Method for evaluating health state of cable line

Abstract

The invention discloses a method for evaluating the health state of a cable line, and the method comprises the following steps: 1, obtaining multi-dimensional health state parameters, and obtaining the health state parameters of the cable line through a plurality of detection means; 2, determining a weight, and utilizing an analytic hierarchy process to determine the weight according to the importance of a cable line, the time-varying characteristic of each index and the influence degree of each index on the overall health condition; and step 3, fuzzy evaluation: combining the obtained health state parameters with the determined weights by using a fuzzy mathematical method to form a multi-dimensional health state matrix, and further performing fuzzy evaluation on the health condition of the cable line. According to the invention, the health condition of the cable line can be effectively evaluated, potential problems can be found in time, and corresponding measures can be taken to ensure stable operation of a power system.

Description

Technical Field

[0001] The present invention relates to the technical field of cable health assessment, and in particular to a method for assessing the health status of a cable line. Background Art

[0002] With the rapid development of economy, the power supply situation in our country is becoming increasingly tense. The economic losses caused by power grid system failures alone in various parts of the country have reached trillions. The main reason for this is that the power grid system failures cannot be handled in a timely manner.

[0003] At present, the guidelines for the implementation of cable line condition maintenance are relatively rough. The maintenance strategy is determined by comparing the monitored cable line status with the critical value using a manual scoring method, which jumps directly from the data layer to the decision layer, and only considers the individual performance of the cable line, lacking consideration of the impact of cable line maintenance on the operation of the power grid. For a long time, power supply companies have only considered the impact of equipment failures when formulating maintenance plans, making maintenance decisions too conservative. To this end, we propose a method for evaluating the health status of cable lines to solve the above problems. Summary of the invention

[0004] The purpose of this section is to summarize some aspects of embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the specification abstract and the invention title of this application to avoid blurring the purpose of this section, the specification abstract and the invention title, and such simplifications or omissions cannot be used to limit the scope of the present invention.

[0005] In view of the problems existing in the above-mentioned existing methods for evaluating the health status of cable lines, the present invention is proposed.

[0006] Therefore, the purpose of the present invention is to provide a method for evaluating the health status of a cable line, which can effectively evaluate the health status of the cable line, discover potential problems in time, and take corresponding measures to ensure the stable operation of the power system.

[0007] In order to solve the above technical problems, the present invention provides the following technical solutions: a method for evaluating the health status of a cable line, comprising the following steps:

[0008] Step 1: Obtain multi-dimensional health status parameters. Obtain the health status parameters of the cable line through a variety of detection methods. At the same time, combine the online monitoring data of the cable with the remote real-time sensor data to achieve all-round dynamic monitoring of the operating status;

[0009] Step 2: Determine the weight. Use the analytic hierarchy process to dynamically assign a corresponding weight to each indicator based on the importance of the cable line, the time-varying characteristics of each indicator and its impact on the overall health status. The weight is adaptively adjusted over time or as operating conditions change, improving the accuracy of the assessment.

[0010] Step 3: Fuzzy evaluation, using fuzzy mathematics methods to combine the acquired health status parameters with the determined weights to form a multi-dimensional health status matrix, and further perform fuzzy evaluation on the health status of the cable line.

[0011] As a preferred scheme of the method for evaluating the health status of a cable line described in the present invention, the multi-dimensional health status parameters of step one include the physical properties of the cable, and the physical properties include current, voltage, temperature and humidity; the detection means used include temperature and humidity monitoring, voltage testing, and current measurement.

[0012] As a preferred solution of the method for evaluating the health status of a cable line according to the present invention, the weight is determined by using the hierarchical analysis method in step 2. The specific steps are as follows:

[0013] S1. Establish a hierarchical structure: First, determine the hierarchical structure of the assessment problem and decompose the problem into different levels and criteria. Specifically, when assessing the health status of the cable line, decompose the problem into top-level goals (such as health status assessment) and bottom-level criteria (including current, voltage, temperature and humidity), ensuring that the levels of the hierarchy are clear and the relationships between the levels are clear;

[0014] S2. Construct a judgment matrix: For each level of criteria, construct a judgment matrix. The judgment matrix is ​​a square matrix in which each element represents the relative importance of two criteria. Use a scale of 1 to 9 to compare and score the importance of each pair of criteria. 1 means that the two criteria are equally important, and 9 means that one criterion is significantly more important than the other.

[0015] S3. Calculate weight: Calculate the weight of each criterion according to the judgment matrix, perform eigenvector analysis on the judgment matrix, solve the eigenvector, and then normalize the eigenvector to obtain the weight of each criterion;

[0016] S4, consistency test: Check the consistency of the judgment matrix to ensure the rationality and reliability of the judgment matrix, calculate the consistency index and consistency ratio, if the consistency ratio is less than 0.1, it means that the judgment matrix has reasonable consistency;

[0017] S5. Repeat steps S2-S4: If the consistency of the judgment matrix does not meet the requirement, adjust it by repeated iteration until the judgment matrix meets the consistency requirement.

[0018] As a preferred solution of the method for evaluating the health status of a cable line according to the present invention, the steps of fuzzy evaluation of the health status of the cable line by the fuzzy mathematical method are as follows:

[0019] 1) Determine health status parameters:

[0020] According to the working environment, operating conditions and evaluation requirements of the cable line, a set of appropriate health status parameters are selected. These parameters should cover the physical characteristics of the cable and its working status. The health status parameters include:

[0021] Cable current: reflects the load condition of the cable;

[0022] Cable voltage: reflects the deviation between the operating voltage of the cable and the rated value;

[0023] Cable temperature: reflects the working thermal state of the cable to avoid failure caused by overheating;

[0024] Cable humidity: environmental factors that affect the insulation performance of cables;

[0025] 2) Determine the weight:

[0026] The weight of each health status parameter was determined using the analytic hierarchy process;

[0027] 3) Fuzzification:

[0028] The acquired health status parameters are converted into fuzzy numbers, and the value of each parameter is mapped to the corresponding fuzzy set using membership functions;

[0029] 4) Establishment of fuzzy rules:

[0030] A set of fuzzy rules is established to map the fuzzy set of health status parameters to the fuzzy set of health status in the form of IF-THEN; each rule includes the following:

[0031] IF part: consists of fuzzy sets of health status parameters;

[0032] THEN part: the fuzzy set of health status corresponding to the fuzzy set of health status parameters;

[0033] 5) Fuzzy reasoning:

[0034] The established fuzzy rules are used for fuzzy reasoning. The specific process of fuzzy reasoning is as follows:

[0035] Input the fuzzy set of health status parameters: input the fuzzified health status parameters into the external fuzzy reasoning system;

[0036] Reasoning process: According to the fuzzy rules and the input fuzzy set, the fuzzy inference engine in the fuzzy inference system is used to perform reasoning to obtain the fuzzy set of the health status of the cable;

[0037] 6) Defuzzification:

[0038] The fuzzy set of health status of fuzzy reasoning results is converted into a deterministic health status evaluation value;

[0039] 7) Health status evaluation:

[0040] Based on the results of defuzzification, the health status of the cable line is divided into different levels and finally evaluated. The levels include:

[0041] Good: The cable has no health problems and is running stably;

[0042] Normal: The cable is within the normal operating range, there may be slight fluctuations, but it does not affect the overall performance;

[0043] General: The cable has some problems, including local overheating or voltage fluctuations, but has not yet reached the failure standard;

[0044] Problematic: The cable has serious health issues and needs to be repaired or replaced immediately.

[0045] As a preferred solution of the method for evaluating the health status of a cable line according to the present invention, wherein: the membership function in 3) adopts a triangular membership function, given a triangular membership function μ A (x), where x is the input variable, including temperature, current, voltage or humidity, and its fuzzy set A is expressed as:

[0046]

[0047] Among them, a, b, and c are the three parameters that define the triangle:

[0048] a is the left endpoint, indicating the starting value of the fuzzy set;

[0049] b is the peak value, indicating the maximum membership of the fuzzy set;

[0050] c is the right endpoint, indicating the end value of the fuzzy set.

[0051] As a preferred solution of the method for evaluating the health status of a cable line according to the present invention, the averaging method is used for defuzzification in step 6), including:

[0052] First, the membership degree of each health status evaluation result is calculated;

[0053] Then, according to the membership degree of each evaluation result and its corresponding weight, a weighted average is calculated as the determined evaluation result;

[0054] The specific expression is as follows:

[0055] Assuming there are n health status evaluation results, the membership degrees are μ1, μ2, ..., μn, and the corresponding weights are w1, w2, ..., wn, then the determined evaluation result is the weighted average, that is:

[0056] Health status evaluation result = (μ1*w1+μ2*w2+...+μn*wn) / (w1+w2+...+wn).

[0057] As a preferred solution of the method for evaluating the health status of a cable line according to the present invention, the characteristic vector analysis in step S3 includes:

[0058] For an n-order judgment matrix A, solve its eigenvector v to satisfy Av = λv, where λ is the eigenvalue of the judgment matrix A;

[0059] Divide each column of the judgment matrix A by the sum of the elements in the column to obtain the normalized judgment matrix A';

[0060] Calculate the eigenvector v' of the normalized judgment matrix A', satisfying A'v'=λ'v', where λ' is the eigenvalue of the normalized judgment matrix A';

[0061] The eigenvector v' is the relative weight of each criterion;

[0062] The step S3 of normalizing the feature vector is specifically as follows:

[0063] The eigenvector v' is normalized so that the sum of its elements is equal to 1, and the normalized eigenvector w is obtained; the normalized eigenvector w is the weight of each criterion.

[0064] As a preferred solution of the method for assessing the health status of cable lines described in the present invention, comprehensive weighting is required after step S5: the weight of each criterion is multiplied by the weight of the level to which it belongs to obtain the final comprehensive weight, and the weight of the bottom-level criterion is transferred to the top-level target through the hierarchical relationship of the hierarchical structure to obtain the relative importance of each criterion to the entire target.

[0065] Beneficial effects of the invention: The invention combines multiple technologies such as fuzzy evaluation, multi-parameter analysis, dynamic monitoring and artificial intelligence through this method, aiming to provide a comprehensive, accurate and easy-to-operate cable line health status assessment solution. Through these steps, the health status of the cable line can be effectively assessed, potential problems can be discovered in time, and corresponding measures can be taken to ensure the stable operation of the power system. In addition, through the hierarchical analysis method, complex assessment problems can be decomposed into easy-to-handle parts, and the relative importance of different criteria can be taken into account to improve the accuracy and reliability of the assessment results. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. Among them:

[0067] Figure 1 The figure is a schematic diagram of the steps of the method for evaluating the health status of a cable line according to the present invention. DETAILED DESCRIPTION

[0068] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0069] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0070] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0071] Secondly, the present invention is described in detail with reference to the schematic diagram. When describing the embodiments of the present invention in detail, for the sake of convenience, the cross-sectional diagrams showing the device structure will not be partially enlarged according to the general scale, and the schematic diagrams are only examples, which should not limit the scope of protection of the present invention. In addition, in actual production, the three-dimensional dimensions of length, width and depth should be included.

[0072] Reference Figure 1 , provides a method for evaluating the health status of a cable line, comprising the following steps:

[0073] Step 1: Obtain multi-dimensional health status parameters. Obtain the health status parameters of the cable line through a variety of detection methods, including temperature and humidity monitoring, voltage testing, and current measurement. At the same time, combine the online monitoring data of the cable with the remote real-time sensor data to achieve all-round dynamic monitoring of the operating status;

[0074] Step 2: Determine the weight. Use the analytic hierarchy process to dynamically assign a corresponding weight to each indicator based on the importance of the cable line, the time-varying characteristics of each indicator and its impact on the overall health status. The weight is adaptively adjusted over time or as operating conditions change, improving the accuracy of the assessment.

[0075] Step 3: Fuzzy evaluation, using fuzzy mathematics methods to combine the acquired health status parameters with the determined weights to form a multi-dimensional health status matrix, and further perform fuzzy evaluation on the health status of the cable line.

[0076] In this embodiment, the multi-dimensional health status parameters of step one include physical properties of the cable, and the physical properties include current, voltage, temperature and humidity; the detection means used include temperature and humidity monitoring, voltage testing, and current measurement.

[0077] In this embodiment, the weights are determined by using the hierarchical analysis method in step 2. The specific steps are as follows:

[0078] S1. Establish a hierarchical structure: First, determine the hierarchical structure of the assessment problem and decompose the problem into different levels and criteria. Specifically, when assessing the health status of the cable line, decompose the problem into top-level goals (such as health status assessment) and bottom-level criteria (including current, voltage, temperature and humidity), ensuring that the levels of the hierarchy are clear and the relationships between the levels are clear;

[0079] S2. Construct a judgment matrix: For each level of criteria, construct a judgment matrix. The judgment matrix is ​​a square matrix in which each element represents the relative importance of two criteria. Use a scale of 1 to 9 to compare and score the importance of each pair of criteria. 1 means that the two criteria are equally important, and 9 means that one criterion is significantly more important than the other.

[0080] S3. Calculate weight: Calculate the weight of each criterion according to the judgment matrix, perform eigenvector analysis on the judgment matrix, solve the eigenvector, and then normalize the eigenvector to obtain the weight of each criterion;

[0081] S4, consistency test: Check the consistency of the judgment matrix to ensure the rationality and reliability of the judgment matrix, calculate the consistency index and consistency ratio, if the consistency ratio is less than 0.1, it means that the judgment matrix has reasonable consistency;

[0082] S5. Repeat steps S2-S4: If the consistency of the judgment matrix does not meet the requirement, adjust it by repeated iteration until the judgment matrix meets the consistency requirement.

[0083] Among them, the steps of fuzzy evaluation of the health status of cable lines by fuzzy mathematics method are as follows:

[0084] 1) Determine health status parameters:

[0085] According to the working environment, operating conditions and evaluation requirements of the cable line, a set of appropriate health status parameters are selected. These parameters should cover the physical characteristics of the cable and its working status. The health status parameters include:

[0086] Cable current: reflects the load condition of the cable;

[0087] Cable voltage: reflects the deviation between the operating voltage of the cable and the rated value;

[0088] Cable temperature: reflects the working thermal state of the cable to avoid failure caused by overheating;

[0089] Cable humidity: environmental factors that affect the insulation performance of cables;

[0090] 2) Determine the weight:

[0091] According to the relative importance of each health status parameter in assessing the health status of the cable and the correlation between them, the weight of each parameter is determined; specifically, in this embodiment, the weight of each health status parameter is determined using the hierarchical analysis method;

[0092] 3) Fuzzification:

[0093] The acquired health status parameters are converted into fuzzy numbers, and the value of each parameter is mapped to the corresponding fuzzy set using membership functions;

[0094] 4) Establishment of fuzzy rules:

[0095] A set of fuzzy rules is established to map the fuzzy set of health status parameters to the fuzzy set of health status in the form of IF-THEN; each rule includes the following:

[0096] IF part: consists of fuzzy sets of health status parameters;

[0097] THEN part: the fuzzy set of health conditions corresponding to the fuzzy set of health status parameters; for example, if the temperature is "high temperature" and the current is "high current", the corresponding THEN cable health condition is "problematic";

[0098] 5) Fuzzy reasoning:

[0099] The established fuzzy rules are used for fuzzy reasoning. The specific process of fuzzy reasoning is as follows:

[0100] Input the fuzzy set of health status parameters: input the fuzzified health status parameters into the external fuzzy reasoning system;

[0101] Reasoning process: According to the fuzzy rules and the input fuzzy set, the fuzzy inference engine in the fuzzy inference system is used to perform reasoning to obtain the fuzzy set of the health status of the cable;

[0102] 6) Defuzzification:

[0103] The fuzzy set of health status of fuzzy reasoning results is converted into a deterministic health status evaluation value;

[0104] 7) Health status evaluation:

[0105] Based on the results of defuzzification, the health status of the cable line is divided into different levels and finally evaluated. The levels include:

[0106] Good: The cable has no health problems and is running stably;

[0107] Normal: The cable is within the normal operating range, there may be slight fluctuations, but it does not affect the overall performance;

[0108] General: The cable has some problems, such as local overheating or voltage fluctuation, but has not yet reached the failure standard;

[0109] Problematic: The cable has serious health issues and needs to be repaired or replaced immediately.

[0110] Specifically, the membership function in 3) adopts the triangular membership function. Given the triangular membership function μ A (x), where x is the input variable (temperature, current, voltage, humidity), and its fuzzy set A is expressed as:

[0111]

[0112] Among them, a, b, and c are the three parameters that define the triangle:

[0113] a is the left endpoint, indicating the starting value of the fuzzy set;

[0114] b is the peak value, indicating the maximum membership of the fuzzy set;

[0115] c is the right endpoint, indicating the end value of the fuzzy set.

[0116] Wherein, in step 6), an average method is used for defuzzification, including:

[0117] First, the membership degree of each health status evaluation result is calculated;

[0118] Then, according to the membership degree of each evaluation result and its corresponding weight, a weighted average is calculated as the determined evaluation result;

[0119] The specific expression is as follows:

[0120] Assuming there are n health status evaluation results, the membership degrees are μ1, μ2, ..., μn, and the corresponding weights are w1, w2, ..., wn, then the determined evaluation result is the weighted average, that is:

[0121] Health status evaluation result = (μ1*w1+μ2*w2+...+μn*wn) / (w1+w2+...+wn).

[0122] Furthermore, the feature vector analysis in step S3 includes:

[0123] For an n-order judgment matrix A, solve its eigenvector v to satisfy Av = λv, where λ is the eigenvalue of the judgment matrix A;

[0124] Divide each column of the judgment matrix A by the sum of the elements in the column to obtain the normalized judgment matrix A';

[0125] Calculate the eigenvector v' of the normalized judgment matrix A', satisfying A'v'=λ'v', where λ' is the eigenvalue of the normalized judgment matrix A';

[0126] The eigenvector v' is the relative weight of each criterion;

[0127] The step S3 of normalizing the feature vector is specifically as follows:

[0128] The eigenvector v' is normalized so that the sum of its elements is equal to 1, and the normalized eigenvector w is obtained; the normalized eigenvector w is the weight of each criterion.

[0129] Among them, comprehensive weighting is required after step S5: the weight of each criterion is multiplied by the weight of the level to which it belongs to obtain the final comprehensive weight, and the weight of the bottom criterion is transferred to the top-level goal through the hierarchical relationship of the hierarchy to obtain the relative importance of each criterion to the entire goal.

[0130] The present invention combines multiple technologies such as fuzzy evaluation, multi-parameter analysis, dynamic monitoring and artificial intelligence through this method, aiming to provide a comprehensive, accurate and easy-to-operate cable line health status assessment solution. Through these steps, the health status of the cable line can be effectively assessed, potential problems can be discovered in time, and corresponding measures can be taken to ensure the stable operation of the power system. In addition, through the hierarchical analysis method, complex assessment problems can be decomposed into easy-to-handle parts, and the relative importance of different criteria can be taken into account to improve the accuracy and reliability of the assessment results.

[0131] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for evaluating the health status of a cable line, characterized in that: The following steps are involved: Step 1: Obtain multi-dimensional health status parameters. Obtain the health status parameters of the cable line through a variety of detection methods. At the same time, combine the online monitoring data of the cable with the remote real-time sensor data to achieve all-round dynamic monitoring of the operating status; Step 2: Determine the weight. Use the analytic hierarchy process to dynamically assign a corresponding weight to each indicator based on the importance of the cable line, the time-varying characteristics of each indicator and its impact on the overall health status. The weight is adaptively adjusted over time or as operating conditions change, improving the accuracy of the assessment. Step 3: Fuzzy evaluation, using fuzzy mathematics methods to combine the acquired health status parameters with the determined weights to form a multi-dimensional health status matrix, and further perform fuzzy evaluation on the health status of the cable line.

2. The method for evaluating the health status of a cable line according to claim 1, characterized in that: The multi-dimensional health status parameters of step one include physical properties of the cable, including current, voltage, temperature and humidity; the detection means used include temperature and humidity monitoring, voltage testing, and current measurement.

3. The method for evaluating the health status of a cable line according to claim 1, characterized in that: In step 2, the weights are determined by using the hierarchical analysis method, and the specific steps are as follows: S1. Establishing a hierarchical structure: First, determine the hierarchical structure of the evaluation problem and decompose the problem into different levels and criteria. Specifically, when evaluating the health status of a cable line, decompose the problem into top-level goals and bottom-level criteria. The top-level goal is health status evaluation, and the bottom-level criteria include current, voltage, temperature, and humidity. S2. Construct a judgment matrix: For each level of criteria, construct a judgment matrix. The judgment matrix is ​​a square matrix in which each element represents the relative importance of two criteria. Use a scale of 1 to 9 to compare and score the importance of each pair of criteria. 1 means that the two criteria are equally important, and 9 means that one criterion is significantly more important than the other. S3. Calculate weight: Calculate the weight of each criterion according to the judgment matrix, perform eigenvector analysis on the judgment matrix, solve the eigenvector, and then normalize the eigenvector to obtain the weight of each criterion; S4, consistency test: Check the consistency of the judgment matrix to ensure the rationality and reliability of the judgment matrix, calculate the consistency index and consistency ratio, if the consistency ratio is less than 0.1, it means that the judgment matrix has reasonable consistency; S5. Repeat steps S2-S4: If the consistency of the judgment matrix does not meet the requirement, adjust it by repeated iteration until the judgment matrix meets the consistency requirement.

4. The method for evaluating the health status of a cable line according to claim 3, characterized in that: The feature vector analysis in step S3 includes: For an n-order judgment matrix A, solve its eigenvector v to satisfy Av = λv, where λ is the eigenvalue of the judgment matrix A; Divide each column of the judgment matrix A by the sum of the elements in the column to obtain the normalized judgment matrix A'; Calculate the eigenvector v' of the normalized judgment matrix A', satisfying A'v'=λ'v'; where λ is the eigenvalue of the normalized judgment matrix The eigenvector v' is the relative weight of each criterion; The step S3 of normalizing the feature vector is specifically as follows: The eigenvector v' is normalized so that the sum of its elements is equal to 1, and the normalized eigenvector w is obtained; the normalized eigenvector w is the weight of each criterion.

5. The method for evaluating the health status of a cable line according to claim 3, characterized in that: After step S5, comprehensive weighting is required: the weight of each criterion is multiplied by the weight of the level to which it belongs to obtain the final comprehensive weight, and the weight of the bottom criterion is transferred to the top-level goal through the hierarchical relationship of the hierarchy to obtain the relative importance of each criterion to the entire goal.

6. The method for evaluating the health status of a cable line according to claim 3, characterized in that: The steps of fuzzy mathematical method for fuzzy evaluation of the health status of cable lines are as follows: 1) Determine health status parameters: According to the working environment, operating conditions and evaluation requirements of the cable line, a set of appropriate health status parameters is selected, and the health status parameters include: Cable current: reflects the load condition of the cable; Cable voltage: reflects the deviation between the operating voltage of the cable and the rated value; Cable temperature: reflects the working thermal state of the cable to avoid failures caused by overheating; Cable humidity: environmental factors that affect the insulation performance of cables; 2) Determine the weight: The weight of each health status parameter was determined using the analytic hierarchy process; 3) Fuzzification: The acquired health status parameters are converted into fuzzy numbers, and the value of each parameter is mapped to the corresponding fuzzy set using membership functions; 4) Establishment of fuzzy rules: A set of fuzzy rules is established to map the fuzzy set of health status parameters to the fuzzy set of health status in the form of IF-THEN; each rule includes the following: IF part: consists of fuzzy sets of health status parameters; THEN part: the fuzzy set of health status corresponding to the fuzzy set of health status parameters; 5) Fuzzy reasoning: The established fuzzy rules are used for fuzzy reasoning. The specific process of fuzzy reasoning is as follows: Input the fuzzy set of health status parameters: input the fuzzified health status parameters into the external fuzzy reasoning system; Reasoning process: According to the fuzzy rules and the input fuzzy set, the fuzzy inference engine in the fuzzy inference system is used to perform reasoning to obtain the fuzzy set of the health status of the cable; 6) Defuzzification: The fuzzy set of health status of fuzzy reasoning results is converted into a deterministic health status evaluation value; 7) Health status evaluation: Based on the results of defuzzification, the health status of the cable line is divided into different levels and finally evaluated. The levels include: Good: The cable has no health problems and is running stably; Normal: The cable is within the normal operating range, there may be slight fluctuations, but it does not affect the overall performance; General: The cable has some problems, including local overheating or voltage fluctuations, but has not yet reached the failure standard; Problematic: The cable has serious health issues and needs to be repaired or replaced immediately.

7. The method for evaluating the health status of a cable line according to claim 6, characterized in that: The membership function in 3) adopts the triangular membership function, given the triangular membership function μ A (x), where x is the input variable, including temperature, current, voltage or humidity, and its fuzzy set A is expressed as: Among them, a, b, and c are the three parameters that define the triangle: a is the left endpoint, indicating the starting value of the fuzzy set; b is the peak value, indicating the maximum membership of the fuzzy set; c is the right endpoint, indicating the end value of the fuzzy set.

8. The method for evaluating the health status of a cable line according to claim 6, characterized in that: In step 6), an average method is used for defuzzification, including: First, the membership degree of each health status evaluation result is calculated; Then, according to the membership degree of each evaluation result and its corresponding weight, a weighted average is calculated as the determined evaluation result; The specific expression is as follows Assuming there are n health status evaluation results, the membership degrees are μ1, μ2, ..., μn, and the corresponding weights are w1, w2, ..., wn, then the determined evaluation result is the weighted average, that is: Health status evaluation result = (μ1*w1+μ2*w2+...+μn*wn) / (w1+w2+...+wn).

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