Operation process partial discharge monitoring analysis system and method adapted to cable terminal

Abstract

This invention belongs to the field of cable terminal operation monitoring technology, specifically a partial discharge monitoring and analysis system and method adapted to the operation process of cable terminals. The system includes a multi-modal signal coupling acquisition module, an adaptive signal conditioning module, a partial discharge characteristic intelligent analysis module, a risk quantification assessment module, a closed-loop feedback control module, and a partial discharge monitoring terminal. Through the coordinated operation of five modules—multi-modal signal coupling acquisition, adaptive signal conditioning, intelligent analysis of partial discharge characteristics, risk quantification assessment, and closed-loop feedback control—this invention achieves comprehensive and accurate monitoring and intelligent analysis of partial discharge phenomena in cable terminals, providing strong technical support for the intelligent operation and maintenance of cable terminals. Furthermore, by accurately analyzing and promptly warning of the degree of partial discharge hazards in cable terminal operation, it contributes to power safety, exhibits a high level of intelligence, and reduces the difficulty of supervision.

Description

Technical Field

[0001] This invention relates to the field of cable terminal operation monitoring technology, specifically to a partial discharge monitoring and analysis system and method adapted to the operation process of cable terminals. Background Technology

[0002] Cable terminations, also known as cable joints, are key connecting components at both ends of a cable line. After the cable is laid, it needs to be connected to other electrical equipment through the termination to ensure the continuity of the circuit. This connection point not only undertakes the core task of electrical conduction, but also needs to have multiple functions such as waterproofing, dustproofing, vibration resistance, insulation and stress control to ensure the safe and stable operation of the cable in complex environments.

[0003] Cable terminals are critical nodes in power transmission systems. Partial discharge caused by factors such as insulation deterioration is a major cause of equipment failure. Chinese invention patent CN103399265A discloses an ultrasonic monitor for partial discharge of high-voltage cable terminals, which includes a partial discharge sensor, a partial discharge signal acquisition and processing device, and a power supply. This invention has the advantages of simple structure, small size, easy implementation, and convenient operation. It is also not easily affected by the electromagnetic environment on site and has strong adaptability.

[0004] However, in practical applications, the above-mentioned invention relies on a single type of sensor, resulting in insufficient signal integrity. It is also difficult to conduct closed-loop management of partial discharge monitoring, analysis, and handling decisions for cable terminals, and it is impossible to reasonably analyze and accurately warn of the operational risks and partial discharge hazards of cable terminals. This is not conducive to ensuring power safety and reducing the difficulty of supervising cable terminals.

[0005] To address the aforementioned technical shortcomings, a solution is proposed. Summary of the Invention

[0006] The purpose of this invention is to provide a partial discharge monitoring and analysis system and method adapted to cable terminals, which solves the problems of existing technologies that rely on a single type of sensor, resulting in insufficient signal integrity, difficulty in closed-loop management for monitoring, analyzing, and making decisions on partial discharge in cable terminals, and inability to reasonably analyze and accurately warn of the operational risks and partial discharge hazards of cable terminals, which is not conducive to ensuring power safety and reducing the difficulty of cable terminal supervision.

[0007] To achieve the above objectives, the present invention provides the following technical solution:

[0008] The partial discharge monitoring and analysis system adapted to cable terminals includes a multi-modal signal coupling acquisition module, an adaptive signal conditioning module, a partial discharge characteristic intelligent analysis module, a risk quantification assessment module, and a partial discharge monitoring terminal. The multi-modal signal coupling acquisition module integrates a high-frequency current sensor, an ultrasonic sensor, and an ultra-high frequency electromagnetic wave sensor for data acquisition. The acquired data is encoded by a multiplexer and transmitted to the adaptive signal conditioning module in digital stream form.

[0009] After receiving the data, the adaptive signal conditioning module processes it to generate a phase-resolved partial discharge spectrum and sends it to the intelligent partial discharge feature analysis module. The intelligent partial discharge feature analysis module performs a two-dimensional convolution kernel scan on the phase-resolved partial discharge spectrum to extract feature parameters including pulse amplitude distribution, phase concentration and energy density gradient. It then dynamically groups the feature vectors using an unsupervised clustering algorithm to generate a partial discharge mode label library. Combined with historical data, it constructs a time-series correlation model to identify the discharge type and its development stage.

[0010] The risk quantification assessment module calculates the risk index based on the partial discharge characteristic analysis results and uses a fuzzy logic reasoning engine. The risk index is a weighted synthesis of pulse repetition rate, energy accumulation and phase offset. It is mapped to four levels of "normal-attention-warning-emergency" through a three-dimensional risk matrix and the risk quantification assessment results are sent to the partial discharge monitoring terminal.

[0011] Furthermore, the multimodal signal coupling acquisition module achieves phase-aligned acquisition of three-channel signals through a spatiotemporal synchronization unit, and adopts an adaptive gain control algorithm to dynamically adjust the sensor sensitivity threshold according to the operating voltage of the cable terminal.

[0012] Furthermore, the processing steps of the adaptive signal conditioning module include:

[0013] The partial discharge pulse and background noise are separated by a frequency band segmentation filter bank. The high-frequency components are nonlinearly filtered by a wavelet packet threshold denoising algorithm to preserve the steep leading edge characteristics of the partial discharge pulse. The time-domain signal is mapped to the power frequency phase coordinate system based on the phase analysis algorithm to generate a phase-resolved partial discharge spectrum.

[0014] Furthermore, the risk quantification assessment module communicates with the closed-loop feedback control module. The risk quantification assessment module sends the risk quantification assessment results to the closed-loop feedback control module. Based on the risk quantification assessment results, the closed-loop feedback control module pushes corresponding alarm information to the partial discharge monitoring terminal through the IoT gateway and triggers the adaptive adjustment mechanism.

[0015] Furthermore, the adaptive adjustment mechanism includes:

[0016] Local shielding is initiated in areas with high-frequency interference sources; the density of subsequent monitoring cycles is dynamically adjusted; and a digital report containing the fault location, type, and recommended measures is generated.

[0017] Furthermore, the partial discharge monitoring terminal is connected to the cable terminal monitoring module. The cable terminal monitoring module monitors the cable terminal, analyzes and judges its operational risk, and generates a low-risk or high-risk monitoring signal accordingly. The low-risk or high-risk monitoring signal is then sent to the partial discharge monitoring terminal. When the partial discharge monitoring terminal receives the high-risk monitoring signal, it issues a corresponding warning.

[0018] Furthermore, the specific analysis process for the cable terminal monitoring module includes:

[0019] The temperature, humidity, and pollution levels of the environment where the cable terminal is located, as well as the vibration value of the cable terminal, are collected. The temperature, humidity, pollution level, and vibration value are weighted and summed to calculate the terminal deterioration value. The terminal deterioration value is compared with the preset terminal deterioration threshold. If the terminal deterioration value exceeds the preset terminal deterioration threshold, the cable terminal is judged to be in a state of easy aging.

[0020] The total usage time of the cable terminal and the total time it was in a vulnerable state in historical periods are obtained and marked as terminal operating time value and terminal aging value, respectively. The number of times the single duration of the cable terminal in a vulnerable state in historical periods exceeded the corresponding preset duration threshold is marked as aging risk frequency value. The terminal external condition value is calculated by weighted summation of terminal operating time value, terminal aging value and aging risk frequency value. The terminal external condition value is compared with the preset terminal external condition threshold. If the terminal external condition value exceeds the preset terminal external condition threshold, a high-risk monitoring signal is generated.

[0021] If the terminal external condition value does not exceed the preset terminal external condition threshold, the surface image of the cable terminal is collected, the surface image of the cable terminal is used to identify defects, and the identified defects are classified. If the data of each characteristic parameter of the corresponding defect meets the preset safety requirements of the corresponding type of defect, the corresponding defect is marked as a low-impact object; otherwise, the corresponding defect is marked as a dangerous object.

[0022] If a dangerous object is present on the cable terminal, a high-risk monitoring signal is generated. If no dangerous object is present on the cable terminal, several sub-regions are defined on the cable terminal. If a defect exists in a corresponding sub-region, the corresponding sub-region is marked as an abnormal region. The number of abnormal regions on the cable terminal is obtained, and the ratio of this number to the total number of sub-regions is calculated to obtain the abnormal region characteristic value. The abnormal region characteristic value is compared with a preset abnormal region characteristic threshold. If the abnormal region characteristic value exceeds the preset abnormal region characteristic threshold, a high-risk monitoring signal is generated. If the abnormal region characteristic value does not exceed the preset abnormal region characteristic threshold, a low-risk monitoring signal is generated.

[0023] Furthermore, the cable terminal monitoring module is connected to the partial discharge retrospective analysis module. The cable terminal monitoring module sends the monitoring low-risk signal to the partial discharge retrospective analysis module. When the partial discharge retrospective analysis module receives the monitoring low-risk signal, it analyzes the degree of partial discharge risk of the cable terminal during the detection period. Through analysis, it generates a partial discharge easy-to-monitor signal or a partial discharge difficult-to-monitor signal, and sends the partial discharge easy-to-monitor signal or partial discharge difficult-to-monitor signal to the partial discharge monitoring terminal. When the partial discharge monitoring terminal receives the partial discharge difficult-to-monitor signal, it issues a corresponding warning.

[0024] Furthermore, the specific analysis process of the partial discharge retrospective analysis module includes:

[0025] The number of partial discharges occurring at the cable terminal during the detection period is obtained and marked as the partial discharge frequency. The partial discharge frequency is compared with a preset partial discharge frequency threshold. If the partial discharge frequency exceeds the preset partial discharge frequency threshold, a partial discharge difficult monitoring signal is generated. If the partial discharge frequency does not exceed the preset partial discharge frequency threshold, the duration of the corresponding partial discharge is marked as the partial discharge time value. All partial discharge time values ​​during the detection period are summed to obtain the partial discharge time measurement value. The number of partial discharges during the detection period whose partial discharge time value exceeds the preset partial discharge time threshold is marked as the partial discharge danger frequency value.

[0026] The partial discharge (PD) backtracking value is calculated by weighting and summing the PD frequency, PD time measurement value, and PD danger frequency value. The PD backtracking value is then compared with a preset PD backtracking threshold. If the PD backtracking value exceeds the preset PD backtracking threshold, a PD difficult-to-monitor signal is generated; if the PD backtracking value does not exceed the preset PD backtracking threshold, a PD easy-to-monitor signal is generated.

[0027] Furthermore, this invention also proposes a method for monitoring and analyzing partial discharge during the operation of cable terminals, comprising the following steps:

[0028] Step 1: Collect data from the cable terminal using a high-frequency current sensor, an ultrasonic sensor, and an ultra-high frequency electromagnetic wave sensor.

[0029] Step 2: Receive and process the data to generate a phase-resolved partial discharge spectrum;

[0030] Step 3: Analyze the partial discharge spectrum based on the phase-resolved partial discharge spectrum and output the partial discharge characteristic analysis results;

[0031] Step 4: Conduct risk quantification and assessment analysis based on the partial discharge characteristic analysis results;

[0032] Step 5: Based on the risk quantification assessment results, push the corresponding alarm information to the local emission monitoring terminal to trigger the adaptive adjustment mechanism.

[0033] Compared with the prior art, the beneficial effects of the present invention are:

[0034] 1. In this invention, through the coordinated operation of five modules—multi-modal signal coupling acquisition, adaptive signal conditioning, intelligent analysis of partial discharge characteristics, risk quantification assessment, and closed-loop feedback control—the partial discharge phenomenon of cable terminals is comprehensively and accurately monitored and intelligently analyzed. This improves the sensitivity of partial discharge detection, reduces the false alarm rate, and enables real-time assessment and intelligent operation and maintenance of the insulation status of cable terminals.

[0035] 2. In this invention, the cable terminal monitoring module monitors the cable terminal and judges its operational risk. When a high-risk monitoring signal is generated, the cable terminal is repaired or replaced in a timely manner. When a low-risk monitoring signal is generated, the partial discharge backtracking analysis module analyzes the degree of partial discharge risk of the cable terminal during the detection period. When a partial discharge easy-to-monitor signal is generated, the subsequent monitoring and management of partial discharge of the cable terminal is strengthened. The invention has a high level of intelligence and low supervision difficulty. Attached Figure Description

[0036] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings;

[0037] Figure 1 This is a system block diagram of Embodiment 1 of the present invention;

[0038] Figure 2 This is a system block diagram of Embodiments 2 and 3 of the present invention;

[0039] Figure 3 This is a flowchart of the method in Embodiment 4 of the present invention. Detailed Implementation

[0040] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0041] Example 1: As Figure 1 As shown, the partial discharge monitoring and analysis system for cable terminals proposed in this invention includes a multi-mode signal coupling acquisition module, an adaptive signal conditioning module, a partial discharge characteristic intelligent analysis module, a risk quantification assessment module, a closed-loop feedback control module, and a partial discharge monitoring terminal.

[0042] The multimodal signal coupling acquisition module integrates a high-frequency current sensor (HFCT), an ultrasonic sensor (AE), and an ultra-high frequency electromagnetic wave sensor (UHF). It achieves phase-aligned acquisition of three-channel signals through a time-space synchronization unit and adopts an adaptive gain control algorithm to dynamically adjust the sensor sensitivity threshold according to the operating voltage of the cable terminal to avoid signal saturation or distortion. The acquired data is encoded by a multiplexer and transmitted to the adaptive signal conditioning module in the form of a digital stream.

[0043] After receiving the data, the adaptive signal conditioning module processes it, separating the partial discharge pulse from the background noise through a frequency band segmentation filter bank. A wavelet packet thresholding denoising algorithm is used to perform nonlinear filtering on the high-frequency components, preserving the abrupt leading-edge characteristics of the partial discharge pulse. Based on a phase analysis algorithm, the time-domain signal is mapped to the power frequency phase coordinate system to generate a phase-resolved partial discharge spectrum, which is then sent to the intelligent partial discharge feature analysis module. It should be noted that this phase-resolved partial discharge spectrum is presented in a two-dimensional matrix form, with the horizontal axis representing the power frequency phase (0°~360°) and the vertical axis representing the pulse amplitude. The pixel value represents the frequency of pulse occurrence under a specific phase-amplitude combination.

[0044] The intelligent partial discharge feature analysis module performs two-dimensional convolution kernel scanning on the phase-resolved partial discharge spectrum to extract feature parameters such as pulse amplitude distribution, phase concentration, and energy density gradient. It dynamically groups the feature vectors using an unsupervised clustering algorithm (such as the improved DBSCAN) to generate a partial discharge mode label library (each label corresponds to a typical discharge type and its development stage). Combined with historical data, it constructs a time-series correlation model (used to predict degradation trends) to identify discharge types (such as internal air gap discharge, corona discharge, and surface flashover discharge) and their development stages (such as nascent stage, development stage, and critical stage).

[0045] It should be noted that the feature parameter extraction process is as follows: Pulse Amplitude Distribution Feature (PAD): Statistically analyze the pulse frequency distribution along the vertical axis (amplitude direction), generate the amplitude probability density curve, and extract the peak position, half width at half maximum (FWHM), and skewness parameters to characterize the energy concentration of the partial discharge signal;

[0046] Phase Concentration Feature (PC): Calculates the phase concentration of pulse frequencies along the horizontal axis (phase direction). By calculating the standard deviation and root mean square phase difference of the pulse distribution, the phase synchronization of partial discharge is quantified. Energy Density Gradient Feature (EDG): Calculates the gradient amplitude of the PRPD spectrum based on the Sobel operator. Extracts the edge sharpness and texture complexity of the pulse cluster to reflect the differences in the physical characteristics of the partial discharge source.

[0047] The risk quantification assessment module calculates the risk index based on the partial discharge characteristic analysis results and uses a fuzzy logic reasoning engine. The risk index is a weighted synthesis of pulse repetition rate, energy accumulation and phase offset. It is mapped to four levels of "normal-attention-warning-emergency" through a three-dimensional risk matrix and sends the risk quantification assessment results to the partial discharge monitoring terminal and the closed-loop feedback control module.

[0048] Based on the risk quantification assessment results, the closed-loop feedback control module pushes corresponding alarm information to the partial discharge monitoring terminal through the IoT gateway, which is conducive to realizing closed-loop control of monitoring-analysis-disposal and triggering adaptive adjustment mechanisms, such as initiating local shielding of high-frequency interference source areas; dynamically adjusting the density of subsequent monitoring cycles; and generating digital reports containing fault location, type and recommended measures, which can improve operation and maintenance efficiency.

[0049] This invention's technical solution achieves synchronous acquisition and dynamic gain control of high-frequency current, ultrasonic waves, and ultra-high-frequency electromagnetic waves through a multi-modal signal coupling acquisition module, significantly improving the integrity of partial discharge signals under complex operating conditions. The adaptive signal conditioning module, combining frequency band segmentation and wavelet packet denoising techniques, effectively suppresses background noise while preserving pulse abrupt change characteristics, providing a high signal-to-noise ratio data foundation for subsequent analysis. The intelligent partial discharge feature analysis module employs convolutional kernel scanning and an improved clustering algorithm to achieve automatic classification of discharge modes and prediction of degradation trends, overcoming the limitations of traditional threshold judgment. The risk quantification assessment module constructs a three-dimensional risk matrix through fuzzy logic, transforming qualitative analysis into a quantifiable four-level early warning mechanism. The closed-loop feedback control module uses the Internet of Things to push early warning information and adaptively adjust, forming a complete closed loop of monitoring-analysis-handling. This improves the sensitivity of partial discharge detection, reduces the false alarm rate, and enables real-time assessment and intelligent operation and maintenance of cable terminal insulation status, thus helping to reduce potential power safety hazards.

[0050] Example 2: Figure 2 As shown, the difference between this embodiment and Embodiment 1 is that the partial discharge monitoring terminal is connected to the cable terminal monitoring module. The cable terminal monitoring module monitors the cable terminal, analyzes and judges its operational risk, and generates a low-risk or high-risk monitoring signal accordingly. This signal is then sent to the partial discharge monitoring terminal. When the monitoring terminal receives a high-risk signal, it issues a corresponding warning to remind regulatory personnel to repair or replace the cable terminal in a timely manner, ensuring subsequent performance and reducing operational risks. The specific analysis process of the cable terminal monitoring module is as follows:

[0051] The temperature, humidity, and pollution level (i.e., the concentration of dust particles in the environment) of the cable terminal and the vibration value (i.e., the vibration amplitude of the cable terminal) of the cable terminal are collected. The terminal operation quality value is calculated by weighted summation of the temperature, humidity, pollution level, and vibration value. That is, the temperature, humidity, pollution level, and vibration value are each assigned a corresponding preset weight coefficient, and the temperature, humidity, pollution level, and vibration value are multiplied by the corresponding preset weight coefficient. The sum of the four sets of product results is marked as the terminal operation quality value.

[0052] It should be noted that the higher the terminal deterioration value, the greater the overall risk of the current operating environment of the cable terminal, and the easier it is to cause aging and damage. The terminal deterioration value is compared with the preset terminal deterioration threshold. If the terminal deterioration value exceeds the preset terminal deterioration threshold, it indicates that the overall risk of the current operating environment of the cable terminal is relatively high, and it is easy to cause aging and damage. In this case, the cable terminal is judged to be in a state of easy aging and damage.

[0053] The total usage time of the cable terminal and the total time in the vulnerable state in the historical period are obtained and marked as terminal operating time value and terminal aging value, respectively. The single duration of the cable terminal in the vulnerable state is compared with the corresponding preset duration threshold. The number of times the single duration of the cable terminal in the vulnerable state in the historical period exceeds the corresponding preset duration threshold is marked as aging risk frequency value.

[0054] The terminal external condition value is obtained by weighted summation of terminal operating time value, terminal old damage value, and old damage risk frequency value. Specifically, the terminal operating time value, terminal old damage value, and old damage risk frequency value are each assigned a corresponding preset weight coefficient, and the terminal operating time value, terminal old damage value, and old damage risk frequency value are each multiplied by the corresponding preset weight coefficient. The sum of the three sets of product results is marked as the terminal external condition value.

[0055] It should be noted that the larger the value of the terminal external condition value, the more serious the potential performance aging of the cable terminal is, and the more likely it is to cause risk events such as partial discharge. The terminal external condition value is compared with the preset terminal external condition threshold. If the terminal external condition value exceeds the preset terminal external condition threshold, it indicates that the potential performance aging of the cable terminal is more serious and that it is more likely to cause risk events such as partial discharge. In this case, a high-risk monitoring signal is generated.

[0056] If the terminal external condition value does not exceed the preset terminal external condition threshold, the surface image of the cable terminal is collected, and the surface image of the cable terminal is used to identify defects (such as cracks, dents, protrusions, etc.). The identified defects are classified. If the data of various characteristic parameters of the corresponding defect (such as the length, depth, width, etc. of the crack) meet the preset safety requirements of the corresponding type of defect, it indicates that the safety hazard caused by the corresponding defect is small. Then the corresponding defect is marked as a low-impact object; otherwise, the corresponding defect is marked as a dangerous object.

[0057] If a dangerous object is present on the cable terminal, it indicates that the surface condition of the cable terminal is poor and the use risk is high, thus generating a high-risk monitoring signal. If no dangerous object is present on the cable terminal, several sub-regions are defined on the cable terminal. If a defect exists in a corresponding sub-region, the corresponding sub-region is marked as an abnormal region. The number of abnormal regions on the cable terminal is obtained and its ratio to the total number of sub-regions is calculated to obtain the abnormal region characteristic value. The abnormal region characteristic value is compared with a preset abnormal region characteristic threshold. If the abnormal region characteristic value exceeds the preset abnormal region characteristic threshold, it indicates that the surface condition of the cable terminal is poor and the use risk is high, thus generating a high-risk monitoring signal. If the abnormal region characteristic value does not exceed the preset abnormal region characteristic threshold, it indicates that the overall use risk of the cable terminal is low, thus generating a low-risk monitoring signal.

[0058] Example 3: Figure 2 As shown, the difference between this embodiment and Embodiment 1 and Embodiment 2 is that the cable terminal monitoring module is connected to the partial discharge retrospective analysis module. The cable terminal monitoring module sends the monitoring low-risk signal to the partial discharge retrospective analysis module. When the partial discharge retrospective analysis module receives the monitoring low-risk signal, it analyzes the degree of partial discharge risk of the cable terminal during the detection period.

[0059] By analyzing and generating signals indicating easy or difficult partial discharge monitoring, and sending these signals to the partial discharge monitoring terminal, the monitoring terminal issues a corresponding warning upon receiving a difficult partial discharge monitoring signal. This reminds monitoring personnel to promptly strengthen the subsequent monitoring and management of partial discharge at cable terminals, further ensuring power safety and demonstrating a high level of intelligence. The specific analysis process of the partial discharge retrospective analysis module is as follows:

[0060] The number of partial discharges occurring at the cable terminal during the detection period is obtained and marked as the partial discharge frequency. The partial discharge frequency is compared with a preset partial discharge frequency threshold. If the partial discharge frequency exceeds the preset partial discharge frequency threshold, it indicates that the partial discharge monitoring of the cable terminal during the detection period is difficult, and a partial discharge difficult monitoring signal is generated.

[0061] If the partial discharge frequency does not exceed the preset partial discharge frequency threshold, the duration of the corresponding partial discharge is marked as the partial discharge time value. All partial discharge time values ​​within the detection period are summed to obtain the partial discharge time measurement value. The partial discharge time value is compared with the preset partial discharge time threshold. The number of partial discharges within the detection period whose partial discharge time value exceeds the preset partial discharge time threshold is marked as the partial discharge critical frequency value.

[0062] The partial discharge retrospective value is obtained by weighted summation of partial discharge frequency, partial discharge time measurement and partial discharge danger frequency value. Specifically, the partial discharge frequency, partial discharge time measurement and partial discharge danger frequency value are assigned corresponding preset weight coefficients, and the partial discharge frequency, partial discharge time measurement and partial discharge danger frequency value are multiplied by the corresponding preset weight coefficients. The sum of the three sets of product results is marked as the partial discharge retrospective value.

[0063] It should be noted that the larger the partial discharge backtracking value, the more serious the partial discharge hazard at the cable terminal, and the more necessary it is to strengthen the monitoring and management of partial discharge at the cable terminal in the future. The partial discharge backtracking value is compared with the preset partial discharge backtracking threshold. If the partial discharge backtracking value exceeds the preset threshold, it indicates that the partial discharge hazard at the cable terminal is relatively serious, and it is necessary to strengthen the monitoring and management of partial discharge at the cable terminal in the future, thus generating a partial discharge difficult to monitor signal. If the partial discharge backtracking value does not exceed the preset threshold, it indicates that the partial discharge hazard at the cable terminal is not serious, thus generating a partial discharge easy to monitor signal.

[0064] Example 4: Figure 3 As shown, the difference between this embodiment and Embodiments 1, 2, and 3 is that the partial discharge monitoring and analysis method for cable terminals proposed in this invention includes the following steps:

[0065] Step 1: Collect data from the cable terminal using a high-frequency current sensor, an ultrasonic sensor, and an ultra-high frequency electromagnetic wave sensor.

[0066] Step 2: Receive and process the data to generate a phase-resolved partial discharge spectrum;

[0067] Step 3: Analyze the partial discharge spectrum based on the phase-resolved partial discharge spectrum and output the partial discharge characteristic analysis results;

[0068] Step 4: Conduct risk quantification and assessment analysis based on the partial discharge characteristic analysis results;

[0069] Step 5: Based on the risk quantification assessment results, push the corresponding alarm information to the local emission monitoring terminal to trigger the adaptive adjustment mechanism.

[0070] The working principle of this invention is as follows: During use, five modules work collaboratively—multi-modal signal coupling acquisition, adaptive signal conditioning, intelligent analysis of partial discharge characteristics, risk quantification assessment, and closed-loop feedback control—to achieve comprehensive and accurate monitoring and intelligent analysis of partial discharge phenomena in cable terminals. This provides strong technical support for the intelligent operation and maintenance of cable terminals. Furthermore, the cable terminal monitoring module monitors the cable terminal and assesses its operational risks. When a high-risk monitoring signal is generated, the cable terminal is repaired or replaced promptly to ensure subsequent performance and reduce operational risks. When a low-risk monitoring signal is generated, the partial discharge retrospective analysis module analyzes the degree of partial discharge risk in the cable terminal during the detection period. When an easily monitored partial discharge signal is generated, subsequent monitoring and management of partial discharge in the cable terminal is strengthened, further ensuring power safety. This invention boasts a high level of intelligence and low monitoring difficulty.

[0071] In this invention, the threshold, preset value, or preset range settings are for result comparison and analysis to determine whether the result is good or bad. The magnitude of these values ​​is determined by a combination of large-scale model analysis of sample data and human experience, and can also be appropriately adjusted based on seasonal or common-sense influence conditions. Similarly, the preset weight coefficients and influence factors are assigned specific values ​​based on the magnitude of each parameter's influence on the result, ultimately reflecting the impact on the result. These settings are also determined by a combination of large-scale model analysis of sample data and human experience, and can also be appropriately adjusted based on seasonal or common-sense influence conditions.

[0072] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to any specific implementation. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, enabling those skilled in the art to better understand and utilize it. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. A partial discharge monitoring and analysis system adapted for cable terminals during operation, characterized in that, It includes a multimodal signal coupling acquisition module, an adaptive signal conditioning module, a partial discharge characteristic intelligent analysis module, a risk quantification assessment module, and a partial discharge monitoring terminal. The multimodal signal coupling acquisition module integrates a high-frequency current sensor, an ultrasonic sensor, and an ultra-high frequency electromagnetic wave sensor for data acquisition. The acquired data is transmitted to the adaptive signal conditioning module in the form of a digital stream. After receiving the data, the adaptive signal conditioning module processes it to generate a phase-resolved partial discharge spectrum and sends it to the partial discharge characteristic intelligent analysis module. The partial discharge feature intelligent analysis module performs two-dimensional convolutional kernel scanning on the phase-resolved partial discharge spectrum, dynamically groups the feature vectors using an unsupervised clustering algorithm, generates a partial discharge mode label library, and constructs a time-series correlation model based on historical data to identify discharge types and their development stages. The risk quantification assessment module calculates the risk index based on the partial discharge feature analysis results using a fuzzy logic inference engine, maps it to a four-level state of "normal-attention-warning-emergency" through a three-dimensional risk matrix, and sends the risk quantification assessment results to the partial discharge regulatory terminal. The partial discharge monitoring terminal is connected to the cable terminal monitoring module. The cable terminal monitoring module monitors the cable terminal, analyzes and judges its operational risk, and generates a low-risk or high-risk monitoring signal accordingly. The low-risk or high-risk monitoring signal is then sent to the partial discharge monitoring terminal. When the partial discharge monitoring terminal receives the high-risk monitoring signal, it issues a corresponding warning. The specific analysis process of the cable terminal monitoring module includes: The temperature, humidity, and pollution levels of the environment where the cable terminal is located, as well as the vibration value of the cable terminal, are collected. The temperature, humidity, pollution level, and vibration value are weighted and summed to calculate the terminal deterioration value. The terminal deterioration value is compared with the preset terminal deterioration threshold. If the terminal deterioration value exceeds the preset terminal deterioration threshold, the cable terminal is judged to be in a state of easy aging. The total usage time of the cable terminal and the total time it was in a vulnerable state in historical periods are obtained and marked as terminal operating time value and terminal aging value, respectively. The number of times the single duration of the cable terminal in a vulnerable state in historical periods exceeded the corresponding preset duration threshold is marked as aging risk frequency value. The terminal external condition value is calculated by weighted summation of terminal operating time value, terminal aging value and aging risk frequency value. The terminal external condition value is compared with the preset terminal external condition threshold. If the terminal external condition value exceeds the preset terminal external condition threshold, a high-risk monitoring signal is generated. If the terminal external condition value does not exceed the preset terminal external condition threshold, the surface image of the cable terminal is collected, the surface image of the cable terminal is used to identify defects, and the identified defects are classified. If the data of each characteristic parameter of the corresponding defect meets the preset safety requirements of the corresponding type of defect, the corresponding defect is marked as a low-impact object; otherwise, the corresponding defect is marked as a dangerous object. If a dangerous object is present on the cable terminal, a high-risk monitoring signal is generated. If no dangerous object is present on the cable terminal, several sub-regions are defined on the cable terminal. If a defect exists in a corresponding sub-region, the corresponding sub-region is marked as an abnormal region. The number of abnormal regions on the cable terminal is obtained and its ratio to the total number of sub-regions is calculated to obtain the abnormal region characteristic value. The abnormal region characteristic value is compared with a preset abnormal region characteristic threshold. If the abnormal region characteristic value exceeds the preset abnormal region characteristic threshold, a high-risk monitoring signal is generated. If the abnormal region characteristic value does not exceed the preset abnormal region characteristic threshold, a low-risk monitoring signal is generated. The cable terminal monitoring module is connected to the partial discharge retrospective analysis module. The cable terminal monitoring module sends the monitoring low-risk signal to the partial discharge retrospective analysis module. When the partial discharge retrospective analysis module receives the monitoring low-risk signal, it analyzes the degree of partial discharge risk of the cable terminal during the detection period. Through analysis, it generates a partial discharge easy-to-monitor signal or a partial discharge difficult-to-monitor signal, and sends the partial discharge easy-to-monitor signal or a partial discharge difficult-to-monitor signal to the partial discharge monitoring end. When the partial discharge monitoring end receives the partial discharge difficult-to-monitor signal, it issues a corresponding warning. The specific analysis process of the partial discharge retrospective analysis module includes: The number of partial discharges occurring at the cable terminal during the detection period is obtained and marked as the partial discharge frequency. The partial discharge frequency is compared with a preset partial discharge frequency threshold. If the partial discharge frequency exceeds the preset partial discharge frequency threshold, a partial discharge difficult monitoring signal is generated. If the partial discharge frequency does not exceed the preset partial discharge frequency threshold, the duration of the corresponding partial discharge is marked as the partial discharge time value. All partial discharge time values ​​during the detection period are summed to obtain the partial discharge time measurement value. The number of partial discharges during the detection period whose partial discharge time value exceeds the preset partial discharge time threshold is marked as the partial discharge danger frequency value. The partial discharge (PD) backtracking value is calculated by weighting and summing the PD frequency, PD time measurement value, and PD danger frequency value. The PD backtracking value is then compared with a preset PD backtracking threshold. If the PD backtracking value exceeds the preset PD backtracking threshold, a PD difficult-to-monitor signal is generated; if the PD backtracking value does not exceed the preset PD backtracking threshold, a PD easy-to-monitor signal is generated.

2. The partial discharge monitoring and analysis system adapted to cable terminals during operation according to claim 1, characterized in that, The multimodal signal coupling acquisition module achieves phase-aligned acquisition of three-channel signals through a spatiotemporal synchronization unit, and adopts an adaptive gain control algorithm to dynamically adjust the sensor sensitivity threshold according to the operating voltage of the cable terminal.

3. The partial discharge monitoring and analysis system and method adapted to cable terminals during operation, as described in claim 1, is characterized in that... The processing steps of the adaptive signal conditioning module include: The partial discharge pulse and background noise are separated by a frequency band segmentation filter bank. The high-frequency components are nonlinearly filtered by a wavelet packet threshold denoising algorithm to preserve the steep leading edge characteristics of the partial discharge pulse. The time-domain signal is mapped to the power frequency phase coordinate system based on the phase analysis algorithm to generate a phase-resolved partial discharge spectrum.

4. The partial discharge monitoring and analysis system adapted to cable terminals during operation according to claim 1, characterized in that, The risk quantification assessment module communicates with the closed-loop feedback control module. The risk quantification assessment module sends the risk quantification assessment results to the closed-loop feedback control module. Based on the risk quantification assessment results, the closed-loop feedback control module pushes the corresponding alarm information to the partial discharge monitoring terminal through the IoT gateway and triggers the adaptive adjustment mechanism.

5. The partial discharge monitoring and analysis system adapted to cable terminals during operation according to claim 4, characterized in that, The adaptive adjustment mechanism includes: initiating local shielding of high-frequency interference source areas; dynamically adjusting the density of subsequent monitoring cycles; and generating digital reports containing fault location, type, and recommended measures.

6. A method for operating a partial discharge monitoring and analysis system adapted to cable terminals as described in claim 1, characterized in that, Includes the following steps: Step 1: Collect data from the cable terminals; Step 2: Receive and process the data to generate a phase-resolved partial discharge spectrum; Step 3: Analyze the partial discharge spectrum based on the phase-resolved partial discharge spectrum and output the partial discharge characteristic analysis results; Step 4: Conduct risk quantification and assessment analysis based on the partial discharge characteristic analysis results; Step 5: Push the corresponding alarm information to the local monitoring terminal to trigger the adaptive adjustment mechanism.

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