Crosslinked polyethylene cable insulation aging risk assessment method

Abstract

The invention discloses a crosslinked polyethylene cable insulation aging risk assessment method, and relates to the field of cable insulation aging assessment, and the method comprises the steps: setting an electric field induction array to carry out the high-speed sampling of a dynamic electric field signal, and carrying out the complementation and space correction of the preprocessed electric field signal data; fourier decomposition is carried out on the high-frequency standing wave field signal, spatial and temporal changes of electric field distribution are simulated, a standing wave and direct-current electric field superposition model is established, and spatial and temporal changes of a hot spot area are captured; an electric field intensity dynamic peak hot spot track in the superposition strengthening area is analyzed, the migration speed and the residence time of a dynamic peak hot spot are quantified, and quantitative description is provided for dynamic evolution characteristics of the risk area; analyzing the local aging degree of the risk area, and evaluating the trend of a chain reaction caused by local aging in combination with the dynamic evolution characteristics of the peak hot spot of each risk area; and carrying out risk degree calibration on the cable insulation aging trend based on a chain reaction trend evaluation result.

Description

Technical Field

[0001] The invention relates to the field of cable insulation aging assessment, and in particular to a method for assessing the aging risk of cross-linked polyethylene cable insulation. Background Art

[0002] The aging of cross-linked polyethylene (XLPE) cable insulation is usually accompanied by a complex dynamic process of local electric field distortion, hot spot migration, and electrical aging chain reaction. These phenomena not only affect the reliability of the cable, but may also cause equipment failure and power system accidents. Therefore, it is of great significance to assess the danger of aging trends in XLPE cable insulation. In the scenario of AC and DC collaborative operation, the superposition of the standing wave effect of AC and the DC electric field will further aggravate the distortion of the electric field intensity in the local area and form dynamic peak hot spots. The migration speed and residence time of these hot spots directly determine the dynamic evolution characteristics of the risk area. Traditional insulation aging assessment methods are mostly based on local discharge detection or analysis of static electric field distribution, which makes it difficult to capture the temporal and spatial variation characteristics of the electric field during cable operation.

[0003] Therefore, how to achieve a comprehensive assessment of the aging chain reaction trend by quantifying the migration speed and residence time of dynamic peak hotspots and combining it with the local aging degree analysis of risk areas is an urgent problem that needs to be solved. Summary of the invention

[0004] In order to solve the above technical problems, a method for assessing the aging risk of cross-linked polyethylene cable insulation is provided. This technical solution solves the problems raised in the above background technology.

[0005] In order to achieve the above purpose, the technical solution adopted by the present invention is:

[0006] A method for assessing the aging risk of cross-linked polyethylene cable insulation, comprising:

[0007] An electric field sensing array is set up to perform high-speed sampling of dynamic electric field signals, and to perform completion and spatial correction on pre-processed electric field signal data;

[0008] Perform Fourier decomposition on high-frequency standing wave field signals, simulate the temporal and spatial changes of electric field distribution, establish a standing wave and DC electric field superposition model, and capture the temporal and spatial changes of hot spots;

[0009] Analyze the hot spot trajectory of the dynamic peak of the electric field intensity in the superimposed enhancement area, quantify the migration speed and residence time of the dynamic peak hot spot, and provide a quantitative description of the dynamic evolution characteristics of the risk area;

[0010] Analyze the degree of local aging in risk areas and evaluate the trend of chain reactions caused by local aging based on the dynamic evolution characteristics of the peak hotspots in each risk area;

[0011] Based on the chain reaction trend assessment results, the hazard level of the cable insulation aging trend is calibrated.

[0012] Preferably, the setting of the electric field sensing array to perform high-speed sampling of the dynamic electric field signal and the completion and spatial correction of the pre-processed electric field signal data specifically include:

[0013] An array of electric field sensing devices is arranged at multiple points on the outer insulation surface of the cable and inside the cable, and each optical fiber electric field sensing device senses the local electric field intensity through the electro-optical effect;

[0014] The acquisition device is connected to the time synchronization module for time calibration to unify the time base of all electric field sensing devices;

[0015] The high-speed sampling frequency is set to perform high-speed sampling on the dynamic electric field signal. The collected initial signal is stored in the form of a time series. The signal includes the instantaneous value of the electric field intensity and the three-dimensional coordinate information of the spatial position;

[0016] Clear the high-frequency noise and low-frequency interference of the collected initial signal, and dynamically adjust the gain of the low-amplitude signal. The low-amplitude signal captures the micro-electric field fluctuation of the collected initial signal;

[0017] An interpolation algorithm is used to complete the data in the uncovered area. At the same time, the electric field signal is spatially corrected according to the cable geometry and insulation layer characteristics to make the data distribution consistent with the actual physical structure of the cable.

[0018] Preferably, the Fourier decomposition of the high-frequency standing wave field signal, simulation of the spatiotemporal variation of the electric field distribution, establishment of a standing wave and direct current electric field superposition model, and capturing the spatiotemporal variation of the hot spot area specifically include:

[0019] Perform Fourier decomposition on the high-frequency standing wave field signal, decompose it into the fundamental wave and a set number of high-frequency harmonic components, extract the amplitude and phase information of each harmonic, calculate its distribution characteristics in space, and simulate the transient change characteristics of the standing point of the standing wave;

[0020] Obtain the insulation material of the cross-linked polyethylene cable and determine the dielectric constant and conductivity characteristics of the insulation material;

[0021] The actual distribution data of space charge is obtained through pulse voltage excitation, and the dynamic diffusion of charge in insulating materials is simulated by finite element method, and the migration and accumulation process of space charge is simulated in real time.

[0022] Taking time domain and space as variables, the dynamic diffusion distribution of the DC field and the dynamic change characteristics of the standing wave field are combined to generate a global dynamic electric field distribution model in the insulation layer;

[0023] In the global dynamic electric field distribution model, the overlap of the charge retention area and the standing wave point of the AC field leads to significant enhancement of the spatial information of the local electric field, and the standing wave point distribution area corresponding to the spatial information is marked as the superposition enhancement area.

[0024] Preferably, the analysis of the dynamic peak hot spot trajectory of the electric field intensity in the superimposed strengthening area, quantifying the migration speed and residence time of the dynamic peak hot spot, and providing a quantitative description of the dynamic evolution characteristics of the risk area specifically includes:

[0025] The electric field model is divided into equally spaced grids, the electric field intensity in each grid is scanned, the local maximum is extracted, and the Gaussian noise filtering algorithm is used to eliminate the false peaks that may be introduced by the model error;

[0026] The local peak point at each acquisition time point is combined with the location of its spatial coordinate mark and associated with its intensity value to form a dynamic peak hot spot trajectory of the electric field intensity in the superimposed enhancement area;

[0027] Based on the global dynamic electric field distribution model, the global electric field mean is calculated for all grid point data at each time point;

[0028] Based on the dynamic peak hot spot trajectory and the global electric field mean value extracted above, the dynamic enhancement amplification factor of the superimposed enhancement area at each time point is calculated, and the enhancement amplification factor is integrated in the time dimension to generate a time series curve of the enhancement amplification factor;

[0029] Set the risk threshold of the enhanced amplification factor, dynamically mark the high-risk locations that exceed the risk threshold in the time series curve, and define the risk area based on the spatial distribution trajectory;

[0030] The migration speed and residence time of dynamic peak hotspots in risk areas are recorded to provide a quantitative description of the dynamic evolution characteristics of peak hotspots in risk areas.

[0031] Preferably, the analyzing the local aging degree of the risk area and evaluating the trend of the chain reaction caused by the local aging in combination with the dynamic evolution characteristics of the peak hotspots of each risk area specifically includes:

[0032] Use an infrared thermal imager to measure the surface temperature distribution of the designated risk area, calculate the deviation between the average temperature of the risk area and the safe operating temperature of the insulation material, and calculate the thermal cumulative aging degree score;

[0033] Extract the discharge intensity data of the risk area from the discharge detection device, including the discharge amplitude and discharge frequency, define the discharge activity energy per unit time based on the discharge amplitude and discharge frequency, and calculate the discharge aging degree score;

[0034] Perform weighted comprehensive calculation on the thermal accumulation aging degree score and the discharge aging degree score to obtain the comprehensive local aging degree of the risk area;

[0035] According to the residence time of dynamic peak hotspots in the risk area, the cumulative impact of hotspots on local aging is evaluated. The time expansion range of the risk area is predicted according to the migration speed of the hotspots. The comprehensive aging degree of the extended area is integrated in time and space, and the integration results are recorded and marked as the aging chain reaction trend assessment value.

[0036] Preferably, the risk level calibration of the cable insulation aging trend based on the chain reaction trend assessment result specifically includes:

[0037] Obtain the aging chain reaction trend assessment values ​​of all risk areas and define the hazard gradient for the aging chain reaction trend assessment values;

[0038] Based on the hazard gradient delineation results, the risk area is calibrated for aging hazard level, and the cable insulation is repaired according to the calibration results.

[0039] Compared with the prior art, the present invention has the following beneficial effects:

[0040] By setting up an electric field sensing array to sample the dynamic electric field signal at high speed, and performing Fourier decomposition on the high-frequency standing wave field signal, (FDTD) simulates the spatiotemporal changes of the electric field distribution, and accurately captures the dynamic behavior characteristics of the hot spot area under the superposition of standing waves and DC electric fields. By quantifying the migration speed and residence time of the dynamic peak hot spots, combined with the analysis of the local aging degree of the risk area, a comprehensive assessment of the aging chain reaction trend can be achieved. Based on the above assessment results, the danger level of the insulation aging trend of the XLPE cable is calibrated, which can not only provide a scientific basis for the operation and maintenance of the cable, but also effectively improve the operation safety and stability of the power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 A flow chart of a method for assessing the aging risk of cross-linked polyethylene cable insulation according to the present invention

[0042] Figure 2 A flow chart of setting up an electric field sensing array to perform high-speed sampling of dynamic electric field signals, and performing completion and spatial correction on pre-processed electric field signal data;

[0043] Figure 3 The present invention performs Fourier decomposition on high-frequency standing wave field signals, simulates the spatiotemporal changes of electric field distribution, establishes a standing wave and DC electric field superposition model, and captures the spatiotemporal changes of hot spot areas;

[0044] Figure 4The dynamic peak hot spot trajectory of the electric field intensity in the superimposed strengthening area of ​​the present invention is analyzed, the migration speed and residence time of the dynamic peak hot spot are quantified, and a quantitative description flow chart is provided for the dynamic evolution characteristics of the risk area;

[0045] Figure 5 A flow chart of analyzing the local aging degree of a risk area and evaluating the trend of a chain reaction caused by local aging in combination with the dynamic evolution characteristics of the peak hotspots of each risk area according to the present invention;

[0046] Figure 6 The present invention provides a flow chart for calibrating the risk level of cable insulation aging trends based on the chain reaction trend assessment results. DETAILED DESCRIPTION

[0047] The following description is used to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments described below are only examples, and those skilled in the art may think of other obvious variations.

[0048] Reference Figure 1 As shown, a method for assessing the aging risk of cross-linked polyethylene cable insulation comprises:

[0049] An electric field sensing array is set to perform high-speed sampling of dynamic electric field signals, and to complete and spatially correct the pre-processed electric field signal data;

[0050] Perform Fourier decomposition on high-frequency standing wave field signals, simulate the temporal and spatial changes of electric field distribution, establish a standing wave and DC electric field superposition model, and capture the temporal and spatial changes of hot spots;

[0051] Analyze the dynamic peak hotspot trajectories of the electric field intensity in the superimposed enhancement area, quantify the migration speed and residence time of the dynamic peak hotspots, and provide a quantitative description of the dynamic evolution characteristics of the risk area;

[0052] Analyze the degree of local aging in risk areas and evaluate the trend of chain reactions caused by local aging based on the dynamic evolution characteristics of the peak hotspots in each risk area;

[0053] Based on the chain reaction trend assessment results, the hazard level of the cable insulation aging trend is calibrated.

[0054] Reference Figure 2 As shown, a method for assessing the aging risk of cross-linked polyethylene cable insulation is provided, wherein an electric field sensing array is set to perform high-speed sampling of dynamic electric field signals, and the pre-processed electric field signal data is supplemented and spatially corrected, specifically including:

[0055] An array of electric field sensing devices is arranged at multiple points on the outer insulation surface of the cable and inside the cable. Each optical fiber electric field sensing device senses the local electric field strength through the electro-optical effect. The array of electric field sensing devices must cover the key areas of the cable to ensure the global collection of dynamic electric field signals and achieve high-precision detection of complex electric field distribution in the cable.

[0056] The acquisition device is connected to the time synchronization module for time calibration, the time base of all electric field sensing devices is unified, and a high-precision time synchronization module (such as GPS or PTP protocol) is used to connect to the optical fiber sensing device to record the timestamp of each sampling point so that the time accuracy reaches ±1 microsecond. Each sensing device performs sampling based on a unified time base, which effectively eliminates the impact of equipment time deviation on signal comparison and ensures data time consistency.

[0057] The high-speed sampling frequency is set to perform high-speed sampling on the dynamic electric field signal. The collected initial signal is stored in the form of a time series. The signal includes the instantaneous value of the electric field intensity and the three-dimensional coordinate information of the spatial position. The sampling frequency is set to f s =10MHZ, the electric field time series signal is E AC (t,x,y,z) represents that t is the acquisition time potential under the set sampling frequency, and x, y, z are the three-dimensional coordinate information of the spatial position of the electric field signal.

[0058] After the high-frequency noise and low-frequency interference of the signal are removed through optimization processing, the dynamic gain adjustment technology can capture the weak low-amplitude signal micro-electric field fluctuations and realize accurate detection of micro-electric field fluctuations.

[0059] An interpolation algorithm is used to complete the data in uncovered areas. At the same time, the electric field signal is spatially corrected according to the cable geometry and insulation layer characteristics, so that the data distribution is consistent with the actual physical structure of the cable (i.e., spatial position). This enables high-precision acquisition and processing of full-process data, provides high-quality data support for electric field distribution modeling, risk area identification, and aging trend analysis, and significantly improves the accuracy and reliability of cable insulation monitoring.

[0060] Reference Figure 3 As shown in the figure, the high-frequency standing wave field signal is decomposed by Fourier, the temporal and spatial changes of the electric field distribution are simulated, and the standing wave and DC electric field superposition model is established to capture the temporal and spatial changes of the hot spot area. Specifically, it includes:

[0061] The high-frequency standing wave field signal is decomposed by Fourier, and it is disassembled into the fundamental wave and a set number of high-frequency harmonic components. By extracting the amplitude and phase information of each harmonic, its distribution characteristics in space are calculated to simulate the transient change characteristics of the standing wave stationary point, specifically:

[0062] For the dynamic electric field signal E AC(t) Perform fast Fourier transform to obtain frequency domain representation: f is the frequency of each harmonic in the corresponding electric field signal, Represents the electric field intensity component at frequency f.

[0063] The spatial distribution simulation synthesis formula of fundamental wave and harmonic wave is:

[0064]

[0065] In the formula, A n is the amplitude of the nth harmonic, f n is the frequency of the nth harmonic, is the phase of the nth harmonic, k n is the wave number ( λ is the wavelength).

[0066] Obtain cross-linked polyethylene cable insulation material and determine the dielectric constant and conductivity characteristics of the insulation material.

[0067] The actual distribution data of space charge is obtained through pulse voltage excitation. The dynamic diffusion of charge in insulating materials is simulated by finite element method. The migration and accumulation process of space charge is simulated in real time. The dynamic diffusion of space charge satisfies the charge migration equation: Among them, ρ is the space charge density, μ is the charge mobility, which indicates the mobility of charge under the action of electric field, E is the electric field strength, and D is the diffusion coefficient, which is measured in square meters per second and indicates the ability of charge to diffuse due to concentration gradient. Based on the dynamic diffusion of space charge, the space charge corresponding to the electric field distribution is annotated with E DC (t,x) represents.

[0068] Taking time domain and space as variables, the dynamic diffusion distribution of the DC field is combined with the dynamic change characteristics of the standing wave field to generate the global dynamic electric field distribution model E in the insulating layer. total (t,x),E total (t,x)=E AC (t,x)+E DC (t,x).

[0069] In the global dynamic electric field distribution model, the overlap of the charge retention region and the AC field standing wave stationary point leads to a significant enhancement of the local electric field. AC (t,x) and E DC9 t,x) and E total In the area where (t, x) exceeds the average value of the electric field strength by 50% or more, the standing wave stagnation point distribution area corresponding to the spatial information is marked as the superposition enhancement area.

[0070] Reference Figure 4As shown in the figure, the dynamic peak hot spot trajectory of the electric field intensity in the superimposed enhancement area is analyzed, the migration speed and residence time of the dynamic peak hot spot are quantified, and a quantitative description of the dynamic evolution characteristics of the risk area is provided. Specifically, it includes:

[0071] The electric field model is divided into equally spaced grids, the electric field intensity in each grid is scanned, and the local maximum is extracted. peak 9 r, θ, z) are represented by r, θ, z are the corresponding spatial coordinates. The Gaussian noise filtering algorithm is used to eliminate the false peaks that may be introduced by the model error. By scanning the local maximum values ​​in the grid, the possible electric field hotspots are determined, laying the foundation for the subsequent dynamic analysis.

[0072] The local peak point at each acquisition time point is combined with the location of its spatial coordinate mark and associated with its intensity value to form the dynamic peak hot spot trajectory of the electric field intensity in the superimposed enhancement area, specifically:

[0073] For each acquisition time point t i , mark the spatial coordinates of the local peak point (r peak ,θ peak ,z peak ) and intensity E peak (t i ), and associate the peak information at each time point to form a dynamic trajectory dataset TR peak , N is the total number of sampling time points.

[0074] Based on the global dynamic electric field distribution model, the global electric field mean is calculated for all grid point data at each time point. E(r,θ,z,t i ) is the spatial coordinate (r,θ,z) at time t i The electric field strength at .

[0075] Based on the dynamic peak hotspot trajectory and global electric field mean extracted above, the dynamic enhancement amplification coefficient of the superimposed enhancement area at each time point is calculated, and the enhancement amplification coefficient is integrated in the time dimension to generate a time series curve of the enhancement amplification coefficient, wherein the dynamic enhancement amplification coefficient is calculated as the ratio of the electric field intensity corresponding to the dynamic peak hotspot trajectory of the electric field intensity in the time series to the global electric field mean.

[0076] Based on the dielectric constant and conductivity characteristics of the insulating material, the risk threshold of the enhanced amplification factor is set in combination with the specific value of the enhanced amplification factor. The high-risk positions that exceed the risk threshold in the time series curve are dynamically marked in time, and the risk area is delineated in combination with the spatial distribution trajectory.

[0077] The migration speed and residence time of dynamic peak hotspots in the risk area are recorded to provide a quantitative description of the dynamic evolution characteristics of the peak hotspots in the risk area. The migration speed of the dynamic peak hotspots is calculated by dividing the spatial displacement of adjacent time points by the time interval. The Euclidean distance of the hotspot positions is calculated for any two adjacent time points. The migration speed value of each time interval is stored and used to analyze the hotspot migration law and define a specific range within the risk area. That is, when the electric field strength and position of the peak hotspot meet specific conditions at the same time, it is recorded as residence.

[0078] Reference Figure 5 As shown in the figure, the local aging degree of the risk area is analyzed, and the trend of chain reaction caused by local aging is evaluated in combination with the dynamic evolution characteristics of the peak hotspots in each risk area. Specifically, the following are included:

[0079] The surface temperature distribution of the designated risk area is measured using an infrared thermal imager, and the deviation between the average temperature of the risk area and the safe operating temperature of the insulation material is calculated. The thermal cumulative aging degree score is calculated as follows:

[0080] Use a high-resolution infrared thermal imager (e.g. 640×480 pixels) to scan the surface temperature of the designated risk area, generate a two-dimensional temperature distribution map, and calculate the average temperature within the risk area. T(x,y,z) is the temperature at x,y,z in the risk area, in °C, R is the spatial extent of the risk area, A R is the area of ​​the risk zone.

[0081] A thermal accumulation aging experiment is carried out on the insulation layer material to set the thermal aging weight factor. The thermal aging weight factor and the temperature deviation are multiplied by the time that the temperature in the risk area exceeds the safe operating temperature. The result is used as the thermal accumulation aging degree score.

[0082] The discharge intensity data of the risk area is extracted from the discharge detection device, including the discharge amplitude and discharge frequency. The discharge activity energy per unit time is defined based on the discharge amplitude and discharge frequency, and the discharge aging degree score is calculated as follows:

[0083] Extracting the discharge amplitude Q from the discharge detection device pd (t) and discharge frequency f pd (t), then the corresponding discharge activity energy per unit time is defined as E pd (t) should be calculated as: E pd (t) = Q pd (t)*f pd(t), the discharge activity energy is integrated within the total discharge detection time, and the discharge aging weight factor is set based on the dielectric constant and conductivity of the insulating material. A higher dielectric constant has a stronger resistance to discharge and should be given a lower weight. A higher conductivity is easy to form a conductive path, which aggravates aging and should be given a higher weight. The specific setting is measured by experiments and will not be repeated here.

[0084] The product of the discharge activity energy integration result within the total discharge detection time and the discharge aging weight factor is used as the discharge aging score.

[0085] The thermal accumulation aging degree score and the discharge aging degree score are normalized to unity and weighted comprehensive calculation is performed to obtain the comprehensive local aging degree of the risk area. local express.

[0086] According to the residence time of the dynamic peak hot spot in the risk area, the cumulative impact of the hot spot on local aging is evaluated. risk (t) = S local *t stay , t stay Assuming that the dynamic peak hotspot migrates at an average speed v, the time expansion range R of the risk area is predicted based on the hotspot migration speed. spread (t), R spread (t) = R risk (t)+v*t.

[0087] The comprehensive aging degree of the extended area is integrated in time and space, and the integration result is recorded and marked as the aging chain reaction trend evaluation value. The calculation expression of the aging chain reaction trend evaluation value is: A cum (t) is the comprehensive local aging degree at time t, S local (w, t) is the local aging score of position w at time t, the critical value of aging growth rate Th is set, and the aging chain reaction trend evaluation value at time t is calculated Screen out the aging chain reaction trend assessment value greater than or equal to the aging growth rate critical value Th (i.e. ) danger zone.

[0088] Reference Figure 6 As shown in the figure, based on the chain reaction trend assessment results, the hazard level calibration of the cable insulation aging trend specifically includes:

[0089] Obtain the aging chain reaction trend assessment values ​​of all risk areas, and divide the aging chain reaction trend assessment values ​​of risk areas into multiple gradients, such as low risk, medium risk, high risk and extremely high risk. Each gradient represents a different intensity of aging, reflecting the state of risk areas from slight aging to possible insulation failure. The division of dangerous gradients is based on experimental data, engineering experience, and actual dynamic characteristics of risk areas, such as changes in temperature, discharge activity intensity, and dynamic peak hot spots. The threshold can be adjusted according to the cable material characteristics and usage scenarios.

[0090] Based on the results of the hazard gradient delineation, the aging hazard level of the risk area is calibrated, and the cable insulation is repaired according to the calibration results. According to the hazard level, high-risk and extremely high-risk areas are treated first. These areas are usually where dynamic hotspots migrate, stay for a long time, or have obvious expansion trends. After the repair is completed, the electric field strength, temperature distribution, and discharge activity of the repaired area are tested to verify whether it has returned to a safe range.

[0091] Furthermore, the present solution also proposes a storage medium for a method for assessing the aging risk of insulation of a cross-linked polyethylene cable, on which a computer-readable program is stored. When the computer-readable program is called, the above-mentioned method for assessing the aging risk of insulation of a cross-linked polyethylene cable is executed.

[0092] It is understandable that the storage medium may be a magnetic medium, such as a floppy disk, a hard disk, or a magnetic tape; an optical medium, such as a DVD; or a semiconductor medium, such as a solid state drive (SSD).

[0093] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions only describe the principles of the present invention. The present invention may be subject to various changes and improvements without departing from the spirit and scope of the present invention. These changes and improvements fall within the scope of the present invention. The scope of protection claimed by the present invention is defined by the attached claims and their equivalents.

Claims

1. A method for assessing the aging risk of cross-linked polyethylene cable insulation, characterized in that: include: An electric field sensing array is set up to perform high-speed sampling of dynamic electric field signals, and to perform completion and spatial correction on pre-processed electric field signal data; Perform Fourier decomposition on high-frequency standing wave field signals, simulate the temporal and spatial changes of electric field distribution, establish a standing wave and DC electric field superposition model, and capture the temporal and spatial changes of hot spots; Analyze the hot spot trajectory of the dynamic peak of the electric field intensity in the superimposed enhancement area, quantify the migration speed and residence time of the dynamic peak hot spot, and provide a quantitative description of the dynamic evolution characteristics of the risk area; Analyze the degree of local aging in risk areas and evaluate the trend of chain reactions caused by local aging based on the dynamic evolution characteristics of the peak hotspots in each risk area; Based on the chain reaction trend assessment results, the hazard level of the cable insulation aging trend is calibrated.

2. A method for assessing the aging risk of cross-linked polyethylene cable insulation according to claim 1, characterized in that: The setting of the electric field sensing array to perform high-speed sampling of the dynamic electric field signal and the completion and spatial correction of the pre-processed electric field signal data specifically include: An array of electric field sensing devices is arranged at multiple points on the outer insulation surface of the cable and inside the cable, and each optical fiber electric field sensing device senses the local electric field intensity through the electro-optical effect; The acquisition device is connected to the time synchronization module for time calibration to unify the time base of all electric field sensing devices; The high-speed sampling frequency is set to perform high-speed sampling on the dynamic electric field signal. The collected initial signal is stored in the form of a time series. The signal includes the instantaneous value of the electric field intensity and the three-dimensional coordinate information of the spatial position; Clear the high-frequency noise and low-frequency interference of the collected initial signal, and dynamically adjust the gain of the low-amplitude signal. The low-amplitude signal captures the micro-electric field fluctuation of the collected initial signal; An interpolation algorithm is used to complete the data in the uncovered area. At the same time, the electric field signal is spatially corrected according to the cable geometry and insulation layer characteristics to make the data distribution consistent with the actual physical structure of the cable.

3. A method for assessing the aging risk of cross-linked polyethylene cable insulation according to claim 2, characterized in that: The Fourier decomposition of the high-frequency standing wave field signal, simulation of the spatiotemporal changes of the electric field distribution, establishment of a standing wave and DC electric field superposition model, and capture of the spatiotemporal changes of the hot spot area specifically include: Perform Fourier decomposition on the high-frequency standing wave field signal, decompose it into the fundamental wave and a set number of high-frequency harmonic components, extract the amplitude and phase information of each harmonic, calculate its distribution characteristics in space, and simulate the transient change characteristics of the standing point of the standing wave; Obtain the insulation material of the cross-linked polyethylene cable and determine the dielectric constant and conductivity characteristics of the insulation material; The actual distribution data of space charge is obtained through pulse voltage excitation, and the dynamic diffusion of charge in insulating materials is simulated by finite element method, and the migration and accumulation process of space charge is simulated in real time. Taking time domain and space as variables, the dynamic diffusion distribution of the DC field and the dynamic change characteristics of the standing wave field are combined to generate a global dynamic electric field distribution model in the insulation layer; In the global dynamic electric field distribution model, the overlap of the charge retention area and the standing wave point of the AC field leads to significant enhancement of the spatial information of the local electric field, and the standing wave point distribution area corresponding to the spatial information is marked as the superposition enhancement area.

4. A method for assessing the aging risk of cross-linked polyethylene cable insulation according to claim 3, characterized in that: The analysis superimposes and strengthens the dynamic peak hot spot trajectory of the electric field intensity in the area, quantifies the migration speed and residence time of the dynamic peak hot spot, and provides a quantitative description of the dynamic evolution characteristics of the risk area, specifically including: The electric field model is divided into equally spaced grids, the electric field intensity in each grid is scanned, the local maximum is extracted, and the Gaussian noise filtering algorithm is used to eliminate the false peaks that may be introduced by the model error; The local peak point at each acquisition time point is combined with the location of its spatial coordinate mark and associated with its intensity value to form a dynamic peak hot spot trajectory of the electric field intensity in the superimposed enhancement area; Based on the global dynamic electric field distribution model, the global electric field mean is calculated for all grid point data at each time point; Based on the dynamic peak hot spot trajectory and the global electric field mean value extracted above, the dynamic enhancement amplification factor of the superimposed enhancement area at each time point is calculated, and the enhancement amplification factor is integrated in the time dimension to generate a time series curve of the enhancement amplification factor; Set the risk threshold of the enhanced amplification factor, dynamically mark the high-risk locations that exceed the risk threshold in the time series curve, and define the risk area based on the spatial distribution trajectory; The migration speed and residence time of dynamic peak hotspots in risk areas are recorded to provide a quantitative description of the dynamic evolution characteristics of peak hotspots in risk areas.

5. A method for assessing the aging risk of cross-linked polyethylene cable insulation according to claim 4, characterized in that: The analysis of the local aging degree of the risk area and the evaluation of the trend of the chain reaction caused by local aging in combination with the dynamic evolution characteristics of the peak hotspots in each risk area specifically include: Use an infrared thermal imager to measure the surface temperature distribution of the designated risk area, calculate the deviation between the average temperature of the risk area and the safe operating temperature of the insulation material, and calculate the thermal cumulative aging degree score; Extract the discharge intensity data of the risk area from the discharge detection device, including the discharge amplitude and discharge frequency, define the discharge activity energy per unit time based on the discharge amplitude and discharge frequency, and calculate the discharge aging degree score; Perform weighted comprehensive calculation on the thermal accumulation aging degree score and the discharge aging degree score to obtain the comprehensive local aging degree of the risk area; According to the residence time of dynamic peak hotspots in the risk area, the cumulative impact of hotspots on local aging is evaluated. The time expansion range of the risk area is predicted according to the migration speed of the hotspots. The comprehensive aging degree of the extended area is integrated in time and space, and the integration results are recorded and marked as the aging chain reaction trend assessment value.

6. A method for assessing the aging risk of cross-linked polyethylene cable insulation according to claim 5, characterized in that: The hazard level calibration of the cable insulation aging trend based on the chain reaction trend assessment result specifically includes: Obtain the aging chain reaction trend assessment values ​​of all risk areas and define the hazard gradient for the aging chain reaction trend assessment values; Based on the hazard gradient delineation results, the risk area is calibrated for aging hazard level, and the cable insulation is repaired according to the calibration results.

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