A method and system for evaluating the corrosion state of a grounding grid

Abstract

The application discloses a kind of ground grid corrosion state evaluation method and system, it is related to electric power system grounding device safety monitoring technical field, including: obtaining PEC receiving signal and EIS differential response signal as original signal, extract features to obtain standardization feature set;Standardization feature set is divided into mutually uncoupled subset, based on skin depth mapping division depth direction, based on each depth layer integral loss and electrochemical parameter homogenization calibration obtains homogenization volume loss rate, based on pitting morphology feature obtains pitting risk and eccentricity coefficient and triggers early warning flag bit;According to the weight of shape confidence vector distribution obtains comprehensive corrosion damage factor;Based on comprehensive corrosion damage factor and early warning flag bit generates two-dimensional grading matrix, outputs corrosion grade and residual life interval.The application solves the problems that existing method cannot inhibit multi-physical field measurement mutual exclusion and signal distortion caused by field interference, it is difficult to extract stable features, and cannot distinguish uniform thinning and local pitting.

Description

Technical Field

[0001] This invention relates to the field of safety monitoring technology for power system grounding devices, specifically to a method and system for assessing the corrosion status of grounding grids. Background Technology

[0002] The grounding grid is a crucial facility for ensuring the safe operation and insulation of equipment in power systems. Buried in the soil for extended periods, it is subject to erosion from stray currents, moisture, and chemical agents, leading to a gradual reduction in conductor cross-section and even breakage, directly threatening the safe operation of the power grid. Therefore, accurate assessment of the corrosion status of the grounding grid has significant engineering value.

[0003] Currently, grounding grid corrosion detection mainly employs two technical approaches: one is pulsed eddy current (PEC) detection based on electromagnetic field principles, which inverts conductor cross-sectional loss by analyzing the induced voltage decay signal; the other is impedance spectroscopy (EIS) detection based on electrochemical principles, which assesses the corrosion rate by measuring interfacial charge transfer resistance. However, these technologies still have the following technical shortcomings in practical engineering applications: 1) Multi-physics field measurement incompatibility and strong on-site interference lead to distortion of raw data: PEC excitation requires the application of pulse currents in the range of several amperes, and the resulting strong magnetic field will seriously interfere with the measurement of EIS micro-voltage signals; at the same time, the grounding grid is adjacent to the transformer, and the power frequency fundamental wave and its higher harmonic interference energy are large, and the grid frequency has a slow-changing drift, so conventional fixed center frequency notch filters cannot effectively filter out dynamically changing harmonic interference. In addition, the on-site probe lift-off distance varies randomly, and single amplitude compensation cannot eliminate the effect of lift-off on the phase distortion of the time domain waveform, resulting in deviation of the input source for subsequent feature extraction.

[0004] 2) Insufficient stability and anti-interference capability of single detection dimensions: Due to the skin effect, pulsed eddy current detection allows for deep penetration of low-frequency components, but these are greatly affected by the lift-off effect. High-frequency components are sensitive to surface corrosion but are easily contaminated by noise. Changes in the permeability of corrosion products cause nonlinear drift in the time and frequency domains. Traditional single-domain analysis cannot reliably extract features strongly correlated with corrosion mass loss rate. Electrochemical impedance spectroscopy (EIS) is affected by the dispersion effect of constant phase angle elements in the soil equivalent circuit, often resulting in multiple solutions in the equivalent circuit fitting, making it difficult to remove soil background interference. When fusing multi-source data, pulsed eddy current reflects volume loss, while EIS reflects surface activity. The two have large differences in spatiotemporal scales, and there is a lack of effective homogenization conversion methods. Direct data layer fusion can lead to large-scale defects being submerged by small-scale noise.

[0005] 3) Existing corrosion assessment models cannot distinguish between corrosion morphologies, making them prone to fundamental errors in assessment direction: Current models typically output a single corrosion score, but the mechanisms by which large-area uniform thinning and localized severe pitting jeopardize power grid safety are completely different—the former leads to a slow decline in current-carrying capacity, while the latter causes a sudden drop in mechanical strength, resulting in electrical connection failure. Confusing the two in assessment can lead to operational and maintenance strategy errors: misclassifying uniform thinning as pitting will trigger unnecessary excavation and inspection, while misclassifying pitting as uniform thinning will lead to sudden line failures. Furthermore, the state of the corrosion product film directly affects the corrosion development trend, but existing models lack physical indicators characterizing the barrier properties of the film, resulting in large deviations in corrosion rate predictions and low reliability in remaining life estimations. Summary of the Invention

[0006] To address the problems of existing grounding grid corrosion status assessment methods, such as inability to suppress signal distortion caused by multi-physics measurement conflicts and field interference, difficulty in extracting stable features, and inability to distinguish between uniform thinning and localized pitting corrosion, this invention provides a grounding grid corrosion status assessment method, the method comprising: S1. Based on the integrated flexible array probe, the PEC received signal and EIS differential response signal of the grounding grid conductor under test are acquired as raw signals, and the raw signals are preprocessed to obtain valid input samples; S2. Extract the features of the valid input samples to obtain a standardized feature set; S3. Divide the standardized feature set into several uncoupled subsets, divide the depth direction into several depth layers based on the subsets and skin depth mapping, and obtain the homogenized volume loss rate based on the homogenization calibration of the integral loss and electrochemical parameters of each depth layer; obtain the pitting risk and eccentricity coefficient based on the pitting morphology characteristics, and trigger the warning flag when the eccentric pitting risk exceeds the standard. Based on the homogenized volume loss rate and pitting risk, a baseline damage component is constructed, and the weight of each damage component is assigned according to the morphological confidence vector of the subset to obtain the comprehensive corrosion damage factor. A two-dimensional classification matrix is ​​generated based on the comprehensive corrosion damage factor and the early warning flag, and the corresponding corrosion degree level is output. The remaining lifespan range is calculated based on the comprehensive corrosion damage factor and the corrosion rate.

[0007] This method effectively solves the problems of raw data distortion caused by the mutual exclusion between the PEC strong magnetic field and EIS micro-voltage measurement, dynamic drift of power frequency harmonics, and random changes in lift-off distance through the preprocessing process of integrated flexible array probe and synchronous timing control, dynamic notch denoising, and first-wave lift-off calibration in S1. This significantly improves the signal-to-noise ratio and repeatability of the raw input signal. At the same time, through skin depth layered sliding window analysis and phase unwinding diamagnetic processing of PEC signal in S2, and DRT spectral morphological analysis and multi-field coupling phase difference extraction of EIS signal, this method solves the problems of unstable features in single detection dimension, magnetic permeability interference, and spatiotemporal scale misalignment of multi-source data, and constructs a standardized feature set with clear physical orientation and strong robustness. Furthermore, by dividing the feature set into four uncoupled physical subsets—volume loss, pitting morphology, interface dynamics, and spatial eccentricity—in S3, a fuzzy morphology discriminator is constructed to distinguish between uniform thinning and local pitting. The volume loss rate is obtained through skin depth layered integration and electrochemical parameter homogenization calibration. The pitting depth is inferred and eccentricity warning is triggered by fractal dimension and DRT peak asymmetry coefficient. Finally, damage weights are dynamically allocated based on the morphology confidence vector, and a two-dimensional hierarchical matrix is ​​generated. This solves the technical defects of existing models that cannot distinguish corrosion morphology, leading to incorrect evaluation direction and low reliability of remaining lifetime prediction. It realizes the classification evaluation of uniform thinning and local pitting and the proactive warning of high-risk eccentric pitting.

[0008] Furthermore, the integrated flexible array probe uses a polyimide flexible substrate, and the dual-ring transceiver coil of pulsed eddy current and the micro three-electrode system of electrochemical impedance spectroscopy are arranged alternately in concentric circles. The dual-ring transceiver coil is located in the outermost ring, and the micro three-electrode system is located in a circular area with a preset diameter at the center. The overlap of the physical areas measured by the two is greater than the preset overlap.

[0009] The flexible polyimide substrate can conform to the rough and corroded surface of the grounding flat steel, achieving conformal contact and reducing the lift-off gap; the alternating arrangement of concentric circles ensures that the two physical field measurements are performed in the same microscopic region, providing a spatial consistency basis for subsequent multi-source data homogeneous fusion.

[0010] Further, the specific steps of S1 include: S101. Set a timing controller to divide the acquisition period into multiple continuous time windows, wherein the continuous time windows include a PEC excitation window, an EIS excitation window, and a dead zone isolation window; S102. Within the PEC excitation window, the timing controller disconnects the EIS loop and injects a damped oscillating bipolar pulse train into the dual-ring transceiver coil to obtain the PEC receiving signal. Within the EIS excitation window, the timing controller disconnects the PEC excitation source and applies a composite excitation signal to the EIS working electrode to obtain the EIS differential response signal. The dead zone isolation window is set at the junction of the PEC excitation window and the EIS excitation window, and all excitation sources are completely silent within this window; S103. Extract long buffer data of a preset length from the original signal, extract the actual frequency of the power system fundamental frequency, generate a notch center frequency sequence based on the actual frequency, and construct a dynamic IIR comb notch filter based on the notch center frequency sequence. S104. The original signal is filtered based on the dynamic IIR comb notch filter to obtain a clean signal, the clean signal including a clean PEC signal and a clean EIS signal; S105. From the pure PEC signal, extract the induced voltage signal within a preset time window after the falling edge of the damped oscillating bipolar pulse train to obtain the first wave leading edge segment, and obtain the normalized average rate of change of the first wave leading edge segment. Construct a standard mapping library, which includes a lift-off distance-normalized average rate of change mapping table; Based on the standard mapping library and the normalized average rate of change, the compensation coefficient is obtained; The pure PEC signal is multiplied by the compensation coefficient to obtain the first signal; The time axis of the first signal is calibrated based on the compensation coefficient to obtain the second signal; The second signal, the pure EIS signal, the normalized average rate of change, the compensation coefficient, and the calibrated time axis are used as valid input samples.

[0011] By employing a timing controller to strictly stagger the PEC and EIS excitations and setting a dead-zone isolation window, in-situ synchronous acquisition of the two physical fields was achieved without electromagnetic crosstalk. A dynamic IIR comb-shaped notch filter tracked the actual frequency of the power frequency fundamental wave and generated a matching notch center sequence, solving the problem of conventional fixed notch filters filtering out effective sideband information under slow frequency drift of the power grid. The leading edge of the first wave of the PEC signal was used as the lift-off sensitive operator. During this period, the eddy current has not yet penetrated into the conductor, and the amplitude change only reflects the lift-off distance and is not related to the degree of corrosion. Based on this, a compensation coefficient was constructed to perform dual normalization of the amplitude and the time axis in the time domain, overcoming the defect that a single amplitude compensation cannot eliminate the effect of lift-off on phase distortion, and effectively improving the repeatability of feature extraction between different measurement batches.

[0012] Furthermore, the specific steps of S104 include: The original signal is filtered using the dynamic IIR comb notch filter to obtain the residual signal; The residual signal is decomposed using VMD to obtain several modal components; Obtain the normalized kurtosis value for each of the modal components; If the normalized kurtosis value is greater than the preset kurtosis value, then the modal component corresponding to the normalized kurtosis value is deleted; The Pearson correlation coefficient was calculated between the deleted modal components and the standard template of the original excitation signal to obtain the correlation value. If the correlation value is less than a preset correlation value, then the modal component corresponding to the correlation value is deleted; The retained modal components are linearly superimposed to obtain the pure signal.

[0013] First, a dynamic IIR comb notch filter is used to remove the main lobe energy of the power frequency and its harmonics to obtain the residual signal. Then, VMD decomposition is performed on the residual signal. The impact noise components such as soil particle collision and probe jitter are removed by using a normalized kurtosis threshold. The effective modal components that are highly correlated with the non-corrosive standard template are screened out and recombined by using a correlation coefficient threshold. The cascaded denoising process takes into account both power frequency narrowband interference suppression and broadband random noise filtering, which significantly improves the signal-to-noise ratio of the clean signal and provides a high-quality data source for subsequent feature extraction.

[0014] Furthermore, the specific steps of S2 include: S201. A preset sliding window, wherein the sliding window has a window width of a time constant and slides along the calibrated time axis with a preset step size; S202. Analyze the second signal based on the sliding window to obtain stable characteristics and characteristic frequency phase curvature; S203. Analyze the pure EIS signal to obtain the first relaxation time, area ratio, absolute roughness increment and phase difference value. S204. Based on the phase difference, the area ratio, the first relaxation time, the characteristic frequency phase curvature, the absolute roughness increment, and the stable feature, obtain the standardized feature set.

[0015] Differential feature extraction was performed on PEC and EIS signals respectively, providing a basic feature set with clear physical meaning, rich dimensions and mutual orthogonality for subsequent morphology discrimination and corrosion assessment.

[0016] Furthermore, the specific steps of S202 include: Within each sliding window, linear regression is performed on the second signal to obtain the instantaneous decay rate, and a skin depth-decay rate mapping curve is constructed based on the instantaneous decay rate. The stable features are obtained based on a preset skin depth and the skin depth-attenuation rate mapping curve. The stable features include a shallow attenuation factor, a deep attenuation factor, and a transition zone curvature. Perform a Fast Fourier Transform on the second signal to extract its spectrum; The phase spectrum of the spectrum is obtained, and an unwinding operation is performed on the phase spectrum. Based on the phase spectrum after the operation, the phase curvature of the characteristic frequency is constructed.

[0017] By using the skin depth formula to map the PEC time-domain signal into a spatial depth-domain signal, a continuous curve of attenuation rate as a function of depth is constructed. The attenuation factors of shallow and deep layers and the second-order curvature of the transition zone are extracted by a sliding window nonfitting method, realizing a layered quantitative description of corrosion along the depth direction, and avoiding the problem of multiple solutions in fitting without the need for a preset exponential model. By unwinding the phase spectrum and extracting the second derivative to construct the characteristic frequency phase curvature, the first-order offset interference introduced by the change in permeability of corrosion products in the phase spectrum is eliminated, so that the feature only reflects the change in conductor conductivity distribution, and the robustness of the feature to permeability drift is enhanced.

[0018] Furthermore, the specific steps in S203 include: The pure EIS signal is subjected to DRT transformation to obtain the relaxation time distribution function; the relaxation time distribution function is then obtained. , obtain the The first relaxation time corresponding to the maximum peak value; Obtain the area ratio of the left and right sides of the half-width at half-maximum of the first relaxation time; Based on the standard parameter fitting of the classical equivalent circuit, the values ​​of charge transfer resistance and double-layer capacitance are extracted. The constant phase angle element index in the EIS measurement loop is mapped to the electrochemical fractal dimension, and the difference between the electrochemical fractal dimension and the reference fractal dimension measured at the initial stage of the grounding grid is obtained to obtain the absolute roughness increment. At a specific frequency point, the phase difference between the PEC received signal and the EIS differential response signal is obtained.

[0019] The EIS frequency domain data is transformed into a relaxation time distribution spectrum using DRT transformation. The relaxation time of the main peak and the area ratio of the half-peak width are extracted from it. The area ratio is physically mapped to the cracked and dense state of the corrosion product layer, which has a better early warning capability than the fitting parameters of conventional equivalent circuits. The charge transfer resistance and double-layer capacitance values ​​are extracted by CNLS fitting, and the exponent of constant phase angle element is mapped to the fractal dimension increment to quantitatively characterize the degree of expansion of the specific surface area of ​​corrosion pits. The phase difference between PEC and EIS is extracted at a specific frequency point. This phase difference reflects the degree of misalignment of the spatial geometric center of the eddy current path and the ion path, which can effectively identify eccentric corrosion on the same cross section of the conductor and fill the gap that single detection methods cannot identify eccentric corrosion.

[0020] Furthermore, the specific steps of S3 include: S301. Divide the standardized feature set into several uncoupled subsets, the subsets including a volumetric electromagnetic loss subset, a local pitting morphology subset, an interface reaction dynamics subset, and a spatially eccentric distribution subset. The volumetric electromagnetic loss subset includes the deep attenuation factor and the characteristic frequency phase curvature. The local pitting morphology subset includes the transition zone curvature, the area ratio, and the absolute roughness increment. The interface reaction dynamics subset includes the first relaxation time. The spatially eccentric distribution subset includes the phase difference value. S302. Construct a shape discriminator, wherein the shape discriminator has a built-in fuzzy rule library, and the fuzzy rule library contains several judgment rules; The normalized mean values ​​of the electromagnetic loss subset and the local pitting morphology subset are obtained, and the first mean and the second mean are obtained respectively. The first mean and the second mean are input into the morphology discriminator and matched with the fuzzy rule base to obtain the morphology confidence vector. S303. Based on the thickness of the grounding flat steel, the longitudinal direction is divided into the surface area, the transition area and the deep matrix area, and the integral area under the skin depth-attenuation rate mapping curve of each area is calculated respectively. The charge transfer resistance is converted into the average corrosion depth rate. A calibration compensation operator is constructed based on the integral area and the average corrosion depth rate. The homogenized volume loss is obtained based on the calibration compensation operator. S304. The maximum pit depth is obtained based on the absolute roughness increment. A pitting activity factor is constructed based on the area ratio. The pitting depth is obtained based on the maximum pit depth and the pitting activity factor. The pitting risk is obtained based on the pitting depth. The eccentricity coefficient is obtained based on the phase difference value. If the pitting risk is greater than the pitting threshold and the eccentricity coefficient is greater than the eccentricity threshold, it is determined to be a high-risk eccentric pitting and a warning flag is triggered. S305. Based on the homogenized volume loss rate, the pitting risk, the charge transfer resistance value, and the double-layer capacitance value, construct a baseline damage component, which includes a conductor loss rate component, a pitting risk component, and an impedance degradation component; assign damage weights to the baseline damage component based on the morphological confidence vector. Based on the baseline damage components and the damage weights, a comprehensive corrosion damage factor is constructed; S306. Based on the comprehensive corrosion damage factor and the early warning flag, a two-dimensional classification matrix is ​​constructed. The corrosion level is obtained based on the two-dimensional classification matrix, and the remaining lifespan range is obtained based on the comprehensive corrosion damage factor.

[0021] First, the feature set is divided into four physically orthogonal subsets: volumetric electromagnetic loss, local pitting morphology, interfacial reaction kinetics, and spatial eccentric distribution. A morphology discriminator is constructed using the TS fuzzy inference system, outputting confidence vectors for three morphologies: uniform thinning, local pitting, and mixed corrosion. This addresses the limitation of existing models that cannot distinguish corrosion morphologies, leading to incorrect assessment directions. Second, the loss area at each depth interval is obtained through skin depth layered integration, and a calibration compensation operator is constructed by combining the corrosion rate calculated from the EIS charge transfer resistance, achieving homogeneous fusion of electromagnetic volume information and electrochemical surface information at a unified physical scale. Third, the maximum pit depth and pitting activity are calculated using fractal dimension increment and DRT peak asymmetry coefficient, respectively. Combined with eccentric phase difference, quantitative inference of pitting depth and proactive early warning of high-risk eccentric pitting are achieved. Furthermore, based on the morphology confidence vector, the game-theoretic Shapley value method is used to dynamically allocate the weights of each damage component. This allows the assessment model to emphasize current-carrying capacity assessment under uniform thinning conditions and mechanical strength assessment under pitting conditions, overcoming the limitation of large assessment deviations in fixed-weight models under different corrosion morphologies. Finally, a two-dimensional hierarchical matrix is ​​constructed by combining comprehensive corrosion damage factors and early warning markers, and the corrosion level and eccentricity warning are output simultaneously. The remaining life confidence interval is given by combining environmental fluctuation variance, providing an accurate decision-making basis for differentiated operation and maintenance on site.

[0022] Furthermore, the formula for calculating the skin depth-attenuation rate mapping curve is as follows: ; in, Represents the permeability of free space. Indicates the equivalent conductivity of a conductor. Indicates skin depth.

[0023] The present invention also provides a grounding grid corrosion status assessment system, the system comprising: Data acquisition unit: used to acquire the PEC received signal and EIS differential response signal of the conductor of the grounding grid under test as raw signals based on the integrated flexible array probe, and preprocess the raw signals to obtain valid input samples; Feature extraction unit: used to extract features from the valid input samples to obtain a standardized feature set; Data analysis unit: used to divide the standardized feature set into several uncoupled subsets, divide the depth direction into several depth layers based on the skin depth mapping based on the subsets, and obtain the homogenized volume loss rate based on the homogenization calibration of the integral loss and electrochemical parameters of each depth layer; obtain the pitting risk and eccentricity coefficient based on the pitting morphology characteristics, and trigger the warning flag when the eccentric pitting risk exceeds the standard. Based on the homogenized volume loss rate and pitting risk, a baseline damage component is constructed, and the weight of each damage component is assigned according to the morphological confidence vector of the subset to obtain the comprehensive corrosion damage factor. A two-dimensional classification matrix is ​​generated based on the comprehensive corrosion damage factor and the early warning flag, and the corresponding corrosion degree level is output. The remaining lifespan range is calculated based on the comprehensive corrosion damage factor and the corrosion rate.

[0024] The principle and beneficial effects of this system are similar to those of this method, and will not be elaborated further on this system.

[0025] One or more technical solutions provided by this invention have at least the following technical effects or advantages: 1. An integrated flexible array probe, combined with time-division multiplexing excitation and dead-zone isolation, solves the physical layer problem of mutual exclusion between PEC strong magnetic field and EIS micro-voltage measurement; SOGI-FLL is used to track the power frequency fundamental frequency in real time and dynamically generate notch center sequence, combined with kurtosis-correlation coefficient dual-criteria mode screening after VMD decomposition, which solves the defect of conventional fixed notch filters filtering out effective sideband information under slow-drift of power grid frequency; a lift-off sensitive operator is constructed using the first wave leading edge of PEC signal and amplitude-time axis dual normalization is implemented, which overcomes the defect that single amplitude compensation cannot eliminate the effect of lift-off on phase distortion, and ensures the signal-to-noise ratio and repeatability of input data from the source.

[0026] 2. By using the skin depth formula to map the PEC time-domain signal into a continuous curve in the depth domain, and extracting the shallow and deep attenuation factors and the curvature of the transition zone through a sliding window non-fitting method, a layered quantitative description of corrosion along the depth is achieved without the need for a pre-set model, thus avoiding multiple fitting solutions. By unwinding the phase spectrum and extracting the second derivative to construct the characteristic frequency phase curvature, the first-order offset interference introduced by the change in magnetic permeability of corrosion products is reduced. By using DRT transformation to extract the relaxation time of the main peak and the area ratio of the half-peak width from the EIS data, and further extracting the fractal dimension increment and the cross-correlation phase difference between PEC and EIS, an eight-dimensional standardized feature set with clear physical orientation is constructed, solving the problems of unstable features in a single detection dimension and spatiotemporal scale misalignment in the fusion of multi-source data.

[0027] 3. The feature set is divided into four physically orthogonal subsets: volumetric loss, pitting morphology, interface dynamics, and spatial eccentricity. A fuzzy morphology discriminator is constructed to output confidence vectors for the three corrosion morphologies, fundamentally solving the problem that existing single fractional models cannot distinguish between uniform thinning and local pitting corrosion, leading to incorrect assessment directions. The volumetric loss rate is obtained through skin depth layered integration and electrochemical corrosion rate homogenization calibration. The pitting depth is jointly inferred using fractal dimension and DRT peak asymmetry coefficient, triggering eccentricity warnings. This achieves quantitative fusion of volume and surface physical quantities and proactive identification of high-risk eccentric pitting corrosion. Damage weights are dynamically allocated based on the morphology confidence vector, allowing the assessment model to adaptively adjust its emphasis according to the corrosion morphology, overcoming the inherent bias of fixed-weight models. The two-dimensional hierarchical matrix combined with the remaining lifetime interval prediction based on environmental fluctuation variance provides accurate and quantifiable decision-making basis for differentiated operation and maintenance in the field. Attached Figure Description

[0028] The accompanying drawings, which are provided to further illustrate embodiments of the invention and constitute a part of this invention, are not intended to limit the scope of the invention. Figure 1 This is a flowchart illustrating a method for assessing the corrosion status of a grounding grid. Detailed Implementation

[0029] To better understand the above-mentioned objectives, features, and advantages of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be noted that, where there is no conflict, the embodiments of the present invention and the features thereof can be combined with each other.

[0030] Many 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 different from those described herein, and therefore the scope of protection of the invention is not limited to the specific embodiments disclosed below.

[0031] Example 1 refer to Figure 1 This embodiment provides a method for assessing the corrosion status of a grounding grid, the method comprising: S1. Based on the integrated flexible array probe, the PEC received signal and EIS differential response signal of the grounding grid conductor under test are acquired as raw signals, and the raw signals are preprocessed to obtain valid input samples; The integrated flexible array probe features a structure employing a flexible polyimide substrate (i.e., a flexible substrate using a polyimide film as the carrier for electronic components, seamlessly bonding the eddy current coil and electrochemical electrodes to a rough, corroded grounding flat steel, ensuring stable and reliable acquisition of both PEC and EIS signals at the same physical point). The dual-ring transceiver coils for pulsed eddy current (PEC) (e.g., an excitation coil with an outer diameter of 30 mm and a receiving coil with an inner diameter of 15 mm) and the micro-three-electrode system for electrochemical impedance spectroscopy (EIS) (the working electrode WE is a platinum column, the reference electrode RE is Ag / AgCl, and the auxiliary electrode CE is a stainless steel ring) are arranged alternately in concentric circles. The PEC coil is located in the outermost ring, and the EIS three electrodes are located within a central circular region with a diameter of 10 mm, ensuring a ≥90% overlap in the physical regions measured by both, and ensuring that they measure the conductor state of the same microscopic region in physical space. The specific steps include: S101. Set a timing controller (such as an FPGA timing controller with a main frequency of 200MHz) to divide the acquisition period T into multiple continuous time windows. The continuous time windows include PEC excitation window (such as ΔT1=5ms), EIS excitation window (such as ΔT2=44.5ms) and dead zone isolation window (such as ΔT3=0.5ms). S102. Within the PEC excitation window, the timing controller disconnects the EIS loop and injects a damped bipolar pulse train into the dual-ring transceiver coil to obtain the PEC received signal. The specific waveform may be as follows: ; in, This represents a damped oscillating bipolar pulse train. Indicates peak voltage. Indicates the attenuation coefficient. The center frequency is indicated and can be adaptively switched according to the thickness of the grounding flat steel being measured (e.g., when the thickness is ≤6mm). When the thickness is greater than 6mm, ), Indicates time.

[0032] In this embodiment, the damped oscillating bipolar pulse train is a finite-length pulse sequence composed of multiple sinusoidal oscillation periods with alternating positive and negative polarities and whose amplitude decays exponentially with time. It is not a single pulse, but a waveform segment that exists continuously within a finite time window (e.g., 4.5ms); the voltage waveform alternately crosses the zero line, meaning that within one period there are both positive and negative amplitudes, exhibiting symmetry; the waveform presents a sinusoidal shape, rather than a rectangular square wave or a triangular wave, and the frequency is determined by the center frequency; the amplitude of the oscillation decays exponentially with time, meaning that the amplitude decreases as time progresses, eventually approaching zero.

[0033] Within the EIS excitation window, the timing controller disconnects the PEC excitation source and applies a composite excitation signal to the EIS working electrode to obtain the EIS differential response signal. In this embodiment, the composite excitation signal is formed by the linear superposition of a swept-frequency sine wave and a fixed high-frequency micro-perturbation wave. For example, a fixed 5kHz high-frequency tail (auxiliary probe wave) with an amplitude of only 5mV is superimposed on a 10mV sine wave (main probe wave) that is slowly changing frequency.

[0034] The dead zone isolation window is set at the junction of the PEC excitation window and the EIS excitation window, and all excitation sources are completely silent within this window.

[0035] The field grounding grid is often located near transformers, where there is strong 50Hz and its odd harmonic power frequency interference, as well as DC bias in the ground potential. Conventional filtering will simultaneously filter out effective information in the corrosion characteristic frequency band (1Hz~10kHz). This embodiment designs a specific noise reduction process: S103. Extract a long buffer data of a preset length (e.g., 1 second) from the original signal, and use a second-order generalized integrator frequency-locked loop (SOGI-FLL) to extract the actual frequency of the power system's fundamental frequency in real time. (Because when the grid load fluctuates, the actual 50Hz will slowly change within the range of 49.7Hz to 50.3Hz, and a fixed notch filter will cause an effective phase shift).

[0036] Based on the actual frequency Generate notch center frequency sequence ,in The frequency quantity is indicated. A dynamic IIR comb notch filter is constructed based on the notch center frequency sequence. For example, it can be constructed by a cascaded biquad notch unit group generated by the frequency sequence after coefficient mapping. This can be achieved using existing technology. S104. Filter the original signal based on the dynamic IIR comb notch filter to obtain the residual signal; The residual signal is decomposed using VMD to obtain several intrinsic mode components (IMFs). For example, if the residual signal is input into the VMD algorithm with a preset decomposition level of 6, a penalty factor of 2000, and a fidelity threshold of 0.1, 6 intrinsic mode components are obtained. .

[0037] Obtain the normalized kurtosis value of each of the modal components (IMFs), wherein the formula for calculating the normalized kurtosis value is: ; in, Indicates the first Normalized kurtosis values ​​of each modal component, Indicates the expected value. Indicates the first One modal component, This represents the mean. Indicates standard deviation, Represents an integer greater than or equal to 1.

[0038] If the normalized kurtosis value is greater than the preset kurtosis value, then the modal component corresponding to the normalized kurtosis value is deleted; The deleted modal components are compared with the standard template of the original signal. (Standard waveform data of the attenuation curve of the receiving coil induced voltage, acquired in advance in a noise-free laboratory using the same detection probe from a health standard test block) are used to calculate the Pearson correlation coefficient to obtain the correlation value. The formula for calculating the correlation value is as follows: ; in, Indicates the first The correlation values ​​of each modal component This represents the covariance operation. Represents a sequence of standard templates. Indicates the first The standard deviation of each modal component This represents the standard deviation of the standard template.

[0039] If the correlation value is less than a preset correlation value, then the modal component corresponding to the correlation value is deleted; The retained modal components are linearly superimposed to obtain the pure signal, which includes a pure PEC signal. and pure EIS signal ; S105. From the pure PEC signal, extract the induced voltage signal within a preset time window (e.g., 0-50 μs) after the falling edge of the damped oscillating bipolar pulse train to obtain the first wave leading edge segment. This segment is extremely short, and the eddy current has not yet penetrated deep into the conductor. Its amplitude change is determined only by the equivalent air gap (lift-off distance) between the probe and the conductor, and is unrelated to the degree of corrosion inside the conductor.

[0040] Obtain the normalized average rate of change of the first wave front segment. The formula for calculating the normalized average rate of change is as follows: ; in, This represents the normalized average rate of change. This indicates the number of sampling points within the preset time window. Indicates the first One sampling point, This indicates the leading edge of the first wave. Indicates the sampling interval. This represents the absolute peak amplitude of the leading edge segment of the first wave. Indicates the current sampling time. Indicates the previous sampling time.

[0041] Construct a standard mapping library, which includes a lift-off distance-normalized average rate of change mapping table. For example, different lift-off distances can be artificially set in a laboratory environment for the same standard non-corrosive test block. Record the corresponding Values ​​are used to establish a monotonic mapping table of lift-off distance-normalized average rate of change.

[0042] Based on the standard mapping library and the normalized average rate of change, the compensation coefficient is obtained; If the lifting distance Using the signal response at time 1 as a reference, cubic spline interpolation is employed to calculate the current signal response. Corresponding compensation coefficient: ; in, express The corresponding compensation coefficient, Represents the interpolation function. Indicates the distance to lift off The signal amplitude reference at that time This represents the lift-off sensitivity operator corresponding to the lift-off distance.

[0043] The pure PEC signal Multiply by the compensation coefficient to obtain the first signal; The time axis of the first signal is calibrated based on the compensation coefficient to obtain the second signal. ,like: ; in, This indicates the calibrated timeline. This indicates the timeline before calibration. Indicates the material correction factor. express The corresponding compensation coefficient; The second signal The pure EIS signal The normalized average rate of change The compensation coefficient and the calibrated time axis , as a valid input sample.

[0044] S2. Extract the features of the valid input samples to obtain a standardized feature set; the specific steps include: S201. A preset sliding window is established, wherein the sliding window operates with a time constant (e.g., ...). () is the window width, along the calibrated time axis With a preset step size (e.g.) )slide; S202. Within each sliding window, perform linear regression on the second signal to obtain the instantaneous attenuation rate; for example, for... Perform linear regression to obtain the instantaneous decay rate at that moment; Based on the instantaneous attenuation rate, a skin depth-attenuation rate mapping curve is constructed, as shown in the electromagnetic field skin depth formula: ; in, Represents the permeability of free space. Indicates the equivalent conductivity of a conductor. Indicates skin depth.

[0045] By mapping the time axis to the equivalent detection depth axis, a curve showing the attenuation rate as a function of depth is obtained.

[0046] Stable features are obtained based on a preset skin depth and the skin depth-attenuation rate mapping curve. These stable features include a shallow attenuation factor, a deep attenuation factor, and a transition zone curvature. Shallow attenuation factor: extraction The instantaneous decay rate at a given point reflects the loss of conductivity of the surface corrosion product film; Deep attenuation factor: extraction The instantaneous attenuation rate at a given point reflects the cross-sectional loss rate of the parent material matrix; Transition zone curvature: Calculate the attenuation rate as a function of depth in the curve. The mean of the second derivative of the interval, the magnitude of which is strongly correlated with the sharpness of the edges of the corrosion pit, can effectively distinguish between uniform thinning and local pitting corrosion; Perform a Fast Fourier Transform (FFT) on the second signal to extract its spectrum. ; The phase spectrum of the spectrum is obtained and an unwrap operation is performed on it to reduce spurious abrupt changes caused by period jumps.

[0047] Based on the manipulated phase spectrum, construct the characteristic frequency phase curvature: ; in, Represents the characteristic frequency phase curvature. This represents the phase spectrum after the operation. Indicates frequency.

[0048] S203, the pure EIS signal Perform DRT (Distributed Relaxation Time) transformation to obtain the relaxation time distribution function. ; The relaxation time distribution function is obtained using the wavelet transform modulus maxima method (WTMM). , will the The first relaxation time corresponding to the maximum peak value is denoted as (Characterizing the charge transfer process), the second relaxation time corresponding to the second peak is denoted as... (Characterizing the diffusion process); Obtain the area ratio of the left and right sides of the full width at half maximum (FWHM) of the first relaxation time: ; in, Indicates the area ratio. This indicates the right half-peak width boundary of the first relaxation time. Indicates the first relaxation time. This indicates the left half-peak width boundary of the first relaxation time. Represents the relaxation time distribution function. Indicates the relaxation time.

[0049] When the corrosion product layer on the surface of the grounding grid is dense and uniform, the main peak is symmetrical. When the etched layer cracks or peels off, the ion diffusion path is blocked, resulting in a noticeable tailing on the right side of the DRT main peak. This morphological parameter is better than that of a conventional fit. It has a greater ability to provide early warnings.

[0050] Based on standard parameter fitting of the classical equivalent circuit, the charge transfer resistance is extracted. and double-layer capacitance value ;like: The classic Randle equivalent circuit is selected as the basic fitting model, and its topology is: solution resistance. With (charge transfer resistance) Parallel constant-phase element (CPE) in series. The impedance expression for CPE is: ; in, The impedance of a constant phase angle element. Represents the admittance constant. Indicates the diffusion index, Represents the imaginary unit. It represents angular frequency.

[0051] Using the Levenberg-Marquardt algorithm, the real part of the measured impedance across the entire frequency band (100kHz-10mHz) was analyzed. and the virtual part Perform global fitting in the complex domain.

[0052] Set the initial range of values ​​for the fitting parameters (e.g., known empirical values): , , , .

[0053] The charge transfer resistance value after fitting convergence is denoted as... The double-layer capacitance is denoted as (pass Conversion, among which (This refers to the angular frequency at the point where the imaginary part of the Nyquist plot reaches its maximum).

[0054] The index of the constant phase angle element in the EIS measurement circuit that reflects the characteristics of double-layer capacitance. (Typically between 0.7 and 1) is mapped to the electrochemical fractal dimension of the conductor surface. ; Constructing absolute roughness increment : to measure the current The reference value measured during the initial operation of the grounding grid (or in the vicinity of the non-corroded area) is compared with that of the grounding grid. Difference, that is This increment is directly and uniquely related to the degree of expansion of the microscopic specific surface area of ​​the corrosion pit, and is a rigid indicator for assessing corrosion activity.

[0055] At a specific frequency (e.g., 200Hz), the phase difference between the PEC received signal and the EIS differential response signal is acquired. This phase difference reflects the spatial deviation between the electromagnetic induced eddy current path and the electrochemical ion migration path in the conductor's depth direction. When uneven corrosion occurs in the conductor, the spatial geometric centers of the eddy current path (volume) and the ion path (surface) are misaligned, causing a sudden change in the phase difference. This feature can effectively identify eccentric corrosion (one side intact, one side severely thinned) on the same cross-section of the conductor, a function that a single measurement method cannot achieve.

[0056] S204, Based on the phase difference value The area ratio First relaxation time The characteristic frequency phase curvature The absolute roughness increment The deep attenuation factor and the curvature of the transition region are used to obtain a standardized feature set; S3. Divide the standardized feature set into several uncoupled subsets, divide the depth direction into several depth layers based on the subsets and skin depth mapping, and obtain the homogenized volume loss rate based on the homogenization calibration of the integral loss and electrochemical parameters of each depth layer; obtain the pitting risk and eccentricity coefficient based on the pitting morphology characteristics, and trigger the warning flag when the eccentric pitting risk exceeds the standard. Based on the homogenized volume loss rate and pitting risk, a baseline damage component is constructed, and the weight of each damage component is assigned according to the morphological confidence vector of the subset to obtain the comprehensive corrosion damage factor. A two-dimensional classification matrix is ​​generated based on the comprehensive corrosion damage factor and the early warning flag, and the corresponding corrosion degree level is output. The remaining lifespan range is calculated based on the comprehensive corrosion damage factor and the corrosion rate.

[0057] The specific steps include: S301. Divide the standardized feature set into several uncoupled (orthogonal) subsets to ensure the physical uniqueness of subsequent morphological discrimination. The subsets include the volume electromagnetic loss subset. Local pitting morphology subset Subset of interfacial reaction kinetics Spatially eccentric subsets ; The volume electromagnetic loss subset The deep attenuation factor and the characteristic frequency phase curvature are included to characterize the depth cross-sectional loss. Both of them originate from the deep response of the PEC signal and have a physical scale of millimeters. Their changes are mainly dominated by the reduction of the effective cross-sectional area of ​​the conductor and the decrease in macroscopic conductivity, and are unrelated to the surface micromorphology.

[0058] The subset of local pitting morphology Includes the curvature of the transition region, the area ratio, and the absolute roughness increment. The three components characterize the microscopic geometric distortion, and together they describe the sharpness of the edges of the corrosion pits, the symmetry of the ion diffusion barrier, and the surface roughness of the specific surface area. The physical scale of this subset is from micrometer to sub-millimeter, and all of them are derived from the secondary analysis of the DRT spectrum of EIS and the shallow transient response of PEC. They are mathematically weakly correlated with the macroscopic cross-sectional area of ​​the conductor (covariance <0.1 in the orthogonality test).

[0059] The subset of interfacial reaction kinetics Including the first relaxation time, it characterizes the corrosion activity and product density. The length of this time constant characterizes the inherent activation energy barrier of the corrosion electrochemical reaction, and it is independent of the geometry of the corrosion pit (even if the pitting is deep, if the surface is passivated, (It may still be very large), therefore with Orthogonal.

[0060] The spatially eccentric distribution subset Including the phase difference value It characterizes the non-uniform offset of corrosion along the cross section. This phase difference is caused by the spatial geometric center misalignment between the eddy current path (volume current) and the ion path (surface current). It is specifically used to determine whether corrosion is concentrated on one side of the conductor and is completely spatially orthogonal to the three dimensions of volume, pitting, and interface mentioned above.

[0061] S302. A morphological discriminator is constructed using the TS fuzzy inference system. The morphological discriminator has a built-in fuzzy rule base, which contains several decision rules: Obtain the electromagnetic loss subset and the subset of local pitting morphology The normalized mean is used to obtain the first mean. Second mean ; The first mean and the second mean are input into the shape discriminator and matched with the fuzzy rule base; like: Rule 1: If High, and If the corrosion level is low, the corrosion type is Type I - uniform thinning; Rule 2: If Low, and If the corrosion rate is high, the corrosion type is Type II - localized pitting corrosion; Rule 3: If High, and If the corrosion rate is high, the corrosion type is Type III - mixed corrosion.

[0062] Rule 4: If the absolute value of the phase difference is greater than a preset threshold Regardless of the output of the above rules, the eccentricity factor will be forcibly set to 1 (marked as eccentric corrosion), and the confidence level of type II will be increased.

[0063] Output morphological confidence vector ,in . These represent the confidence levels for Type I, Type II, and Type III, respectively.

[0064] S303, based on the thickness of the grounding flat steel (Preset typical value, such as 6mm), the depth direction is divided into surface zone (0-1mm), transition zone (1-3mm) and deep matrix zone (3mm-). ); Calculate the area under the skin depth-attenuation rate mapping curve for each region: ; in, Indicates the first The integral area of ​​each region and They represent the first The upper and lower boundaries of the skin depth of each region, This represents the attenuation rate distribution function with depth, which is the function obtained by replacing the time axis with the depth axis according to the skin depth formula of electromagnetic field.

[0065] The charge transfer resistor (Inversely proportional to corrosion current density) Converted to average corrosion depth rate using Faraday's law. ; Based on the integral area and the average corrosion depth rate Constructing calibration compensation operators : ; in, Indicates the calibration compensation operator, This represents the soil environmental correction factor. Indicates the average corrosion depth rate. Indicates the service life of the grounding grid; Based on the calibration compensation operator Obtaining homogenized volume loss rate : ; S304, Based on the absolute roughness increment To obtain the maximum pit depth ; According to the fractal theory of electrochemical interfaces, the maximum pit depth... With absolute roughness increment Satisfies the power law relationship: ; in, Indicates the maximum pit depth. and All of these represent material constants.

[0066] Based on the area ratio Constructing pitting activity factor It is confined to the interval [0,1].

[0067] Based on the maximum pit depth and the pitting activity factor Obtaining pitting depth : ; Based on the pitting depth Gaining pitting risk Based on the phase difference value Obtain the eccentricity coefficient ; If the pitting risk is greater than the pitting threshold, and the eccentricity coefficient is... If the value exceeds the eccentricity threshold, it is judged as high-risk eccentric pitting and a warning flag is triggered. .

[0068] S305. Construct baseline damage components: The conductor loss rate component is constructed based on the homogenized volume loss rate. Based on the pitting risk, a pitting risk component is constructed. Based on the charge transfer resistance value and the double-layer capacitance value Construct impedance degradation components, ; Based on the morphological confidence vector The damage weights of the baseline damage components are assigned using the game-theoretic Shapley value method, such as: when (Uniform type) at its highest point: (Focusing on current carrying capacity assessment); when (Pitting type) at its highest point: (Focusing on mechanical strength assessment); when (Hybrid type) at its highest point: (Balanced assessment).

[0069] Based on the baseline damage components and the damage weights, a comprehensive corrosion damage factor is constructed. : ; ; As an eccentricity penalty, an additional damage assessment value is added when severe eccentric corrosion is detected to highlight its high risk.

[0070] S306. Based on the comprehensive corrosion damage factor and the early warning flag, a two-dimensional classification matrix is ​​constructed, and the corrosion level is obtained based on the two-dimensional classification matrix, such as: The remaining lifetime range is obtained based on the aforementioned comprehensive corrosion damage factor: ; in, The set failure threshold, The average corrosion depth rate, This represents the historical variance of soil temperature and humidity fluctuations.

[0071] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including both the preferred embodiments and all changes and modifications falling within the scope of the invention.

[0072] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A method for assessing the corrosion status of a grounding grid, characterized in that, The method includes: S1. Based on the integrated flexible array probe, the PEC received signal and EIS differential response signal of the grounding grid conductor under test are acquired as raw signals, and the raw signals are preprocessed to obtain valid input samples; S2. Extract the features of the valid input samples to obtain a standardized feature set; S3. Divide the standardized feature set into several uncoupled subsets, divide the depth direction into several depth layers based on the subsets and skin depth mapping, and obtain the homogenized volume loss rate based on the homogenization calibration of the integral loss and electrochemical parameters of each depth layer; obtain the pitting risk and eccentricity coefficient based on the pitting morphology characteristics, and trigger the warning flag when the eccentric pitting risk exceeds the standard. Based on the homogenized volume loss rate and pitting risk, a baseline damage component is constructed, and the weight of each damage component is assigned according to the morphological confidence vector of the subset to obtain the comprehensive corrosion damage factor. A two-dimensional classification matrix is ​​generated based on the comprehensive corrosion damage factor and the early warning flag, and the corresponding corrosion degree level is output. The remaining lifespan range is calculated based on the comprehensive corrosion damage factor and the corrosion rate.

2. The method for assessing the corrosion status of a grounding grid according to claim 1, characterized in that, The integrated flexible array probe uses a polyimide flexible substrate, and the dual-ring transceiver coil of pulsed eddy current and the micro three-electrode system of electrochemical impedance spectroscopy are arranged alternately in concentric circles. The dual-ring transceiver coil is located in the outermost ring, and the micro three-electrode system is located in a circular area with a preset diameter at the center. The overlap of the physical areas measured by the two is greater than the preset overlap.

3. The method for assessing the corrosion status of a grounding grid according to claim 2, characterized in that, The specific steps in S1 include: S101. Set a timing controller to divide the acquisition period into multiple continuous time windows, wherein the continuous time windows include a PEC excitation window, an EIS excitation window, and a dead zone isolation window; S102. Within the PEC excitation window, the timing controller disconnects the EIS loop and injects a damped oscillating bipolar pulse train into the dual-ring transceiver coil to obtain the PEC receiving signal. Within the EIS excitation window, the timing controller disconnects the PEC excitation source and applies a composite excitation signal to the EIS working electrode to obtain the EIS differential response signal. The dead zone isolation window is set at the junction of the PEC excitation window and the EIS excitation window, and all excitation sources are completely silent within this window; S103. Extract long buffer data of a preset length from the original signal, extract the actual frequency of the power system fundamental frequency, generate a notch center frequency sequence based on the actual frequency, and construct a dynamic IIR comb notch filter based on the notch center frequency sequence. S104. The original signal is filtered based on the dynamic IIR comb notch filter to obtain a clean signal, the clean signal including a clean PEC signal and a clean EIS signal; S105. From the pure PEC signal, extract the induced voltage signal within a preset time window after the falling edge of the damped oscillating bipolar pulse train to obtain the first wave leading edge segment, and obtain the normalized average rate of change of the first wave leading edge segment. Construct a standard mapping library, which includes a lift-off distance-normalized average rate of change mapping table; Based on the standard mapping library and the normalized average rate of change, the compensation coefficient is obtained; The pure PEC signal is multiplied by the compensation coefficient to obtain the first signal; The time axis of the first signal is calibrated based on the compensation coefficient to obtain the second signal; The second signal, the pure EIS signal, the normalized average rate of change, the compensation coefficient, and the calibrated time axis are used as valid input samples.

4. The method for assessing the corrosion status of a grounding grid according to claim 3, characterized in that, The specific steps of S104 include: The original signal is filtered using the dynamic IIR comb notch filter to obtain the residual signal; The residual signal is decomposed using VMD to obtain several modal components; Obtain the normalized kurtosis value for each of the modal components; If the normalized kurtosis value is greater than the preset kurtosis value, then the modal component corresponding to the normalized kurtosis value is deleted; The Pearson correlation coefficient of the deleted modal components and the standard template of the original excitation signal is calculated to obtain the correlation value. If the correlation value is less than a preset correlation value, then the modal component corresponding to the correlation value is deleted; The retained modal components are linearly superimposed to obtain the pure signal.

5. The method for assessing the corrosion status of a grounding grid according to claim 4, characterized in that, The specific steps of S2 include: S201. A preset sliding window, wherein the sliding window has a window width of a time constant and slides along the calibrated time axis with a preset step size; S202. Analyze the second signal based on the sliding window to obtain stable characteristics and characteristic frequency phase curvature; S203. Analyze the pure EIS signal to obtain the first relaxation time, area ratio, absolute roughness increment and phase difference value. S204. Based on the phase difference, the area ratio, the first relaxation time, the characteristic frequency phase curvature, the absolute roughness increment, and the stable feature, obtain the standardized feature set.

6. The method for assessing the corrosion status of a grounding grid according to claim 5, characterized in that, The specific steps of S202 include: Within each sliding window, linear regression is performed on the second signal to obtain the instantaneous decay rate, and a skin depth-decay rate mapping curve is constructed based on the instantaneous decay rate. The stable features are obtained based on a preset skin depth and the skin depth-attenuation rate mapping curve. The stable features include a shallow attenuation factor, a deep attenuation factor, and a transition zone curvature. Perform a Fast Fourier Transform on the second signal to extract its spectrum; The phase spectrum of the spectrum is obtained, and an unwinding operation is performed on the phase spectrum. Based on the phase spectrum after the operation, the phase curvature of the characteristic frequency is constructed.

7. The method for assessing the corrosion status of a grounding grid according to claim 6, characterized in that, The specific steps in S203 include: The pure EIS signal is subjected to DRT transformation to obtain the relaxation time distribution function; the relaxation time distribution function is then obtained. , obtain the The first relaxation time corresponding to the maximum peak value; Obtain the area ratio of the left and right sides of the half-width at half-maximum of the first relaxation time; Based on the standard parameter fitting of the classical equivalent circuit, the values ​​of charge transfer resistance and double-layer capacitance are extracted. The constant phase angle element index in the EIS measurement loop is mapped to the electrochemical fractal dimension, and the difference between the electrochemical fractal dimension and the reference fractal dimension measured at the initial stage of the grounding grid is obtained to obtain the absolute roughness increment. At a specific frequency point, the phase difference between the PEC received signal and the EIS differential response signal is obtained.

8. The method for assessing the corrosion status of a grounding grid according to claim 7, characterized in that, The specific steps of S3 include: S301. Divide the standardized feature set into several uncoupled subsets, the subsets including a volumetric electromagnetic loss subset, a local pitting morphology subset, an interface reaction dynamics subset, and a spatially eccentric distribution subset. The volumetric electromagnetic loss subset includes the deep attenuation factor and the characteristic frequency phase curvature. The local pitting morphology subset includes the transition zone curvature, the area ratio, and the absolute roughness increment. The interface reaction dynamics subset includes the first relaxation time. The spatially eccentric distribution subset includes the phase difference value. S302. Construct a shape discriminator, wherein the shape discriminator has a built-in fuzzy rule library, and the fuzzy rule library contains several judgment rules; The normalized mean values ​​of the electromagnetic loss subset and the local pitting morphology subset are obtained, and the first mean and the second mean are obtained respectively. The first mean and the second mean are input into the morphology discriminator and matched with the fuzzy rule base to obtain the morphology confidence vector. S303. Based on the thickness of the grounding flat steel, the longitudinal direction is divided into the surface area, the transition area and the deep matrix area, and the integral area under the skin depth-attenuation rate mapping curve of each area is calculated respectively. The charge transfer resistance is converted into the average corrosion depth rate. A calibration compensation operator is constructed based on the integral area and the average corrosion depth rate. The homogenized volume loss is obtained based on the calibration compensation operator. S304. The maximum pit depth is obtained based on the absolute roughness increment. A pitting activity factor is constructed based on the area ratio. The pitting depth is obtained based on the maximum pit depth and the pitting activity factor. The pitting risk is obtained based on the pitting depth. The eccentricity coefficient is obtained based on the phase difference value. If the pitting risk is greater than the pitting threshold and the eccentricity coefficient is greater than the eccentricity threshold, it is determined to be a high-risk eccentric pitting and a warning flag is triggered. S305. Based on the homogenized volume loss rate, the pitting risk, the charge transfer resistance value, and the double-layer capacitance value, construct a baseline damage component, which includes a conductor loss rate component, a pitting risk component, and an impedance degradation component; assign damage weights to the baseline damage component based on the morphological confidence vector. Based on the baseline damage components and the damage weights, a comprehensive corrosion damage factor is constructed; S306. Based on the comprehensive corrosion damage factor and the early warning flag, a two-dimensional classification matrix is ​​constructed. The corrosion level is obtained based on the two-dimensional classification matrix, and the remaining lifespan range is obtained based on the comprehensive corrosion damage factor.

9. The method for assessing the corrosion status of a grounding grid according to claim 8, characterized in that, The formula for calculating the skin depth-attenuation rate mapping curve is as follows: ； in, Represents the permeability of free space. Indicates the equivalent conductivity of a conductor. Indicates skin depth.

10. A grounding grid corrosion status assessment system, characterized in that, The system includes: Data acquisition unit: used to acquire the PEC received signal and EIS differential response signal of the conductor of the grounding grid under test as raw signals based on the integrated flexible array probe, and preprocess the raw signals to obtain valid input samples; Feature extraction unit: used to extract features from the valid input samples to obtain a standardized feature set; Data analysis unit: used to divide the standardized feature set into several uncoupled subsets, divide the depth direction into several depth layers based on the skin depth mapping based on the subsets, and obtain the homogenized volume loss rate based on the homogenization calibration of the integral loss and electrochemical parameters of each depth layer; obtain the pitting risk and eccentricity coefficient based on the pitting morphology characteristics, and trigger the warning flag when the eccentric pitting risk exceeds the standard. Based on the homogenized volume loss rate and pitting risk, a baseline damage component is constructed, and the weight of each damage component is assigned according to the morphological confidence vector of the subset to obtain the comprehensive corrosion damage factor. A two-dimensional classification matrix is ​​generated based on the comprehensive corrosion damage factor and the early warning flag, and the corresponding corrosion degree level is output. The remaining lifespan range is calculated based on the comprehensive corrosion damage factor and the corrosion rate.

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