Operation state monitoring operation and maintenance method and system for power cable

Abstract

The invention relates to the technical field of power monitoring, in particular to an operation state monitoring operation and maintenance method and system for a power cable, and the method comprises the following steps: transmitting a test signal with preset frequency and intensity to a target cable; capturing a test signal transmitted through the cable at the other end of the cable, and predicting the aging degree of the cable through an attenuation index; analyzing the time delay and intensity of a reflected signal in the cable by using a TDR technology, and determining the initial position of potential damage or discontinuity in the cable; performing a multi-frequency signal test on the cable, and analyzing the transmission characteristics of the cable to each frequency signal so as to obtain a fault type; and comprehensively analyzing by using a multi-task learning model to determine the aging condition and the specific damage position of the cable. According to the invention, obvious external damage of the cable can be detected, tiny damage or aging phenomena, invisible to naked eyes, in the cable can be identified, and the requirement of manual operation is reduced, so that the detection efficiency and reliability are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of power monitoring, and in particular to a method and system for monitoring and operating the operating status of a power cable. Background Art

[0002] As an important part of the power system, power cables play a vital role in the transmission and distribution of electric energy. As the power system develops towards higher reliability and efficiency, cable health monitoring and maintenance have become key links to ensure the stable operation of the power system. However, traditional cable monitoring methods mainly rely on regular physical inspections and local electrical tests. These methods are not only time-consuming and labor-intensive, but also often fail to detect minor damage or initial signs of aging inside the cable in a timely manner, resulting in an increased risk of potential cable failures.

[0003] In addition, traditional methods have limitations in locating cable damage. Since cables are usually buried underground or hidden in other facilities, it is very difficult and limited to directly access the cables for inspection, which leads to inefficient manual inspections and difficulty in conducting a comprehensive inspection of the entire cable line. In this case, even minor damage may gradually deteriorate over time, eventually affecting the performance and safety of the cable, and may even cause unexpected interruptions to the power system.

[0004] With the advancement of technology, some emerging monitoring technologies have begun to be applied to cable status monitoring, such as time domain reflectometry (TDR)-based technology and frequency response analysis. These technologies can provide more detailed cable status information, including the location of cable damage and the degree of aging, but they often require complex data processing and analysis methods. Therefore, how to effectively integrate and analyze data from these advanced technologies, and how to improve the accuracy and efficiency of cable damage detection and aging assessment have become technical challenges that need to be urgently addressed in the current field of cable health monitoring. Summary of the invention

[0005] Based on the above objectives, the present invention provides a method and system for monitoring and maintaining the operating status of a power cable.

[0006] A method for monitoring and maintaining the operation status of a power cable comprises the following steps: S1: Signal transmission, sending a test signal of predetermined frequency and strength to the target cable; S2: Signal capture and attenuation analysis: Capture the test signal transmitted through the cable at the other end of the cable or at the detection point set in the segment, compare the attenuation degree between the original signal and the received signal, and predict the aging degree of the cable through the attenuation index; S3: Time Domain Reflectometry (TDR) technology uses TDR technology to analyze the time delay and strength of the reflected signal in the cable to determine the preliminary location of potential damage or discontinuity in the cable; S4: Frequency response analysis: Perform multi-frequency signal tests on the cable to analyze the transmission characteristics of the cable for each frequency signal, identify the impact of cable aging or minor damage on the transmission of different frequency signals, and thus obtain the fault type; S5: Based on the analysis results of S2, S3, and S4, a multi-task learning model is used for comprehensive analysis to determine the aging condition of the cable and the specific damage location.

[0007] Furthermore, the S1 specifically includes: S11, configuring a signal generator, wherein the signal generator includes an adjustable frequency and an adjustable output intensity, and the frequency range and intensity level of the test signal are preset according to the characteristics of the cable and the detection requirements; S12, connecting the signal generator to the target cable through a cable test head or an adapter matching the cable; S13, generating a pulse waveform using a modulation function of a signal generator; S13, test sequence initialization: start the test sequence through the signal generator, send test signals of predetermined frequency and strength in sequence, and monitor the stability and continuity of the signal at the same time to ensure the signal quality of the entire test process.

[0008] Furthermore, the S2 specifically includes: S21, set up detection points at the other end of the cable or in sections according to the cable length and structure, and install an oscilloscope at each detection point; S22, while transmitting the test signal, ensuring that the oscilloscope at the detection point synchronously records the signal through the synchronous output port of the signal generator; S23, record the received signal through an oscilloscope, compare it with the original signal, analyze the attenuation degree between the two, use the attenuation model to convert the attenuation degree into the aging index of the cable, and judge the aging degree of the cable.

[0009] Furthermore, the attenuation model is expressed as: ,in, is in the distance The signal attenuation at is the basic attenuation, taking into account factors such as cable connections and initial losses, is the attenuation coefficient per unit length, Is the cable length, converting the attenuation degree into the cable aging index specifically includes: Establish a relationship model between attenuation and aging: Based on historical monitoring data, establish a relationship model between cable attenuation and aging degree; Attenuation parameter calibration: When the cable is first put into use, measure and record the basic attenuation and the attenuation coefficient per unit length , as a benchmark for future attenuation measurements; Periodic attenuation measurement: Regularly measure the actual attenuation of the cable by using a test signal , and record the distance ; Aging degree calculation: Based on the relationship model, the actual measured attenuation Converting to an aging index for the cable involves calculating the difference between actual attenuation and base attenuation, and correlating the difference with the degree of aging.

[0010] Furthermore, the S3 specifically includes: S31, send a short pulse or step signal to the cable through the TDR device, and start recording the signal transmission time at the device end; S32, Reflection signal reception and recording: Use the same TDR equipment to capture the reflection signal caused by discontinuities in the cable (such as broken or aged areas) and record the arrival time and strength of the reflection signal; S33, calculating the time delay between the reflected signal and the original transmitted signal, the time delay Obtained directly from TDR equipment; S34, Determine the location of the break or discontinuity : ,in, is the distance from the start of the cable to the discontinuity, is the propagation speed of the signal in the cable (depending on the dielectric constant of the cable), is the time delay from transmitting the signal to receiving the reflected signal; S35, by analyzing the intensity of the reflected signal, a preliminary judgment is made on the nature of the discontinuity, and a high reflection intensity indicates severe damage or discontinuity.

[0011] Furthermore, the S4 specifically includes: S41, determine the test frequency, starting from low frequency and gradually increasing to high frequency to evaluate the frequency response characteristics of the cable; S42, for each selected test frequency, using a signal generator to generate a test signal of the corresponding frequency, and transmitting the test signal through the cable, and capturing the transmitted signal at the other end of the cable or at a detection point set in a segment; S43, phase analysis, for each test frequency, measures and records the phase change of the signal transmitted through the cable, the phase change being measured by comparing the phase difference between the transmitted signal and the received signal; S44, drawing a frequency response curve of the cable according to the phase analysis result combined with the attenuation analysis of the attenuation model, including a curve of attenuation variation with frequency and a curve of phase variation with frequency; S45, by analyzing the characteristics of the frequency response curve, can identify the impact of cable aging or minor damage on signal transmission. Different types of faults (such as insulation aging, minor cracks or connector damage) show different characteristics on the frequency response curve.

[0012] Further, the phase change is calculated as: ;in, is the frequency Phase change under (degrees), and are the phases of the signals at the receiving and transmitting ends respectively.

[0013] Furthermore, the S5 specifically includes: S51, data preprocessing: preprocessing the attenuation, TDR results, frequency response curve characteristics and phase change, including denoising, normalization, and feature extraction to ensure that the data is suitable for model input; S52, define tasks: define cable aging condition analysis and damage location determination as two related learning tasks, where the aging condition is considered a classification problem (e.g., classifying into several levels according to the degree of aging), and the damage location determination is considered a positioning problem (e.g., predicting the specific location of the damage or the interval where the damage exists); S53, Design of multi-task learning model: The multi-task learning model processes multiple types of input data and can output the results of multiple tasks. It uses a shared hidden layer to extract the common features of all tasks, and then provides a dedicated output layer for each task. The multi-task learning model based on deep learning is implemented; S54, training model: using a training data set containing attenuation, TDR results, frequency response curve characteristics and phase change to train the model. During the training process, it is necessary to optimize the loss functions of the two tasks at the same time, which is achieved in the form of a weighted loss function, where the weights reflect the importance of different tasks; S55, model evaluation and adjustment: Use the validation set to evaluate the performance of the model in the tasks of aging condition analysis and damage location determination, and adjust the model structure, parameters and task weights based on the evaluation results; S56, apply the model for analysis: apply the trained deep learning-based multi-task learning model to the new test data, comprehensively analyze the aging condition of the cable and the specific damage location, and output the evaluation results of the aging condition and the prediction of the damage location.

[0014] Furthermore, the multi-task learning model based on deep learning specifically includes: Shared layer: It consists of several convolutional layers or recurrent layers and is used to extract common features of all input data; Task-specific layers: Each task (aging analysis and damage location determination) has its own set of fully connected layers to learn the representation of the task from the features extracted by the shared layers; The input data are attenuation data, TDR results, frequency response characteristics and phase difference information; Shared layer feature extraction: As input data, the feature extraction of the shared layer is expressed as ,in is a function of the shared layer, are the parameters of the shared layer; Task-specific layer output: For the aging analysis task, let its output be ,in, is the function of the aging status analysis task layer, is the parameter of the task layer. For the damage location determination task, its output is ,in, is a function of the damage location determination task layer, is the parameter of the task layer; Loss function: The model loss function is the weighted sum of the two task loss functions, expressed as: ,in and are the loss functions for the aging condition analysis and damage location determination tasks, respectively. and are the true labels of the corresponding tasks, and is the weight used to balance the importance of different tasks.

[0015] A system for monitoring and maintaining the operation status of a power cable, used to implement the above-mentioned method for monitoring and maintaining the operation status of a power cable, comprises the following modules: Signal transmitting module: sends a test signal of predetermined frequency and strength to the target cable; Signal capture and attenuation analysis module: It is set at the other end or segment of the cable to capture the test signal transmitted through the cable and analyze the attenuation between the original signal and the received signal, and predict the aging degree of the cable through the attenuation index; Time Domain Reflectometry (TDR) module: uses TDR technology to analyze the time delay and strength of the reflected signal in the cable to preliminarily determine the potential damage or discontinuity location in the cable; Frequency response analysis module: performs multi-frequency signal tests on the cable and analyzes the transmission characteristics of the cable for signals of different frequencies. It identifies the impact of cable aging or minor damage on signal transmission and determines the fault type. Comprehensive analysis and diagnosis module: A multi-task learning model is used to perform comprehensive analysis to determine the aging condition of the cable and the specific damage location.

[0016] Beneficial effects of the present invention: By sending a predefined test signal to the cable and analyzing its attenuation, phase change, frequency response and other characteristics during cable transmission, it is able to automatically and accurately identify aging and damage in the cable. Compared with traditional manual troubleshooting, such as physical inspection or simple visual inspection, it has significant advantages. It can not only detect obvious damage on the outside of the cable, but also identify tiny damage or aging inside the cable that is invisible to the naked eye, reducing the need for manual operation and thus improving the efficiency and reliability of detection.

[0017] The present invention realizes comprehensive monitoring of the cable status by integrating the cable attenuation data, time domain reflectometry (TDR) results, frequency response characteristics and phase difference information. Compared with single indicator analysis, this multi-dimensional analysis method can more comprehensively capture the subtle changes of cable aging or damage, thereby significantly improving the accuracy of cable aging status and damage location diagnosis. TDR technology can accurately locate the physical damage of the cable, while frequency response analysis helps to reveal the characteristic changes caused by the aging of the cable material. The combination of the two can provide a more accurate assessment of the cable health status.

[0018] The present invention adopts a multi-task learning (MTL) model to simultaneously process the cable aging condition analysis and damage location determination tasks under the same learning framework, which not only greatly improves the efficiency of data analysis, but also enhances the generalization ability of the model on various tasks because the correlation between tasks is learned by the model together. This information-sharing learning method is particularly suitable for the field of cable monitoring, in which the aging condition of the cable and the specific damage are often interrelated. The MTL model can better capture these intrinsic connections and improve the accuracy and stability of the prediction. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only for the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0020] Figure 1 A schematic diagram of the operation and maintenance method according to an embodiment of the present invention; Figure 2 This is a schematic diagram of the functional modules of the operation and maintenance system according to an embodiment of the present invention; Figure 3A schematic diagram of a curve showing attenuation changes with frequency according to an embodiment of the present invention; Figure 4 Schematic diagram of a curve showing phase variation versus frequency according to an embodiment of the present invention. DETAILED DESCRIPTION

[0021] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with specific embodiments.

[0022] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the present invention should be understood by people with ordinary skills in the field to which the present invention belongs. The "first", "second" and similar words used in the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0023] like Figure 1-4 As shown, a method for monitoring and maintaining the operation status of a power cable comprises the following steps: S1: Signal transmission, sending a test signal of predetermined frequency and strength to the target cable; S2: Signal capture and attenuation analysis: Capture the test signal transmitted through the cable at the other end of the cable or at the detection point set in the segment, compare the attenuation degree between the original signal and the received signal, and predict the aging degree of the cable through the attenuation index; S3: Time Domain Reflectometry (TDR) technology uses TDR technology to analyze the time delay and strength of the reflected signal in the cable to determine the preliminary location of potential damage or discontinuity in the cable; S4: Frequency response analysis: Perform multi-frequency signal tests on the cable to analyze the transmission characteristics of the cable for each frequency signal, identify the impact of cable aging or minor damage on the transmission of different frequency signals, and thus obtain the fault type; S5: Based on the analysis results of S2, S3, and S4, a multi-task learning model is used for comprehensive analysis to determine the aging condition of the cable and the specific damage location.

[0024] S1 specifically includes: S11, configure the signal generator, which includes adjustable frequency and adjustable output intensity. According to the characteristics of the cable and the detection requirements, preset the frequency range and intensity level of the test signal, and select the Keysight 33600A series waveform generator; S12, connecting the signal generator to the target cable through a cable test head or an adapter matching the cable; S13, using the modulation function of the signal generator to generate a pulse wave waveform, the signal waveform includes a sine wave, a square wave, a pulse wave or a custom waveform, considering that the goal of the present invention is to monitor and maintain the operation status of the power cable, including the detection of aging and minor damage, the pulse wave is the most suitable choice. The application of the pulse wave in the TDR technology can efficiently and accurately locate the fault point in the cable, which is very important for maintenance and repair work; S13, test sequence initialization: start the test sequence through the signal generator, send test signals of predetermined frequency and strength in sequence, and monitor the stability and continuity of the signal at the same time to ensure the signal quality of the entire test process.

[0025] S2 specifically includes: S21, set up detection points at the other end of the cable or in sections according to the cable length and structure, and install an oscilloscope at each detection point; S22, while transmitting the test signal, ensuring that the oscilloscope at the detection point synchronously records the signal through the synchronous output port of the signal generator; S23, record the received signal through an oscilloscope, compare it with the original signal, analyze the attenuation degree between the two, use the attenuation model to convert the attenuation degree into the aging index of the cable, and judge the aging degree of the cable.

[0026] The attenuation model is used to describe the reduction in signal strength when passing through a cable. It is related to the physical properties, length, material, and aging of the cable. The attenuation model is expressed as a linear relationship. The attenuation model is expressed as: ,in, is in the distance The signal attenuation at is the basic attenuation, taking into account factors such as cable connections and initial losses, is the attenuation coefficient per unit length, Is the cable length, converting the attenuation degree into the cable aging index specifically includes: Establish a relationship model between attenuation and aging: Based on historical monitoring data, establish a relationship model between cable attenuation and aging degree; Attenuation parameter calibration: When the cable is first put into use, measure and record the basic attenuation and the attenuation coefficient per unit length , as a benchmark for future attenuation measurements; Periodic attenuation measurement: Regularly measure the actual attenuation of the cable by using a test signal , and record the distance ; Aging degree calculation: Based on the relationship model, the actual measured attenuation Converting to an aging index for the cable involves calculating the difference between actual attenuation and base attenuation, and correlating the difference with the degree of aging.

[0027] In order to convert the attenuation degree into the aging index of the cable, a linear model is set. There is a direct linear relationship between the aging index of the cable and the attenuation degree of the signal passing through the cable. The model is expressed as: ,in, It is the aging index of the cable, which can be a percentage from 0 to 100, where 0% represents no aging and 100% represents complete aging; is the intercept of the linear model, representing the baseline aging index of the cable when there is no aging. Ideally, if the cable has no aging at all, Should be close to is the slope of the linear model, indicating the degree of attenuation and aging indicators The strength of the relationship between. The value of determines the impact of the attenuation change on the aging index. It is the degree of attenuation, which can be expressed by the difference between the attenuation calculated by the above attenuation model and the initial attenuation (i.e. the attenuation when the cable is new).

[0028] Here is an example: Through experiments and historical data analysis, a specific cable aging model was obtained, whose parameters are (Even new cables may have of "baseline aging"), (That is, for every 1dB increase in attenuation, the aging index increases .

[0029] If the initial attenuation of a cable segment is , the measured attenuation after a period of time is , then the attenuation increases , according to the model, the aging index of this cable can be calculated as: , which means that the cable has aged more than the initial state. .

[0030] S3 specifically includes: S31, send a short pulse or step signal to the cable through the TDR device, and start recording the signal transmission time at the device end; S32, Reflection signal reception and recording: Use the same TDR equipment to capture the reflection signal caused by discontinuities in the cable (such as broken or aged areas) and record the arrival time and strength of the reflection signal; S33, calculating the time delay between the reflected signal and the original transmitted signal, the time delay Obtained directly from TDR equipment; S34, Determine the location of the break or discontinuity : ,in, is the distance from the start of the cable to the discontinuity, is the propagation speed of the signal in the cable (depending on the dielectric constant of the cable), is the time delay from transmitting the signal to receiving the reflected signal; S35, by analyzing the intensity of the reflected signal, a preliminary judgment is made on the nature of the discontinuity, and a high reflection intensity indicates severe damage or discontinuity.

[0031] S4 specifically includes: S41, determine the test frequency, starting from low frequency and gradually increasing to high frequency to evaluate the frequency response characteristics of the cable; S42, for each selected test frequency, using a signal generator to generate a test signal of the corresponding frequency, and transmitting the test signal through the cable, and capturing the transmitted signal at the other end of the cable or at a detection point set in a segment; S43, phase analysis, for each test frequency, measures and records the phase change of the signal transmitted through the cable, the phase change being measured by comparing the phase difference between the transmitted signal and the received signal; S44, drawing a frequency response curve of the cable according to the phase analysis result combined with the attenuation analysis of the attenuation model, including a curve of attenuation variation with frequency and a curve of phase variation with frequency; S45, by analyzing the characteristics of the frequency response curve, such as abnormal increase in attenuation or phase mutation in a specific frequency range, to identify the impact of cable aging or minor damage on signal transmission. Different types of faults (such as insulation aging, minor cracks or joint damage) show different characteristics on the frequency response curve.

[0032] The following are common fault types and their characteristics on the frequency response curve: 1. Cable insulation aging.

[0033] Characteristics: The aging of insulating materials will cause the overall attenuation to gradually increase with the increase of frequency. In the high-frequency area, this increase is more significant.

[0034] Frequency response curve performance: In the low-frequency area, the attenuation remains relatively stable, but as the frequency increases, the slope of the attenuation curve gradually increases, showing that the curve bends upward.

[0035] 2. Minor cracks or local damage.

[0036] Characteristics: Small cracks or localized damage can cause significant attenuation peaks at specific frequencies because these damages cause signal reflections and scattering.

[0037] Frequency response curve performance: At a specific frequency (or nearby frequency), a sharp peak will appear in the attenuation curve, reflecting the local reflection of the signal at the damage site.

[0038] 3. The connector or connector is damaged.

[0039] Characteristics: Damage to a connector or connector can cause an overall increase in attenuation at all frequencies, especially if the connector loses good electrical contact.

[0040] Frequency response curve performance: In the entire frequency range, the attenuation curve moves upward as a whole, showing a higher attenuation than normal.

[0041] 4. The shielding layer is damaged.

[0042] Characteristics: If the shielding layer of the cable is damaged, especially at high frequencies, it will lead to an increase in electromagnetic interference, thereby increasing signal attenuation.

[0043] Frequency response curve performance: In the high-frequency region, the attenuation curve rises faster than that of an undamaged cable, and an abnormal attenuation increase occurs in the high-frequency range.

[0044] 5. Moisture intrusion.

[0045] Characteristics: Moisture intrusion causes increased attenuation of the cable within a specific frequency range, especially at frequencies where moisture absorption is stronger.

[0046] Frequency response curve performance: In certain frequency regions, such as the microwave frequency band, the attenuation curve may show a more obvious upward trend than normal.

[0047] By testing the cable with multiple frequency signals, the following Figure 3 , Figure 4 The curve of exist Figure 3In the figure, the Total Attenuation curve represents the total attenuation of the cable under the influence of aging and specific damage. It can be seen that at about 500Hz, due to cable damage, an obvious attenuation peak appears, which is consistent with the characteristics of tiny cracks or local damage mentioned in the above analysis. At the same time, the trend of overall attenuation increasing with increasing frequency indicates the aging of cable insulation; the Normal Attenuation curve (dashed line) represents the normal attenuation of the cable when there is no aging or damage.

[0048] exist Figure 4 In the figure, the phase change curve shows periodic fluctuations as the frequency changes, which is a manifestation of phase change.

[0049] The phase change is calculated as: ;in, is the frequency Phase change under (degrees), and are the phases of the signals at the receiving and transmitting ends respectively.

[0050] S5 specifically includes: S51, data preprocessing: preprocessing the attenuation, TDR results, frequency response curve characteristics and phase change, including denoising, normalization, and feature extraction to ensure that the data is suitable for model input; S52, define tasks: define cable aging condition analysis and damage location determination as two related learning tasks, where the aging condition is considered a classification problem (e.g., classifying into several levels according to the degree of aging), and the damage location determination is considered a positioning problem (e.g., predicting the specific location of the damage or the interval where the damage exists); S53, Design of multi-task learning model: The multi-task learning model processes multiple types of input data and can output the results of multiple tasks. It uses a shared hidden layer to extract the common features of all tasks, and then provides a dedicated output layer for each task. The multi-task learning model based on deep learning is implemented; S54, training model: using a training data set containing attenuation, TDR results, frequency response curve characteristics and phase change to train the model. During the training process, it is necessary to optimize the loss functions of the two tasks at the same time, which is achieved in the form of a weighted loss function, where the weights reflect the importance of different tasks; S55, model evaluation and adjustment: Use the validation set to evaluate the performance of the model in the tasks of aging condition analysis and damage location determination, and adjust the model structure, parameters and task weights based on the evaluation results; S56, apply the model for analysis: apply the trained deep learning-based multi-task learning model to the new test data, comprehensively analyze the aging condition of the cable and the specific damage location, and output the evaluation results of the aging condition and the prediction of the damage location.

[0051] The multi-task learning model based on deep learning specifically includes: Shared layer: It consists of several convolutional layers or recurrent layers and is used to extract common features of all input data; Task-specific layers: Each task (aging analysis and damage location determination) has its own set of fully connected layers to learn the representation of the task from the features extracted by the shared layers; The input data are attenuation data, TDR results, frequency response characteristics and phase difference information; Shared layer feature extraction: As input data, the feature extraction of the shared layer is expressed as ,in is a function of the shared layer, are the parameters of the shared layer; Task-specific layer output: For the aging analysis task, let its output be ,in, is the function of the aging status analysis task layer, is the parameter of the task layer. For the damage location determination task, its output is ,in, is a function of the damage location determination task layer, is the parameter of the task layer; Loss function: The model loss function is the weighted sum of the two task loss functions, expressed as: ,in and are the loss functions for the aging condition analysis and damage location determination tasks, respectively. and are the true labels of the corresponding tasks, and is the weight used to balance the importance of different tasks.

[0052] In the training phase, by minimizing the loss function To update the shared layer parameters And each task-specific layer parameters and ,In the application phase, given new input data, the model can ,provide both the assessment of the aging condition and the prediction of the ,damage location.

[0053] like Figure 2As shown, a system for monitoring and maintaining the operation status of a power cable is used to implement the above-mentioned method for monitoring and maintaining the operation status of a power cable, and includes the following modules: Signal transmitting module: sends a test signal of predetermined frequency and strength to the target cable; Signal capture and attenuation analysis module: It is set at the other end or segment of the cable to capture the test signal transmitted through the cable and analyze the attenuation between the original signal and the received signal, and predict the aging degree of the cable through the attenuation index; Time Domain Reflectometry (TDR) module: uses TDR technology to analyze the time delay and strength of the reflected signal in the cable to preliminarily determine the potential damage or discontinuity location in the cable; Frequency response analysis module: performs multi-frequency signal tests on the cable and analyzes the transmission characteristics of the cable for signals of different frequencies. It identifies the impact of cable aging or minor damage on signal transmission and determines the fault type. Comprehensive analysis and diagnosis module: A multi-task learning model is used to perform comprehensive analysis to determine the aging condition of the cable and the specific damage location.

[0054] Those skilled in the art should understand that the discussion of any of the above embodiments is merely illustrative and is not intended to imply that the scope of the present invention is limited to these examples. Under the concept of the present invention, the technical features in the above embodiments or different embodiments may be combined, the steps may be implemented in any order, and there are many other variations of the different aspects of the present invention as described above, which are not provided in detail for the sake of simplicity.

[0055] The present invention is intended to cover all such substitutions, modifications and variations that fall within the broad scope of the claims. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc. 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 monitoring and maintaining the operation status of a power cable, characterized in that: The following steps are involved: S1: Signal transmission, sending a test signal of predetermined frequency and strength to the target cable; S2: Signal capture and attenuation analysis: Capture the test signal transmitted through the cable at the other end of the cable or at the detection point set in the segment, compare the attenuation degree between the original signal and the received signal, and predict the aging degree of the cable through the attenuation index; S3: Time Domain Reflectometry (TDR) technology uses TDR technology to analyze the time delay and strength of the reflected signal in the cable to determine the preliminary location of potential damage or discontinuity in the cable; S4: Frequency response analysis: Perform multi-frequency signal tests on the cable to analyze the transmission characteristics of the cable for each frequency signal, identify the impact of cable aging or minor damage on the transmission of different frequency signals, and thus obtain the fault type; S5: Based on the analysis results of S2, S3, and S4, a multi-task learning model is used for comprehensive analysis to determine the aging condition of the cable and the specific damage location.

2. A method for monitoring and operating the power cable according to claim 1, characterized in that: The S1 specifically includes: S11, configuring a signal generator, wherein the signal generator includes an adjustable frequency and an adjustable output intensity, and the frequency range and intensity level of the test signal are preset according to the characteristics of the cable and the detection requirements; S12, connecting the signal generator to the target cable through a cable test head or an adapter matching the cable; S13, generating a pulse waveform using a modulation function of a signal generator; S13, test sequence initialization: start the test sequence through the signal generator, send test signals of predetermined frequency and strength in sequence, and monitor the stability and continuity of the signal at the same time to ensure the signal quality of the entire test process.

3. A method for monitoring and operating the operation status of a power cable according to claim 1, characterized in that: The S2 specifically includes: S21, set up detection points at the other end of the cable or in sections according to the cable length and structure, and install an oscilloscope at each detection point; S22, while transmitting the test signal, ensuring that the oscilloscope at the detection point synchronously records the signal through the synchronous output port of the signal generator; S23, recording the received signal through an oscilloscope, comparing it with the original signal, analyzing the attenuation degree between the two, converting the attenuation degree into the aging index of the cable using the attenuation model, and judging the aging degree of the cable.

4. A method for monitoring and operating the operation status of a power cable according to claim 3, characterized in that: The attenuation model is expressed as: ,in, is in the distance The signal attenuation at is the basic attenuation, taking into account factors such as cable connections and initial losses, is the attenuation coefficient per unit length, Is the cable length, converting the attenuation degree into the cable aging index specifically includes: Establish a relationship model between attenuation and aging: Based on historical monitoring data, establish a relationship model between cable attenuation and aging degree; Attenuation parameter calibration: When the cable is first put into use, measure and record the basic attenuation and the attenuation coefficient per unit length , as a benchmark for future attenuation measurements; Periodic attenuation measurement: Regularly measure the actual attenuation of the cable by using a test signal , and record the distance ; Aging degree calculation: Based on the relationship model, the actual measured attenuation Converting to an aging index for the cable involves calculating the difference between actual attenuation and base attenuation, and correlating the difference with the degree of aging.

5. A method for monitoring and operating the operation status of a power cable according to claim 1, characterized in that: The S3 specifically includes: S31, send a short pulse or step signal to the cable through the TDR device, and start recording the signal transmission time at the device end; S32, receiving and recording reflected signals: using the same TDR device to capture reflected signals caused by discontinuities in the cable, and recording the arrival time and strength of the reflected signals; S33, calculating the time delay between the reflected signal and the original transmitted signal, the time delay Obtained directly from TDR equipment; S34, Determine the location of the break or discontinuity : ,in, is the distance from the start of the cable to the discontinuity, is the propagation speed of the signal in the cable, is the time delay from transmitting the signal to receiving the reflected signal; S35, by analyzing the intensity of the reflected signal, a preliminary judgment is made on the nature of the discontinuity, and a high reflection intensity indicates severe damage or discontinuity.

6. A method for monitoring and operating the operation status of a power cable according to claim 4, characterized in that: The S4 specifically includes: S41, determine the test frequency, starting from low frequency and gradually increasing to high frequency to evaluate the frequency response characteristics of the cable; S42, for each selected test frequency, using a signal generator to generate a test signal of the corresponding frequency, and transmitting the test signal through the cable, and capturing the transmitted signal at the other end of the cable or at a detection point set in a segment; S43, phase analysis, for each test frequency, measures and records the phase change of the signal transmitted through the cable, the phase change being measured by comparing the phase difference between the transmitted signal and the received signal; S44, drawing a frequency response curve of the cable according to the phase analysis result combined with the attenuation analysis of the attenuation model, including a curve of attenuation variation with frequency and a curve of phase variation with frequency; S45, by analyzing the characteristics of the frequency response curve, to identify the impact of cable aging or minor damage on signal transmission. Different types of faults present different characteristics on the frequency response curve.

7. A method for monitoring and operating the operation status of a power cable according to claim 6, characterized in that: The phase change is calculated as: ;in, is the frequency The phase change under and are the phases of the signals at the receiving and transmitting ends respectively.

8. A method for monitoring and operating the operation status of a power cable according to claim 7, characterized in that: The S5 specifically includes: S51, data preprocessing: preprocessing the attenuation, TDR results, frequency response curve characteristics and phase change, including denoising, normalization, and feature extraction to ensure that the data is suitable for model input; S52, define the task: define the cable aging condition analysis and damage location determination as two related learning tasks, the aging condition is regarded as a classification problem, and the damage location determination is regarded as a positioning problem; S53, Design of multi-task learning model: The multi-task learning model processes multiple types of input data and can output the results of multiple tasks. It uses a shared hidden layer to extract the common features of all tasks, and then provides a dedicated output layer for each task. The multi-task learning model based on deep learning is implemented; S54, training model: using a training data set containing attenuation, TDR results, frequency response curve characteristics and phase change to train the model. During the training process, it is necessary to optimize the loss functions of the two tasks at the same time, which is achieved in the form of a weighted loss function, where the weights reflect the importance of different tasks; S55, model evaluation and adjustment: Use the validation set to evaluate the performance of the model in the tasks of aging condition analysis and damage location determination, and adjust the model structure, parameters and task weights based on the evaluation results; S56, apply the model for analysis: apply the trained deep learning-based multi-task learning model to the new test data, comprehensively analyze the aging condition of the cable and the specific damage location, and output the evaluation results of the aging condition and the prediction of the damage location.

9. A method for monitoring and operating the operation status of a power cable according to claim 8, characterized in that: The multi-task learning model based on deep learning specifically includes: Shared layer: It consists of several convolutional layers or recurrent layers and is used to extract common features of all input data; Task-specific layers: Each task has its own set of fully connected layers to learn the task’s representation from the features extracted by the shared layers; The input data are attenuation data, TDR results, frequency response characteristics and phase difference information; Shared layer feature extraction: As input data, the feature extraction of the shared layer is expressed as ,in is a function of the shared layer, are the parameters of the shared layer; Task-specific layer output: For the aging analysis task, let its output be ,in, is the function of the aging status analysis task layer, is the parameter of the task layer. For the damage location determination task, its output is ,in, is a function of the damage location determination task layer, is the parameter of the task layer; Loss function: The model loss function is the weighted sum of the two task loss functions, expressed as: ,in and are the loss functions for the aging condition analysis and damage location determination tasks, respectively. and are the true labels of the corresponding tasks, and is the weight used to balance the importance of different tasks.

10. A system for monitoring and operating the operation of a power cable, used to implement a method for monitoring and operating the operation of a power cable as claimed in any one of claims 1 to 9, characterized in that: Includes the following modules: Signal transmitting module: sends a test signal of predetermined frequency and strength to the target cable; Signal capture and attenuation analysis module: It is set at the other end or segment of the cable to capture the test signal transmitted through the cable and analyze the attenuation between the original signal and the received signal, and predict the aging degree of the cable through the attenuation index; Time Domain Reflectometry (TDR) module: uses TDR technology to analyze the time delay and strength of the reflected signal in the cable to preliminarily determine the potential damage or discontinuity location in the cable; Frequency response analysis module: performs multi-frequency signal tests on the cable and analyzes the transmission characteristics of the cable for signals of different frequencies. It identifies the impact of cable aging or minor damage on signal transmission and determines the fault type. Comprehensive analysis and diagnosis module: A multi-task learning model is used to perform comprehensive analysis to determine the aging condition of the cable and the specific damage location.

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