Wire conductor performance comprehensive test method and system

Abstract

The invention discloses a wire conductor performance comprehensive test method and system, and relates to the technical field of electrical engineering, and the test method comprises the steps: carrying out the uniform section division of a current test sample, analyzing the actual sampling resistance change condition of each resistance sampling point at each monitoring moment, and screening out a conductive abnormal section; and performing continuous temperature rise strain test and periodic loading test of the trapezoidal load on each abnormal conduction section, analyzing the overall structure degradation degree of the abnormal conduction section in each load cycle period, and analyzing the overall structure degradation trend of the abnormal conduction section according to a central difference method algorithm. Determining an overall structure degradation trend index of the conductive abnormal section; and judging whether the abnormal conduction section in the current test sample is in an overall structure degradation trend or not, and sending out a performance test report of a corresponding grade, thereby realizing degradation trend judgment and quantitative evaluation of the structure state of the wire conductor along with time lapse.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of electrical engineering, in particular to a wire conductor performance comprehensive testing method and system. BACKGROUND

[0002] In modern industry, as the core connection medium of power, telecommunications and automation control systems, the conductor performance of the wire directly affects the stability, energy efficiency and safety of the system. For a long time, the testing of conductor performance has been focused on material physical property measurement and resistance static value sampling at the initial factory stage, such as resistivity testing and on-off detection methods. However, with the extension of the running cycle, the conductor structure will change microscopically under the action of periodic thermal stress and mechanical load factors, thereby affecting its conductivity and structural integrity. Therefore, developing a system and method that can monitor and dynamically evaluate the performance evolution trend of the conductor in the actual use environment has become a key problem that needs to be solved in the industry.

[0003] Although resistance measurement, insulation layer integrity testing and short-time load simulation methods are commonly used in the current performance testing process of wire conductors, these methods have very limited dynamic evaluation capability in the actual service stage. Traditional testing methods can only obtain the static performance indicators of the conductor at a certain time or in a stable environment, and it is difficult to capture the structural degradation trend of the conductor under the influence of thermal expansion, periodic load and fatigue stress factors during long-term work. Especially when facing long-length and multi-section cable systems, the existing testing methods lack fine segmented measurement mechanisms and dynamic data accumulation methods, and early local conductivity abnormalities are easily ignored. In addition, the current testing model cannot combine thermal strain accumulation, load strain response and structural degradation trend, and it is difficult to realize the degradation trend judgment and quantitative evaluation of the conductor structure state over time.

[0004] The deficiencies of the existing wire conductor performance test technology are rooted in that the detection logic still stays in the static state and the single-point data evaluation model, and a three-dimensional test system covering dynamic state, multi-point data and trend analysis is not established. In actual application, the wire conductor is often in a complex service environment, such as temperature cycle change, mechanical vibration and load fluctuation. These environmental factors cause the microstructure of the conductor to change in the microstructure of thermal expansion, metal migration, dislocation accumulation and lattice slip. However, this micro-degradation process usually lacks obvious external characteristics in the early stage, which makes it difficult for the existing static test means to perceive in time. Especially in the scene of long service period and complex load environment, if the early degradation of the local conductive abnormal section is not detected, it may evolve into a serious system risk. For example, the local abnormal increase of conductor resistance is easy to cause uneven current carrying, induce overheating and insulation ablation, and even cause safety accidents such as electrical fire. At the same time, the structural fatigue generated under periodic load may accelerate the crack propagation or fracture of the conductor in a short time, and then cause the whole line to be invalid. SUMMARY

[0005] In view of the deficiencies of the prior art, the present application provides a wire conductor performance comprehensive test method and system, which solves the problems in the above background art.

[0006] To achieve the above purpose, the present application is realized by the following technical scheme: a wire conductor performance comprehensive test method, comprising the following steps:

[0007] S1, uniformly dividing the current test sample into sections, and combining the four-terminal measurement method to obtain the actual sampling resistance value of each resistance sampling point at each monitoring time, and screening out the conductive abnormal section by analyzing the actual sampling resistance change of each resistance sampling point at each monitoring time;

[0008] S2, continuously testing the temperature rise strain of each conductive abnormal section, analyzing the thermal expansion strain accumulation degree of the conductor structure of the conductive abnormal section in different temperature rise cycle intervals, and periodically loading the trapezoidal load to each conductive abnormal section, and analyzing the load strain degree of the conductor structure of the conductive abnormal section in each load cycle period;

[0009] S3, based on the temperature rise strain test and the periodic loading test, analyzing the overall structure degradation degree of the conductive abnormal section in each load cycle period, analyzing the overall structure degradation trend of the conductive abnormal section according to the central difference method algorithm, and determining the overall structure degradation trend index of the conductive abnormal section;

[0010] S4, judging whether the conductive abnormal section in the current test sample is in the overall structure degradation trend according to the numerical value of the overall structure degradation trend index of the conductive abnormal section, and issuing a performance test report of the corresponding level.

[0011] Preferably, S1 comprises the following specific steps:

[0012] S11, after the current test sample is divided into test segments, the actual sampling resistance values of each resistance sampling point at each monitoring time are determined by combining the four-terminal measurement method, specifically comprising:

[0013] S111, a fixed length of wire conductor is selected as the current test sample, the current test sample is uniformly divided into test segments according to the preset test segment division length, a plurality of test segments are obtained, and the initial conductor length of each test segment is recorded, the center point of each test segment is taken as a resistance sampling point, and each resistance sampling point is integrated with a four-terminal resistance measurement device, which is connected to the communication bus by wired connection and controlled by the central collector to synchronize the sampling period, wherein the four-terminal resistance measurement device comprises a voltage sensor and a Hall current sensor;

[0014] S112, during the continuous energization operation in the sampling period, the current and voltage of each resistance sampling point in the current test sample are sampled in real time according to the four-terminal resistance measurement device integrated with each resistance sampling point, and the four-terminal measurement method is adopted to obtain the current and voltage values of each resistance sampling point at each monitoring time;

[0015] S113, the current and voltage values of each resistance sampling point at each monitoring time are input into an Ohm's law calculation model to analyze the actual resistance value state of each resistance sampling point at each monitoring time, and the actual sampling resistance value of each resistance sampling point at each monitoring time is obtained.

[0016] Preferably, S1 further comprises the following specific steps:

[0017] S12, the actual sampling resistance values of each resistance sampling point at two consecutive monitoring times are differentially processed to analyze the actual sampling resistance change of each resistance sampling point at each monitoring time, and the resistance change rate of each resistance sampling point at each monitoring time is determined, specifically: ; wherein, represents the resistance change rate of the i th resistance sampling point at the j th monitoring time, represents the actual sampling resistance value of the i th resistance sampling point at the j th monitoring time, represents the actual sampling resistance value of the i th resistance sampling point at the j-1 th monitoring time, wherein i represents the number of resistance sampling points, and j represents the number of monitoring times.

[0018] Preferably, S1 further comprises the following specific steps:

[0019] S13, based on the determined resistance change rate of each resistance sampling point at each monitoring time, after digital-analog analysis, an abnormal conduction section is selected, specifically comprising:

[0020] S131. Based on the resistance change rate of each resistance sampling point at each monitoring time, and combined with the statistical mean-averaging algorithm, obtain the average resistance change rate of each resistance sampling point within the sampling period.

[0021] S132. Perform numerical simulation analysis on the average resistance change rate of each resistance sampling point within the sampling period, and establish a two-dimensional coordinate system with the value of the average resistance change rate as the vertical axis and the number of the resistance sampling point as the horizontal axis. Plot the average resistance change rate of each resistance sampling point within the sampling period on the two-dimensional coordinate system in the form of a broken line to construct a resistance change broken line graph, wherein the resistance change broken line graph includes the resistance change broken line of each resistance sampling point.

[0022] S133. Record the angle formed by the resistance change line at each resistance sampling point in the resistance change graph and the horizontal line to obtain the resistance change angle at each resistance sampling point. Combined with the statistical mean-value algorithm, calculate the average resistance change angle at each resistance sampling point. Compare and analyze the resistance change angle at each resistance sampling point with the average resistance change angle. If the resistance change angle at the corresponding resistance sampling point is greater than the average resistance change angle, it indicates that the conductivity of the test section where the corresponding resistance sampling point is located is abnormal. Then, mark the corresponding test section as a conductivity abnormal section. Based on the initial unloaded conductor length of each conductivity abnormal section, calculate the total initial unloaded conductor length of the conductivity abnormal section. Otherwise, mark the corresponding test section as a conductivity normal section.

[0023] Preferably, step S2 specifically includes:

[0024] S21. Based on multiple preset temperature rise cycle intervals, continuous temperature rise strain tests are performed on each conductive abnormal section in the current test sample. The thermal expansion conductor length of each conductive abnormal section in each temperature rise cycle interval is collected by a laser displacement sensor. Combined with a statistical summation algorithm, the total thermal expansion conductor length of the conductive abnormal section in each temperature rise cycle interval is calculated. The total thermal expansion conductor length of the conductive abnormal section in each temperature rise cycle interval is calculated by subtracting it from the initial unloaded conductor length to determine the total change length of the thermal expansion conductor of the conductive abnormal section in each temperature rise cycle interval. The temperature rise strain test process includes a heating stage, a constant temperature stage, and a cooling stage.

[0025] S22. Correlate the total change in thermal expansion length of the conductor in the abnormal conductivity section within each temperature rise cycle interval with the initial unloaded conductor length. After dimensionless processing, analyze the degree of thermal expansion strain accumulation in the conductor structure of the abnormal conductivity section within different temperature rise cycle intervals, and determine the thermal expansion strain accumulation coefficient, specifically: In the formula, This represents the cumulative coefficient of thermal expansion strain. This represents the total change in conductor length due to thermal expansion during the f-th temperature rise cycle in the section with abnormal conductivity. This represents the initial unloaded total length of the abnormal conductivity section, and n represents the number of temperature rise cycle intervals.

[0026] Preferably, step S2 further includes:

[0027] S23. Fix both ends of the current test sample between the loading fixtures. Drive the fixtures to move back and forth according to the preset loading frequency and loading amplitude by the electric servo controller to perform a periodic loading test of trapezoidal load on each conductive abnormal section in the current test sample. The periodic loading test process includes a loading stage, a holding stage and an unloading stage.

[0028] S24. The time required to complete a single cycle loading test is denoted as the load cycle. During the continuous load strain test of each conductive abnormal section, the conductor strain state of each conductive abnormal section in each load cycle is monitored by a laser displacement sensor. The strain-stable conductor length of each conductive abnormal section in each load cycle is obtained. Combined with a statistical summation algorithm, the total strain-stable conductor length of the conductive abnormal section in each load cycle is calculated.

[0029] S25. Correlate the total strain-stabilized conductor length of the abnormal conductivity section in each load cycle with the initial unloaded conductor length. After dimensionless processing, analyze the load strain degree of the conductor structure in each load cycle of the abnormal conductivity section, and determine the load strain degree coefficient of the abnormal conductivity section in each load cycle. Specifically: In the formula, This represents the load strain degree coefficient of the abnormal conductivity section during the k-th load cycle. This represents the total strain-stabilized conductor length of the abnormal conductivity section during the k-th load cycle. t represents the initial unloaded total length of the abnormal conductivity section, and t represents the duration of the load cycle.

[0030] Preferably, step S3 specifically includes:

[0031] S31. Correlate the load strain degree coefficient of the conductive abnormal section with the thermal expansion strain cumulative coefficient in each load cycle to analyze the overall structural degradation degree of the conductive abnormal section in the current test sample in each load cycle, and determine the structural degradation degree index of the conductive abnormal section in each load cycle, specifically: In the formula, An index representing the degree of structural degradation in the abnormal conductivity section during the k-th load cycle. This represents the load strain degree coefficient of the abnormal conductivity section during the k-th load cycle. This represents the cumulative coefficient of thermal expansion strain.

[0032] Preferably, step S3 further includes:

[0033] S32. Based on the determined structural degradation index of the conductive abnormal segment in each load cycle, and combined with the central difference method algorithm, analyze the structural degradation trend of the conductive abnormal segment in the current test sample in each load cycle, and determine the structural degradation trend index of the conductive abnormal segment in each load cycle, specifically: In the formula, The index represents the structural degradation trend of the abnormal conductivity section during the k-th load cycle. The index represents the degree of structural degradation of the abnormal conductivity section in the kth load cycle, and t represents the duration of the load cycle.

[0034] S33. Based on the structural degradation trend index of the determined conductive abnormal section in each load cycle, and combined with the statistical summation algorithm, obtain the overall structural degradation trend index of the conductive abnormal section in the current test sample.

[0035] Preferably, step S4 specifically includes:

[0036] S41. Based on the magnitude of the overall structural degradation trend index of the conductive abnormal section in the current test sample, determine whether the conductive abnormal section in the current test sample is in an overall structural degradation trend, and issue a performance test report of the corresponding level, specifically including:

[0037] If the overall structural degradation trend index of the conductive abnormal section in the current test sample does not exceed zero, it indicates that the conductive abnormal section in the current test sample is not in an overall structural degradation trend, and a first-level performance test report is issued, stating that the performance test of the current test sample is qualified.

[0038] If the overall structural degradation trend index of the conductive abnormal section in the current test sample exceeds zero, it indicates that the conductive abnormal section in the current test sample is in an overall structural degradation trend, and a secondary performance test report will be issued, stating that the performance test of the current test sample is unqualified.

[0039] A comprehensive testing system for the performance of electrical wire conductors includes an abnormal section screening module, a performance testing module, a degradation assessment module, and a judgment module.

[0040] The abnormal section screening module is used to divide the current test sample into uniform sections and, combined with the four-terminal measurement method, obtain the actual sampling resistance value of each resistance sampling point at each monitoring time. By analyzing the changes in the actual sampling resistance of each resistance sampling point at each monitoring time, abnormal conductive sections are screened out.

[0041] The performance testing module is used to perform continuous temperature rise strain tests on each conductive abnormal section, analyze the degree of thermal expansion strain accumulation of the conductor structure in different temperature rise cycle intervals, and perform periodic loading tests of trapezoidal loads on each conductive abnormal section to analyze the degree of load strain of the conductor structure in each load cycle.

[0042] The degradation assessment module is used to analyze the overall structural degradation degree of the conductive abnormal section in each load cycle based on temperature rise strain test and periodic loading test. According to the central difference method algorithm, it analyzes the overall structural degradation trend of the conductive abnormal section and determines the overall structural degradation trend index of the conductive abnormal section.

[0043] The judgment module is used to determine whether the conductive abnormal section in the current test sample is in an overall structural degradation trend based on the value of the overall structural degradation trend index of the conductive abnormal section, and to issue a performance test report of the corresponding level.

[0044] This invention provides a comprehensive testing method and system for the performance of electrical wire conductors, which has the following beneficial effects:

[0045] (1) By constructing a multi-dimensional testing mechanism that integrates dynamic resistance change monitoring, thermal strain accumulation analysis and load strain response evaluation, the limitations of existing wire conductor performance testing, which can only statically obtain single-point resistance or short-term continuity information, are overcome. This enables continuous tracking and quantitative judgment of the performance evolution trend of conductors in long-term service environments. By introducing a four-terminal measurement method combined with a segmented sampling structure, the accuracy of identifying local anomalies in long-length, multi-segment conductors is effectively improved. Furthermore, by using laser displacement measurement and periodic trapezoidal load loading technology, the micro-strain response of the conductor is dynamically acquired under thermal stress and mechanical load conditions, constructing a complete state evolution chain covering thermal expansion, strain accumulation and structural degradation. The structural degradation trend index is derived using the central difference method and statistical modeling, providing a quantitative basis for the assessment and early warning of conductor safety status. This invention significantly improves the ability to assess the long-term operational stability of wire conductors and the efficiency of identifying local degradation. It can be widely applied to high reliability requirements in scenarios such as power transmission, aerospace, automatic control and communication infrastructure, effectively enhancing the system's safety, intelligence and maintenance foresight.

[0046] (2) By dividing the test sample into fine segments and deploying a four-terminal resistance measurement unit at the center of each test segment, dynamic sampling and tracking of the resistance values ​​of each segment of the conductor at multiple times and multiple cycles can be achieved during the test. This method breaks the limitation of the traditional method, which can only measure static indicators of resistivity and continuity at the factory. It can identify the abnormal conductivity trend caused by micro-defects inside the conductor by differential calculation, mean analysis and statistical analysis of the resistance change rate at different monitoring times. On this basis, by constructing a resistance change line graph and a comparison model of the average angle, it can achieve accurate screening of potential abnormal segments. This dynamic, multi-point and continuous monitoring mechanism enables the entire conductor testing technology to achieve self-sensing and self-diagnosis, improves the ability to identify potential safety hazards in advance, and provides stable and reliable data support for subsequent strain loading and degradation trend analysis, effectively filling the gap in the lack of segmented trend assessment in the existing technology.

[0047] (3) By integrating the results of temperature rise strain test and cyclic loading strain test, a quantitative assessment model of degradation trend covering the entire life cycle of the conductor was established. Specifically, the thermal strain accumulation coefficient was obtained by performing dimensionless calculation on the total change length of thermal expansion conductor in different temperature rise cycle intervals of the abnormal conductivity section. At the same time, the total length of strain-stable conductor under cyclic loading was statistically analyzed to calculate the load strain degree coefficient. The two together constitute the core index describing the conductor's stress response and structural deformation. By constructing the structural degradation degree index and its central difference analysis model, the structural degradation trend index was derived to reflect the structural performance degradation trajectory of the conductor in continuous working cycles. The structural degradation trend index quantitatively characterizes the degree of conductor degradation, realizes the automatic identification and reporting of conductor performance test results, and thus significantly enhances the efficiency of intelligent testing and operation and maintenance decision support. The trend index and hierarchical judgment mechanism proposed in this invention provide a more scientific, detailed and quantitative assessment method for conductor structural degradation trend, which has extremely important engineering value for building smart grids and realizing predictive maintenance. Attached Figure Description

[0048] Figure 1 This is a schematic diagram of the process for a comprehensive testing method for the performance of wire conductors according to the present invention;

[0049] Figure 2 This is a block diagram of a comprehensive testing system for the performance of electrical wire conductors according to the present invention;

[0050] Figure 3 This is a logic diagram of a comprehensive testing method for the performance of electrical conductors according to the present invention. Detailed Implementation

[0051] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0052] Example 1

[0053] Please see Figure 1 This invention provides a comprehensive testing method for the performance of electrical wire conductors, comprising the following steps:

[0054] S1. Divide the current test sample into uniform sections and combine the four-terminal measurement method to obtain the actual sampling resistance value of each resistance sampling point at each monitoring time. By analyzing the changes in the actual sampling resistance of each resistance sampling point at each monitoring time, the abnormal conductivity sections are screened out.

[0055] S2. Conduct continuous temperature rise strain tests on each conductive abnormal section to analyze the degree of thermal expansion strain accumulation of the conductor structure in different temperature rise cycle intervals. Conduct periodic loading tests of trapezoidal loads on each conductive abnormal section to analyze the degree of load strain of the conductor structure in each load cycle.

[0056] S3. Based on temperature rise strain test and periodic loading test, analyze the overall structural degradation degree of the conductive abnormal section in each load cycle. According to the central difference method algorithm, analyze the overall structural degradation trend of the conductive abnormal section and determine the overall structural degradation trend index of the conductive abnormal section.

[0057] S4. Based on the magnitude of the overall structural degradation trend index of the abnormal conductivity section, determine whether the abnormal conductivity section in the current test sample is in an overall structural degradation trend, and issue a performance test report of the corresponding level.

[0058] In this embodiment, a multi-dimensional comprehensive evaluation system integrating segmented dynamic detection, thermal strain accumulation analysis, cyclic load response testing, and structural degradation trend judgment is constructed. This significantly overcomes the limitations of existing technologies, which only offer static evaluation, single-point sampling, ignore trends, and lack detailed partitioning. By performing detailed segmentation of the wire conductor sample at the initial stage of testing and combining it with the four-terminal measurement method to collect resistance change data of each sampling point at different times in real time, the shortcomings of traditional technologies in accurately identifying local conductivity anomalies when dealing with long-length, multi-segment conductors are effectively compensated for. Furthermore, addressing the performance degradation of conductor structures during long-term service caused by factors such as thermal expansion, cyclic loads, and fatigue stress, as mentioned in the background technology, this system effectively overcomes these limitations. To address the practical challenges of operating conditions, this method further incorporates temperature rise strain testing and cyclic loading testing to dynamically capture the strain evolution of conductor structures under different environmental stress conditions. In particular, by constructing a structural degradation trend index, it can not only quantitatively determine the structural change trend of conductors during their service life but also classify and automatically generate test reports based on this index. This marks the first time that trend identification and intelligent level output of conductor performance degradation have been achieved. This method effectively fills the gaps in existing conductor performance evaluation methods in terms of "dynamics, trends, and precision." It is suitable for industrial scenarios requiring long-term stable operation and complex service conditions, and has significant engineering value in ensuring system safety, extending conductor life, and preventing local failures from evolving into system accidents.

[0059] Example 2

[0060] Please refer to Figure 1 Specifically: S1 includes the following steps:

[0061] S11. After dividing the current test sample into test segments, and using the four-terminal measurement method, determine the actual sampling resistance value of each resistance sampling point at each monitoring time, specifically including:

[0062] S111. Select a wire conductor of fixed length as the current test sample. Divide the current test sample into uniform sections according to the preset test section division length to obtain several test sections. Record the initial unloaded conductor length of each test section. Use the center point of each test section as the resistance sampling point. At the same time, each resistance sampling point is integrated with a four-terminal resistance measuring device. It is connected to the communication bus through a wired connection and the sampling cycle is synchronously controlled by the central acquisition unit. The four-terminal resistance measuring device includes a voltage sensor and a Hall current sensor.

[0063] S112. During the continuous power-on operation within the sampling period, the current and voltage of each resistance sampling point in the current test sample are sampled in real time using the four-terminal resistance measuring device integrated at each resistance sampling point and the four-terminal measurement method, so as to obtain the current and voltage values ​​of each resistance sampling point at each monitoring time.

[0064] S113. Input the current and voltage values ​​of each resistance sampling point at each monitoring time into the Ohm's law calculation model, analyze the actual resistance state of each resistance sampling point at each monitoring time, and obtain the actual sampling resistance value of each resistance sampling point at each monitoring time.

[0065] Specifically, the S1 steps also include:

[0066] S12. Differentiate the actual sampling resistance values ​​of each resistance sampling point at two consecutive monitoring times, analyze the changes in the actual sampling resistance of each resistance sampling point at each monitoring time, and determine the rate of change of resistance of each resistance sampling point at each monitoring time, specifically as follows: In the formula, This represents the rate of change of resistance at the i-th resistance sampling point at the j-th monitoring time. This represents the actual sampled resistance value of the i-th resistance sampling point at the j-th monitoring time. This represents the actual sampled resistance value of the i-th resistance sampling point at the (j-1)-th monitoring time, where i represents the number of resistance sampling points and j represents the number of monitoring times.

[0067] It should be noted that the above formula originates from the discrete-time series relative change rate calculation model, which essentially quantitatively expresses the trend of conductor resistance change. By differentiating and normalizing the actual resistance values ​​of the i-th resistance sampling point at two adjacent monitoring times j and j-1, the relative resistance change rate per unit time is calculated. This processing method not only retains the change information of the original resistance sampling data, but also eliminates the influence of different initial values ​​through normalization, making the change data of different segments and different times comparable and trend-expressing. In this invention, this formula is applied to resistance change rate analysis, which is the key mathematical basis for subsequent screening of abnormal conductivity segments. By further performing statistical graphical analysis on the resistance change rate of each sampling point, the identification of small but continuous electrical abnormal fluctuations is achieved, thereby locking in the abnormal conductivity segments in advance before the conductor shows obvious degradation or damage. Therefore, in this invention, this formula not only plays the role of a mathematical tool for signal amplification and trend modeling, but also directly supports the early discrimination capability and refined monitoring advantages of the entire conductor performance dynamic evaluation mechanism, possessing extremely high practicality and engineering value.

[0068] Specifically, the S1 steps also include:

[0069] S13. Based on the resistance change rate at each monitoring time of the determined resistance sampling points, after numerical simulation analysis, the abnormal conductivity sections are screened out, specifically including:

[0070] S131. Based on the resistance change rate of each resistance sampling point at each monitoring time, and combined with the statistical mean-averaging algorithm, obtain the average resistance change rate of each resistance sampling point within the sampling period.

[0071] S132. Perform numerical simulation analysis on the average resistance change rate of each resistance sampling point within the sampling period, and establish a two-dimensional coordinate system with the value of the average resistance change rate as the vertical axis and the number of the resistance sampling point as the horizontal axis. Plot the average resistance change rate of each resistance sampling point within the sampling period on the two-dimensional coordinate system in the form of a broken line to construct a resistance change broken line graph, wherein the resistance change broken line graph includes the resistance change broken line of each resistance sampling point.

[0072] S133. Record the angle formed by the resistance change line at each resistance sampling point in the resistance change graph and the horizontal line to obtain the resistance change angle at each resistance sampling point. Combined with the statistical mean-value algorithm, calculate the average resistance change angle at each resistance sampling point. Compare and analyze the resistance change angle at each resistance sampling point with the average resistance change angle. If the resistance change angle at the corresponding resistance sampling point is greater than the average resistance change angle, it indicates that the conductivity of the test section where the corresponding resistance sampling point is located is abnormal. Then, mark the corresponding test section as a conductivity abnormal section. Based on the initial unloaded conductor length of each conductivity abnormal section, calculate the total initial unloaded conductor length of the conductivity abnormal section. Otherwise, mark the corresponding test section as a conductivity normal section.

[0073] In this embodiment, the complete set of segmented resistance dynamic sampling and conductivity anomaly segment identification process designed in S1 based on the four-terminal measurement method effectively solves the key technical bottlenecks in the prior art, such as the difficulty in fine segmented detection of long conductors, the difficulty in identifying early degradation trends through static single-point testing, and the lack of an effective data processing model to extract local anomaly features. First, through the uniform segmentation of the conductor sample and the central arrangement of resistance sampling points in S111, and by integrating a four-terminal resistance measuring device with high-precision measurement capabilities, synchronous sampling and high-resolution recording of multi-point resistance values ​​are achieved, providing structural support for continuous monitoring of multiple times and multiple segments. Compared with the traditional evaluation method that relies on single-point static resistance values, this configuration improves the sensitivity to local electrical fluctuations inside the conductor. Second, in S112 and S113, by introducing real-time current and voltage acquisition data into the Ohm's law model, the actual sampling resistance at each monitoring time is dynamically deduced, forming a time series. The system utilizes performance evolution data to lay the foundation for trend analysis and fluctuation identification. Furthermore, through resistance change rate differential analysis in S12 and digital model graphical analysis (resistance change line graph construction and angle statistical analysis) in S13, the system can quickly identify segments with significant electrical anomalies in massive segmented data. Especially when the conductor is in the early stage of slight degradation and has not yet shown obvious physical damage characteristics, it can still provide early warning through the mathematical feature of the angle of change exceeding the mean, thus achieving a major breakthrough in the ability to screen for potential conductive risks in the early stage. Compared with the existing traditional methods that can only be tested when the conductor is severely degraded, this method has the ability to extract and judge dynamic, trend-based, segmented, and quantitative features. It truly establishes a front-end basic framework for dynamic monitoring and anomaly identification of conductor resistance throughout its entire life cycle, providing a solid data foundation and initial screening basis for subsequent thermal strain analysis and structural degradation trend assessment, and enhancing the comprehensive control over the safety status of conductors in operation.

[0074] Example 3

[0075] Please refer to Figure 1 Specifically: The specific steps of S2 include:

[0076] S21. Based on multiple preset temperature rise cycle intervals, continuous temperature rise strain tests are performed on each conductive abnormal section in the current test sample. The thermal expansion conductor length of each conductive abnormal section in each temperature rise cycle interval is collected by a laser displacement sensor. Combined with a statistical summation algorithm, the total thermal expansion conductor length of the conductive abnormal section in each temperature rise cycle interval is calculated. The total thermal expansion conductor length of the conductive abnormal section in each temperature rise cycle interval is calculated by subtracting it from the initial unloaded conductor length to determine the total change length of the thermal expansion conductor of the conductive abnormal section in each temperature rise cycle interval. The temperature rise strain test process includes a heating stage, a constant temperature stage, and a cooling stage.

[0077] S22. Correlate the total change in thermal expansion length of the conductor in the abnormal conductivity section within each temperature rise cycle interval with the initial unloaded conductor length. After dimensionless processing, analyze the degree of thermal expansion strain accumulation in the conductor structure of the abnormal conductivity section within different temperature rise cycle intervals, and determine the thermal expansion strain accumulation coefficient, specifically: In the formula, This represents the cumulative coefficient of thermal expansion strain. This represents the total change in conductor length due to thermal expansion during the f-th temperature rise cycle in the section with abnormal conductivity. This represents the initial unloaded total length of the abnormal conductivity section, and n represents the number of temperature rise cycle intervals.

[0078] It should be noted that this formula is derived based on the principle of multi-stage dimensionless cumulative effect modeling. It is mainly used to quantify the total accumulation of structural strain caused by thermal expansion in the abnormal conductive section during multiple temperature rise cycles. The core of its derivation is to normalize the total change in length of the conductor in the abnormal section caused by thermal expansion in each temperature rise cycle interval to the initial unloaded conductor length of the abnormal section, thereby obtaining the strain borne by a unit initial length. The strain is then accumulated over all temperature rise cycle intervals to obtain the thermal expansion strain accumulation coefficient. This dimensionless coefficient not only eliminates the bias caused by inconsistent sample lengths, but also has good comparability across samples and time periods. In practical applications of this invention, the formula is used in the quantitative analysis of thermal strain in S22 as a core evaluation index for microstructure evolution under thermal stress. By analyzing the changing trend of the cumulative coefficient of thermal expansion strain, it effectively determines whether abnormal sections exhibit abnormal plastic deformation, material migration, or potential structural degradation during continuous temperature rise. Its effect is that it can deduce the trend of microstructure performance changes from macroscopic thermal cycling behavior, enhancing the reliability and foresight of conductor performance testing methods in long-term service simulation, life prediction, and hazard identification. The introduction of this formula means that this invention is no longer limited to static performance evaluation, but has the ability to model dynamic response during thermal environment evolution, significantly improving the testing method's ability to perceive early thermally induced structural risks.

[0079] Specifically, the S2 steps also include:

[0080] S23. Fix both ends of the current test sample between the loading fixtures. Drive the fixtures to move back and forth according to the preset loading frequency and loading amplitude by the electric servo controller to perform a periodic loading test of trapezoidal load on each conductive abnormal section in the current test sample. The periodic loading test process includes a loading stage, a holding stage and an unloading stage.

[0081] S24. The time required to complete a single cycle loading test is denoted as the load cycle. During the continuous load strain test of each conductive abnormal section, the conductor strain state of each conductive abnormal section in each load cycle is monitored by a laser displacement sensor. The strain-stable conductor length of each conductive abnormal section in each load cycle is obtained. Combined with a statistical summation algorithm, the total strain-stable conductor length of the conductive abnormal section in each load cycle is calculated.

[0082] S25. Correlate the total strain-stabilized conductor length of the abnormal conductivity section in each load cycle with the initial unloaded conductor length. After dimensionless processing, analyze the load strain degree of the conductor structure in each load cycle of the abnormal conductivity section, and determine the load strain degree coefficient of the abnormal conductivity section in each load cycle. Specifically: In the formula, This represents the load strain degree coefficient of the abnormal conductivity section during the k-th load cycle. This represents the total strain-stabilized conductor length of the abnormal conductivity section during the k-th load cycle. t represents the initial unloaded total length of the abnormal conductivity section, and t represents the duration of the load cycle.

[0083] It should be noted that this formula originates from the structural strain normalization modeling method in engineering mechanics. Essentially, it constructs an index that quantitatively describes the degree of plastic deformation of a conductor structure under mechanical load over time by subtracting the strain-stabilized total length of the conductor in the kth load cycle from its initial unloaded total length and then normalizing the difference. This formula can not only measure the macroscopic performance of elongation, yielding, or microcrack evolution of a conductor structure within a single cycle, but also possesses good standardization and trend expression capabilities. In this invention, this formula is applied to the load strain response analysis process in S25, where its function is to continuously record the load strain degree coefficient under each load cycle. This invention dynamically identifies the deformation evolution trajectory and fatigue response of conductors under cyclic loads, providing highly reliable data support for subsequent degradation trend analysis and risk level classification. In terms of effectiveness, this formula significantly expands upon the limitations of traditional testing methods that can only assess current-carrying capacity or short-term tensile strength. For the first time, it achieves a quantifiable expression of structural deformation changes with cyclic loads, enabling early identification of fatigue-induced structural fragility or fracture risks, thus providing a more accurate and dynamic health assessment capability. Overall, the load strain coefficient constructs a mapping bridge between "mechanical stress—structural response—degradation trend," and is one of the core mathematical supports for this invention's advancement towards intelligent load perception and structural self-diagnosis.

[0084] In this embodiment, the dual mechanism of temperature rise strain testing and cyclic loading testing introduced in S2 provides a complete solution to the core problems of traditional technologies, such as difficulty in simulating actual service stress environments, lack of dynamic strain response monitoring capabilities, and difficulty in assessing the cumulative fatigue degradation of conductor structures. Firstly, in S21 and S22, multiple temperature rise cycle intervals are set to simulate the heating, isothermal, and cooling processes experienced by the conductor in real-world environments. Combined with a laser displacement sensor, the thermal expansion conductor length in abnormal conductivity sections is continuously monitored, accurately obtaining the actual physical expansion response of the conductor under thermal excitation. A model of the total change in conductor length under thermal expansion is established based on the initial unloaded conductor length. Furthermore, after dimensionless normalization, the cumulative coefficient of thermal expansion strain is derived, effectively quantifying the historical cumulative degradation degree of the conductor under temperature stress. This method overcomes the shortcomings of traditional static resistance testing, which cannot reflect the influence of temperature stress, and fills the gap in comprehensive thermal environment degradation monitoring. Secondly, in S23 to S25, a gradient... The method employs a waveform-cycle loading approach, utilizing a servo-driven fixture to control the conductor throughout the entire "loading-holding-unloading" process. A laser displacement sensor is used to collect data on the strain-stabilized conductor length, yielding the true strain response under cyclic loads. By summarizing and processing the strain changes across different load cycles, a load strain coefficient model is established to reflect the structural deformation stability of the conductor in the stress environment. Notably, this method achieves structural response modeling and measurement index construction based on both thermal and mechanical stress dimensions, effectively reproducing the multi-factor degradation process of the conductor under complex service scenarios. Compared to existing technologies that can only evaluate a single indicator (resistance or current-carrying capacity), the strain dual-model evaluation mechanism constructed in this invention can, from the perspective of microstructural changes, form a realistic, dynamic, and trend-based characterization of performance degradation in abnormal conductive sections. This enhances the predictive and identification capabilities of conductor safety hazards, providing a solid technical foundation and practical path for building a safer, more controllable, and highly reliable power line operation monitoring system.

[0085] Example 4

[0086] Please refer to Figure 1 Specifically: The specific steps of S3 include:

[0087] S31. Correlate the load strain degree coefficient of the conductive abnormal section with the thermal expansion strain cumulative coefficient in each load cycle to analyze the overall structural degradation degree of the conductive abnormal section in the current test sample in each load cycle, and determine the structural degradation degree index of the conductive abnormal section in each load cycle, specifically: In the formula, An index representing the degree of structural degradation in the abnormal conductivity section during the k-th load cycle. This represents the load strain degree coefficient of the abnormal conductivity section during the k-th load cycle. This represents the cumulative coefficient of thermal expansion strain.

[0088] It should be noted that this formula is a unified evaluation model constructed based on the idea of ​​superimposing multi-source strain accumulation factors, used to comprehensively evaluate the overall structural degradation degree of the conductive anomaly segment in the k-th load cycle. This formula linearly superimposes the load strain degree coefficient, representing the deformation response capability under cyclic load, with the thermal expansion strain accumulation coefficient representing the total strain accumulation during the historical temperature rise process, forming a unified quantitative index of structural degradation. This achieves attribution and comprehensive modeling of the microstructural changes of the conductor under the superposition of different external stress sources. Its derivation logic embodies the dynamic evaluation idea of ​​"historical accumulation + current response." In the implementation process of this invention, this formula is applied to the structural degradation stage judgment loop in S31. By continuously tracking the structural degradation index value in each load cycle, the stability of the structure in the abnormal conductivity section can be gradually monitored and confirmed in stages. The main effects are: on the one hand, it improves the global coverage and temporal continuity of the assessment; on the other hand, it enhances the ability to sensitively identify and quantify the material performance degradation caused by thermo-mechanical coupling. As a bridge connecting the two core factors of thermal expansion and mechanical load, this index is a key foundation for building a structural degradation trend prediction model and a performance grading judgment mechanism. It helps to promote the upgrading of conductor performance assessment from static index detection to dynamic evolution identification, and significantly improves its practical value and technological leadership in long-term service environments.

[0089] Specifically, the S3 steps also include:

[0090] S32. Based on the determined structural degradation index of the conductive abnormal segment in each load cycle, and combined with the central difference method algorithm, analyze the structural degradation trend of the conductive abnormal segment in the current test sample in each load cycle, and determine the structural degradation trend index of the conductive abnormal segment in each load cycle, specifically: In the formula, The index represents the structural degradation trend of the abnormal conductivity section during the k-th load cycle. The index represents the degree of structural degradation of the abnormal conductivity section in the kth load cycle, and t represents the duration of the load cycle.

[0091] It should be noted that this formula originates from the central difference method in numerical analysis. This algorithm is often used to quantitatively determine the concavity and trend of function curves in continuous time series. In this invention, this formula is used as... The input variable, namely the structural degradation index obtained in S13, is used to capture the acceleration of its change (the trend of degradation rate) by differentiating its values ​​at three consecutive periodic points. Unlike the first-order rate of change, which can only reflect a rough trend of increase or decrease, the second-order difference calculation result can reveal whether the degree of structural degradation exhibits complex dynamic evolution characteristics such as accelerated deterioration, slowing down and stabilizing, or inflection point reversal, and has stronger sensitivity and foresight. In the implementation of this invention, this formula is used for the analysis and quantitative identification of the degradation trend of the conductive anomaly section in S32, and its output result serves as a trend indicator. The indicators, after further accumulation, constitute the overall degradation trend index in S33, which is ultimately used in the performance level judgment mechanism. Its effect is to give it the ability to dynamically predict the trend of conductor structure changes, especially in the implicit stage when the conductor has not yet shown obvious performance degradation, but its degradation trend has already begun to accelerate. This formula can keenly capture the change signal, thereby achieving abnormal response and operation and maintenance intervention earlier than traditional methods. In summary, the introduction of this formula not only enriches the mathematical depth of structural degradation modeling, but also makes this invention have stronger engineering application value and intelligent processing capabilities in trend identification, early warning and control, and life prediction.

[0092] S33. Based on the structural degradation trend index of the determined conductive abnormal section in each load cycle, and combined with the statistical summation algorithm, obtain the overall structural degradation trend index of the conductive abnormal section in the current test sample.

[0093] In this embodiment, the degradation assessment model constructed through S3 effectively overcomes the key shortcomings of existing technologies, such as the lack of multi-factor fusion modeling, difficulty in quantifying the degradation process of conductor structures, and difficulty in forming trend-based early warning indicators. It proposes a structural degradation trend analysis method that integrates both thermal strain and mechanical strain parameters. By correlating the load strain degree coefficient and the thermal expansion strain accumulation coefficient in S31, a quantitative characterization of the comprehensive performance degradation level of the conductive anomaly section under each load cycle is achieved, thereby constructing a structural degradation degree index. The structural degradation degree index takes into account both temperature-induced changes in the material's microstructure and the deformation response caused by mechanical loading, effectively overcoming the shortcomings of previous single-factor analyses that could not accurately reflect the actual degradation degree, ensuring the physical meaning and structural correspondence of the assessment results. Simultaneously, the central difference algorithm is introduced in S32 to perform time-series difference calculations, obtaining the structural degradation trend index, which can accurately depict the directionality and evolution of conductor performance degradation during continuous operating cycles. This improves efficiency and overcomes the lag and insensitivity issues inherent in traditional "current state determination methods." Furthermore, S33 uses statistical summaries of multiple periodic trend indices to form an overall structural degradation trend index, serving as a digital benchmark for the macroscopic conductor performance health level and providing a highly reliable basis for subsequent automatic grading and structural degradation prediction. Crucially, this degradation trend analysis system solves the technical challenge mentioned in the background technology: "the conductor's microstructure lacks external manifestations in the early degradation stage and is difficult to capture by traditional methods." It enables proactive identification and trend prediction of potential hazards, effectively preventing systemic failures caused by untimely warnings of local degradation. In summary, S3 not only achieves a closed-loop logic from raw sampling data to trend health indicators but also constructs an intelligent evaluation mechanism with long-term tracking capabilities, dynamic evolution monitoring capabilities, and data-driven prediction capabilities, providing important technical support for advancing wire conductor testing from static evaluation to dynamic intelligent diagnosis.

[0094] Example 5

[0095] Please refer to Figure 1 Specifically: The specific steps of S4 include:

[0096] S41. Based on the magnitude of the overall structural degradation trend index of the conductive abnormal section in the current test sample, determine whether the conductive abnormal section in the current test sample is in an overall structural degradation trend, and issue a performance test report of the corresponding level, specifically including:

[0097] If the overall structural degradation trend index of the conductive abnormal section in the current test sample does not exceed zero, it indicates that the conductive abnormal section in the current test sample is not in an overall structural degradation trend, and a first-level performance test report is issued, stating that the performance test of the current test sample is qualified.

[0098] If the overall structural degradation trend index of the conductive abnormal section in the current test sample exceeds zero, it indicates that the conductive abnormal section in the current test sample is in an overall structural degradation trend, and a secondary performance test report will be issued, stating that the performance test of the current test sample is unqualified.

[0099] In this embodiment, the performance grading and judgment mechanism based on the structural degradation trend index established in S4 effectively solves the prominent problems in the prior art, such as "difficulty in realizing trend judgment and automatic grade output of conductor performance status" and "evaluation results remaining at the fuzzy qualitative stage and lacking clear decision-making basis," significantly improving the intelligence and practicality of the wire conductor performance testing system. Specifically, S4 achieves quantitative combination and graded judgment of state and trend by numerically judging the overall structural degradation trend index of the abnormal conductivity section, using whether it exceeds zero as a clear judgment threshold. When the overall structural degradation trend index does not exceed zero, it indicates that the current conductor structure is in a stable state, and a first-level performance test report will be automatically generated to confirm that it is a qualified sample. Conversely, when the trend index is positive, it indicates that the conductor structure is developing in an unfavorable direction and has shown a persistent degradation. If the tendency to degrade continues, it will be judged as unqualified and a level 2 performance test report will be output. This level output mode based on objective calculation indicators abandons the traditional detection method that relies on human experience, has ambiguous results, and has a delayed response. It enables the evaluation system to have real-time judgment, automatic reporting, and standardized output characteristics, which enhances its engineering adaptability and promotion and application value. Especially in the fields of long service life, complex environment and high risk level of wire conductors in large industrial systems, energy transmission and rail transit, this method can effectively support operation and maintenance personnel to carry out forward maintenance, risk classification intervention and resource optimization allocation, fundamentally alleviate the risk of sudden failure caused by the lag in early hidden danger identification. In summary, S4 summarizes all the data modeling and trend analysis results in the early stage and transforms them into actionable decision outputs, truly realizing a complete closed loop from testing to evaluation, and from evaluation to judgment.

[0100] Example 6

[0101] Please refer to Figure 1 Specifically: a comprehensive testing system for the performance of wire conductors, including an abnormal section screening module, a performance testing module, a degradation assessment module, and a judgment module;

[0102] The abnormal section screening module is used to divide the current test sample into uniform sections and, combined with the four-terminal measurement method, obtain the actual sampling resistance value of each resistance sampling point at each monitoring time. By analyzing the changes in the actual sampling resistance of each resistance sampling point at each monitoring time, abnormal conductive sections are screened out.

[0103] The performance testing module is used to perform continuous temperature rise strain tests on each conductive abnormal section, analyze the degree of thermal expansion strain accumulation of the conductor structure in different temperature rise cycle intervals, and perform periodic loading tests of trapezoidal loads on each conductive abnormal section to analyze the degree of load strain of the conductor structure in each load cycle.

[0104] The degradation assessment module is used to analyze the overall structural degradation degree of the conductive abnormal section in each load cycle based on temperature rise strain test and periodic loading test. According to the central difference method algorithm, it analyzes the overall structural degradation trend of the conductive abnormal section and determines the overall structural degradation trend index of the conductive abnormal section.

[0105] The judgment module is used to determine whether the conductive abnormal section in the current test sample is in an overall structural degradation trend based on the value of the overall structural degradation trend index of the conductive abnormal section, and to issue a performance test report of the corresponding level.

[0106] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A comprehensive testing method for the performance of electrical wire conductors, characterized in that: Includes the following steps: S1. Divide the current test sample into uniform sections and combine the four-terminal measurement method to obtain the actual sampling resistance value of each resistance sampling point at each monitoring time. By analyzing the changes in the actual sampling resistance of each resistance sampling point at each monitoring time, the abnormal conductivity sections are screened out. S2. Conduct continuous temperature rise strain tests on each conductive abnormal section to analyze the degree of thermal expansion strain accumulation of the conductor structure in different temperature rise cycle intervals. Conduct periodic loading tests of trapezoidal loads on each conductive abnormal section to analyze the degree of load strain of the conductor structure in each load cycle. S3. Based on temperature rise strain test and periodic loading test, analyze the overall structural degradation degree of the conductive abnormal section in each load cycle. According to the central difference method algorithm, analyze the overall structural degradation trend of the conductive abnormal section and determine the overall structural degradation trend index of the conductive abnormal section. S4. Based on the magnitude of the overall structural degradation trend index of the abnormal conductivity section, determine whether the abnormal conductivity section in the current test sample is in an overall structural degradation trend, and issue a performance test report of the corresponding level.

2. The comprehensive testing method for the performance of wire conductors according to claim 1, characterized in that: The specific steps in S1 include: S11. After dividing the current test sample into test segments, and using the four-terminal measurement method, determine the actual sampling resistance value of each resistance sampling point at each monitoring time, specifically including: S111. Select a wire conductor of fixed length as the current test sample. Divide the current test sample into uniform sections according to the preset test section division length to obtain several test sections. Record the initial unloaded conductor length of each test section. Use the center point of each test section as the resistance sampling point. At the same time, each resistance sampling point is integrated with a four-terminal resistance measuring device. It is connected to the communication bus through a wired connection and the sampling cycle is synchronously controlled by the central acquisition unit. The four-terminal resistance measuring device includes a voltage sensor and a Hall current sensor. S112. During the continuous power-on operation within the sampling period, the current and voltage of each resistance sampling point in the current test sample are sampled in real time using the four-terminal resistance measuring device integrated at each resistance sampling point and the four-terminal measurement method, so as to obtain the current and voltage values ​​of each resistance sampling point at each monitoring time. S113. Input the current and voltage values ​​of each resistance sampling point at each monitoring time into the Ohm's law calculation model, analyze the actual resistance state of each resistance sampling point at each monitoring time, and obtain the actual sampling resistance value of each resistance sampling point at each monitoring time.

3. The comprehensive testing method for the performance of wire conductors according to claim 2, characterized in that: The specific steps in S1 also include: S12. Differentiate the actual sampling resistance values ​​of each resistance sampling point at two consecutive monitoring times, analyze the changes in the actual sampling resistance of each resistance sampling point at each monitoring time, and determine the rate of change of resistance of each resistance sampling point at each monitoring time, specifically as follows: In the formula, This represents the rate of change of resistance at the i-th resistance sampling point at the j-th monitoring time. This represents the actual sampled resistance value of the i-th resistance sampling point at the j-th monitoring time. This represents the actual sampled resistance value of the i-th resistance sampling point at the (j-1)-th monitoring time, where i represents the number of resistance sampling points and j represents the number of monitoring times.

4. The comprehensive testing method for the performance of wire conductors according to claim 3, characterized in that: The specific steps in S1 also include: S13. Based on the resistance change rate at each monitoring time of the determined resistance sampling points, after numerical simulation analysis, the abnormal conductivity sections are screened out, specifically including: S131. Based on the resistance change rate of each resistance sampling point at each monitoring time, and combined with the statistical mean-averaging algorithm, obtain the average resistance change rate of each resistance sampling point within the sampling period. S132. Perform numerical simulation analysis on the average resistance change rate of each resistance sampling point within the sampling period, and establish a two-dimensional coordinate system with the value of the average resistance change rate as the vertical axis and the number of the resistance sampling point as the horizontal axis. Plot the average resistance change rate of each resistance sampling point within the sampling period on the two-dimensional coordinate system in the form of a broken line to construct a resistance change broken line graph, wherein the resistance change broken line graph includes the resistance change broken line of each resistance sampling point. S133. Record the angle formed by the resistance change line at each resistance sampling point in the resistance change graph and the horizontal line to obtain the resistance change angle at each resistance sampling point. Combined with the statistical mean-value algorithm, calculate the average resistance change angle at each resistance sampling point. Compare and analyze the resistance change angle at each resistance sampling point with the average resistance change angle. If the resistance change angle at the corresponding resistance sampling point is greater than the average resistance change angle, it indicates that the conductivity of the test section where the corresponding resistance sampling point is located is abnormal. Then, mark the corresponding test section as a conductivity abnormal section. Based on the initial unloaded conductor length of each conductivity abnormal section, calculate the total initial unloaded conductor length of the conductivity abnormal section. Otherwise, mark the corresponding test section as a conductivity normal section.

5. The method for comprehensive testing of wire conductor performance according to claim 4, characterized in that: The specific steps in S2 include: S21. Based on multiple preset temperature rise cycle intervals, continuous temperature rise strain tests are performed on each conductive abnormal section in the current test sample. The thermal expansion conductor length of each conductive abnormal section in each temperature rise cycle interval is collected by a laser displacement sensor. Combined with a statistical summation algorithm, the total thermal expansion conductor length of the conductive abnormal section in each temperature rise cycle interval is calculated. The total thermal expansion conductor length of the conductive abnormal section in each temperature rise cycle interval is calculated by subtracting it from the initial unloaded conductor length to determine the total change length of the thermal expansion conductor of the conductive abnormal section in each temperature rise cycle interval. The temperature rise strain test process includes a heating stage, a constant temperature stage, and a cooling stage. S22. Correlate the total change in thermal expansion length of the conductor in the abnormal conductivity section within each temperature rise cycle interval with the initial unloaded conductor length. After dimensionless processing, analyze the degree of thermal expansion strain accumulation in the conductor structure of the abnormal conductivity section within different temperature rise cycle intervals, and determine the thermal expansion strain accumulation coefficient, specifically: In the formula, This represents the cumulative coefficient of thermal expansion strain. This represents the total change in conductor length due to thermal expansion during the f-th temperature rise cycle in the section with abnormal conductivity. This represents the initial unloaded total length of the abnormal conductivity section, and n represents the number of temperature rise cycle intervals.

6. The method for comprehensive testing of wire conductor performance according to claim 5, characterized in that: The specific steps in S2 also include: S23. Fix both ends of the current test sample between the loading fixtures. Drive the fixtures to move back and forth according to the preset loading frequency and loading amplitude by the electric servo controller to perform a periodic loading test of trapezoidal load on each conductive abnormal section in the current test sample. The periodic loading test process includes a loading stage, a holding stage and an unloading stage. S24. The time required to complete a single cycle loading test is denoted as the load cycle. During the continuous load strain test of each conductive abnormal section, the conductor strain state of each conductive abnormal section in each load cycle is monitored by a laser displacement sensor. The strain-stable conductor length of each conductive abnormal section in each load cycle is obtained. Combined with a statistical summation algorithm, the total strain-stable conductor length of the conductive abnormal section in each load cycle is calculated. S25. Correlate the total strain-stabilized conductor length of the abnormal conductivity section in each load cycle with the initial unloaded conductor length. After dimensionless processing, analyze the load strain degree of the conductor structure in each load cycle of the abnormal conductivity section, and determine the load strain degree coefficient of the abnormal conductivity section in each load cycle. Specifically: In the formula, This represents the load strain degree coefficient of the abnormal conductivity section during the k-th load cycle. This represents the total strain-stabilized conductor length of the abnormal conductivity section during the k-th load cycle. t represents the initial unloaded total length of the abnormal conductivity section, and t represents the duration of the load cycle.

7. The method for comprehensive testing of wire conductor performance according to claim 6, characterized in that: The specific steps of S3 include: S31. Correlate the load strain degree coefficient of the conductive abnormal section with the thermal expansion strain cumulative coefficient in each load cycle to analyze the overall structural degradation degree of the conductive abnormal section in the current test sample in each load cycle, and determine the structural degradation degree index of the conductive abnormal section in each load cycle, specifically: In the formula, An index representing the degree of structural degradation in the abnormal conductivity section during the k-th load cycle. This represents the load strain degree coefficient of the abnormal conductivity section during the k-th load cycle. This represents the cumulative coefficient of thermal expansion strain.

8. The method for comprehensive testing of wire conductor performance according to claim 7, characterized in that: The specific steps in S3 also include: S32. Based on the determined structural degradation index of the conductive abnormal segment in each load cycle, and combined with the central difference method algorithm, analyze the structural degradation trend of the conductive abnormal segment in the current test sample in each load cycle, and determine the structural degradation trend index of the conductive abnormal segment in each load cycle, specifically: In the formula, The index represents the structural degradation trend of the abnormal conductivity section during the k-th load cycle. The index represents the degree of structural degradation of the abnormal conductivity section in the kth load cycle, and t represents the duration of the load cycle. S33. Based on the structural degradation trend index of the determined conductive abnormal section in each load cycle, and combined with the statistical summation algorithm, obtain the overall structural degradation trend index of the conductive abnormal section in the current test sample.

9. The comprehensive testing method for the performance of wire conductors according to claim 8, characterized in that: The specific steps of S4 include: S41. Based on the magnitude of the overall structural degradation trend index of the conductive abnormal section in the current test sample, determine whether the conductive abnormal section in the current test sample is in an overall structural degradation trend, and issue a performance test report of the corresponding level, specifically including: If the overall structural degradation trend index of the conductive abnormal section in the current test sample does not exceed zero, it indicates that the conductive abnormal section in the current test sample is not in an overall structural degradation trend, and a first-level performance test report is issued, stating that the performance test of the current test sample is qualified. If the overall structural degradation trend index of the conductive abnormal section in the current test sample exceeds zero, it indicates that the conductive abnormal section in the current test sample is in an overall structural degradation trend, and a secondary performance test report will be issued, stating that the performance test of the current test sample is unqualified.

10. A comprehensive testing system for the performance of electrical wire conductors, used to implement the comprehensive testing method for the performance of electrical wire conductors as described in any one of claims 1 to 9, characterized in that: It includes an abnormal segment screening module, a performance testing module, a degradation assessment module, and a judgment module; The abnormal section screening module is used to divide the current test sample into uniform sections and, combined with the four-terminal measurement method, obtain the actual sampling resistance value of each resistance sampling point at each monitoring time. By analyzing the changes in the actual sampling resistance of each resistance sampling point at each monitoring time, abnormal conductive sections are screened out. The performance testing module is used to perform continuous temperature rise strain tests on each conductive abnormal section, analyze the degree of thermal expansion strain accumulation of the conductor structure in different temperature rise cycle intervals, and perform periodic loading tests of trapezoidal loads on each conductive abnormal section to analyze the degree of load strain of the conductor structure in each load cycle. The degradation assessment module is used to analyze the overall structural degradation degree of the conductive abnormal section in each load cycle based on temperature rise strain test and periodic loading test. According to the central difference method algorithm, it analyzes the overall structural degradation trend of the conductive abnormal section and determines the overall structural degradation trend index of the conductive abnormal section. The judgment module is used to determine whether the conductive abnormal section in the current test sample is in an overall structural degradation trend based on the value of the overall structural degradation trend index of the conductive abnormal section, and to issue a performance test report of the corresponding level.

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