmonic screening variable is determined based on a Lasso regression cross-validation graph and a Lasso regression fitting coefficient trajectory graph; and a Lasso regression model is constructed based on the remaining harmonic variables after screening, so that the deterioration degree of the cable to be detected is determined by an output value. The application can reduce the labor and time cost of cable detection.

Description

Technical Field

[0001] This invention relates to the field of cable testing technology, specifically to a method, equipment, and computer-readable storage medium for detecting the degree of cable deterioration. 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 operational safety of urban power grids.

[0003] Currently, although there are relatively mature live detection technologies for traditional high-voltage cables, such as partial discharge and grounding current, there are significant differences between distribution network cables and high-voltage cables in terms of structural characteristics and grounding systems. Therefore, live detection technologies for high-voltage cables, such as high-frequency partial discharge and grounding current, are difficult to apply to the condition detection of distribution network cable lines.

[0004] Common existing methods for live-line testing of distribution network cables include high-frequency pulse partial discharge, ultrasonic partial discharge, and infrared thermal imaging. However, in practical applications, these methods all require multiple measurements of the distribution network cable's deterioration defects, resulting in high labor and time costs. 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 the degree of cable deterioration, so as to improve the efficiency of cable deterioration detection.

[0006] To solve the above-mentioned technical problems, the present invention provides a method for detecting the degree of cable degradation, comprising:

[0007] Step S101: Obtain the magnetic field distribution of the preset sample cable under different degrees of degradation, and determine the reference harmonic current corresponding to the degraded cable based on the magnetic field distribution.

[0008] Step S102: Obtain the harmonic components of the cable under test, and determine whether the cable under test is degraded based on the harmonic components and the reference harmonic current.

[0009] Step S103: When the cable under test is degraded, cross-validation and data fitting are performed on the preset Lasso regression objective function based on the harmonic components corresponding to the cable under test to obtain the Lasso regression cross-validation plot and the Lasso regression fitting coefficient trajectory plot. Based on the Lasso regression cross-validation plot and the Lasso regression fitting coefficient trajectory plot, the harmonic screening variables are determined.

[0010] Step S104: Construct a Lasso regression model based on the remaining harmonic variables after screening, and determine the degree of degradation of the cable under test according to the output value of the Lasso regression model.

[0011] Preferably, determining the harmonic screening variable based on the Lasso regression cross-validation plot and the Lasso regression fitting coefficient trajectory plot specifically includes:

[0012] Based on the Lasso regression cross-validation plot and the mean square error of the Lasso regression model, the regularization coefficient that meets the preset requirements is determined.

[0013] Based on the Lasso regression fitting coefficient trajectory plot, the change trajectory corresponding to the coefficients of different independent variables is determined.

[0014] The order in which each of the said change trajectories tends toward the 0 coordinate axis is determined, and the said change trajectories are sorted based on the order;

[0015] Based on the sorting, a preset number of change trajectories are selected, and the harmonics corresponding to the preset number of change trajectories are used as the harmonic selection variables.

[0016] Preferably, the step of constructing a Lasso regression model based on the remaining harmonic variables after screening, and determining the degree of degradation of the cable under test based on the output value of the Lasso regression model, specifically includes:

[0017] Based on the remaining harmonic variables after screening and the intercept term of the preset variables, a Lasso regression model is constructed.

[0018] The output value of the Lasso regression model is determined, and the output value is compared with a preset degradation degree data table to determine the degradation degree of the cable under test; wherein, the preset degradation degree data table includes multiple output values, and also includes the degradation degree corresponding to each of the multiple output values;

[0019] The output value is proportional to the degree of degradation.

[0020] Preferably, the step of acquiring the magnetic field distribution of the pre-set sample cable under different degrees of degradation, and determining the reference harmonic current corresponding to the degraded cable based on the magnetic field distribution, specifically includes:

[0021] A cross-linked polyethylene cable model was built using COMSOL finite element simulation software.

[0022] For the cross-linked polyethylene cable model, normal aging defects of the cable insulation layer and water tree defects of the cable are constructed; wherein, the porosity generated after cable aging is simulated by wedge structures of different depths, and the wedge structures in the damp cable contain moisture;

[0023] Defect adjustments are made to both the normal aging defects of the cable insulation layer and the water tree defects of the cable; wherein the defect adjustment includes at least one of the following: defect quantity adjustment, defect depth adjustment, and defect type adjustment;

[0024] Obtain the magnetic flux density distribution corresponding to the cross-linked polyethylene cable model, and determine the corresponding reference harmonic current based on the magnetic flux density distribution.

[0025] Preferably, obtaining the harmonic components corresponding to the cable under test specifically includes:

[0026] Obtain the distorted current waveform corresponding to the cable under test;

[0027] The distorted current wave is expanded using a fast Fourier transform to decompose it into the corresponding harmonic components of the cable under test.

[0028] Preferably, determining whether the cable under test has deteriorated based on the harmonic components and the reference harmonic current specifically includes:

[0029] Obtain the harmonic diagrams corresponding to each harmonic component;

[0030] The harmonic diagrams corresponding to each harmonic component are compared with the preset reference harmonic diagrams; wherein the preset reference harmonic diagrams are related to the reference harmonic current.

[0031] Determine the similarity between the harmonic diagram and the preset reference harmonic diagram;

[0032] If the similarity is greater than a preset similarity threshold, it is determined that the cable under test has deteriorated.

[0033] Preferably, before obtaining the magnetic field distribution of the pre-set sample cable under different degrees of degradation, the method further includes:

[0034] A pre-set series resonant voltage boosting device is used to apply pressure to a pre-set sample cable that has no defects; wherein, the pre-set series resonant voltage boosting device includes at least one or more of the following: a voltage regulator, a transformer, a voltage divider, a high current generator, and a current limiting resistor;

[0035] The pre-set sample cable without defects is heated by a pre-set temperature rise control system.

[0036] The harmonic content of the cable on the terminal branch corresponding to the pre-set sample cable without defects was detected multiple times using a pre-set power quality analyzer.

[0037] The average value of the data from multiple tests by the preset power quality analyzer is calculated to obtain the first cable harmonic data corresponding to the preset sample cable without defects.

[0038] Preferably, before obtaining the magnetic field distribution of the pre-set sample cable under different degrees of degradation, the method further includes:

[0039] The harmonic content of the cable on the terminal branch corresponding to the pre-sample cable immersed in water is detected multiple times using a pre-set power quality analyzer. The pre-sample cable immersed in water has a gap and is immersed in a sealed plastic cavity with a pre-set water pressure so that water is injected into the pre-sample cable through the gap by the water pressure.

[0040] The average value of the data from multiple tests by the preset power quality analyzer is calculated to obtain the second cable harmonic data corresponding to the preset sample cable immersed in water.

[0041] The present invention also provides a cable degradation detection device, comprising:

[0042] One or more processors;

[0043] Memory;

[0044] 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, and the one or more applications are configured to perform the cable degradation detection method.

[0045] 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 degradation detection method.

[0046] The present invention has the following beneficial effects: The embodiments of the present invention obtain the magnetic field distribution of pre-sample cables under different degrees of degradation through electromagnetic simulation, and determine the reference harmonic currents corresponding to the pre-sample cables under different degrees of degradation based on the magnetic field distribution, thereby obtaining the time harmonic current characteristics of the cables under different degradation states; the Lasso regression analysis method is used to provide degradation degree discrimination, and a regularization term is added to the data fitting by minimizing the sum of squared residuals to prevent overfitting, thus completing the detection of cable degradation degree with less data, which not only reduces the difficulty of data processing but also ensures the accuracy of the detection results. Attached Figure Description

[0047] 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.

[0048] Figure 1 This is a flowchart illustrating a method for detecting the degree of cable degradation according to an embodiment of the present invention.

[0049] Figure 2 This is a schematic diagram of the cable testing experimental platform in an embodiment of the present invention.

[0050] Figure 3 This is a Lasso regression cross-validation plot in an embodiment of the present invention.

[0051] Figure 4 This is a trajectory diagram of the Lasso regression fitting coefficients in an embodiment of the present invention.

[0052] Figure 5 This is a schematic diagram comparing the Lasso regression predicted value with the original predicted value in an embodiment of the present invention.

[0053] Figure 6 This is a schematic diagram of the structure of a cable degradation detection device according to Embodiment 2 of the present invention. Detailed Implementation

[0054] 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.

[0055] Please refer to Figure 1 As shown, Embodiment 1 of the present invention provides a method for detecting the degree of cable degradation, comprising:

[0056] Step S101: Obtain the magnetic field distribution of the preset sample cable under different degrees of degradation, and determine the reference harmonic current corresponding to the cable with degradation based on the magnetic field distribution.

[0057] Step S102: Obtain the harmonic components of the cable under test, and determine whether the cable under test is degraded based on the harmonic components and the reference harmonic current.

[0058] Step S103: When the cable under test is degraded, cross-validation and data fitting are performed on the preset Lasso regression objective function based on the harmonic components corresponding to the cable under test to obtain the Lasso regression cross-validation plot and the Lasso regression fitting coefficient trajectory plot. Based on the Lasso regression cross-validation plot and the Lasso regression fitting coefficient trajectory plot, the harmonic screening variables are determined.

[0059] Step S104: Construct a Lasso regression model based on the remaining harmonic variables after screening, and determine the degree of degradation of the cable under test according to the output value of the Lasso regression model.

[0060] As can be seen from the above steps, this embodiment of the invention obtains the magnetic field distribution of the pre-set sample cables under different degrees of degradation through electromagnetic simulation, and determines the reference harmonic currents corresponding to the pre-set sample cables under different degrees of degradation based on the magnetic field distribution, thereby obtaining the time harmonic current characteristics of the cables under different degradation states; the degradation degree is discriminated by using the Lasso regression analysis method, and a regularization term is added to the data fitting by minimizing the sum of squared residuals to prevent overfitting, thus completing the detection of cable degradation degree with less data, which not only reduces the difficulty of data processing, but also ensures the accuracy of the detection results.

[0061] In step S101, a pre-set sample cable without defects is pressurized using a pre-set series resonant voltage booster device; wherein the pre-set series resonant voltage booster device includes at least one or more of the following: a voltage regulator, a transformer, a voltage divider, a high-current generator, and a current-limiting resistor. A pre-set temperature rise control system is used to heat the pre-set sample cable without defects. A pre-set power quality analyzer is used to repeatedly detect the cable harmonic content on the terminal branch corresponding to the pre-set sample cable without defects. The average of the data from the multiple detections by the pre-set power quality analyzer is calculated to obtain the first cable harmonic data corresponding to the pre-set sample cable without defects.

[0062] Specifically, to study the overheating aging phenomenon of cables, this paper selected a 10kV cross-linked polyethylene (XLPE) insulated cable as the research object. The cable had never been used and had no defects. The cable cross-sectional area was 300mm², the insulation thickness was 5mm, the semi-conductive shielding layer thickness was 0.6mm, and the length was 15m. Using a series resonant voltage booster device and a temperature rise control system, excitation voltages ranging from 8.7kV to 21.75kV were applied to the defective cable in stages, while a 400A current was simultaneously applied. During the heating process, the temperature of the cable's metallic parts was controlled at 100℃. The harmonic content of the cable at the cable terminal branch was detected using a power quality analyzer, and the measurement data was averaged three times to obtain relatively accurate cable harmonic data, i.e., the first cable harmonic data corresponding to the pre-set sample cable without defects.

[0063] Figure 2 This is a schematic diagram of a cable testing experimental platform provided in an embodiment of the present invention, as shown below. Figure 2 As shown, the cable testing experimental platform includes a voltage boosting device, a high-current generating device, and a power quality analyzer. The voltage boosting device includes a voltage regulator, transformer, voltage divider, and current-limiting resistor, while the power quality analyzer includes a computer and a current transformer.

[0064] In one embodiment of the present invention, a preset power quality analyzer is used to repeatedly detect the harmonic content of the cable on the terminal branch corresponding to the preset sample cable immersed in water. The preset sample cable immersed in water has a gap, and is immersed in a sealed plastic cavity with a preset water pressure, so that water is injected into the preset sample cable through the gap by the water pressure. The average value of the data from the multiple detections by the preset power quality analyzer is calculated to obtain the second cable harmonic data corresponding to the preset sample cable immersed in water.

[0065] Specifically, the embodiments of the present invention also include a damping cable joint testing device, which immerses a completely dry cable joint with a pre-reserved gap into a sealed plastic cavity filled with a certain water pressure.

[0066] Specifically, moisture intrusion mainly relies on water pressure, continuously injecting into the cable insulation layer through gaps. A pre-installed power quality analyzer can be used to detect the harmonic content of the water-immersed cable, and the average of multiple measurements can be calculated to obtain the second harmonic data for the pre-sampled cable with water immersion.

[0067] In one embodiment of the present invention, a cross-linked polyethylene (XLPE) cable model is constructed using COMSOL finite element simulation software. For the XLPE cable model, normal aging defects in the cable insulation layer and water treeing defects are constructed; wherein, "wedge" structures of different depths are used to simulate the porosity generated after cable aging, and the "wedge" structures in damp cables contain moisture. Defect adjustments are performed on the normal aging defects in the cable insulation layer and the water treeing defects, respectively; wherein, defect adjustment includes at least one of defect quantity adjustment, defect depth adjustment, and defect type adjustment. The magnetic flux density distribution corresponding to the XLPE cable model is obtained, and the corresponding reference harmonic current is determined based on the magnetic flux density distribution.

[0068] Specifically, in this embodiment of the invention, the degree of cable degradation is related to the number of voids and the moisture content of the insulation layer of the pre-sampled cable. Power cable insulation, under stress (such as moisture, thermal stress, and electric fields), exhibits abnormal or degraded phenomena. When the cable is subjected to severe degradation factors, stress aging leads to nonlinearity in the cable insulation, causing distortion of the internal magnetic flux, which can be measured as a distorted current wave.

[0069] 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 high-order harmonics.

[0070] Specifically, in this embodiment of the invention, a cross-linked polyethylene cable model was constructed using COMSOL finite element simulation software. All two-dimensional modeling used a conductor cross-sectional area of ​​300 mm². 2 The cable joint cross-sectional model is shown. This location is relatively simple compared to the overall structure of the cable joint, and the interface between the cable insulation and the reinforcing insulation accounts for a large part of the cable joint, making it a defect issue that requires special attention.

[0071] Furthermore, we constructed a cable insulation layer under normal aging and a water tree cable defect, and compared and analyzed the changes in the magnetic field strength of the cable under different defects in the cable insulation layer.

[0072] 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 were calculated. The conductivity of un-moisturized cable joints and cable joints after one month of accelerated moisture absorption were measured using an electrometer. The dielectric constant of the materials required for the simulation was measured using the Novocontrol broadband dielectric spectroscopy system. The core current frequency was 50Hz, and the amplitude was 400A.

[0073] The simulation parameter tables are shown in Table 1 and Table 2. Table 1 shows the simulation parameter settings for normal aging cables, and Table 2 shows the simulation parameter settings for water tree cables.

[0074] Table 1

[0075] wire core 0.992 5.714e7[S / m] 100 Semiconducting layer 1.078491 1e-4[S / m] 50 XLPE 1.057041 2e-15[S / m] 2.5 SIR 1.04817 2e-14[S / m] 3.17 Air 1 1e-15[S / m] 1 Metal sheath 1.12 3.53e4 [S / m] 100

[0076] Table 2

[0077]

[0078]

[0079] In one embodiment of the invention, the dielectric material generates a stress density determined by the Helmholtz equation under the influence of an external electric field, thereby altering the physical structure of XLPE and creating micropores and gaps. If the cable is submerged in water, moisture migrates into the submicropores of the insulation material under the influence of the electric field, continuously developing and creating defects, ultimately making the material more sparse and increasing the amorphous region. Therefore, this embodiment of the invention mainly simulates two scenarios: thermal aging and water immersion thermal aging. Different depths of "wedge" structures are used to simulate the micropores generated after cable aging; half of the "wedge" structures in the damp cable contain moisture. The difference between water immersion thermal aging and normal thermal aging lies mainly in the presence of a large amount of moisture in the micropores, as well as the pore depth and number of pores.

[0080] Furthermore, the localized porosity caused by electrothermal aging generates 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 distortion is more pronounced on the inner side of the SIR layer. The magnetic flux density at the cable outer sheath also becomes distorted with increasing porosity and moisture content. This change in magnetic flux induces current changes, generating harmonic currents. Simulation results verify that defects in the cable insulation layer affect the magnetic field distribution. Further simulations using COMSOL were conducted on the cable insulation layer with porosity defects, extracting the variation of induced current harmonics at the outer sheath with the number of porosity points and moisture content.

[0081] Harmonic current testing was used to obtain the harmonic characteristics of distribution network cables with different degrees of thermal aging under different voltages. After insulation degradation, the cable current does not exhibit an ideal sine wave. The thermal aging process of the insulation causes distortion components in the harmonic current. These harmonic currents contain important information reflecting the thermal aging process.

[0082] Furthermore, this embodiment of the invention simulated the porosity and water tree defects in the XLPE insulation layer of the cable using COMSOL finite element software. The magnetic field strength distribution of the XLPE cable under different defect states was compared and analyzed, revealing the influence of aging-induced porosity depth and externally infiltrated moisture on the induced current. Induced currents from aging defects and water tree defects in the XLPE cable insulation layer were collected, and different current harmonics under different insulation defects were extracted. For example, this embodiment of the invention extracted the 2nd to 11th current harmonics under different insulation defects to construct reference harmonic currents corresponding to cables with different levels of degradation.

[0083] In step S102, the distortion current waveform corresponding to the cable under test is first obtained. The distortion current waveform is expanded by fast Fourier transform to decompose it into the harmonic components corresponding to the cable under test.

[0084] Specifically, after obtaining the time harmonic current characteristics of XLPE materials under different degradation states, the degree of degradation is determined by Lasso regression analysis.

[0085] Specifically, after identifying the cable to be tested, the corresponding distortion current waveform of the cable is measured. By expanding the current using a Fast Fourier Transform (FFT), the harmonic components corresponding to the cable under test can be obtained.

[0086] In one embodiment of the present invention, harmonic schematic diagrams corresponding to each harmonic component are obtained. These diagrams are then compared with a preset reference harmonic schematic diagram, which is related to a reference harmonic current. The similarity between the harmonic schematic diagrams and the preset reference harmonic schematic diagram is determined. If the similarity is greater than a preset similarity threshold, it is determined that the cable under test has deteriorated.

[0087] Specifically, the harmonic diagrams corresponding to each order of the cable under test are obtained, and these diagrams are compared with preset reference harmonic diagrams. In this embodiment of the invention, preset reference harmonic diagrams are provided in advance. Different preset reference harmonic diagrams can be used to demonstrate the harmonic content under different degrees of degradation.

[0088] Furthermore, the similarity between the schematic diagram of each harmonic of the current cable under test and the schematic diagram of the preset reference harmonic is determined. If the similarity is greater than the preset similarity threshold, it is determined that the current cable under test has deteriorated.

[0089] In step S103, based on the Lasso regression cross-validation plot and the mean square error of the Lasso regression model, the regularization coefficients that meet the preset requirements are determined. Based on the Lasso regression fitted coefficient trajectory plot, the change trajectories corresponding to the coefficients of different independent variables are determined. The order in which each change trajectory tends towards the 0 axis is determined, and the change trajectories are sorted based on this order. A preset number of change trajectories are selected based on the sorting, and the harmonics corresponding to each of the preset number of change trajectories are used as harmonic screening variables.

[0090] Specifically, the objective function of Lasso regression is:

[0091]

[0092] To minimize the objective function, the value of λ is first determined using cross-validation. Then, the variables selected for model selection are determined using the graph of λ and regression coefficients, including the standardized coefficient b. i Variables with a value of zero can be considered to be removed from the Lasso regression model. This leads to the final formula for the Lasso regression model.

[0093]

[0094] Taking a cable undergoing normal electrothermal aging as an example, Figure 3 This is a Lasso regression cross-validation plot provided in an embodiment of the present invention. The vertical axis represents the mean squared error of the model, and the horizontal axis represents λ. The optimization objective is to select the model with the fewest feature variables and the smallest error. In the plot, the dashed line represents the line with the lowest error on the left and the line with the fewest feature variables on the right.

[0095] Furthermore, when λ = 0.02, the minimum mean squared error of the model is obtained. Within a variance range of λ = 0.0045, the model has the fewest feature variables. After λ reaches a certain value, further increasing the number of independent variables does not significantly improve model performance.

[0096] For cables undergoing normal electrothermal aging, Figure 4 A trajectory plot of Lasso regression fitting coefficients provided in an embodiment of the present invention, such as... Figure 4 As shown, each curve in the graph represents the trajectory of the coefficient of each independent variable. The vertical axis represents the value of the coefficient, and the horizontal axis represents λ. As the value of λ changes, the variable whose coefficient is compressed to 0 later is more important. Figure 4It can be observed that the 4th and 6th harmonics first become zero, and therefore are removed. As the value of λ changes, the 5th harmonic is eventually compressed to 0, thus making it the most important dependent variable. The graph shows that the 5th harmonic plays a more significant role than the 3rd harmonic when used for aging assessment. Furthermore, the difference in the 5th harmonic is smaller for cables subjected to thermal aging and those subjected to water immersion. Therefore, the resulting assessment model exhibits better generalization ability.

[0097] In step S104, a Lasso regression model is constructed based on the remaining harmonic variables after screening and the intercept term of the preset variables. The output value of the Lasso regression model is determined, and the output value is compared with the preset degradation degree data table to determine the degradation degree of the cable under test. The preset degradation degree data table includes multiple output values ​​and the degradation degree corresponding to each output value. The output value is proportional to the degradation degree.

[0098] Figure 5 This diagram illustrates a comparison between Lasso regression predicted values ​​and original predicted values ​​provided in an embodiment of the invention. The Lasso regression results show that, based on the standardized coefficients of the variable intercept term and the 3rd, 4th, 5th, 6th, and 7th harmonics, the variable intercept term, 3rd, and 5th harmonics are retained, while the 4th, 6th, and 7th harmonics are deleted. The standardized formula of the model is: y = 10.679 + 1795.82 × 3rd harmonic + 5348.4 × 5th harmonic, which shows a good fit.

[0099] like Figure 6 As shown, corresponding to the cable degradation detection method described in Embodiment 1 of the present invention, Embodiment 2 of the present invention also provides a cable degradation detection device, comprising:

[0100] One or more processors;

[0101] Memory;

[0102] 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 degradation detection method according to Embodiment 1 of the present invention.

[0103] Corresponding to the cable degradation 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 degradation detection method as described in Embodiment 1 of the present invention.

[0104] 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 a specific function, and the instruction segments are used to describe the execution process of the computer program in the device.

[0105] 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.

[0106] 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.

[0107] 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.

[0108] 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.

[0109] As can be seen from the above description, compared with the prior art, the beneficial effects of the present invention are as follows: The embodiments of the present invention obtain the magnetic field distribution of the pre-set sample cables under different degrees of degradation through electromagnetic simulation, and determine the reference harmonic currents of the pre-set sample cables under different degrees of degradation based on the magnetic field distribution, thereby obtaining the time harmonic current characteristics of the cables under different degradation states; the Lasso regression analysis method is used to provide degradation degree discrimination, and a regularization term is added to the data fitting by minimizing the sum of squared residuals to prevent overfitting, thereby completing the detection of cable degradation degree with less data, which not only reduces the difficulty of data processing, but also ensures the accuracy of the detection results.

[0110] 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 the degree of cable deterioration, characterized in that, include: Step S101: Obtain the magnetic field distribution of the preset sample cable under different degrees of degradation, and determine the reference harmonic current corresponding to the cable with degradation based on the magnetic field distribution. Step S102: Obtain the harmonic components of the cable under test, and determine whether the cable under test is degraded based on the harmonic components and the reference harmonic current. Step S103: When the cable under test is degraded, cross-validation and data fitting are performed on the preset Lasso regression objective function based on the harmonic components corresponding to the cable under test to obtain the Lasso regression cross-validation plot and the Lasso regression fitting coefficient trajectory plot. Based on the Lasso regression cross-validation plot and the Lasso regression fitting coefficient trajectory plot, the harmonic screening variables are determined. Step S104: Construct a Lasso regression model based on the remaining harmonic variables after screening, and determine the degree of degradation of the cable under test according to the output value of the Lasso regression model.

2. The method according to claim 1, characterized in that, The determination of harmonic screening variables based on the Lasso regression cross-validation plot and the Lasso regression fitting coefficient trajectory plot specifically includes: Based on the Lasso regression cross-validation plot and the mean square error of the Lasso regression model, the regularization coefficient that meets the preset requirements is determined. Based on the Lasso regression fitting coefficient trajectory plot, the change trajectory corresponding to the coefficients of different independent variables is determined. The order in which each of the said change trajectories tends toward the 0 coordinate axis is determined, and the said change trajectories are sorted based on the order; Based on the sorting, a preset number of change trajectories are selected, and the harmonics corresponding to the preset number of change trajectories are used as the harmonic selection variables.

3. The method according to claim 1, characterized in that, The process of constructing a Lasso regression model based on the remaining harmonic variables after screening, and determining the degree of degradation of the cable under test based on the output value of the Lasso regression model, specifically includes: Based on the remaining harmonic variables after screening and the intercept term of the preset variables, a Lasso regression model is constructed. The output value of the Lasso regression model is determined, and the output value is compared with a preset degradation degree data table to determine the degradation degree of the cable under test; wherein, the preset degradation degree data table includes multiple output values, and also includes the degradation degree corresponding to each of the multiple output values; The output value is proportional to the degree of degradation.

4. The method according to claim 1, characterized in that, The process of acquiring the magnetic field distribution of a pre-set sample cable under different degrees of degradation, and determining the reference harmonic current corresponding to the degraded cable based on the magnetic field distribution, specifically includes: A cross-linked polyethylene cable model was built using COMSOL finite element simulation software. For the cross-linked polyethylene cable model, normal aging defects of the cable insulation layer and water tree defects of the cable are constructed; wherein, the porosity generated after cable aging is simulated by wedge structures of different depths, and the wedge structures in the damp cable contain moisture; Defect adjustments are made to both the normal aging defects of the cable insulation layer and the water tree defects of the cable; wherein the defect adjustment includes at least one of the following: defect quantity adjustment, defect depth adjustment, and defect type adjustment; Obtain the magnetic flux density distribution corresponding to the cross-linked polyethylene cable model, and determine the corresponding reference harmonic current based on the magnetic flux density distribution.

5. The method according to claim 1, characterized in that, The specific steps of obtaining the harmonic components corresponding to the cable under test include: 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.

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

7. The method according to claim 1, characterized in that, Before obtaining the magnetic field distribution of the pre-set sample cable under different degrees of degradation, the method further includes: A pre-set series resonant voltage boosting device is used to apply pressure to a pre-set sample cable that has no defects; wherein, the pre-set series resonant voltage boosting device includes at least one or more of the following: a voltage regulator, a transformer, a voltage divider, a high current generator, and a current limiting resistor; The pre-set sample cable without defects is heated by a pre-set temperature rise control system. The harmonic content of the cable on the terminal branch corresponding to the pre-set sample cable without defects was detected multiple times using a pre-set power quality analyzer. The average value of the data from multiple tests by the preset power quality analyzer is calculated to obtain the first cable harmonic data corresponding to the preset sample cable without defects.

8. The method according to claim 7, characterized in that, Before obtaining the magnetic field distribution of the pre-set sample cable under different degrees of degradation, the method further includes: The harmonic content of the cable on the terminal branch corresponding to the pre-sample cable immersed in water is detected multiple times using a pre-set power quality analyzer. The pre-sample cable immersed in water has a gap and is immersed in a sealed plastic cavity with a pre-set water pressure so that water is injected into the pre-sample cable through the gap by the water pressure. The average value of the data from multiple tests by the preset power quality analyzer is calculated to obtain the second cable harmonic data corresponding to the preset sample cable immersed in water.

9. A cable degradation 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 degradation detection method as described in any one of claims 1 to 8.

10. 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 degradation detection method as described in any one of claims 1 to 8.

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