Non-destructive evaluation method and system for cable microstructure based on alternating current impedance spectroscopy

Abstract

The present application belongs to the technical field of power equipment detection, and particularly relates to a cable microstructure nondestructive evaluation method and system based on alternating current impedance spectrum. The scheme realizes the transformation of the microdefects inside the cable conductor from qualitative analysis to quantitative evaluation. The scheme proposes a feature frequency point optimization strategy based on impedance change sensitivity coefficient, optimizes the traditional long full-band scanning into fast measurement of only several key frequency points, and significantly improves the field detection efficiency. At the same time, by constructing a three-stage equivalent circuit model including a volume resistance branch, a grain boundary parallel impedance branch and a defect parallel impedance branch, the circuit parameters obtained by inversion are mapped to two quantitative indexes of grain boundary degradation and microdefect concentration, and the direct quantitative characterization of grain boundary quality and defect density is realized. Finally, with the aid of weighted least squares inversion algorithm and temperature compensation technology, the accuracy of parameter extraction and the consistency of evaluation results are ensured.

Description

Technical Field

[0001] This invention belongs to the field of power equipment testing technology, specifically relating to a non-destructive evaluation method and system for cable microstructure based on AC impedance spectroscopy. Background Technology

[0002] As a key component of power transmission networks, the microstructure of the conductor material of power cables (grain size, grain boundary state, microcracks, and pores, etc.) directly affects the mechanical strength, conductivity, and long-term operational reliability of the cables.

[0003] Traditional cable testing methods (such as DC resistance testing, partial discharge detection, and infrared thermography) primarily focus on macroscopic electrical and thermal properties, failing to quantitatively assess microscopic defects within the conductor. While laboratory metallographic analysis and electron microscopy can observe microstructures, these methods require destructive sampling, making them impractical for field applications.

[0004] While AC impedance spectroscopy-based methods can reflect the microstructure of materials by measuring their impedance response at different frequencies, these methods still have the following problems: the measurement frequency range is too wide (usually requiring hundreds of frequency points), the measurement time is long, making them unsuitable for rapid on-site testing; there is a lack of characteristic frequency selection methods for the microstructure of cable conductors, resulting in large data redundancy; and the quantitative relationship between impedance spectroscopy data and micro-defects is unclear, making it impossible to output quantitative evaluation indicators. Summary of the Invention

[0005] This invention addresses the problems existing in the prior art by providing a non-destructive evaluation method and system for cable microstructure based on AC impedance spectroscopy, effectively solving the problems existing in the prior art.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows: Non-destructive evaluation methods for cable microstructure based on AC impedance spectroscopy include: An AC excitation signal is applied to the cable conductor at several predetermined characteristic frequency points, and the complex impedance value at each characteristic frequency point is measured. Based on the measured complex impedance data, the equivalent circuit parameters of the cable conductor microstructure are calculated by nonlinear fitting inversion. The equivalent circuit includes a bulk resistance branch reflecting the internal conductivity of the grain, a parallel impedance branch reflecting the grain boundary characteristics, and a parallel impedance branch reflecting the micro-defect characteristics. Based on the equivalent circuit parameters obtained from the inversion calculation, the grain boundary degradation degree, which reflects the degree of grain boundary degradation, and the micro-defect concentration, which reflects the severity of micro-defects, are calculated through a pre-constructed mapping relationship. The calculated grain boundary degradation degree and micro-defect concentration are compared with the preset level thresholds, and the comprehensive evaluation level of the cable conductor microstructure state is determined based on the comparison results.

[0007] Furthermore, the determination of the characteristic frequency points specifically involves: A full-band impedance scan is performed at N frequency points within a predetermined frequency range to obtain preliminary impedance spectrum data. Calculate the impedance change sensitivity coefficient at each scanning frequency point, where the impedance change sensitivity coefficient is the ratio of the absolute value of the impedance change rate with respect to frequency to the impedance modulus value. Select the frequency points where the impedance change sensitivity coefficient is a local maximum as candidate feature frequency points; From the candidate feature frequency points, M feature frequency points were finally selected based on the principle of uniform distribution across low, mid, and high frequency bands. <N。

[0008] Furthermore, the impedance change sensitivity coefficient is specifically expressed as follows: in, The complex impedance measured at frequency f is... This is the derivative of impedance with respect to frequency.

[0009] Furthermore, the calculation of the grain boundary degradation degree, reflecting the degree of grain boundary degradation, and the micro-defect concentration, reflecting the severity of micro-defects, through a pre-constructed mapping relationship, specifically involves: Based on the grain boundary resistance and grain boundary capacitance parameters obtained by inversion, the grain boundary degradation degree is obtained by calculating the ratio of their product to the reference value. Based on the volume resistance and defect capacitance parameters obtained from the inversion, the micro-defect concentration is obtained by weighted linear combination of the reciprocal value of the volume resistance and the defect capacitance value.

[0010] Furthermore, the grain boundary degradation degree and micro-defect concentration are specifically expressed as follows: Grain boundary degradation: Microscopic defect concentration: in, Grain boundary resistance, Grain boundary capacitance, This is a reference value for grain boundary resistance. This is a reference value for grain boundary capacitance. This refers to the volume resistance within the grain. This is a reference value for the volume resistivity inside the grain. For defect-related capacitance, This is a reference value for defect-related capacitance. and These are the weighting coefficients.

[0011] Furthermore, the equivalent circuit parameters of the cable conductor microstructure are calculated by nonlinear fitting inversion, specifically as follows: based on the measured complex impedance data, a weighted least squares method is used for nonlinear fitting. In the fitting process, the objective function simultaneously considers the impedance modulus error and the phase error, and the measurement errors at different frequency points are normalized and weighted according to the standard deviation. Only the selected characteristic frequency point data is used for fitting calculation.

[0012] Furthermore, the objective function is specifically expressed as follows: in, and The frequencies calculated based on the equivalent circuit model are respectively Impedance modulus and phase at the point, and The measured frequencies are respectively Impedance modulus and phase at the point, and , respectively, represent the standard deviations of the impedance modulus and phase measurements, and M is the number of characteristic frequency points.

[0013] Furthermore, the method also includes temperature measurement and compensation, specifically: The actual temperature of the cable conductor is measured simultaneously during impedance measurement; Temperature compensation is applied to the measured impedance values ​​to uniformly correct the impedance values ​​measured at different temperatures to the equivalent impedance values ​​at the reference temperature.

[0014] Furthermore, the comprehensive evaluation level is set to four levels, specifically: The grain boundary degradation degree is less than the first threshold and the micro-defect concentration is less than the second threshold, and the evaluation level is excellent. The grain boundary degradation degree is between the first and third thresholds and the micro-defect concentration is between the second and fourth thresholds, and the evaluation level is good. The grain boundary degradation degree is between the third and fifth thresholds and the micro-defect concentration is between the fourth and sixth thresholds, and the evaluation level is "Caution". If the grain boundary degradation is greater than or equal to the fifth threshold or the micro-defect concentration is greater than or equal to the sixth threshold, the assessment level is severe.

[0015] A non-destructive evaluation system for cable microstructure based on AC impedance spectroscopy includes: The characteristic frequency point impedance measurement unit is used to apply AC excitation signals to the cable conductor at several predetermined characteristic frequency points and measure the complex impedance value at each characteristic frequency point. The parameter inversion unit is used to calculate the equivalent circuit parameters of the cable conductor microstructure by nonlinear fitting based on the measured complex impedance data. The equivalent circuit includes a bulk resistance branch reflecting the internal conductivity of the grain, a parallel impedance branch reflecting the grain boundary characteristics, and a parallel impedance branch reflecting the micro-defect characteristics. The quantitative evaluation index calculation unit is used to calculate the grain boundary degradation degree, which reflects the degree of grain boundary degradation, and the micro-defect concentration, which reflects the severity of micro-defects, based on the equivalent circuit parameters obtained by inversion calculation and through a pre-constructed mapping relationship. The comprehensive condition level assessment unit is used to compare the calculated grain boundary deterioration degree and micro defect concentration with the preset level threshold, and determine the comprehensive assessment level of the microstructure state of the cable conductor based on the comparison results.

[0016] Compared with the prior art, the advantages and positive effects of the present invention are as follows: The present invention provides a non-destructive evaluation method and system for cable microstructure based on AC impedance spectroscopy. This method transforms the assessment of microscopic defects within cable conductors from qualitative analysis to quantitative evaluation. It proposes a characteristic frequency point optimization strategy based on impedance change sensitivity coefficients, optimizing the traditional lengthy full-band scanning into rapid measurement requiring only a few key frequency points, significantly improving on-site inspection efficiency. Simultaneously, by constructing a three-level equivalent circuit model including bulk resistance branches, grain boundary parallel impedance branches, and defect parallel impedance branches, the inverted circuit parameters are mapped to two quantitative indicators: grain boundary degradation degree and microscopic defect concentration, achieving direct quantitative characterization of grain boundary quality and defect density. Finally, the weighted least squares inversion algorithm and temperature compensation technology ensure the accuracy of parameter extraction and the consistency of evaluation results.

[0017] The solution described in this invention introduces a weighted least squares inversion algorithm and simultaneously implements temperature compensation, ensuring the accuracy of parameter extraction and the consistency of evaluation results under different environmental conditions. Furthermore, the solution outputs not abstract spectra or complex parameters, but a comprehensive evaluation result combining quantitative indicators and preset thresholds, encompassing four levels of conclusions: "Excellent," "Good," "Caution," and "Severe." This provides on-site maintenance personnel with a clear, intuitive, and actionable basis for decision-making, transforming cable condition-based maintenance and lifespan management from relying on experience-based judgment to scientific decision-making based on objective quantitative data. Attached Figure Description

[0018] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below: Figure 1 This is a flowchart of the non-destructive evaluation method for cable microstructure based on AC impedance spectroscopy as described in this embodiment of the invention. Figure 2 This is a flowchart of the method for determining characteristic frequency points as described in this embodiment of the invention; Figure 3 This is a schematic diagram of the non-destructive evaluation structure of cable microstructure based on AC impedance spectrum as described in an embodiment of the present invention. Figure 4 This is a schematic diagram of an electronic device structure according to an embodiment of the present invention. Detailed Implementation

[0019] To better understand the above-mentioned objectives, features and advantages of the present invention, the present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0020] Numerous specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways than those described herein, and therefore the invention is not limited to the specific embodiments disclosed in the following specification.

[0021] Example 1 The non-destructive evaluation method for cable microstructure based on AC impedance spectrum in Example 1 will be described in detail below with reference to the accompanying drawings.

[0022] In one or more embodiments, such as Figure 1 As shown, the non-destructive evaluation method for cable microstructure based on AC impedance spectroscopy includes: An AC excitation signal is applied to the cable conductor at several predetermined characteristic frequency points, and the complex impedance value at each characteristic frequency point is measured. Based on the measured complex impedance data, the equivalent circuit parameters of the cable conductor microstructure are calculated by nonlinear fitting inversion. The equivalent circuit includes a bulk resistance branch reflecting the internal conductivity of the grain, a parallel impedance branch reflecting the grain boundary characteristics, and a parallel impedance branch reflecting the micro-defect characteristics. Based on the equivalent circuit parameters obtained from the inversion calculation, the grain boundary degradation degree, which reflects the degree of grain boundary degradation, and the micro-defect concentration, which reflects the severity of micro-defects, are calculated through a pre-constructed mapping relationship. The calculated grain boundary degradation degree and micro-defect concentration are compared with the preset level thresholds, and the comprehensive evaluation level of the cable conductor microstructure state is determined based on the comparison results.

[0023] In one or more embodiments, such as Figure 2As shown, the determination of the characteristic frequency point is specifically as follows: A full-band impedance scan is performed at N frequency points within a predetermined frequency range to obtain preliminary impedance spectrum data. Calculate the impedance change sensitivity coefficient at each scanning frequency point, where the impedance change sensitivity coefficient is the ratio of the absolute value of the impedance change rate with respect to frequency to the impedance modulus value. Select the frequency points where the impedance change sensitivity coefficient is a local maximum as candidate feature frequency points; From the candidate feature frequency points, M feature frequency points were finally selected based on the principle of uniform distribution across low, mid, and high frequency bands. <N。

[0024] In specific implementation, the step of applying AC excitation signals to the cable conductor at several predetermined characteristic frequency points and measuring the complex impedance value at each characteristic frequency point specifically involves using an impedance analyzer to apply AC excitation signals to the cable conductor and performing impedance measurements at the selected characteristic frequency points; the specific processing steps are as follows: Research has revealed that the microstructure of cable conductors exhibits characteristic responses to AC signals of different frequencies: Low frequency band (1-100 Hz): mainly reflects grain boundary resistance and grain boundary capacitance, and is sensitive to the integrity of the inter-grain interface; Mid-frequency band (100 Hz-10 kHz): reflects defects and pores inside the grain; High frequency band (10-100 kHz): reflects surface condition and micro-cracks; (1) Selection of characteristic frequencies: Let the total frequency scanning range be arrive First, a coarse scan is performed across the entire frequency band (N frequency points, N... ), to obtain the preliminary impedance spectrum ; Calculate the impedance change sensitivity coefficient at each frequency point. Specifically, it is expressed as follows: in, For frequency f The complex impedance measured at [location] This is the derivative of impedance with respect to frequency.

[0025] It should be noted here that traditional solutions typically adopt... As a sensitivity indicator, the scheme described in this embodiment introduces the idea of ​​normalization processing, by dividing by... This eliminates the influence of impedance base differences at different frequency points, making It becomes a dimensionless, relatively sensitive indicator, making it more suitable for comparing different cable specifications.

[0026] choose The local maxima are used as candidate feature frequencies, and the candidate point set is denoted as: (2) Optimization selection criteria: 1) Frequency distribution uniformity: Ensure that representative points exist in the low-frequency, mid-frequency, and high-frequency bands; 2) Sensitivity threshold: ,in, This is an empirical threshold; 3) Minimize correlation: Minimize the impedance correlation between the selected frequency points.

[0027] Based on the above selection criteria, 3 to 5 feature frequency points were ultimately selected: .

[0028] In one or more embodiments, the method further includes temperature measurement and compensation, specifically: The actual temperature of the cable conductor is measured simultaneously during impedance measurement; Temperature compensation is applied to the measured impedance values ​​to uniformly correct the impedance values ​​measured at different temperatures to the equivalent impedance values ​​at the reference temperature.

[0029] In one or more embodiments, the calculation of equivalent circuit parameters of the cable conductor microstructure through nonlinear fitting inversion specifically involves: based on the measured complex impedance data, performing nonlinear fitting using the weighted least squares method. During the fitting process, the objective function simultaneously considers impedance modulus error and phase error, and performs standard deviation normalization weighting on the measurement errors at different frequency points. Only selected characteristic frequency point data is used for fitting calculations, specifically including the following processing steps: (1) Classification of microstructure: Microscopic defects in cable conductors mainly fall into three categories: 1) Grain boundary defects: oxidation, impurities, and microcracks at grain boundaries; 2) Intracrystalline defects: voids and impurity atoms inside the grain; 3) Dislocation network: Dislocation lines generated by plastic deformation; (2) Microstructure modeling to obtain the mathematical expression of the equivalent circuit: Total impedance Specifically, it is expressed as follows: in, The bulk resistance inside the grain ( (This is used to reflect the integrity and purity of the grains.) Grain boundary resistance ( It is used to reflect the quality and continuity of grain boundaries. Grain boundary capacitance (F) is used to reflect the charge accumulation capacity at grain boundaries. Defect-related resistance ( This comprehensively reflects the obstruction of electric current by microscopic defects. This is the defect-related capacitance (F), which reflects the polarization effect at the defect location. The frequency is the alternating frequency (Hz). It is the imaginary unit.

[0030] It should be noted here that the mathematical representation of the equivalent circuit in the scheme described in this embodiment explicitly includes... Corresponding to the interior of the grain, and Corresponding to grain boundaries, and To address the defects, a three-level physical structure correspondence was achieved, ensuring that each parameter has a clear microstructural correspondence.

[0031] (3) Parameter physical meaning mapping relationship: Establish a quantitative relationship between equivalent circuit parameters and physical defects: Grain boundary quality index : in, and These are the ideal reference values ​​for grain boundary resistance and grain boundary capacitance, respectively. The scheme described in this embodiment uses a product rather than a ratio (not a simple ratio). or The above design can effectively reflect the relaxation time constant of the grain boundary (its change can better characterize the quality of the grain boundary).

[0032] Microscopic defect density: in, and The calibration coefficients are material-related. The scheme described in this embodiment characterizes micro-defects by linearly combining resistance and capacitance effects. Through the design of adjustable parameters, it can be adjusted according to the material type, and has good adaptability.

[0033] (4) Nonlinear least squares fitting Impedance data at characteristic frequency points were obtained by measurement: ; The objective function is defined as follows: in, and The frequencies calculated based on the equivalent circuit model are respectively Impedance modulus and phase at the point, and The measured frequencies are respectively Impedance modulus and phase at the point, and , respectively, represent the standard deviations of the impedance modulus and phase measurements, and M is the number of characteristic frequency points.

[0034] It should be noted that the objective function in the scheme described in this embodiment considers both impedance modulus and phase error, and also measures the standard deviation. and First, the measurement accuracy differences at different frequency points are taken into account. Second, the scheme described in this embodiment only performs calculations on the selected M characteristic frequency points instead of the entire frequency band, which effectively improves the fitting efficiency.

[0035] In one or more embodiments, the calculation of the grain boundary degradation degree, reflecting the degree of grain boundary degradation, and the micro-defect concentration, reflecting the severity of micro-defects, through a pre-constructed mapping relationship specifically includes: Based on the grain boundary resistance and grain boundary capacitance parameters obtained by inversion, the grain boundary degradation degree is obtained by calculating the ratio of their product to the reference value. Based on the volume resistance and defect capacitance parameters obtained from the inversion, the micro-defect concentration is obtained by weighted linear combination of the reciprocal value of the volume resistance and the defect capacitance value.

[0036] Specifically, the grain boundary degradation degree and micro-defect concentration are expressed as follows: Grain boundary degradation: Microscopic defect concentration: in, Grain boundary resistance, Grain boundary capacitance, This is a reference value for grain boundary resistance. This is a reference value for grain boundary capacitance. This refers to the volume resistance within the grain. This is a reference value for the volume resistivity inside the grain. For defect-related capacitance, This is a reference value for defect-related capacitance. and These are the weighting coefficients.

[0037] In one or more embodiments, the comprehensive evaluation level is set to four levels, specifically: The grain boundary degradation degree is less than the first threshold and the micro-defect concentration is less than the second threshold, and the evaluation level is excellent. The grain boundary degradation degree is between the first and third thresholds and the micro-defect concentration is between the second and fourth thresholds, and the evaluation level is good. The grain boundary degradation degree is between the third and fifth thresholds and the micro-defect concentration is between the fourth and sixth thresholds, and the evaluation level is "Caution". If the grain boundary degradation is greater than or equal to the fifth threshold or the micro-defect concentration is greater than or equal to the sixth threshold, the assessment level is severe.

[0038] In one or more embodiments, the first threshold, the second threshold, the third threshold, the fourth threshold, the fifth threshold, and the sixth threshold are set to 0.1, 0.2, 0.3, 0.4, 0.6, and 0.7, respectively.

[0039] Understandably, the above thresholds are not final limits and can be set according to actual needs.

[0040] In one or more embodiments, taking a 110kV copper core cable as an example, its conductor cross-sectional area is 400mm². 2 It has been running for 15 years; Based on the measurement results of the above method in this embodiment: Characteristic frequency points: 10Hz, 100Hz, 1kHz, 10kHz; Impedance data: Z(10Hz)=15.2mΩ∠-5.2°, Z(100Hz)=14.8mΩ∠-8.6°, Z(1kHz)=14.1mΩ∠-15.3°, Z(10kHz)=13.6mΩ∠-22.7°; Temperature: 45℃ (compensated to 20℃ reference temperature); The equivalent circuit parameters obtained by inversion: ; ; ; ; ; Quantitative evaluation indicators: , ; The overall status assessment result is: Note.

[0041] Example 2 In one or more embodiments, corresponding to the above method embodiments, such as Figure 3As shown, this embodiment provides a non-destructive evaluation system for cable microstructure based on AC impedance spectroscopy, including: The characteristic frequency point impedance measurement unit is used to apply AC excitation signals to the cable conductor at several predetermined characteristic frequency points and measure the complex impedance value at each characteristic frequency point. The parameter inversion unit is used to calculate the equivalent circuit parameters of the cable conductor microstructure by nonlinear fitting based on the measured complex impedance data. The equivalent circuit includes a bulk resistance branch reflecting the internal conductivity of the grain, a parallel impedance branch reflecting the grain boundary characteristics, and a parallel impedance branch reflecting the micro-defect characteristics. The quantitative evaluation index calculation unit is used to calculate the grain boundary degradation degree, which reflects the degree of grain boundary degradation, and the micro-defect concentration, which reflects the severity of micro-defects, based on the equivalent circuit parameters obtained by inversion calculation and through a pre-constructed mapping relationship. The comprehensive condition level assessment unit is used to compare the calculated grain boundary deterioration degree and micro defect concentration with the preset level threshold, and determine the comprehensive assessment level of the microstructure state of the cable conductor based on the comparison results.

[0042] It is understood that the system described in this embodiment corresponds one-to-one with the method described in Embodiment 1, and its technical details have been described in detail in Embodiment 1, so they will not be repeated here.

[0043] In further embodiments, the following is also provided: like Figure 4 As shown, an electronic device includes a memory and a processor, as well as computer instructions stored in the memory and running on the processor. When executed by the processor, the computer instructions perform the methods described in the above embodiments. For brevity, further details are omitted here.

[0044] It should be understood that in this embodiment, the processor can be a central processing unit (CPU), or it can be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), 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 any conventional processor, etc.

[0045] Memory may include read-only memory and random access memory, and provides instructions and data to the processor. A portion of memory may also include non-volatile random access memory. For example, memory may also store information about the device type.

[0046] A computer-readable storage medium for storing computer instructions, which, when executed by a processor, perform the methods described in the above embodiments.

[0047] The methods described in the above embodiments can be directly executed by a hardware processor, or executed by a combination of hardware and software modules within the processor. The software modules can reside in readily available storage media in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, or registers. This storage medium is located in memory, and the processor reads information from the memory and, in conjunction with its hardware, completes the steps of the above method. To avoid repetition, detailed descriptions are omitted here.

[0048] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments that can be applied to other fields. However, any simple modifications or equivalent changes made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A non-destructive evaluation method for cable microstructure based on AC impedance spectroscopy, characterized in that, include: An AC excitation signal is applied to the cable conductor at several predetermined characteristic frequency points, and the complex impedance value at each characteristic frequency point is measured. Based on the measured complex impedance data, the equivalent circuit parameters of the cable conductor microstructure are calculated by nonlinear fitting inversion. The equivalent circuit includes a bulk resistance branch reflecting the internal conductivity of the grain, a parallel impedance branch reflecting the grain boundary characteristics, and a parallel impedance branch reflecting the micro-defect characteristics. Based on the equivalent circuit parameters obtained from the inversion calculation, the grain boundary degradation degree, which reflects the degree of grain boundary degradation, and the micro-defect concentration, which reflects the severity of micro-defects, are calculated through a pre-constructed mapping relationship. The calculated grain boundary degradation degree and micro-defect concentration are compared with the preset level thresholds, and the comprehensive evaluation level of the cable conductor microstructure state is determined based on the comparison results.

2. The non-destructive evaluation method for cable microstructure based on AC impedance spectroscopy as described in claim 1, characterized in that, The determination of the characteristic frequency points is specifically as follows: A full-band impedance scan is performed at N frequency points within a predetermined frequency range to obtain preliminary impedance spectrum data. Calculate the impedance change sensitivity coefficient at each scanning frequency point, where the impedance change sensitivity coefficient is the ratio of the absolute value of the impedance change rate with respect to frequency to the impedance modulus value. Select the frequency points where the impedance change sensitivity coefficient is a local maximum as candidate feature frequency points; From the candidate feature frequency points, M feature frequency points were finally selected based on the principle of uniform distribution across low, mid, and high frequency bands. <N。 3. The non-destructive evaluation method for cable microstructure based on AC impedance spectroscopy as described in claim 2, characterized in that, The impedance change sensitivity coefficient is specifically expressed as follows: in, The complex impedance measured at frequency f is... This is the derivative of impedance with respect to frequency.

4. The non-destructive evaluation method for cable microstructure based on AC impedance spectroscopy as described in claim 1, characterized in that, The calculation of the grain boundary degradation degree, reflecting the degree of grain boundary degradation, and the micro-defect concentration, reflecting the severity of micro-defects, through a pre-constructed mapping relationship, specifically involves: Based on the grain boundary resistance and grain boundary capacitance parameters obtained by inversion, the grain boundary degradation degree is obtained by calculating the ratio of their product to the reference value. Based on the volume resistance and defect capacitance parameters obtained from the inversion, the micro-defect concentration is obtained by weighted linear combination of the reciprocal value of the volume resistance and the defect capacitance value.

5. The non-destructive evaluation method for cable microstructure based on AC impedance spectroscopy as described in claim 4, characterized in that, The specific grain boundary degradation degree and microdefect concentration are expressed as follows: Grain boundary degradation: Microscopic defect concentration: in, Grain boundary resistance, Grain boundary capacitance, This is a reference value for grain boundary resistance. This is a reference value for grain boundary capacitance. This refers to the volume resistance within the grain. This is a reference value for the volume resistivity inside the grain. For defect-related capacitance, This is a reference value for defect-related capacitance. and These are the weighting coefficients.

6. The non-destructive evaluation method for cable microstructure based on AC impedance spectroscopy as described in claim 1, characterized in that, The method of calculating the equivalent circuit parameters of the cable conductor microstructure by nonlinear fitting is as follows: based on the measured complex impedance data, a weighted least squares method is used for nonlinear fitting. In the fitting process, the objective function considers both impedance modulus error and phase error, and the measurement error at different frequency points is normalized and weighted. Only the selected characteristic frequency point data is used for fitting calculation.

7. The non-destructive evaluation method for cable microstructure based on AC impedance spectroscopy as described in claim 6, characterized in that, The objective function is specifically expressed as follows: in, and The frequencies calculated based on the equivalent circuit model are respectively Impedance modulus and phase at the point, and The measured frequencies are respectively Impedance modulus and phase at the point, and , respectively, represent the standard deviations of the impedance modulus and phase measurements, and M is the number of characteristic frequency points.

8. The non-destructive evaluation method for cable microstructure based on AC impedance spectroscopy as described in claim 1, characterized in that, The method also includes temperature measurement and compensation, specifically: The actual temperature of the cable conductor is measured simultaneously during impedance measurement; Temperature compensation is applied to the measured impedance values ​​to uniformly correct the impedance values ​​measured at different temperatures to the equivalent impedance values ​​at the reference temperature.

9. The non-destructive evaluation method for cable microstructure based on AC impedance spectroscopy as described in claim 1, characterized in that, The comprehensive evaluation level is set at four levels, specifically: The grain boundary degradation degree is less than the first threshold and the micro-defect concentration is less than the second threshold, and the evaluation level is excellent. The grain boundary degradation degree is between the first and third thresholds and the micro-defect concentration is between the second and fourth thresholds, and the evaluation level is good. The grain boundary degradation degree is between the third and fifth thresholds and the micro-defect concentration is between the fourth and sixth thresholds, and the evaluation level is "Caution". If the grain boundary degradation is greater than or equal to the fifth threshold or the micro-defect concentration is greater than or equal to the sixth threshold, the assessment level is severe.

10. A non-destructive evaluation system for cable microstructure based on AC impedance spectroscopy, characterized in that, include: The characteristic frequency point impedance measurement unit is used to apply AC excitation signals to the cable conductor at several predetermined characteristic frequency points and measure the complex impedance value at each characteristic frequency point. The parameter inversion unit is used to calculate the equivalent circuit parameters of the cable conductor microstructure by nonlinear fitting based on the measured complex impedance data. The equivalent circuit includes a bulk resistance branch reflecting the internal conductivity of the grain, a parallel impedance branch reflecting the grain boundary characteristics, and a parallel impedance branch reflecting the micro-defect characteristics. The quantitative evaluation index calculation unit is used to calculate the grain boundary degradation degree, which reflects the degree of grain boundary degradation, and the micro-defect concentration, which reflects the severity of micro-defects, based on the equivalent circuit parameters obtained by inversion calculation and through a pre-constructed mapping relationship. The comprehensive condition level assessment unit is used to compare the calculated grain boundary deterioration degree and micro defect concentration with the preset level threshold, and determine the comprehensive assessment level of the microstructure state of the cable conductor based on the comparison results.

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