Cable insulation layer defect classification identification method, device, equipment and medium
By obtaining the actual electric field strength of the cable insulation layer and establishing a simulation model, the defect attributes of the cable insulation layer are determined, which solves the problem of being unable to accurately determine the defects of the cable insulation layer in the existing technology, and achieves non-destructive and accurate defect classification and severity assessment. .
Patent Information
- Application Number
- CN202411410233.9
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-10-10
- Publication Date
- 2025-01-24
AI Technical Summary
The prior art cannot accurately judge the defect properties and degree of defects of the cable insulation layer, which may cause cable failure and even cause paralysis of the entire power system.
By obtaining the actual electric field strength of the cable insulation layer to be tested, a cable simulation model is established to simulate the field strength ranges of different defect attribute information, and the actual defect attribute information is determined based on the field strength range where the actual electric field strength is located.
It realizes the nondestructive determination of the defect properties of the cable insulation layer, avoids cable damage analysis, and reduces labor and time costs.
Smart Images
Figure CN119357771A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the field of cable technology, and in particular to a method, device, equipment and medium for classifying and identifying defects in cable insulation layers. Background Art
[0002] In modern power systems, cables are important carriers for electric energy transmission and distribution, and their safety and reliability are directly related to the stable operation of the entire power system.
[0003] The insulation performance of the cable body directly affects the safe operation of the power system. Therefore, its insulation defects and the breakdown accidents caused by the development of defects are the focus of cable body insulation research. Various defects in the cable insulation layer become the weakest link in the cable insulation, which may form local high field strength, or even the electric field strength exceeds the allowable range to produce local discharge, which may lead to insulation breakdown. Failures caused by defects will seriously affect the power supply reliability of the power system. However, due to poor craftsmanship, long-term operation, environmental factors, material aging and other reasons, the cable insulation layer may have various internal, external and composite defects, such as impurities, water branches, foreign body intrusion, etc. If these defects are not discovered and handled in time, they may cause cable failures and even paralyze the entire power system.
[0004] Traditional cable insulation fault detection methods mainly rely on regular maintenance and current over-limit detection, which cannot accurately locate, classify and evaluate the severity of defects. When facing cables laid in special environments, such as offshore wind power cables, the cost of defect repair is extremely high, so it is necessary to accurately judge the nature and severity of the defects to assist in decision-making. Summary of the invention
[0005] In view of the defects in the prior art, the present invention provides a cable insulation layer defect classification and identification method, device, equipment and medium to solve the current problem that it is impossible to accurately judge the nature and degree of defects in the cable insulation layer, which may cause cable failures and even paralysis of the entire power system.
[0006] In a first aspect, the present invention provides a method for classifying and identifying defects in a cable insulation layer, comprising: Obtain the actual electric field strength of the insulation layer of the cable to be tested; A cable simulation model is established according to the parameters of the cable to be tested, and field strength intervals of different defect attribute information are simulated based on the cable simulation model; the field strength intervals associated with different defect attribute information do not overlap; Actual defect attribute information is determined according to the field strength interval in which the actual electric field strength is located.
[0007] Optionally, the defect attribute information includes defect type and variable parameters, the defect type includes internal defects and external defects, the variable parameters of internal defects include defect diameter, defect material, defect location and defect shape; the variable parameters of external defects include defect location and defect formation cause.
[0008] Optionally, before establishing a cable simulation model according to the parameters of the cable to be tested and simulating field strength intervals of different defect attribute information based on the cable simulation model, the method further includes: A preliminary experiment is performed to determine the influence of electric field strength of different defect attribute information; the influence of electric field strength determines the order of determining the defect attribute information corresponding to the actual electric field strength.
[0009] Optionally, the method for determining the influence of electric field strength of different defect attribute information includes: Determine the maximum electric field strength associated with different defect attribute information one by one by using a control variable method; Based on the maximum electric field strength and the electric field strength when there is no defect, determining the maximum field strength deviation rate caused by the corresponding defect attribute information; The electric field strength influence degree is determined according to the maximum field strength deviation rate.
[0010] Optionally, establishing a cable simulation model according to the parameters of the cable to be tested, and simulating field strength intervals of different defect attribute information based on the cable simulation model includes: Establish a cable simulation model according to the parameters of the cable to be tested; Determine by simulation the maximum electric field strength associated with different defect attribute information; Based on the maximum electric field strength, field strength intervals for different defect attribute information are determined.
[0011] Optionally, determining actual defect attribute information according to the field strength interval in which the actual electric field strength is located includes: Matching the actual electric field strength to the field strength intervals associated with different defect attribute information according to the order of the electric field strength influence; According to the matched field strength interval, the defect attribute information corresponding to the actual electric field strength is determined.
[0012] Optionally, after determining the electric field strength influence degree according to the maximum field strength deviation rate, the method further includes: According to the different defect types, the variable parameters whose electric field strength influence satisfies the preset conditions are selected; the variable parameters that meet the preset conditions are the defect attribute information to be determined according to the actual electric field strength.
[0013] In a second aspect, the present invention provides a device for classifying and identifying defects in a cable insulation layer, comprising: An acquisition module is used to obtain the actual electric field strength of the insulation layer of the cable to be tested; A simulation module, used to establish a cable simulation model according to the parameters of the cable to be tested, and simulate field strength intervals of different defect attribute information based on the cable simulation model; the field strength intervals associated with different defect attribute information do not overlap; The matching module is used to determine the actual defect attribute information according to the field strength interval in which the actual electric field strength is located.
[0014] Optionally, in the matching module, the defect attribute information includes defect type and variable parameters, the defect type includes internal defects and external defects, the variable parameters of internal defects include defect diameter, defect material, defect location and defect shape; the variable parameters of external defects include defect location and defect formation cause.
[0015] Optionally, a pre-experimental module is also included, specifically for: Before establishing a cable simulation model according to the parameters of the cable to be tested and simulating field strength intervals of different defect attribute information based on the cable simulation model, A preliminary experiment is performed to determine the influence of electric field strength of different defect attribute information; the influence of electric field strength determines the order of determining the defect attribute information corresponding to the actual electric field strength.
[0016] Optionally, the pre-experiment module is further used to: Determining the influence of the electric field strength of different defect attribute information includes: Determine the maximum electric field strength associated with different defect attribute information one by one by using a control variable method; Based on the maximum electric field strength and the electric field strength when there is no defect, determining the maximum field strength deviation rate caused by the corresponding defect attribute information; The electric field strength influence degree is determined according to the maximum field strength deviation rate.
[0017] Optionally, the simulation module is further used to: Establish a cable simulation model according to the parameters of the cable to be tested; Determine by simulation the maximum electric field strength associated with different defect attribute information; Based on the maximum electric field strength, field strength intervals for different defect attribute information are determined.
[0018] Optionally, the matching module is further configured to: Matching the actual electric field strength to the field strength intervals associated with different defect attribute information according to the order of the electric field strength influence; According to the matched field strength interval, the defect attribute information corresponding to the actual electric field strength is determined.
[0019] Optionally, the pre-experiment module is further used to: According to the different defect types, the variable parameters whose electric field strength influence satisfies the preset conditions are selected; the variable parameters that meet the preset conditions are the defect attribute information to be determined according to the actual electric field strength.
[0020] In a third aspect, an embodiment of the present invention provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of any of the above methods when executing the computer program.
[0021] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium having computer program instructions stored thereon, which implement the steps of any of the above methods when executed by a processor.
[0022] By adopting the above technical solution, the present application has the following beneficial effects: The present invention provides a method for classifying and identifying defects in cable insulation layers, which can match the field strength interval of different defect attribute information obtained in advance by simulation of a cable simulation model according to the actual electric field strength collected, thereby non-destructively determining the defect attributes of the cable insulation layer, avoiding cable damage analysis, and reducing manpower and time costs. BRIEF DESCRIPTION OF THE DRAWINGS
[0023] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following is a brief introduction to the drawings required for the specific embodiments or the description of the prior art. In all the drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, the elements or parts are not necessarily drawn according to the actual scale.
[0024] Figure 1 A flow chart of a cable insulation layer defect classification and identification method provided by an embodiment of the present invention is shown; Figure 2 A schematic diagram of a cable model provided by an embodiment of the present invention is shown; Figure 3 A schematic diagram showing defect locations of internal defects provided by an embodiment of the present invention is shown; Figure 4 A schematic diagram showing defect locations of external defects provided by an embodiment of the present invention is shown; Figure 5 A schematic diagram showing the simulation results of the electric field strength of the internal defects provided by the embodiment of the present invention is shown; Figure 6 A schematic diagram showing the simulation results of the electric field strength of an external defect provided by an embodiment of the present invention is shown; Figure 7A schematic diagram of a cable insulation layer defect classification and identification device provided by an embodiment of the present invention is shown; Figure 8 A schematic diagram of an electronic device provided by an embodiment of the present invention is shown. DETAILED DESCRIPTION
[0025] The following embodiments of the technical solution of the present invention are described in detail in conjunction with the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, and are therefore only used as examples, and cannot be used to limit the protection scope of the present invention. It should be noted that, unless otherwise specified, the technical terms or scientific terms used in this application should have the common meanings understood by those skilled in the art to which the present invention belongs.
[0026] like Figure 1 As shown, this embodiment provides a cable insulation layer defect classification method, including: S101. Obtain the actual electric field strength of the insulation layer of the cable to be tested.
[0027] In this embodiment, an electric field strength tester model FMX-004 is used to measure the actual electric field strength of the insulation layer of the cable to be tested. The following is a specific description of a certain offshore 66kV wind power cable, and the measurement object is mainly the above-ground part of the offshore wind power cable.
[0028] S102. Establish a cable simulation model according to the parameters of the cable to be tested, and simulate field strength intervals of different defect attribute information based on the cable simulation model; the field strength intervals associated with different defect attribute information do not overlap.
[0029] S103. Determine actual defect attribute information according to the field strength range in which the actual electric field strength is located.
[0030] In one embodiment, the defect attribute information includes defect type and variable parameters. The defect type includes internal defects and external defects. The variable parameters of internal defects include defect diameter, defect material, defect location and defect shape; the variable parameters of external defects include defect location and defect formation cause.
[0031] In one embodiment, before step S102, the method further includes: Preliminary experiments are performed to determine the influence of electric field strength on different defect attribute information; the influence of electric field strength determines the order in which the defect attribute information corresponding to the actual electric field strength is determined.
[0032] In fact, different defect attribute information induces different maximum electric field strengths, and after changing the corresponding defect attribute information, the change trend of the electric field strength is also different. For example, if only the defect diameter is changed to make the defect material, defect position and defect shape consistent, or if only the defect material is changed to make the defect diameter, defect position and defect shape consistent, the changes in the maximum electric field strength caused by the two will be different. The defect attribute information that causes a greater change in the electric field strength obviously has a higher influence on the electric field strength.
[0033] Therefore, in this step, through preliminary experiments, before simulating the cable to be tested, the electric field strength influence of each defect attribute information is determined in advance, so that step S102 can give priority to processing the defect attribute information with higher electric field strength influence in the order of electric field strength influence, which can improve the efficiency of determining the field strength interval and quickly locate the field strength interval corresponding to the defect attribute information.
[0034] Furthermore, how to determine the influence of the electric field strength of different defect attribute information? In one embodiment, a method for determining the influence of the electric field strength of different defect attribute information is provided, including: S201. Determine the maximum electric field strength associated with different defect attribute information one by one through the control variable method.
[0035] Taking the four variable parameters of internal defects as an example, only a single variable parameter is changed, and the other variable parameters remain unchanged, specifically: When the defect material, defect position and defect shape are consistent, the maximum electric field intensity of different defect diameters is obtained; When the defect diameter, defect position and defect shape are consistent, the maximum electric field strength of different defect materials is obtained; When the defect diameter, defect material and defect shape are consistent, the maximum electric field intensity at different defect locations is obtained; When the defect diameter, defect position and defect material are consistent, the maximum electric field strength of different defect shapes is obtained.
[0036] In one embodiment, a cable model is provided, such as Figure 2As shown, the cable model from inside to outside is: copper conductor, inner semi-conductive layer, insulating layer, outer semi-conductive layer, and the diameters are: 16.5mm, 18.1mm, 36.1mm, 37.7mm. Based on the above cable model, the maximum electric field strength associated with different defect attribute information is determined one by one by the control variable method. Among them, the internal defects are specifically: the defect diameter is selected as 0.5 mm, 1 mm, 1.5 mm, the defect material is selected as low-resistance particles, rubber impurity defects, bubbles, the defect position is selected as the inner position, the middle position, and the outer position, and the defect shape is selected as diamond, circle, and square. The external defects are specifically: the defect position is selected as the outer, middle, and inner positions, and the causes of the defects are steel needle induced and water gap induced. The results obtained according to COMSOL simulation are as follows: Among the internal defects: The defect material is low-resistance particles, the defect position is the middle position, the defect shape is circular, and the maximum electric field strength induced by the defect with a defect diameter of 0.5 mm, 1 mm, and 1.5 mm is , and , stronger than the defect-free field , an increase of 36%, 40% and 44% respectively.
[0037] The defect position is in the middle, the defect shape is circular, the defect diameter is 1 mm, the defect material is low-resistance particles, rubber impurity defects, and bubble defects. The maximum electric field strengths are , and , an increase of 40%, 4% and 37% respectively compared with the defect-free case.
[0038] The defect material is low-resistance particles, the defect shape is circular, and the defect diameter is 1 mm. Figure 3 As shown in the figure, the maximum electric field strength induced by the defects at the inner, middle and outer positions are respectively , and , increased by 88%, 40%, and 15% respectively compared with the defect-free case; the maximum electric field strength induced by the internal contact and external contact defects are and , an increase of 89% and 3% respectively compared with the defect-free case.
[0039] The maximum electric field intensities induced by the defects with the defect position being the middle position, the defect material being low-resistance particles, the defect diameter being 1 mm, and the defect shapes being diamond, circle, and square are , , , an increase of 309%, 40% and 176% compared with the defect-free case.
[0040] According to the above simulation data, we can get Figure 5 Simulation results of the electric field strength for the internal defect shown.
[0041] Among the external defects, such as Figure 4 As shown in the figure, both the steel needle induction and the water gap induction enter the insulation layer from the outside of the sheath: The maximum electric field intensities induced by the insertion of the steel needle at the outer, middle, and inner positions are , and , an increase of 461%, 1060% and 2440% compared with the defect-free situation.
[0042] At the outer, middle and inner positions, the maximum electric field intensities induced by the depth of the water gap are , and , an increase of 439%, 1258% and 2824% compared with the defect-free situation.
[0043] At the outer, middle and inner positions, the maximum electric field intensities induced by the stagnant water gap are , and , an increase of 211%, 524% and 1093% compared with the defect-free situation.
[0044] According to the above simulation data, we can get Figure 6 The simulation results of the electric field strength of the external defect are shown. Figure 6 (a) is the simulation result of the electric field strength induced by the steel needle. Figure 6 (b) is the simulation result of the electric field strength induced by the water gap. Figure 6 (c) is the simulation result of the electric field strength induced by the stagnant water gap. The electric field strength induced by the external defects is significantly greater than the electric field strength induced by the internal defects of the insulating layer.
[0045] S202. Based on the maximum electric field strength and the electric field strength when there is no defect, determine the maximum field strength deviation rate caused by the corresponding defect attribute information.
[0046] S203. Determine the influence of the electric field strength according to the maximum field strength deviation rate.
[0047] Based on the maximum electric field strength of the obtained defect attribute information, the maximum field strength deviation rate compared to the defect-free state is determined, and the maximum field strength deviation rate is positively correlated with the electric field strength influence. The maximum strength deviation rate can determine a specific value based on the cable model provided above, that is, the growth rate of each defect attribute information compared to the defect-free state. Based on the maximum strength deviation rate, a ranking of the degree of influence on the electric field strength can be obtained, thereby determining the electric field strength influence. The electric field strength influence can directly correspond to the maximum strength deviation rate.
[0048] In one embodiment, step S102 includes: S301. Establish a cable simulation model according to the parameters of the cable to be tested.
[0049] S302. Determine the maximum electric field strength associated with different defect attribute information through simulation.
[0050] S303. Based on the maximum electric field strength, determine the field strength range of different defect attribute information.
[0051] For the cable to be tested, the finite element simulation software COMSOL is used to establish a cable simulation model, and various cable parameters are input to realize cable simulation under various defect conditions, and the electric field strength of various cable insulation layers is obtained. The finite element method (FEM) is based on the variational principle. By combining the finite difference method, the solution of the differential equation is transformed into an equivalent variational solution problem of the functional extreme value. The specific method is to use a finite number of units to divide the entire field to be solved, and use the approximate solution of the variational problem as the approximate solution of the boundary value problem of the original differential equation. The analysis steps of the finite element are as follows: (1) Model building: Convert the structure to be solved into a geometric model.
[0052] (2) Discretization: decompose the model into a finite number of units.
[0053] (3) Establishing mathematical model: Selecting appropriate mathematical model for each unit to describe the physical phenomenon.
[0054] (4) Establishing discrete equations: Assemble the mathematical models of each unit into the mathematical model of the entire structure. By applying appropriate boundary conditions and loading conditions, a complete set of discrete equations is obtained.
[0055] (5) Solving the system of equations: Solve the discrete system of equations and obtain numerical solutions.
[0056] (6) Post-processing: Post-process the numerical solution to analyze the rationality and accuracy of the results.
[0057] In one embodiment, a method for establishing a cable simulation model based on COMSOL specifically includes the following steps: First, in the simulation of electric field strength calculation, 66kV voltage is applied to the copper conductor and grounding is set at the outer edge. In COMSOL software, select the copper conductor to apply "terminal" and set its voltage to 66kV, and select "grounding" at the outer edge of the cable.
[0058] Then the mesh is divided. Specifically, two-dimensional triangular mesh is used for mesh division of each cable structure. The maximum mesh size is 0.05 mm. For thinner structures such as semi-conductive layers, local mesh encryption is used. The solution model is solved based on differential equations. The differential equations used in electrical research are Maxwell equations, and their differential form is: ; ; ; In the formula, is the magnetic field strength, in units of ; is the current density vector, in units of ; is the electric displacement vector, in units of ; is the magnetic induction intensity, the unit is ; is the electric field strength, in units of ; is the charge density, in units of After the electrical parameters of the material and the electrical simulation conditions are input, the electric field strength of the structure can be solved using the differential form of Maxwell's equations.
[0059] Finally, the electric field strength of the cable insulation layer is extracted. The calculated electric field strength of the cable insulation layer is visualized and data extracted using the post-processing function in the COMSOL software. The extracted electric field strength of the cable insulation layer includes the maximum electric field strength required in step S302, thereby determining the field strength interval corresponding to the defect attribute information.
[0060] At the same time, different drawing options can be selected according to needs, such as contour maps, vector maps, etc., to more intuitively display the distribution of electric field strength in the insulating layer, and further analyze and process the exported electric field strength data.
[0061] After obtaining the field strength intervals of different defect attribute information in step S102, the cause of the actual electric field strength, that is, the defect type of the cable insulation layer, can be determined based on the actual electric field strength collected in step S101.
[0062] In one embodiment, step S103 specifically includes: S401. Matching the actual electric field strength to the field strength intervals associated with different defect attribute information according to the order of electric field strength influence; S402. Determine defect attribute information corresponding to the actual electric field strength according to the matched field strength interval.
[0063] Specifically, a Python program can be used to use an if statement to determine which defect type it belongs to based on the numerical range of different electric field strengths. The program first inputs the electric field strength, and then uses the if statement to determine the defect type; the program confirms the properties of the insulation layer defect, and its characteristics include the location, type, size and material of the defect.
[0064] The cable insulation layer defect classification and identification method provided in this embodiment further includes: According to different defect types, variable parameters whose electric field strength influence satisfies preset conditions are selected; the variable parameters satisfying the preset conditions are defect attribute information to be determined according to the actual electric field strength.
[0065] In this step, when the influence of electric field strength does not meet the preset conditions, that is, the degree of change in electric field strength caused by the corresponding defect attribute information is very small, so there is no need to clarify the specific defect type in actual operation. Specifically, in internal defects, the defect material is low-resistance particles, the defect position is the middle position, the defect shape is circular, and the defect diameter is 0.5mm, 1mm, 1.5mm. The difference between the maximum electric field strength induced by the defect is very small, so the range of electric field strength caused by the variable parameter of defect diameter is limited. Therefore, the variable parameter of defect diameter can be filtered out, and this variable parameter can be omitted when determining the defect attribute information by the actual electric field strength, thereby improving the efficiency of classification.
[0066] In one embodiment, Figure 7 As shown, a device for classifying and identifying defects in cable insulation layers is provided, comprising: The acquisition module 501 is used to obtain the actual electric field strength of the insulation layer of the cable to be tested; The simulation module 502 is used to establish a cable simulation model according to the parameters of the cable to be tested, and simulate the field strength intervals of different defect attribute information based on the cable simulation model; the field strength intervals associated with different defect attribute information do not overlap; The matching module 503 is used to determine the actual defect attribute information according to the field strength interval in which the actual electric field strength is located.
[0067] The cable insulation layer defect classification and identification device 50 provided in the embodiment of the present application adopts the same inventive concept as the above-mentioned cable insulation layer defect classification and identification method, and can achieve the same beneficial effects, which will not be repeated here.
[0068] Optionally, in the matching module, the defect attribute information includes defect type and variable parameters, the defect type includes internal defects and external defects, the variable parameters of internal defects include defect diameter, defect material, defect location and defect shape; the variable parameters of external defects include defect location and defect formation cause.
[0069] Optionally, a pre-experimental module is also included, specifically for: Before establishing a cable simulation model according to the parameters of the cable to be tested and simulating field strength intervals of different defect attribute information based on the cable simulation model, A preliminary experiment is performed to determine the influence of electric field strength of different defect attribute information; the influence of electric field strength determines the order of determining the defect attribute information corresponding to the actual electric field strength.
[0070] Optionally, the pre-experiment module is further used to: Determining the influence of the electric field strength of different defect attribute information includes: Determine the maximum electric field strength associated with different defect attribute information one by one by using a control variable method; Based on the maximum electric field strength and the electric field strength when there is no defect, determining the maximum field strength deviation rate caused by the corresponding defect attribute information; The electric field strength influence degree is determined according to the maximum field strength deviation rate.
[0071] Optionally, the simulation module is further used to: Establish a cable simulation model according to the parameters of the cable to be tested; Determine by simulation the maximum electric field strength associated with different defect attribute information; Based on the maximum electric field strength, field strength intervals for different defect attribute information are determined.
[0072] Optionally, the matching module is further configured to: Matching the actual electric field strength to the field strength intervals associated with different defect attribute information according to the order of the electric field strength influence; According to the matched field strength interval, the defect attribute information corresponding to the actual electric field strength is determined.
[0073] Optionally, the pre-experiment module is further used to: According to the different defect types, the variable parameters whose electric field strength influence satisfies the preset conditions are selected; the variable parameters that meet the preset conditions are the defect attribute information to be determined according to the actual electric field strength.
[0074] Based on the same inventive concept as the above-mentioned cable insulation layer defect classification and identification method, the embodiment of the present application also provides an electronic device 60, such as Figure 8 As shown, the electronic device 60 may include a processor 601 and a memory 602 .
[0075] The processor 601 may be a general-purpose processor, and may implement or execute the methods, steps, and logic diagrams disclosed in the embodiments of the present invention. The general-purpose processor may be a microprocessor or any conventional processor, etc. The steps of the method disclosed in the embodiments of the present invention may be directly embodied as being executed by a hardware processor, or may be executed by a combination of hardware and software modules in the processor.
[0076] The memory 602 is a non-volatile computer-readable storage medium that can be used to store non-volatile software programs, non-volatile computer executable programs, and modules. The memory may include at least one type of storage medium. The memory 602 is any other medium that can be used to carry or store desired program codes in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto. The memory 602 in the embodiment of the present invention can also be a circuit or any other device that can implement a storage function, and is used to store program instructions and / or data.
[0077] An embodiment of the present invention provides a computer-readable storage medium for storing computer program instructions used for the above-mentioned electronic device, which includes a program for executing the above-mentioned cable insulation layer defect classification and identification method.
[0078] The above-mentioned computer storage media can be any available media or data storage devices that can be accessed by a computer, including but not limited to magnetic storage (such as floppy disks, hard disks, magnetic tapes, magneto-optical disks (MO), etc.), optical storage (such as CD, DVD, BD, HVD, etc.), and semiconductor storage (such as ROM, EPROM, EEPROM, non-volatile memory (NAND FLASH), solid-state drive (SSD)), etc.
[0079] The above embodiments are only used to introduce the technical solutions of the present application in detail, but the description of the above embodiments is only used to help understand the methods of the embodiments of the present invention and should not be understood as limiting the embodiments of the present invention. Any changes or substitutions that can be easily thought of by technicians in this technical field should be included in the protection scope of the embodiments of the present invention.
Claims
1. A method for classifying and identifying defects in cable insulation layers, characterized in that: include: Obtain the actual electric field strength of the insulation layer of the cable to be tested; Establishing a cable simulation model according to the parameters of the cable to be tested, and simulating field strength intervals of different defect attribute information based on the cable simulation model; The field strength intervals associated with different defect attribute information do not overlap; Actual defect attribute information is determined according to the field strength interval in which the actual electric field strength is located.
2. The method according to claim 1, characterized in that The defect attribute information includes defect type and variable parameters. The defect type includes internal defects and external defects. The variable parameters of internal defects include defect diameter, defect material, defect location and defect shape; the variable parameters of external defects include defect location and defect formation cause.
3. The method according to claim 2, characterized in that Before establishing a cable simulation model according to the parameters of the cable to be tested and simulating field strength intervals of different defect attribute information based on the cable simulation model, the method further includes: A preliminary experiment is performed to determine the influence of electric field strength of different defect attribute information; the influence of electric field strength determines the order of determining the defect attribute information corresponding to the actual electric field strength.
4. The method according to claim 3, characterized in that The method for determining the influence of electric field strength of different defect attribute information includes: Determine the maximum electric field strength associated with different defect attribute information one by one by using a control variable method; Based on the maximum electric field strength and the electric field strength when there is no defect, determining the maximum field strength deviation rate caused by the corresponding defect attribute information; The electric field strength influence degree is determined according to the maximum field strength deviation rate.
5. The method according to claim 3 or 4, characterized in that: The step of establishing a cable simulation model according to the parameters of the cable to be tested, and simulating field strength intervals of different defect attribute information based on the cable simulation model includes: Establish a cable simulation model according to the parameters of the cable to be tested; Determine by simulation the maximum electric field strength associated with different defect attribute information; Based on the maximum electric field strength, field strength intervals for different defect attribute information are determined.
6. The method according to claim 5, characterized in that The determining actual defect attribute information according to the field strength interval in which the actual electric field strength is located includes: Matching the actual electric field strength to the field strength intervals associated with different defect attribute information according to the order of the electric field strength influence; According to the matched field strength interval, the defect attribute information corresponding to the actual electric field strength is determined.
7. The method according to claim 6, characterized in that After determining the electric field strength influence according to the maximum field strength deviation rate, the method further includes: According to the different defect types, the variable parameters whose electric field strength influence satisfies the preset conditions are selected; the variable parameters that meet the preset conditions are the defect attribute information to be determined according to the actual electric field strength.
8. A device for classifying and identifying defects in cable insulation layers, characterized in that: include: An acquisition module is used to obtain the actual electric field strength of the insulation layer of the cable to be tested; A simulation module, used to establish a cable simulation model according to the parameters of the cable to be tested, and simulate field strength intervals of different defect attribute information based on the cable simulation model; The field strength intervals associated with different defect attribute information do not overlap; The matching module is used to determine the actual defect attribute information according to the field strength interval in which the actual electric field strength is located.
9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.
10. A computer-readable storage medium having computer program instructions stored thereon, characterized in that: When the computer program instructions are executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.