Cable life evaluation device and method based on interdigital sensing
By acquiring the dissipation factor and capacitance signals of the cable using interdigitated sensors and combining them with an intelligent evaluation model, the problem of inaccurate cable life assessment is solved, enabling rapid and accurate cable life prediction and improving the screening efficiency and reuse value of waste cables.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-11-25
- Publication Date
- 2026-03-10
AI Technical Summary
Existing technologies lack portable sensing devices that can simultaneously and non-contactly obtain information on the aging degree and mechanical damage of cable insulation materials, resulting in inaccurate cable life assessments and making it difficult to achieve rapid screening and efficient reuse of waste cables.
Interdigitated sensors are used to acquire the dissipation factor and capacitance signals of the cable. The signals are then processed using an LCR digital bridge and a processor. The K-nearest neighbor algorithm and decision tree regression model are used for evaluation, and the damage state and aging degree are fused to predict the cable life.
It enables comprehensive diagnosis of cable aging and damage, with fast detection speed and high accuracy, reducing the risk of misjudgment and improving the screening efficiency and economic benefits of waste cable reuse.
Smart Images
Figure CN121633710A_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of cable life assessment technology, and particularly relates to a cable life assessment device and method based on interdigital sensing. Background Technology
[0002] With the continuous expansion of the power grid and the accelerated pace of equipment upgrades, power companies generate a large number of obsolete power cables each year due to line renovations, decommissioning due to faults, or reaching their preset service life. A significant portion of these cables still possess good overall insulation performance and have extremely high recycling value. Rapid and accurate lifespan assessment and screening of qualified cables would greatly promote the recycling of power resources, aligning with the national strategy of green, low-carbon, and sustainable development, while also saving power companies considerable material procurement costs. However, current methods for testing and assessing obsolete cables face significant bottlenecks. Traditional laboratory testing methods, such as breakdown tests, while accurate, are destructive, time-consuming, labor-intensive, and costly, making them unsuitable for large-scale on-site screening. Existing on-site testing equipment, such as handheld insulation resistance testers, have limited measurement parameters and often fail to comprehensively and accurately reflect the aging state of cable insulation and potential localized defects, easily leading to misjudgments. This results in power companies often resorting to a "one-size-fits-all" scrapping approach due to a lack of efficient and reliable screening tools, causing a huge waste of resources.
[0003] Ultimately, the lifespan of a cable is primarily determined by the aging of its insulation material and the extent of mechanical damage. The dielectric dissipation factor sensitively reflects the overall aging of the insulation material due to electrical and thermal stress, while changes in capacitance are closely related to moisture absorption, water tree growth, or physical damage. Current technological challenges include: first, the lack of a portable sensing device capable of simultaneously, non-contactly, and in-situ acquiring these two key characteristic parameters; and second, the lack of an intelligent assessment model that can accurately correlate multi-dimensional measurement information with the remaining cable lifespan. Therefore, there is an urgent need in this field for a cable lifespan assessment technology and device that is applicable to field environments, offers fast detection speeds, and provides high assessment accuracy. This would enable rapid preliminary screening of massive quantities of waste cables, accurately determine their reusability, and significantly improve the efficiency and economic benefits of cable recycling. Summary of the Invention
[0004] The purpose of this invention is to provide a cable life assessment device and method based on interdigital sensing, which aims to solve the problems mentioned in the background art.
[0005] This invention is implemented as follows: a cable life assessment device based on interdigital sensing, comprising: The signal sensing unit includes interdigitated capacitor plates that can be coupled to the power cable under test to simultaneously acquire the dissipation factor reflecting the aging state of the cable. Signal and capacitance value reflecting cable damage status Signal; The signal processing unit, connected to the signal sensing unit, includes an LCR digital bridge for processing signals. Signals and The signal is measured and processed, and output at different frequencies. Measured values and capacitance values Measured value; The processor, connected to the signal processing unit via a data acquisition card, includes a data preprocessing and evaluation unit, an aging evaluation module, and a lifespan pre-evaluation module. The data preprocessing and evaluation unit receives data... Measured values and Measured values and used the K-Nearest Neighbors (KNN) algorithm. The measured values are processed to determine the cable's damage condition; the aging assessment module is used to combine prior knowledge to analyze the values measured at different frequencies. The measured values are linearly compensated and corrected, and the aging assessment results of the cable are output using a trained decision tree (DT) regression model; the life pre-assessment module is used to integrate the damage state and aging assessment results.
[0006] In a further technical solution, the interdigitated capacitor plate includes an insulating substrate, on which a first electrode group and a second electrode group are disposed. The first electrode group includes at least two parallel and electrically interconnected first interdigitated electrodes, and the second electrode group is staggered with the first electrode group, including at least two parallel and electrically interconnected second interdigitated electrodes. The first electrode group and the second electrode group are insulated from each other, forming a staggered capacitor structure. The first electrode group and the second electrode group constitute the main sensing area, and the finger strip width of the main sensing area and gap Satisfying the relation Used for high-precision sensing in the low-frequency band of 0.1 Hz-1 kHz. Signal; An auxiliary sensing area is also provided on the insulating substrate. The electrode strips of the auxiliary sensing area are electrically isolated from the electrodes of the main sensing area. The width of the strips in the auxiliary sensing area is... And the gap between the fingers Used for high-sensitivity sensing in the 1 kHz-100 kHz high-frequency band. The changes.
[0007] A further technical solution is that the measurement frequency range of the LCR digital bridge is set from 0.1 Hz to 100 kHz, and a frequency sweep mode is used to automatically acquire at least three discrete frequency points. and .
[0008] A further technical solution involves the data preprocessing and evaluation unit determining the cable's damage status as follows: Construct a sample library of cable capacitance values containing known damage states, including "intact", "minor damage" and "severe damage"; For real-time measured multi-frequency capacitance value vector ,in For frequency The measured capacitance value is calculated and compared with the value of the first sample in the sample library. Sample Weighted Euclidean distance The calculation formula is: ; in, Representing the Each measurement frequency, To measure frequency The relevant weighting coefficients, and satisfy the following conditions For high-frequency signals that are more sensitive to damage, Larger value; select the one with the smallest distance. The cable damage status corresponding to the real-time measured capacitance value is determined by using a nearest neighbor sample and a majority voting method.
[0009] A further technical solution is that the linear compensation correction method in the aging assessment module is specifically as follows: Obtain prior knowledge about the cable under test, including cable type and insulation material; based on this prior knowledge, retrieve the corresponding information from the standard database. Baseline curve For the actual measurement curve Perform compensation correction to obtain the corrected result. value The correction formula is: ; in, For the selected reference frequency, For the current frequency, The compensation factor is related to the cable type. To select a frequency The actual measurement below curve, To select a frequency Down Correction value.
[0010] Further technical solutions, including training methods for the DT regression model, include: After linear compensation and correction, at different frequencies value As input features: ; in, In frequency Down Correction value; The actual aging degree of the cable corresponding to the input features is used as the target variable. A regression tree is constructed using the CART algorithm, and features are selected when nodes split. and threshold The cost function is to minimize the weighted mean square error (MSE) after splitting. for: ; in, This is the number of samples in the current node. and These are the sample numbers of the left and right child nodes after the split, respectively; The output value of this node during the prediction phase can be calculated as follows: ; in, It is the average of the squared differences between the true values and the predicted values of all samples within a given node. This represents the number of training samples contained in the current tree node. For the current node The true target value corresponding to each training sample. The true target value for all training samples within the current node. The arithmetic mean of the values is used as the predicted output value for any new sample falling to that node.
[0011] Another objective of this invention is to provide a cable life assessment method based on interdigital sensing, which, based on the aforementioned assessment device, includes the following steps: Step 1: Couple the interdigitated capacitor plates to the cable under test, and measure at multiple frequencies using an LCR digital bridge. Value and capacitance value ; Step 2: Process capacitance values using the KNN algorithm To determine the damage condition of the cable; Step 3: Based on prior knowledge of cables, [the following steps are taken]... The measured values are subjected to linear compensation correction; Step 4: Compensate and correct The values are input into a pre-trained DT regression model to obtain the aging assessment results of the cable; Step 5: Combine the results of the damage assessment and the aging assessment to pre-assess the remaining life of the output cable.
[0012] In a further technical solution, in step 5, the rule for assessing the remaining life of the cable is as follows: If the damage condition is judged as "severely damaged", then regardless of the aging assessment result, the cable's lifespan is directly terminated. If the damage status is "intact" or "minorly damaged", then the degree of aging is determined based on the output of the DT regression model. ( The calibration value is between 0 and 1, where 1 represents brand new and the cable has been in operation for a certain period of time. The remaining life of the cable is predicted using the following model. : ; in, It is a correction factor related to cable type and operating environment.
[0013] The cable life assessment device and method based on interdigital sensing provided in this invention have the following advantages: (1) Comprehensive and efficient detection: Through the innovative multi-band interdigital sensor, the two key parameters most related to the cable life, dissipation factor and capacitance value, are acquired simultaneously in one non-contact manner, realizing the comprehensive diagnosis of the cable's "overall aging" and "local damage". The detection speed is fast and it is very suitable for the rapid initial screening of large batches of waste cables on site.
[0014] (2) High measurement accuracy and strong anti-interference: The flexible multi-layer structure and protective ring design of the sensor ensure stable conformal contact with the cable, effectively suppressing edge effects and electromagnetic interference, and ensuring the accuracy and stability of the original measurement signal.
[0015] (3) The evaluation model is intelligent and reliable: a data-driven evaluation strategy is adopted, and the weighted KNN algorithm is used to process the capacitance data, which is sensitive to local defects. The linear compensation and DT regression model is used to process the dissipation factor data, which effectively overcomes the individual differences of the cable and makes the aging evaluation results more objective and accurate.
[0016] (4) Life prediction integrates multi-dimensional information, making the results more reliable: It abandons the single parameter criterion and creatively uses "damage status" as a veto item, and integrates it with "quantitative aging degree" through a physical model. The final remaining life prediction result is more in line with engineering reality, greatly reducing the risk of misjudgment, significantly improving the screening efficiency and accuracy of waste cable reuse, and bringing huge economic benefits. Attached Figure Description
[0017] Figure 1 A schematic diagram of a cable life assessment device based on interdigital sensing provided in an embodiment of the present invention; Figure 2 A flowchart of a cable life assessment method based on interdigital sensing provided in an embodiment of the present invention.
[0018] In the attached diagram: signal sensing unit 1; interdigitated capacitor plate 11; insulating substrate 111; first electrode group 112; second electrode group 113; signal processing unit 2; LCR digital bridge 21; acquisition card 3; processor 4; data preprocessing and evaluation unit 41; aging evaluation module 42; lifespan pre-evaluation module 43. Detailed Implementation
[0019] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.
[0020] The specific implementation of the present invention will be described in detail below with reference to specific embodiments.
[0021] like Figure 1 As shown, an embodiment of the present invention provides a cable life assessment device based on interdigital sensing, comprising: Signal sensing unit 1, comprising interdigitated capacitor plates 11, which can be coupled to the power cable under test to simultaneously acquire the dissipation factor reflecting the aging state of the cable. Signal and capacitance value reflecting cable damage status Signal; Signal processing unit 2, connected to signal sensing unit 1, includes an LCR digital bridge 21 for processing signals. Signals and The signal is measured and processed, and output at different frequencies. Measured values and capacitance values Measured value; Processor 4, connected to signal processing unit 2 via acquisition card 3, includes a data preprocessing and evaluation unit 41, an aging evaluation module 42, and a lifespan pre-evaluation module 43. The data preprocessing and evaluation unit 41 receives data... Measured values and Measured values, and used the KNN algorithm to... The measured values are processed to determine the cable's damage status; the aging assessment module 42 is used to combine prior knowledge to analyze the values measured at different frequencies. The measured values are linearly compensated and corrected, and the aging degree assessment result of the cable is output using the trained DT regression model; the life pre-assessment module 43 is used to integrate the damage state and aging degree assessment results.
[0022] like Figure 1 As shown, in a preferred embodiment of the present invention, the interdigitated capacitor plate 11 includes an insulating substrate 111, on which a first electrode group 112 and a second electrode group 113 are disposed. The first electrode group 112 includes at least two parallel and electrically interconnected first interdigitated electrodes, and the second electrode group 113 is arranged alternately with the first electrode group 112, including at least two parallel and electrically interconnected second interdigitated electrodes. The first electrode group and the second electrode group are insulated from each other, forming an alternating capacitor structure. The first electrode group 112 and the second electrode group 113 constitute the main sensing area, and the finger width of the main sensing area and gap Satisfying the relation Used for high-precision sensing of cable aging-related parameters in the low-frequency band of 0.1 Hz-1 kHz. Signal; An auxiliary sensing area is further provided on the insulating substrate 111. The electrode strips of the auxiliary sensing area are electrically isolated from the electrodes of the main sensing area. The width of the strips of the auxiliary sensing area is... And the gap between the fingers It is used for high-sensitivity sensing of cable local damage and micro water trees in the 1 kHz-100 kHz high-frequency band. The changes.
[0023] In a preferred embodiment of the present invention, the measurement frequency range of the LCR digital bridge 21 is set to 0.1 Hz to 100 kHz, and a frequency sweep mode is used to automatically acquire at least three discrete frequency points. and .
[0024] In a preferred embodiment of the present invention, the data preprocessing and evaluation unit 41 determines the damage status of the cable as follows: Construct a sample library of cable capacitance values containing known damage states, including "intact", "minor damage" and "severe damage"; For real-time measured multi-frequency capacitance value vector ,in For frequency The measured capacitance value is calculated and compared with the value of the first sample in the sample library. Sample Weighted Euclidean distance The calculation formula is: ; in, Representing the Each measurement frequency, To measure frequency The relevant weighting coefficients, and satisfy the following conditions For high-frequency signals that are more sensitive to damage, Larger value; select the one with the smallest distance. The cable damage status corresponding to the real-time measured capacitance value is determined by using a nearest neighbor sample and a majority voting method.
[0025] In a preferred embodiment of the present invention, the linear compensation correction method in the aging assessment module 42 is specifically as follows: Obtain prior knowledge about the cable under test, including cable type and insulation material; based on this prior knowledge, retrieve the corresponding information from the standard database. Baseline curve For the actual measurement curve Perform compensation correction to obtain the corrected result. value The correction formula is: ; in, For the selected reference frequency, For the current frequency, The compensation factor is related to the cable type. To select a frequency The actual measurement below curve, To select a frequency Down Correction value.
[0026] As a preferred embodiment of the present invention, the training method of the DT regression model includes: After linear compensation and correction, at different frequencies value As input features: ; in, In frequency Down Correction value.
[0027] The actual aging degree of the cable, obtained through accelerated aging tests or historical data, corresponding to the input characteristics, is used as the target variable. A regression tree is constructed using the CART algorithm, and features are selected when nodes split. and threshold The cost function is to minimize the weighted mean square error (MSE) after splitting. for: ; in, This is the number of samples in the current node. and These represent the number of samples in the left and right child nodes after the split, respectively.
[0028] The output value of this node during the prediction phase can be calculated as follows: ; in, It is the average of the squared differences between the true values and the predicted values of all samples within a given node. This represents the number of training samples contained in the current tree node. For the current node The true target value corresponding to each training sample. The true target value for all training samples within the current node. The arithmetic mean of the values is used as the predicted output value for any new sample falling to that node.
[0029] like Figure 2 As shown, another embodiment of the present invention provides a cable life assessment method based on interdigital sensing, which, based on the above-described assessment device, includes the following steps: Step 1: Couple the interdigitated capacitor plates 11 to the cable under test, and measure at multiple frequencies using the LCR digital bridge 21. Value and capacitance value ; Step 2: Process capacitance values using the KNN algorithm To determine the damage condition of the cable; Step 3: Based on prior knowledge of cables, [the following steps are taken]... The measured values are subjected to linear compensation correction; Step 4: Compensate and correct The values are input into a pre-trained DT regression model to obtain the aging assessment results of the cable; Step 5: Combine the results of the damage assessment and the aging assessment to pre-assess the remaining life of the output cable.
[0030] In a preferred embodiment of the present invention, in step 5, the remaining life assessment rule for the cable is as follows: If the damage condition is judged as "severely damaged", then regardless of the aging assessment result, the cable's lifespan is directly terminated. If the damage status is "intact" or "minorly damaged", then the degree of aging is determined based on the output of the DT regression model. (A calibration value between 0 and 1, where 1 represents brand new) and the cable's service life. The remaining life of the cable is predicted using the following model. : ; in, It is a correction factor related to cable type and operating environment.
[0031] The effectiveness of the present invention will be verified through a specific embodiment below.
[0032] For the evaluation device, its insulating substrate 111 is made of a 50μm thick flexible polyimide film. Main sensing area , (Right now Width of the finger strip in the auxiliary sensing area. ,gap The guard ring electrode has a width of 0.5 mm and a distance of 0.5 mm from the main sensing area. The interdigitated capacitor plates 11 are fixed to the surface of the cable under test by back-pressure Velcro or elastic straps.
[0033] The LCR digital bridge 21 is a self-made LCR digital bridge module based on the AD5933 impedance conversion chip. Its frequency output range is set to six discrete frequency points: 1 Hz, 10 Hz, 100 Hz, 1 kHz, 10 kHz, and 50 kHz for frequency sweep measurement. This module is controlled by an STM32F407 microcontroller and sends the measurement data to a host computer via serial communication.
[0034] The data preprocessing and evaluation unit 41 is a computer embedded with an evaluation algorithm. The software is developed using Python and integrates machine learning libraries for running KNN and DT algorithms.
[0035] The evaluation method specifically includes the following steps: Step 1: System initialization and calibration; Before starting the test, couple the interdigitated capacitor plates 11 to a new cable of the same type that is known to be in good condition, and run the system's calibration program. The system automatically records the capacitance value at each frequency point. and This data, as one of the benchmark data for this type of cable, is stored in the standard database.
[0036] Step 2: Acquire signals from the cable under test; Clean the surface of the obsolete YJV22 cable to be tested, and firmly fix the interdigitated capacitor plates 11 to the middle of the cable. Start the measurement program; the LCR digital bridge 21 automatically performs frequency sweep measurement and outputs an array containing measurement values at six frequency points: Capacitance value vector: ; Dissipation factor vector: ; Step 3: Determine the damage condition; (1) Call the sample library: Call the constructed capacitance value sample library containing 500 samples from the database. Each sample has a corresponding label of "intact", "slightly damaged" and "severely damaged".
[0037] (2) Calculate the weighted distance: For Calculate its relationship with the first in the sample library. Sample The weighted Euclidean distance. In this embodiment, the weighting coefficients... The settings are as follows: for 1Hz, 10Hz, and 100Hz, For 1kHz, For 10kHz and 50kHz, The calculation example is as follows: ; (3) Majority voting: Set k=5 and find the 5 nearest neighbor samples with the smallest distance. Among them, 4 are labeled "slightly damaged" and 1 is labeled "intact". The module determines the current cable damage status as "slightly damaged" by majority voting.
[0038] Step 4: Aging degree assessment; The aging assessment module 42 then starts and processes... data: Linear compensation correction: The system retrieves the corresponding standard from the database based on the input cable type (YJV22, cross-linked polyethylene insulation). Baseline curve Select a reference frequency. compensation coefficient Set to 0.05. For actual measurements... Perform corrections.
[0039] For example, at a frequency of 10kHz, the measured , and the benchmark value .
[0040] Correction calculation: ; Perform the same operation on all frequency points to obtain the corrected feature vector. .
[0041] Decision tree model evaluation: Feature vectors The input is fed into a pre-trained decision tree regression model. This model was trained using 300 sets of historical cable aging data. Based on the input features, the model iterates through its decision rules and finally outputs an aging assessment value of 0.72 for the cable.
[0042] Step 5: Lifetime Pre-assessment and Report Generation; The lifespan pre-assessment module 43 receives the results of the first two steps and the cable's operational time T=15 years, and adjusts the factor according to the cable's operating environment. The value is 0.9.
[0043] Execute predefined evaluation rules: (1) Since the damage status is not "severely damaged", it does not trigger a veto.
[0044] (2) Call the remaining lifetime prediction model: Year.
[0045] Step 6: Output the results; Generate an evaluation report, including: (1) Test results: The cable can be reused.
[0046] (2) Main parameters: damage status (minor damage), aging degree (72% of new), and predicted remaining life (approximately 35 years).
[0047] This embodiment fully demonstrates the entire process of this invention, from signal acquisition and data processing to final lifespan assessment. Using this invention, operators can complete a rapid, non-destructive diagnosis of a decommissioned cable on-site within 5-10 minutes. The system combines multi-dimensional sensor signals with intelligent algorithms, and its assessment results are far superior to those of traditional single insulation resistance measurements. This provides power companies with a scientific and reliable basis for selecting reusable cables, significantly improving the efficiency and accuracy of material recycling.
[0048] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.
Claims
1. A cable life assessment device based on interdigital sensing, characterized by, The application relates to a method for evaluating the remaining life of a cable, and belongs to the technical field of cable life evaluation. a signal sensing unit including interdigital capacitive plates which can be coupled to the power cable to be measured for simultaneously acquiring a dissipation factor reflecting an aging state of the cable a signal and a capacitance value reflecting a state of damage of the cable a signal; The signal processing unit, connected to the signal sensing unit, includes an LCR digital bridge for processing signals. Signals and The signal is measured and processed, and output at different frequencies. Measured values and capacitance values Measured value; Processor, the processor is connected with signal processing unit through acquisition card, data preprocessing and evaluation unit, aging evaluation module and life pre-evaluation module are provided in the processor;The data preprocessing and evaluation unit is used for receiving Measurement value and Measurement value, and the KNN algorithm is handled to Measurement value, judges the damage state of cable;The aging evaluation module is used for carrying out linear compensation correction to the measured Measurement value under different frequencies in combination with priori knowledge, and using the trained DT regression model, output the aging degree evaluation result of cable;The life pre-evaluation module is used for fusing damage state and aging degree evaluation result.
2. The interdigitated sensing based cable life assessment device of claim 1, wherein, The interdigital capacitor electrode plate comprises an insulating substrate, and a first electrode group and a second electrode group are arranged on the insulating substrate; the first electrode group comprises at least two first interdigital electrodes arranged in parallel and electrically interconnected; the second electrode group is arranged in an interlaced mode with the first electrode group and comprises at least two second interdigital electrodes arranged in parallel and electrically interconnected; the first electrode group and the second electrode group are insulated from each other, thereby forming an interlaced capacitor structure. The first electrode group and the second electrode group constitute a main sensing area, a finger strip width of the main sensing area satisfies a relationship satisfies a relationship , for high-precision sensing at a low frequency band of 0.1 Hz-1 kHz signal; The insulating substrate is further provided with an auxiliary sensing area, the electrode fingers of the auxiliary sensing area are electrically isolated from the electrodes of the main sensing area, the finger width of the auxiliary sensing area is , and the finger gap is used to perceive the change in the high frequency band of 1 kHz-100 kHz with high sensitivity. 3. The interdigitated sensing based cable life assessment device of claim 1, wherein, The measurement frequency range of the LCR digital bridge is set to 0.1 Hz to 100 kHz, and at least three discrete frequency points under the automatic acquisition of the sweep mode and .
4. The interdigitated sensing based cable life assessment device of claim 1, wherein, The process of judging the damage state of the cable by the data preprocessing and evaluation unit is as follows: A cable capacitance value sample library containing known damage states is constructed, and the damage states include "intact", "slight damage" and "severe damage"; For real-time measured multi-frequency capacitance value vector ,in For frequency The measured capacitance value is calculated and compared with the value of the first sample in the sample library. Sample Weighted Euclidean distance The calculation formula is: ； wherein, represent the first measuring frequency, is a weight coefficient related to the measuring frequency , and satisfies , the value is larger for high-frequency signals more sensitive to damage; select the nearest neighbor samples with the smallest determine the real-time measurement of the cable damage state corresponding to the capacitance value by majority voting method.
5. The interdigitated sensing based cable life assessment device of claim 4, wherein, The linear compensation correction method in the aging evaluation module is specifically as follows: acquiring prior knowledge of the measured cable, including cable type and insulation material; based on the prior knowledge, calling corresponding reference curve from a standard database; compensating and correcting the measured curve to obtain a corrected value , and the correction formula is: ； wherein is a selected reference frequency, is a current frequency, is a compensation factor related to the cable type, is a measured curve at the selected frequency , is a correction value at the selected frequency . 6. The interdigitated sensing based cable life assessment device of claim 5, wherein, The training method of the DT regression model comprises the following steps: The values of the linearly compensated and corrected, at different frequencies values as input features: ； in, In frequency Down Correction value; The actual aging degree of the cable corresponding to the input features is used as the target variable. A regression tree is constructed using the CART algorithm, and features are selected when nodes split. and threshold The cost function is to minimize the weighted mean square error after splitting. for: ； wherein, is the number of samples of the current node, and are the number of samples of the left and right child nodes, respectively, after splitting; The output value of the node in the prediction stage is calculated as follows: ； wherein, is the average of the squared differences between the true values and the node predicted values for all samples within a node, is the number of training samples contained in the current tree node, is the true target value for the th training sample in the current node, is the arithmetic mean of the true target values of all training samples within the current node, as the predicted output value for any new sample falling into the node.
7. A method for interdigital sensing based cable life assessment, based on the interdigital sensing based cable life assessment device according to any one of claims 1 to 6, characterized in that, The method comprises the following steps: Step 1 : Interdigitated capacitive plates are coupled to the cable under test, and the capacitance is measured at multiple frequencies by an LCR digital bridge values and capacitance values ; Step 2: Processing the capacitance value using KNN algorithm to determine the damage state of the cable; Step 3: Linearly compensating the measurements based on the prior knowledge of the cable correction; Step 4: input the compensated and corrected values into the pre-trained DT regression model to obtain the aging degree evaluation result of the cable. Step 4: input the compensated and corrected values into the pre-trained DT regression model to obtain the aging degree evaluation result of the cable. Step 5: fusing the judgment result of the damage state and the evaluation result of the aging degree, and outputting the remaining life pre-evaluation of the cable.
8. The interdigitated sensing based cable life assessment method of claim 7, wherein, In the step 5, the remaining life evaluation rule of the cable is as follows: If the damage state is judged as "severe damage", no matter the evaluation result of the aging degree, the cable life is directly judged as terminated. If the damage state is "intact" or "minor damage", the age of the cable is predicted by the DT regression model output and the cable has been in operation for time : ； wherein is a correction factor related to the cable type and the operating environment.