Defect fault detection method and device for electric wire and cable

Abstract

The invention relates to the technical field of cable testing, and discloses an electric wire and cable defect fault detection method and device, and the method comprises the steps: obtaining the burying trend information of a target cable and the test characteristics of a test item, analyzing and determining the position of a cable detection end point, deploying a corresponding detection instrument according to the position of the detection end point, and carrying out the detection. A plurality of tests including electric pulse reflection test, sheath grounding circulation test, infrared temperature measurement test and the like are carried out by using deployed instruments, multi-item test data of the cable are acquired, comprehensive analysis is carried out on the multi-item test data, defects and faults of the cable are accurately positioned, the accuracy and efficiency of fault positioning are improved, and the system can adapt to a complex cable network environment and is suitable for popularization and application. The method has high flexibility and practicability, and solves the problem that cable defects and faults are difficult to accurately position in the prior art.

Description

Technical Field

[0001] The present invention relates to the technical field of cable testing, and in particular to a method and device for detecting defects and faults of electric wires and cables. Background Art

[0002] With the continuous development of infrastructure such as electricity, communications, and transportation, wires and cables play an extremely important role in modern society. The quality and status of cables directly affect the safety, stability, and reliability of these systems. In particular, with the scale and complexity of power and communication networks, the risk of cable failure is gradually increasing, and the location and cause of the failure are often relatively hidden, which brings great challenges to maintenance.

[0003] In order to ensure the normal operation of the cable system, timely detection and accurate location of cable faults has become an important task in the power, communication and other industries. However, traditional cable fault detection methods often rely on a single detection method, such as current load, insulation impedance, etc. Although these methods can detect faults to a certain extent, they often have the limitation of low fault location accuracy. Summary of the invention

[0004] The purpose of the present invention is to provide a method and device for detecting defects and faults in electric wires and cables, aiming to solve the problem of difficulty in accurately locating cable defects and faults in the prior art.

[0005] The present invention is implemented in this way. In a first aspect, the present invention provides a method for detecting a defect fault of a wire and cable, comprising: Acquire the buried direction information of the target cable and the test characteristics of several test items to be prepared for defect and fault testing of the target cable, and perform simulation analysis and weighted fusion of the detection scheme on the buried direction information according to each of the test characteristics to obtain the positioning information of the detection endpoints of the target cable corresponding to each of the test items; Deploy detection instruments on the target cable according to the positioning information of the detection endpoint, and perform an electric pulse reflection test, a sheath grounding loop current test, and an infrared temperature measurement test on the target cable based on the deployed detection instruments to obtain multi-item test data of the target cable; Defect and fault location of the target cable is performed according to the multi-item test data of the target cable to obtain defect and fault information of the target cable.

[0006] In a second aspect, the present invention provides a defect and fault detection device for electric wires and cables, which is used to implement a defect and fault detection method for electric wires and cables as described in any one of the first aspects, comprising: An information acquisition module is used to acquire the buried direction information of the target cable and the test characteristics of several test items to be prepared for defect and fault testing of the target cable, and to perform simulation analysis and weighted fusion of the detection scheme on the buried direction information according to each of the test characteristics, so as to obtain the positioning information of the detection endpoints of the target cable corresponding to each of the test items; A cable testing module, used to deploy a detection instrument on the target cable according to the positioning information of the detection endpoint, and perform an electric pulse reflection test, a sheath grounding loop current test and an infrared temperature measurement test on the target cable based on the deployed detection instrument to obtain multi-item test data of the target cable; The positioning and analysis module is used to locate the defect and fault of the target cable according to the multi-item test data of the target cable to obtain the defect and fault information of the target cable.

[0007] The present invention provides a method for detecting faults in electric wires and cables, which has the following beneficial effects: The present invention obtains the burying direction information of the target cable and the test characteristics of the test items, analyzes and determines the position of the cable detection endpoint, deploys corresponding detection instruments according to the position of the detection endpoint, uses the deployed instruments to perform multiple tests, including electric pulse reflection test, sheath grounding loop current test, infrared temperature measurement test, etc., collects multi-item test data of the cable, performs comprehensive analysis on the multi-item test data, accurately locates the defect fault of the cable, improves the accuracy and efficiency of fault location, can adapt to complex cable network environments, has strong flexibility and practicality, and solves the problem of difficulty in accurately locating cable defect faults in the prior art. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] Figure 1 It is a schematic diagram of the steps of a method for detecting a defect fault of a wire or cable provided by an embodiment of the present invention; Figure 2 It is a structural schematic diagram of a defect fault detection device for electric wires and cables provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0009] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0010] The implementation of the present invention is described in detail below in conjunction with specific embodiments.

[0011] Reference Figure 1 , Figure 2 As shown, a preferred embodiment of the present invention is provided.

[0012] In a first aspect, the present invention provides a method for detecting a defect of a wire or cable, comprising: S1: Acquire the buried direction information of the target cable and the test characteristics of several test items to be prepared for defect fault testing of the target cable, and perform simulation analysis and weighted fusion of the detection scheme on the buried direction information according to each of the test characteristics to obtain the positioning information of the detection endpoints of the target cable corresponding to each of the test items; S2: deploying detection instruments on the target cable according to the positioning information of the detection endpoint, and performing an electric pulse reflection test, a sheath grounding loop current test, and an infrared temperature measurement test on the target cable based on the deployed detection instruments to obtain multi-item test data of the target cable; S3: locating defects and faults of the target cable according to the multi-item test data of the target cable to obtain defect and fault information of the target cable.

[0013] More specifically, the burial direction information is obtained by combining the original design information with the path detection information. By fusing and analyzing the original design information and the path detection information, a more accurate cable burial direction can be obtained. This process usually uses a geographic information system (GIS), map matching technology or special software tools to merge and correct data. In the actual detection process, the cable may be offset due to external factors (such as buildings, obstacles, etc.), so the original design information needs to be optimized to obtain the true direction of the cable.

[0014] More specifically, based on the acquired burial direction information and combined with the different characteristics of the test items (such as electric pulse reflection, infrared temperature measurement, circulating current test, etc.), a simulation analysis is performed on each test item to formulate a suitable detection plan. This step can be performed through simulation software or a predictive model based on machine learning to determine the best detection position and method. After obtaining the accurate direction information of the cable, the optimal layout of the detection instrument and the specific location of the detection endpoint are determined according to the requirements of each test method. Different test methods (such as electric pulse reflection, infrared temperature measurement) may have different requirements for the detection endpoint position of the cable, so it is necessary to perform endpoint positioning analysis according to the specific test method.

[0015] More specifically, the detection endpoints corresponding to different test items (such as current detection, thermal imaging, etc.) are weightedly fused. The specific approach is to conduct a comprehensive analysis based on the characteristics and requirements of each test combined with the weights to ensure that all tests can be performed in the appropriate locations. Finally, the system outputs precise detection endpoint locations, which will serve as the basis for subsequent testing and analysis.

[0016] It is understandable that by combining the original design information with the actual path detection information, the actual buried direction of the cable can be accurately restored, avoiding the problem of inaccurate positioning due to design deviation or detection error. This precise positioning analysis provides a reliable basis for the subsequent deployment of detection instruments and data collection. Automated simulation analysis and solution integration greatly reduce errors in manual operation, especially for cable positioning in complex environments (such as areas with dense underground pipelines). Through the analysis and weighting of intelligent algorithms, the detection scheme can be optimized to ensure that the detection work is more efficient and reliable. Accurate detection endpoint positioning helps to reduce blind spots during the test process and improve the efficiency of instrument deployment. The test instrument can be placed more accurately in the area that needs to be detected, avoiding the inefficient work of repeated adjustment and repositioning. In complex buried environments (such as underground pipelines, areas with dense power facilities, etc.), it can effectively overcome the limitations of traditional methods. No matter how the actual direction of the cable changes, by integrating path detection information and design drawings, the system can flexibly adapt to various complex environments and obstacles and improve the comprehensiveness of detection.

[0017] Specifically, in step S2 of the embodiment provided by the present invention, according to the detection endpoint positioning information obtained in the previous step, a suitable location is selected to install various detection instruments. Each detection instrument has its specific detection range and requirements. Therefore, when deploying the instrument, it is necessary to ensure: the appropriate cable access method ensures the stability of the cable contact point and the connection between the sensor and the cable, and the appropriate environmental factors ensure that the instrument can work normally in the cable burial environment, such as avoiding high temperature, high humidity or other environmental interference. The instrument selection specifically includes: an electric pulse reflection tester: used to test the impedance and reflection characteristics of the cable to help determine the location of the fault point, a sheath grounding loop current tester: used to measure the sheath grounding current of the cable, and detect potential electrical faults through loop current analysis, and an infrared thermometer: used to monitor the temperature distribution on the cable surface in real time, find abnormal hot areas, and infer possible fault points.

[0018] More specifically, after the equipment is installed, the instruments are debugged according to the cable specifications and working modes to ensure that the setting parameters of each instrument match the cable status, and each instrument is calibrated to ensure its detection accuracy, for example, setting the appropriate signal frequency and detection range to ensure accurate reflection test results.

[0019] More specifically, start the electric pulse reflection tester, send a short pulse signal to the cable and monitor the echo of the reflected signal. According to the time difference and waveform characteristics of the echo, analyze the impedance changes of each part of the cable. According to the characteristics of the pulse reflection, determine the specific location of the fault point (such as poor contact, short circuit or open circuit location). The intensity and time difference of the reflected wave can reveal the abnormal points in the cable and their distance.

[0020] More specifically, start the sheath ground loop current tester, inject current into the outer sheath of the cable, monitor the current changes, and determine whether there are problems such as open circuit, poor contact or leakage in the cable sheath by analyzing the abnormal ground loop current. The abnormal waveform of the loop current test can help locate the fault area.

[0021] More specifically, an infrared thermal imager is used to scan the surface of the cable to capture the cable surface temperature distribution in real time. Through infrared image analysis, abnormal temperature areas can be identified. Usually, overheated areas may be faulty parts of the cable (such as overload, poor contact, etc.). Infrared temperature measurement can help analyze the operating status of the cable load and predict possible fault points (such as fire hazards caused by overheating).

[0022] More specifically, various tests (such as reflection test, circulating current test, infrared test) will collect data at different time points. These data include: reflection waveform, wave velocity, pulse time and fault point location information, amplitude, phase, waveform and other parameters of sheath grounding current, infrared thermal map, temperature difference and hot zone information. The above test data will be integrated, and data fusion technology will be used to merge various data sources. The information obtained from each test will be analyzed and cross-validated. This can avoid misjudgment caused by a single test data and ensure that multi-dimensional information can comprehensively improve the accuracy of fault location.

[0023] More specifically, multiple test data are analyzed through machine learning algorithms, statistical analysis or image recognition technology. For example, time domain / frequency domain analysis of reflection test data is performed to determine the fault type (such as open circuit, short circuit, corrosion, etc.), abnormal values ​​of the sheath grounding loop current are filtered to determine whether the electrical state of the cable is normal, and temperature distribution image analysis is performed to mark temperature abnormality areas and infer possible fault areas. All test data and analysis results are summarized to generate a detailed inspection report that clearly indicates the location of the fault point, possible fault type and cause, and provides repair suggestions.

[0024] It is understandable that through precise instrument deployment and debugging, it is ensured that each test can be carried out at the correct cable position, thereby reducing errors and missed detections. The tests verify and cross-complement each other, which improves the accuracy of fault diagnosis. Through multiple testing methods (reflection test, sheath grounding loop current test, infrared temperature measurement), the operating status of the cable can be understood from multiple angles, covering the electrical, mechanical, thermal and other dimensions of the cable, reducing the limitations of a single test. Data fusion and analysis not only rely on traditional manual methods, but can also process historical data through machine learning and automated analysis to improve diagnostic speed and accuracy. Through machine learning models, potential faults can be identified and predicted, and the health management level of the cable can be improved.

[0025] Specifically, in step S3 of the embodiment provided by the present invention, the data from various tests (electric pulse reflection, sheath ground loop current, infrared temperature measurement) are integrated to form a unified data set. These data come from different sensors or instruments, so time synchronization and data format conversion are required. The data is denoised to remove abnormal values ​​or noise signals caused by environmental factors, instrument errors, etc. to ensure the accuracy of the data. The reflected waveform data is analyzed in time domain and frequency domain to extract characteristic information such as peaks, troughs, and reflection time. According to the change of the reflected waveform, the type of fault in the cable (such as open circuit, short circuit, poor contact, etc.) is determined, and the specific location of the fault is located according to the reflection time. The current intensity, phase and waveform of the ground loop are analyzed to identify abnormal values, determine whether there is leakage, grounding fault or damage to the outer sheath of the cable, and further infer the specific location of the cable fault according to the distribution and change of the current. The change of the cable surface temperature is identified through thermal map data analysis. Focus on the overheating area, because overheating is often related to internal cable faults (such as overload, poor contact, insulation aging, etc.), and use the temperature difference feature in the infrared image to locate the possible fault area.

[0026] More specifically, the data from the reflection test, ground loop current test and infrared temperature measurement test are fused, and data fusion algorithms (such as weighted average, fuzzy logic, support vector machine, etc.) are used to integrate the results of the three types of test data to remove possible errors in a single test. Data fusion can provide more comprehensive and accurate fault location information and avoid the deviations that may be caused by relying on a single data source. Machine learning algorithms (such as decision trees, random forests, neural networks, etc.) or rule-based pattern recognition methods are used to combine all test data to build a fault diagnosis model. The model is trained based on historical data to identify the characteristic patterns of different fault types and output the type and location of the cable fault.

[0027] More specifically, by combining multiple test data and comparing the degree of match between the test results and known fault modes, the fault type (such as open circuit, short circuit, overload, insulation damage, corrosion, etc.) and the exact location of the fault are determined. In the reflection test, the fault point is located according to the time and amplitude of the echo; in the circulating current test, the location of the electrical fault is determined by the abnormal change of the current; in the infrared test, the area with abnormal temperature is located by the thermal map. By analyzing the fault type, combined with the cable's working environment, historical maintenance records, load conditions, etc., the possible cause of the fault is determined. For example, if the cable temperature is too high, it may be due to overload, poor contact or insulation aging; if the grounding circulation is abnormal, it may be due to leakage caused by damaged sheath. The fault location information, fault type and cause analysis are integrated to generate a detailed cable defect fault report, which will include the location of the fault point, possible fault type, fault cause analysis, maintenance suggestions and repair plans.

[0028] More specifically, the accuracy of the fault location results is verified through actual maintenance or repair operations. If the location is found to be biased, the algorithm and analysis method are further adjusted to optimize the fault location process, the detection method and model, and the detection process and machine learning model are adjusted and optimized based on the results of subsequent verification to improve the accuracy and reliability of the fault diagnosis system.

[0029] It is understandable that the accuracy of fault location can be significantly improved through the fusion analysis of multi-project test data, especially in complex environments, avoiding the problem that traditional single test methods cannot detect hidden faults. Through comprehensive analysis of multi-dimensional data, different types of faults (such as electrical faults, thermal failures, mechanical damage, etc.) can be distinguished more accurately, rather than relying on a single test signal for diagnosis, thereby increasing the ability to identify fault types. By integrating different test data, the limitations of a single test method are avoided, and the misjudgment and missed judgment caused by instrument errors, environmental influences or external interference are reduced. Through real-time data collection and fault location, the cable can be dynamically monitored, and potential faults can be discovered and predicted in time, thereby providing decision support for cable maintenance and management. By using intelligent algorithms such as machine learning and pattern recognition, fault location not only relies on manual experience, but can also automatically optimize decisions based on large amounts of data, thereby improving the intelligence level of fault diagnosis.

[0030] The present invention provides a method for detecting faults in electric wires and cables, which has the following beneficial effects: The present invention obtains the burying direction information of the target cable and the test characteristics of the test items, analyzes and determines the position of the cable detection endpoint, deploys corresponding detection instruments according to the position of the detection endpoint, uses the deployed instruments to perform multiple tests, including electric pulse reflection test, sheath grounding loop current test, infrared temperature measurement test, etc., collects multi-item test data of the cable, performs comprehensive analysis on the multi-item test data, accurately locates the defect fault of the cable, improves the accuracy and efficiency of fault location, can adapt to complex cable network environments, has strong flexibility and practicality, and solves the problem of difficulty in accurately locating cable defect faults in the prior art.

[0031] Preferably, the steps of obtaining the buried direction information of the target cable and the test characteristics of several test items for preparing to perform defect and fault tests on the target cable, and performing simulation analysis and weighted fusion of the detection scheme on the buried direction information according to each of the test characteristics to obtain the positioning information of the detection endpoints of the target cable corresponding to each of the test items include: S11: acquiring original design information and path detection information of a target cable, and combining the original design information and the path detection information of the target cable to obtain buried direction information of the target cable; S12: acquiring test characteristics of several test items to be prepared for defect and fault testing of the target cable, and performing simulation analysis of a detection scheme on the buried direction information according to each of the test characteristics, so as to obtain a test scheme for the target cable corresponding to each of the test characteristics; S13: The test schemes corresponding to the test features of the target cable are integrated based on preset weights to obtain the positioning information of the detection endpoints of the target cable corresponding to the test items.

[0032] Specifically, by obtaining the original design drawings or information in the database of the target cable from the power or communication company, including the cable's burial depth, direction, starting and ending points, crossing areas, and layout of surrounding facilities, including the cable's specific length, path, bending radius and other design parameters.

[0033] More specifically, ground detection technology (such as geological radar (GPR), magnetic detection or electromagnetic induction detection) is used to detect the actual buried cable path. The actual buried position of the cable will be recorded during the detection process, including whether there are deviations or obstacles.

[0034] More specifically, the original design information is integrated with the path detection information to identify the difference between the design and the actual burial, correct the path deviation, and calibrate the specific burial direction of the cable through a coordinate system (such as GPS). For specific locations of the cable, such as turns, intersections and other key nodes, the direction changes are accurately recorded. Based on the above data, a map of the actual burial direction of the cable is drawn, indicating the starting point, end point and intermediate key points, and the direction is visualized to facilitate subsequent detection and positioning analysis.

[0035] More specifically, according to the actual use environment of the cable and the known fault modes, select several suitable test items (for example: cable reflection wave test, sheath grounding test, infrared temperature measurement, insulation resistance test, etc.), extract features for each test item, and obtain relevant test features, such as the delay and amplitude characteristics of the reflection wave, the temperature gradient of infrared temperature measurement, the sheath current change, etc. Each test feature can provide different information, such as fault location, fault type, temperature change, etc., simulate and analyze the buried direction of the cable, evaluate how each test item affects the positioning of the detection endpoint, simulate the effects of different detection methods based on the buried direction map and test features, evaluate the detection range, accuracy and possible blind spots of each method, and determine the appropriate test plan and detection path through simulation analysis. For example, in places where the buried direction changes, higher frequency reflection wave testing or additional detection may be required, and the test plan should be adjusted in combination with key nodes and environmental factors in the cable path.

[0036] More specifically, the weight of each test scheme is set according to the reliability, accuracy and scope of application of each test feature. For example, the reflection wave test is more accurate for fault location, but there may be environmental interference, so it can be given a higher weight; while infrared temperature measurement is sensitive to temperature and is suitable for detecting overheating faults, so it can be given a lower weight. Different test schemes are integrated using weighted average, fuzzy logic and other algorithms to obtain the integrated detection endpoint positioning information. Combined with the results and weights of each test scheme, the detection endpoint position of the cable is finally determined, providing accurate detection endpoint position and possible fault information, such as cable damage, insulation damage, etc.

[0037] More specifically, the final positioning results are generated into a visual report, including the cable burial route map, the precise location of the detection endpoint, and the detection results of each test item. The detection endpoint location is marked to facilitate the subsequent maintenance team to perform precise positioning and repair. In the actual cable detection, the positioning accuracy of the detection endpoint is verified. Based on the verification results, the plan is further optimized, and the test method and weight setting are adjusted to improve the accuracy and reliability of positioning.

[0038] It is understandable that by combining the original design information with the path detection information, the actual burial direction of the cable can be accurately obtained, avoiding the path error caused by design deviation or environmental changes. The combination of multiple test features and program optimization ensures that the detection endpoint positioning has high accuracy, avoiding the blind spots or errors that may exist in the traditional single method. Based on the simulation analysis of different test features, the test plan can be adjusted according to the actual burial direction and environmental factors to ensure that each detection plan can cover the fault risk area of ​​the cable to the maximum extent, improve the comprehensiveness and accuracy of the detection, and through the weight-based program fusion algorithm, multiple test results can be intelligently integrated to make the final detection endpoint positioning information more scientific and accurate. The advantages of each test method are maximized and error accumulation is reduced.

[0039] Preferably, the step of deploying a detection instrument on the target cable according to the positioning information of the detection endpoint, and performing an electric pulse reflection test, a sheath grounding loop current test and an infrared temperature measurement test on the target cable based on the deployed detection instrument to obtain multi-item test data of the target cable includes: S21: deploying a detection instrument on the target cable according to the positioning information of the detection endpoint, so that the detection instrument used for performing a multi-item test on the target cable is in a detection position; S22: Debugging initial working parameters of the detection instrument at the detection position, so that the detection instrument is in a working mode matching the target cable; S23: Instructing the detection instrument in the working mode to perform an electric pulse reflection test on the target cable to obtain electric pulse reflection test item data of the target cable; S24: Instructing the detection instrument in the working mode to perform a sheath grounding loop current test on the target cable to obtain sheath grounding loop current test item data of the target cable; S25: Instructing the detection instrument in working mode to perform an infrared temperature measurement test on the target cable to obtain infrared temperature measurement test item data of the target cable; S26: combining the electric pulse reflection test item data, the sheath grounding loop current test item data and the infrared temperature measurement test item data of the target cable to obtain multi-item test data of the target cable.

[0040] Specifically, based on the cable detection endpoint positioning information obtained in the previous steps, the specific location and test area of ​​the target cable are determined. Using the positioning information, it can be ensured that the detection instrument is accurately deployed to the detection endpoint or key node of the cable. At the detection position of the target cable, the corresponding detection instrument is deployed. Common detection instruments include electric pulse reflectometers, ground loop current testers, infrared thermometers, etc. These instruments need to be reasonably arranged according to the cable's burial depth, path and environmental conditions to ensure that the target cable can be fully detected.

[0041] More specifically, the deployed detection instruments are initially debugged to ensure that their working status matches the test requirements of the target cable, including adjusting the instrument's frequency, sensitivity, signal amplitude and other parameters to ensure that the instrument's output and input settings match the cable's characteristics (such as resistance, insulation resistance, conductor type, etc.) to achieve the best detection effect. After debugging, the electric pulse reflectometer is started to transmit electric pulse signals to the target cable. The reflected signals in the cable will generate reflected waves due to cable faults (such as breakage, damage, insulation faults, etc.). After receiving these reflected waves, the instrument will generate corresponding test results based on the reflected delay and amplitude data. By measuring the time and amplitude of the reflected wave, the possible fault location in the cable can be located, and the "electrical pulse reflection test project data" of the cable can be recorded. These data will provide a basis for subsequent fault location.

[0042] More specifically, a ground loop current tester is used to perform a ground loop current test on the sheath of the target cable. By applying a certain current and monitoring the loop current signal, the integrity of the cable sheath is judged. This test is mainly used to check whether the metal sheath of the cable is short-circuited, open-circuited or poorly grounded, which in turn affects the safety and operational stability of the cable. The current data of the cable sheath ground loop current is obtained to analyze whether there are problems such as sheath leakage current and poor grounding, and the relevant "sheath ground loop current test project data" is recorded.

[0043] More specifically, start the infrared thermometer and perform infrared scanning on the target cable. This process is used to detect whether the cable is overheated during operation. The infrared thermometer can detect the temperature change on the cable surface without contact, and can quickly identify the abnormal temperature area, prompting possible overload, insulation damage or poor connection problems, and record infrared temperature measurement data, including the distribution of cable surface temperature and hot spots. Through these data, it is determined whether the cable has hidden dangers such as overheating and aging, and obtain "infrared temperature measurement test project data".

[0044] More specifically, the aforementioned three test data (electric pulse reflection test data, sheath grounding loop current test data, infrared temperature measurement test data) are combined and analyzed, and multi-dimensional data fusion technology can be used to cross-validate the test data to identify potential cable problems and obtain comprehensive fault diagnosis. Through data analysis, a "multi-item test data" report of the target cable is obtained, which contains important information such as cable fault location, status assessment, and risk analysis. These data will provide a reference for subsequent maintenance and repair.

[0045] It is understandable that through the previously obtained detection endpoint positioning information, the detection instruments can be accurately deployed to ensure that each test covers the key areas of the cable, thereby improving the accuracy and comprehensiveness of the test. The combination of pulse reflection test, sheath ground loop current test, and infrared temperature measurement test can comprehensively detect various possible faults of the cable. These test methods focus on different aspects of the cable (such as fault location, sheath integrity, temperature change), and the combined data provides a comprehensive cable health assessment. The fusion of multiple test data makes fault diagnosis more accurate. For example, the electric pulse reflection test can locate the fault location, the sheath ground loop current test can confirm whether there is a ground fault, and the infrared temperature measurement test can identify overheating areas. This information works together to improve the reliability of fault diagnosis. By integrating multiple test methods, multiple tasks can be completed simultaneously in one detection, which greatly saves detection time, and each test data complements each other, reducing the possibility of omissions and misjudgments.

[0046] Preferably, the step of causing the detection instrument in working mode to perform an electric pulse reflection test on the target cable to obtain the electric pulse reflection test item data of the target cable includes: S231: transmitting electric pulses from the detection endpoint to the target cable through the cable fault tester host, so that the electric pulses are transmitted at a uniform speed in the target cable, so as to generate reflected pulses corresponding to the position where the cable impedance changes during the uniform speed transmission; S232: The reflected pulse is received by the cable fault tester host, and the range of the cable impedance change position is specified for the buried direction information of the target cable according to the reflected pulse, so as to obtain the range data of the cable impedance change position of the target cable, and the range data of the cable impedance change position of the target cable is used as the electric pulse reflection test item data.

[0047] Specifically, the cable fault tester host transmits an electric pulse signal by connecting to the detection end point of the target cable. The electric pulse signal is usually a short, high-energy electric signal with a transmission speed close to the speed of light and can propagate evenly in the cable. The characteristics of the target cable (such as the material of the cable, the insulation layer, etc.) will affect the transmission speed and reflection characteristics of the electric pulse. The electric pulse signal will be transmitted along the length of the cable and generate reflected pulses at certain positions of the cable due to impedance mismatch of the cable (such as breakage, short circuit, poor contact, etc.).

[0048] More specifically, when an electrical pulse signal is transmitted in a cable, reflection will occur when it encounters an impedance change area in the cable (such as a damaged part, joint or other defect). The intensity and reflection time of the reflected pulse will be affected by the impedance change at the damaged location of the cable and the cable structure. The reflected pulse contains key information about the location of the cable fault, and the delay in reflection time is proportional to the fault distance.

[0049] More specifically, the cable fault tester receives the pulse signal reflected from the cable and analyzes the time difference of the reflected pulse (i.e. the delay from the pulse transmission to the reception). This time difference can be directly converted into the distance of the fault point in the cable. By analyzing multiple reflected pulses, multiple fault locations in the cable can be accurately determined, even the area of ​​slight impedance change.

[0050] More specifically, based on the return time and amplitude of the reflected pulse, the cable fault tester host will calculate the specific range of the cable's impedance change position. Specifically, the instrument accurately measures the arrival time of the reflected wave, combined with the propagation speed of the cable, to deduce the specific location of the cable fault area. If the cable has multiple impedance change areas, the instrument will analyze the location and range of these changes through multiple returns of the reflected pulse. For example, a certain joint of the cable may have a slight impedance change, and the instrument will mark this location and give its range.

[0051] More specifically, in the end, the cable fault tester will generate "electric pulse reflection test item data" based on the range data of the measured cable impedance change position. These data include the specific location of each impedance change area in the cable, the range of change, and the intensity of the reflection. Through these data, it can be determined whether there is a fault in the cable, the type of fault, and the approximate location of the fault.

[0052] It is understandable that the electric pulse reflection test can accurately locate the fault position in the cable. There is a clear mathematical relationship between the time difference of the reflected pulse and the fault position in the cable, which provides high-precision data support for fault location. The reflected pulse can not only detect large faults (such as breakage, short circuit, etc.), but also detect smaller impedance changes, and timely discover potential hidden dangers of the cable. By analyzing the range data of the cable impedance change position, the overall health status of the cable can be evaluated. For areas where small impedance changes occur multiple times, it may indicate cable aging or imminent failure, so that maintenance preparations can be made in advance.

[0053] Preferably, the step of causing the detection instrument in working mode to perform a sheath grounding loop current test on the target cable to obtain sheath grounding loop current test item data of the target cable comprises: S241: continuously collecting and recording the current value of the outer sheath or the grounding wire of the target cable by using a FLUKE-381 multi-function clamp meter to obtain a current parameter sequence of the target cable; S242: Repeat the above current value collection and recording for the target cable based on a plurality of preset test time periods to obtain a current parameter sequence of the target cable corresponding to each test time period; S243: extracting current form characteristics of the current parameter sequence of the target cable corresponding to each test time period according to a preset standard to obtain current detection characteristics of the target cable; S244: analyzing abnormal current values ​​of the current parameter sequence of the target cable corresponding to each test time period according to a preset standard to obtain an abnormal detection feature of the target cable; S245: performing location identification and classification identification of a target cable fault point on the current detection feature and the abnormality detection feature according to a pre-trained machine learning model, so as to obtain a number of possible fault data fed back by the current detection feature and the abnormality detection feature; wherein the possible fault data includes a possible fault type, a possible fault location, and a possibility index; S246: Combining the possible fault data to obtain the sheath grounding loop current test item data of the target cable.

[0054] Specifically, a FLUKE-381 multi-function clamp meter is used to continuously collect current values ​​from the outer sheath or ground wire of the target cable. The clamp meter clamps the outer sheath or ground wire of the cable to monitor the current flowing through the cable sheath in real time. The sequence of these current parameters will be recorded as basic data for subsequent analysis. The goal of this step is to obtain the current parameters of the target cable under normal working conditions, including current amplitude, frequency, waveform and other information.

[0055] More specifically, the above-mentioned current value collection and recording are repeated within multiple preset test time periods. The current data within each time period can reflect the current characteristics of the target cable under different working states or load conditions. By collecting data in multiple time periods, the current changes of the target cable under different working conditions can be obtained, which helps to identify potential sheath grounding loop current anomalies.

[0056] More specifically, based on preset standards, the current form characteristics of the current parameter sequence in each test time period are extracted. The current form characteristics mainly include the current amplitude, frequency, waveform, phase, etc. The waveform and frequency characteristics of the current can help identify whether there are periodic fluctuations, pulse interference or other abnormal phenomena. These phenomena may be related to the abnormal grounding loop current of the cable sheath. After the current characteristics are extracted, the current parameters of each time period are analyzed according to the preset standards to identify abnormal current values. Abnormal currents usually manifest as sudden changes in current values, continuous deviations from normal values, or exceeding safety ranges. This abnormal analysis can help identify possible faults or hidden dangers that may occur in the target cable during operation. For example, the cable sheath or grounding wire may have faults or the insulation layer may be damaged, resulting in abnormal current.

[0057] More specifically, based on the current characteristics and abnormal current, current detection characteristics and abnormal detection characteristics are extracted. These characteristics include parameters such as current change trend, fluctuation amplitude, instantaneous change, etc. The current detection characteristics can reveal the normal working mode of the current, while the abnormal detection characteristics focus on identifying sudden changes, continuous deviations or periodic interferences in the current.

[0058] More specifically, based on pre-trained machine learning models (such as decision trees, support vector machines, etc.), the current detection features and anomaly detection features are analyzed to identify possible fault points of the target cable. The model will input feature data, classify and predict, and output the location information of the fault point. The machine learning model will not only identify the location of the fault, but also learn the fault type and possibility index based on historical data. The model automatically identifies and classifies the fault of the target cable by analyzing the current waveform, abnormal features, etc. After the machine learning model analyzes the current detection features and anomaly detection features, it will feedback a number of possible fault data. Each fault data contains three key elements: possible fault type: the type of fault, such as short circuit, poor grounding, loose joints, etc., possible fault location: the specific location where the fault occurs, and possible index: indicating the probability or confidence of the fault. These possible fault data provide detailed diagnostic basis for subsequent cable maintenance and repair work.

[0059] More specifically, all possible fault data are integrated to obtain complete sheath grounding loop current test project data. This data contains detailed fault analysis results of the cable sheath grounding loop current, helping users understand the operating status and potential risks of the cable. The data will include the possibility of multiple fault types and fault locations, ultimately providing accurate cable fault diagnosis information for operation and maintenance personnel.

[0060] It is understandable that the continuous collection of current values ​​using the FLUKE-381 multi-function clamp meter enables the detection process to track the cable sheath grounding loop current in real time, provide dynamic current data, and reflect the working status of the cable under different working conditions. The abnormal detection of current values ​​and the extraction of current form features can efficiently identify abnormal currents or sheath grounding problems that may exist in the cable. By analyzing data from different time periods, the potential faults of the cable in long-term operation can be revealed. The use of machine learning models for fault point location and identification not only improves the degree of automation of fault diagnosis, but also optimizes the accuracy and efficiency of fault identification based on historical data. Machine learning algorithms can extract implicit rules from big data, reduce human errors and improve diagnostic capabilities. Classification and identification based on machine learning can not only accurately locate fault points, but also distinguish different types of faults. This provides an accurate basis for cable maintenance and repair, helping operation and maintenance personnel to quickly take appropriate repair measures. The combination of current detection features and abnormal current analysis can analyze cable faults from multiple dimensions. Compared with the traditional single detection method, this method can comprehensively consider the different characteristics of current and conduct more comprehensive and accurate fault diagnosis.

[0061] Preferably, the step of causing the detection instrument in working mode to perform an infrared temperature measurement test on the target cable to obtain infrared temperature measurement test item data of the target cable includes: S251: driving the target cable to perform a number of current load tests of specified specifications, and capturing the real-time temperature distribution of the target cable through a T540 infrared thermal imager to obtain the real-time temperature distribution of the target cable corresponding to each current load test of the specified specifications; S252: collecting measurement time and environmental conditions of the real-time temperature distribution of the target cable corresponding to each current load test of the specified specification, so as to obtain analysis elements of each corresponding real-time temperature distribution; S253: Performing data analysis on each of the real-time temperature distributions under element conditions according to the analysis elements of each of the real-time temperature distributions to obtain defect and fault identification results corresponding to the infrared temperature measurement test items of the target cable, and using the defect and fault identification results as the infrared temperature measurement test item data of the target cable.

[0062] Specifically, the target cable is driven to perform several current load tests of specified specifications. Under different load conditions, the current flow of the cable in normal and abnormal working conditions can be simulated, so as to observe the temperature changes of the cable under various loads, and use the FLIR T540 infrared thermal imager to capture the real-time temperature distribution of the target cable. The infrared thermal imager can detect the spatial distribution of the cable surface temperature and generate a temperature heat map, thereby intuitively displaying the temperature status of various parts of the cable. The thermal imager can accurately capture the temperature changes of the cable under different current loads, especially in the cable connection points, joints, sheaths and other areas, which are often potential fault areas.

[0063] More specifically, during each current load test, it is necessary to record the time information of each measurement and the environmental conditions at that time. Environmental conditions such as ambient temperature, humidity, wind speed, etc. will affect the temperature change of the cable. Therefore, it is very important to accurately collect these environmental parameters when conducting infrared temperature measurement tests. The record of measurement time can help analyze the temperature change trend in different time periods, identify whether the temperature fluctuation is a reaction under normal working conditions, or abnormal temperature rise caused by some fault, and extract a series of analysis elements based on the captured real-time temperature distribution. These elements include but are not limited to: uniformity of temperature distribution: whether there is an abnormal temperature concentration area on the cable surface, such as local overheating, temperature fluctuation: whether there is an obvious temperature change or a trend of sharp rise, location of high temperature area: which part of the cable (such as the joint, conductor or sheath) has abnormal temperature rise, which may be a hot spot caused by poor contact or overload, temperature difference: whether the temperature difference between different locations exceeds the normal threshold.

[0064] More specifically, based on the extracted temperature analysis elements, each real-time temperature distribution is analyzed in detail. At this time, the current load, measurement time, environmental conditions and other factors are comprehensively considered, and certain analysis methods (such as thermal model analysis, trend analysis, anomaly detection algorithm, etc.) are used to comprehensively evaluate the temperature data, and further fault diagnosis is performed for areas with abnormal temperature rise. By comparing with the preset temperature standard, it is identified whether there are potential faults caused by cable aging, poor contact, overload, etc. According to the data analysis results, the possible defects or faults of the target cable are identified. For example, if the temperature in the joint area is too high, it may indicate poor contact or current overload at the joint, the temperature of the sheath part is abnormal, which may be leakage or local short circuit caused by damage to the cable protective layer, and the cable temperature is uneven under the overall current load, which may indicate local overload or material problems in the cable. All identification results are fed back as defect fault identification results to provide a basis for cable repair or maintenance.

[0065] More specifically, the fault identification results are collated into the final infrared temperature measurement test project data. These data include: temperature distribution diagrams of various parts of the cable, temperature change trends under various environmental conditions and current loads, identified potential fault locations and their possible causes. These data will be used as infrared temperature measurement test project data for the target cable to provide fault location information for the operation and maintenance personnel of the power equipment, helping them to repair or prevent faults more accurately.

[0066] It is understandable that using the T540 infrared thermal imager to capture the temperature distribution of the cable in real time can not only intuitively view the temperature of the cable surface, but also monitor the potential heat sources and fault areas inside the cable. This real-time monitoring method can timely detect cable overheating, especially heat accumulation under high load or long-term working conditions. By combining different loads, current conditions and environmental data, it can conduct a more comprehensive analysis of the temperature distribution of the cable, identify which temperature changes are normal and which are caused by faults or abnormalities. During the analysis process, the temperature state of the cable can be evaluated from different angles and dimensions, avoiding the one-sidedness of traditional temperature monitoring methods. By collecting and analyzing factors such as ambient temperature, humidity, and air pressure, a more accurate interpretation of temperature changes can be made, avoiding the interference of environmental factors on cable temperature, thereby improving the accuracy of fault identification. Based on the analysis of temperature distribution data of infrared temperature measurement, the potential fault points of the cable can be identified early, especially at the joints or local overheating areas. Through early warning, repairs or replacements can be carried out in time to avoid a wider range of faults.

[0067] Preferably, the step of locating the defect and fault of the target cable according to the multi-item test data of the target cable to obtain the defect and fault information of the target cable includes: S31: performing independent defect fault location of each item of the target cable according to the multi-item test data of the target cable, so as to obtain independent defect fault location results of each item of the target cable corresponding to the multi-item test data; S32: performing a weighted comprehensive analysis on the independent defect fault location results of each of the items to obtain a weighted fault location result of the target cable; S33: performing model prediction on the multiple-item test data of the target cable according to the pre-trained machine learning model to obtain a model prediction result of the target cable corresponding to the multiple-item test data; S34: The weighted fault location result and the model prediction result together constitute the defect fault information of the target cable.

[0068] Specifically, the target cable collects multi-item test data, which includes different test items, such as infrared temperature measurement test, current load test, insulation impedance test, etc. Each item provides information about different characteristics and status of the cable. Based on the test data of each item, independent defect fault location is performed on the target cable. Each test item analyzes specific cable characteristics (such as temperature, current, insulation, etc.) to identify possible defects or faults, such as: infrared temperature measurement test: through temperature distribution analysis, identify overheating areas, faults at joints, etc., current load test: check whether the current distribution is normal, and determine whether there is overload or short circuit, insulation impedance test: analyze the insulation status of the cable and identify possible leakage points. Each item separately obtains defect location results, which are usually analyzed through threshold comparison, anomaly detection or model-based methods.

[0069] More specifically, the results of independent fault location of each item are weighted and integrated to obtain the weighted fault location result of the target cable. The weighted comprehensive analysis process takes into account the priority, reliability and relevance of each test item to the fault. For example, some test items (such as infrared temperature measurement test) may be more sensitive to fault identification, so their weighting coefficient will be higher. Other test items (such as current load test) are given appropriate weights according to their impact on the health status of the cable. The results of multiple test items are combined in a weighted manner to ensure that the fault location result is more accurate and reliable.

[0070] More specifically, a portion of historical test data is used to train a machine learning model, which can predict the fault status of the cable based on multi-item test data. The training data includes test data of multiple cables and known fault conditions. The model can identify and predict potential fault types by learning the characteristics of these data. Common machine learning models include decision trees, random forests, support vector machines (SVM), neural networks, etc. During the training process, these models will output corresponding fault prediction results based on the input characteristics of each test item (such as temperature value, current load, insulation value, etc.). After the training is completed, the multi-item test data of the target cable is input into the trained machine learning model. The model predicts the possible fault type and location of the cable based on the input test data. The prediction results of the machine learning model usually include: Fault type: such as connector damage, overheating, short circuit, etc. Fault location: By analyzing the comprehensive results of various test data, the model can infer the cable area where the fault may occur.

[0071] More specifically, the weighted comprehensive fault location results are finally combined with the prediction results of the machine learning model to form the complete defect fault information of the target cable. In this way, the combination of weighted analysis of manual experience and automatic prediction of machine learning can effectively reduce misdiagnosis and improve the accuracy of fault location. In the fusion process, different strategies can be adopted: weighted average method: weighted average the weighted fault location results and machine learning prediction results respectively, decision rules: according to the severity of the fault type or the importance of the test results, decide which result (weighted fault location or machine learning prediction) is used as the final decision basis, voting mechanism: if multiple prediction results match, the credibility of the result is strengthened and the accuracy of the final decision is increased. Finally, through the combination of weighted fault location results and machine learning prediction results, complete defect fault information is output, including fault location, type and possible causes. This information will be used for subsequent maintenance decisions, formulation of repair plans and evaluation of cable health status.

[0072] It is understandable that through comprehensive analysis of multi-item test data, potential cable faults can be identified from different dimensions (such as temperature, current, insulation, etc.). This multi-dimensional fault detection greatly improves the comprehensiveness and accuracy of fault location, avoiding abnormal problems that may be ignored by a single test method. Weighted comprehensive analysis can optimize the fault results according to the importance and credibility of each test item, making fault location more targeted and reliable. The application of machine learning models further improves the accuracy of fault identification, especially in complex fault modes, and can identify more hidden defects. Through the training and prediction of machine learning models, automated fault diagnosis can be achieved. This reduces manual intervention, improves detection efficiency, and avoids human errors, especially when dealing with large-scale cable networks, which can significantly improve work efficiency.

[0073] Reference Figure 2 As shown, in a second aspect, the present invention provides a defect fault detection device for electric wires and cables, which is used to implement a defect fault detection method for electric wires and cables as described in any one of the first aspects, comprising: An information acquisition module is used to acquire the buried direction information of the target cable and the test characteristics of several test items to be prepared for defect and fault testing of the target cable, and to perform simulation analysis and weighted fusion of the detection scheme on the buried direction information according to each of the test characteristics, so as to obtain the positioning information of the detection endpoints of the target cable corresponding to each of the test items; A cable testing module, used to deploy a detection instrument on the target cable according to the positioning information of the detection endpoint, and perform an electric pulse reflection test, a sheath grounding loop current test and an infrared temperature measurement test on the target cable based on the deployed detection instrument to obtain multi-item test data of the target cable; The positioning and analysis module is used to locate the defect and fault of the target cable according to the multi-item test data of the target cable to obtain the defect and fault information of the target cable.

[0074] In this embodiment, for the specific implementation of each module in the above-mentioned device embodiment, please refer to the above-mentioned method embodiment, which will not be described in detail here.

[0075] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for detecting faults in electric wires and cables, characterized in that: include: Acquire the buried direction information of the target cable and the test characteristics of several test items to be prepared for defect and fault testing of the target cable, and perform simulation analysis and weighted fusion of the detection scheme on the buried direction information according to each of the test characteristics to obtain the positioning information of the detection endpoints of the target cable corresponding to each of the test items; Deploy detection instruments on the target cable according to the positioning information of the detection endpoint, and perform an electric pulse reflection test, a sheath grounding loop current test, and an infrared temperature measurement test on the target cable based on the deployed detection instruments to obtain multi-item test data of the target cable; Defect and fault location of the target cable is performed according to the multi-item test data of the target cable to obtain defect and fault information of the target cable.

2. The method for detecting faults of electric wires and cables according to claim 1, characterized in that: The steps of obtaining the buried direction information of the target cable and the test characteristics of several test items for preparing defect and fault tests on the target cable, and performing simulation analysis and weighted fusion of the detection scheme on the buried direction information according to each of the test characteristics to obtain the positioning information of the detection endpoints of the target cable corresponding to each of the test items include: Acquire original design information and path detection information of the target cable, and combine the original design information and path detection information of the target cable to obtain buried direction information of the target cable; Acquire test characteristics of several test items for defect and fault testing of the target cable, and simulate and analyze the detection scheme of the buried direction information according to each of the test characteristics to obtain a test scheme for the target cable corresponding to each of the test characteristics; The test schemes corresponding to the test features of the target cable are fused based on preset weights to obtain the positioning information of the detection endpoints of the target cable corresponding to the test items.

3. The method for detecting faults of electric wires and cables according to claim 1, characterized in that: The steps of deploying a detection instrument on the target cable according to the positioning information of the detection endpoint, and performing an electric pulse reflection test, a sheath grounding loop current test, and an infrared temperature measurement test on the target cable based on the deployed detection instrument to obtain multi-item test data of the target cable include: Deploy a detection instrument on the target cable according to the positioning information of the detection endpoint, so that the detection instrument used for performing a multi-item test on the target cable is in a detection position; Debugging initial working parameters of a detection instrument at a detection position to place the detection instrument in a working mode matching the target cable; Instructing the detection instrument in working mode to perform an electric pulse reflection test on the target cable to obtain the electric pulse reflection test item data of the target cable; Instructing the detection instrument in working mode to perform a sheath grounding loop current test on the target cable to obtain sheath grounding loop current test item data of the target cable; Instructing the detection instrument in working mode to perform an infrared temperature measurement test on the target cable to obtain infrared temperature measurement test item data of the target cable; The electric pulse reflection test item data, the sheath grounding loop current test item data and the infrared temperature measurement test item data of the target cable are combined to obtain the multi-item test data of the target cable.

4. The method for detecting faults of electric wires and cables according to claim 3, characterized in that: The step of causing the detection instrument in working mode to perform an electric pulse reflection test on the target cable to obtain the electric pulse reflection test item data of the target cable comprises: The cable fault tester host transmits an electric pulse from the detection end point to the target cable, so that the electric pulse is transmitted at a uniform speed in the target cable, so as to generate a reflected pulse corresponding to the position where the cable impedance changes during the uniform transmission process; The reflected pulse is received by the cable fault tester host, and the range of the cable impedance change position is specified for the buried direction information of the target cable according to the reflected pulse, so as to obtain the range data of the cable impedance change position of the target cable, and the range data of the cable impedance change position of the target cable is used as the electric pulse reflection test item data.

5. The method for detecting faults of electric wires and cables according to claim 3, characterized in that: The step of causing the detection instrument in working mode to perform a sheath grounding loop current test on the target cable to obtain sheath grounding loop current test item data of the target cable comprises: The current value of the outer sheath or grounding wire of the target cable is continuously collected and recorded by a FLUKE-381 multi-function clamp meter to obtain a current parameter sequence of the target cable; Repeating the above current value collection and recording for the target cable based on a plurality of preset test time periods to obtain a current parameter sequence of the target cable corresponding to each test time period; Extracting current form characteristics of the current parameter sequence of the target cable corresponding to each test time period according to a preset standard to obtain current detection characteristics of the target cable; Analyzing abnormal current values ​​of the current parameter sequence of the target cable corresponding to each test time period according to a preset standard to obtain abnormal detection characteristics of the target cable; The target cable fault point is located and classified according to the pre-trained machine learning model for the current detection feature and the abnormality detection feature to obtain a number of possible fault data fed back by the current detection feature and the abnormality detection feature; wherein the possible fault data includes a possible fault type, a possible fault location and a possibility index; The possible fault data are combined to obtain the sheath grounding loop current test item data of the target cable.

6. The method for detecting faults of electric wires and cables according to claim 3, characterized in that: The step of causing the detection instrument in working mode to perform an infrared temperature measurement test on the target cable to obtain infrared temperature measurement test item data of the target cable comprises: The target cable is driven to perform current load tests of several specified specifications, and the real-time temperature distribution of the target cable is captured by a T540 infrared thermal imager to obtain the real-time temperature distribution of the target cable corresponding to each current load test of the specified specifications; The real-time temperature distribution of the target cable corresponding to each current load test of the specified specification is respectively measured at the time and the environmental conditions are collected to obtain the corresponding analysis elements of each real-time temperature distribution; According to the analysis elements of each of the real-time temperature distributions, data analysis is performed on each of the real-time temperature distributions under element conditions to obtain defect and fault identification results corresponding to the infrared temperature measurement test items of the target cable, and the defect and fault identification results are used as the infrared temperature measurement test item data of the target cable.

7. The method for detecting faults of electric wires and cables according to claim 1, characterized in that: The step of locating the defect and fault of the target cable according to the multi-item test data of the target cable to obtain the defect and fault information of the target cable includes: Performing independent defect fault location of each item of the target cable according to the multi-item test data of the target cable to obtain independent defect fault location results of each item of the target cable corresponding to the multi-item test data; Performing a weighted comprehensive analysis on the independent defect fault location results of each of the items to obtain a weighted fault location result of the target cable; Performing model prediction on the multiple-item test data of the target cable according to a pre-trained machine learning model to obtain a model prediction result of the target cable corresponding to the multiple-item test data; The weighted fault location result and the model prediction result together constitute the defect fault information of the target cable.

8. A defect fault detection device for electric wires and cables, characterized in that: A method for detecting a defect of a wire or cable according to any one of claims 1 to 7, comprising: An information acquisition module is used to acquire the buried direction information of the target cable and the test characteristics of several test items to be prepared for defect and fault testing of the target cable, and to perform simulation analysis and weighted fusion of the detection scheme on the buried direction information according to each of the test characteristics, so as to obtain the positioning information of the detection endpoints of the target cable corresponding to each of the test items; A cable testing module, used to deploy a detection instrument on the target cable according to the positioning information of the detection endpoint, and perform an electric pulse reflection test, a sheath grounding loop current test and an infrared temperature measurement test on the target cable based on the deployed detection instrument to obtain multi-item test data of the target cable; The positioning and analysis module is used to locate the defect and fault of the target cable according to the multi-item test data of the target cable to obtain the defect and fault information of the target cable.

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