Capacitor lead wire condition monitoring system based on optical fiber sensing

Abstract

The present invention discloses a capacitor lead wire status monitoring system based on optical fiber sensing, which relates to the technical field of capacitor monitoring. The system comprises: a strong impact environmental index determination module for analyzing and determining strong impact environmental indicators and matching optical fiber sensor types; an optical fiber sensing module acquisition module for sequentially deploying optical fiber sensing equipment; a lead wire status monitoring module for performing real-time status monitoring of the target capacitor lead wire; a working environment monitoring module for acquiring real-time working environment data; and a lead wire status warning module for predicting status trends and providing lead wire status warnings. The system solves the technical problems in the prior art of capacitor lead wire monitoring being unrealistic and unable to effectively cope with the impact of complex working environments, resulting in poor capacitor fault warning capabilities and safety. The system implements real-time, high-precision capacitor lead wire status monitoring, achieving the technical effect of improving capacitor fault warning capabilities and operational safety.

Description

Technical Field

[0001] The present application relates to the technical field related to capacitor monitoring, and in particular to a capacitor lead wire status monitoring system based on optical fiber sensing. Background Art

[0002] Capacitors, as key electrical components in high-voltage power systems, are commonly used for filtering, power factor correction, and reactive power compensation. They are typically connected to other electrical equipment via lead wires, which transmit the capacitor's electrical signals or energy to other parts. These lead wires are often subject to various stress factors, such as current, temperature, and vibration, and their condition is crucial to the safe operation of the equipment. However, traditional methods, which rely heavily on electrical testing, lack real-time monitoring capabilities and exhibit slow response speeds, failing to meet the demands of modern, intelligent equipment for real-time monitoring of capacitor status. Furthermore, underground power facilities, such as underground substations or underground power tunnels, can be subject to problems such as poor ventilation and high humidity, which can affect the sensor's contact and transmission signal. This, in turn, impacts the precise, real-time monitoring of the capacitor lead wire status, making it impossible to accurately predict equipment failures.

[0003] Therefore, in the current related technologies, there are technical problems such as the capacitor lead wire monitoring is not real-time and cannot effectively cope with the influence of complex working environment, resulting in poor capacitor fault warning capability and safety. Summary of the Invention

[0004] This application solves the technical problems in the prior art of capacitor lead wire status monitoring, such as the non-real-time monitoring of capacitor lead wires and the inability to effectively cope with the influence of complex working environments, resulting in poor capacitor fault warning capabilities and safety, by providing a capacitor lead wire status monitoring system based on optical fiber sensing. It realizes real-time and high-precision capacitor lead wire status monitoring, achieving the technical effect of improving capacitor fault warning capabilities and operational safety.

[0005] The present application provides a capacitor lead wire status monitoring system based on optical fiber sensing, the system comprising: a strong impact environmental index determination module, for analyzing and determining the strong impact environmental index based on the basic environmental attributes of the target capacitor's workplace, and matching the highly adaptable optical fiber sensor type according to the strong impact environmental index; an optical fiber sensing module acquisition module, for extracting key monitoring points of the target capacitor lead wire, and sequentially laying out the optical fiber sensing equipment according to the optical fiber sensor type to obtain the optical fiber sensing module, and at the same time, laying out the environmental monitoring module according to the spatial structure layout of the target capacitor's workplace; a lead wire status monitoring module, for using the optical fiber sensing module to perform real-time status monitoring of the target capacitor lead wire and obtain real-time status data of the lead wire; a working environment monitoring module, for using the environmental monitoring module to perform real-time working environment monitoring and obtain real-time working environment data; a lead wire status early warning module, for performing real-time status evaluation based on the real-time status data of the lead wire, and extracting the strong impact environmental index value in combination with the real-time working environment data to predict the status trend, and issuing a lead wire status early warning based on the prediction result.

[0006] In a possible implementation, the fiber optic sensing-based capacitor lead wire status monitoring system further performs the following processing: obtaining basic environmental attributes of the workplace of the target capacitor, wherein the basic environmental attributes include at least temperature, humidity, pH, electromagnetic interference, and vibration interference; based on the basic environmental attributes, performing monitoring interference analysis and lead wire performance impact analysis respectively, and performing fusion analysis and sorting to generate an environmental impact indicator sequence; based on the environmental impact indicator sequence, extracting strongly influencing environmental indicators, and matching highly adaptable fiber optic sensor types according to the types of strongly influencing environmental indicators.

[0007] In a possible implementation, the fiber optic sensing-based capacitor lead wire status monitoring system further performs the following processing: performing centralized analysis based on the fault record data of the target capacitor lead wire, and extracting the key monitoring points of the target capacitor lead wire in combination with the conventional weak point locations; obtaining the environmental change interval of the target location; and configuring daily operation equipment and emergency activation equipment for each fiber optic sensor type based on the environmental change interval, and deploying them at the corresponding key monitoring nodes to obtain the fiber optic sensing module.

[0008] In a possible implementation, the capacitor lead wire status monitoring system based on optical fiber sensing also performs the following processing: the tracking and monitoring data includes: receiving the real-time status data of the lead wire, extracting multiple lead wire status indicators to perform single indicator status evaluation and comprehensive indicator status evaluation respectively, and generating real-time status evaluation results; performing abnormality judgment based on the real-time status evaluation results, if it is judged to be abnormal, directly performing a status warning; if it is judged to be normal, combining the real-time working environment data, extracting the value of the strong impact environment indicator to predict the status trend.

[0009] In a possible implementation, the capacitor lead wire status monitoring system based on optical fiber sensing also performs the following processing: based on the real-time working environment data, extracting the strong impact environment indicator value, the strong impact environment indicator value includes multiple strong impact environment indicator sequences, including temperature change sequence, humidity change sequence, pH change sequence, electromagnetic interference change sequence and vibration interference change sequence; according to the multiple strong impact environment indicator sequences, combined with the real-time status data of the lead wire, the lead wire status trend prediction and risk assessment are performed to generate a lead wire risk assessment result.

[0010] In a possible implementation, the capacitor lead wire status monitoring system based on optical fiber sensing also performs the following processing: using the multiple strong-influence environmental indicator sequences to predict environmental trend changes respectively, and generating multiple environmental impact factors according to the change prediction direction, the environmental impact factors include positive impact factors and negative impact factors; extracting multiple lead wire status indicator values ​​based on the lead wire real-time status data, constructing a basic decision matrix after normalization processing, and calibrating the basic decision matrix through the multiple environmental impact factors to generate a risk decision matrix; defining ideal solutions and negative ideal solutions for the multiple key monitoring nodes respectively; based on the risk decision matrix, combining the ideal solution and the negative ideal solution, performing lead wire status risk assessment to generate a lead wire risk assessment result.

[0011] In a possible implementation, the fiber optic sensing-based capacitor lead wire state monitoring system further performs the following processing: for each key monitoring point, extracting multiple sample lead wire state index values ​​based on the risk decision matrix; based on the multiple sample lead wire state index values, respectively calculating their relative distances to the ideal solution and the negative ideal solution, and calculating the relative proximity of each key monitoring point based on the relative distances; combining the relative proximity of each key monitoring point, comprehensively evaluating the overall risk of the lead wire, and generating a lead wire risk assessment result.

[0012] In a possible implementation, the capacitor lead wire status monitoring system based on optical fiber sensing further performs the following processing: constructing a basic decision matrix, which is expressed as:

[0013] ;

[0014] Among them, m is the number of key monitoring points, n is the number of monitoring indicators, Indicates the value of the mth monitoring point on the nth indicator.

[0015] The fiber-optic sensing-based capacitor lead wire status monitoring system proposed in this application includes a strong environmental index determination module for analyzing and determining strong environmental indexes and matching fiber-optic sensor types; a fiber-optic sensing module acquisition module for sequentially deploying fiber-optic sensing equipment; a lead wire status monitoring module for real-time status monitoring of the target capacitor lead wire; a working environment monitoring module for acquiring real-time working environment data; and a lead wire status warning module for status trend prediction and lead wire status warning. This solves the technical problems in the prior art of capacitor lead wire monitoring being unrealistic and unable to effectively cope with the impact of complex working environments, resulting in poor capacitor fault warning capabilities and safety. This system implements real-time, high-precision capacitor lead wire status monitoring, achieving the technical effect of improving capacitor fault warning capabilities and operational safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] To more clearly illustrate the technical solutions of the embodiments of the present disclosure, the accompanying drawings of the embodiments of the present disclosure are briefly introduced below. Flowcharts are used in this application to illustrate the operations performed by the systems according to the embodiments of the present application. It should be understood that the preceding or following operations are not necessarily performed in precise order. Instead, various steps may be processed in reverse order or simultaneously as needed. Furthermore, other operations may be added to these processes, or one or more operations may be removed from these processes.

[0017] Figure 1 A schematic diagram of the structure of a capacitor lead wire status monitoring system based on optical fiber sensing provided in an embodiment of the present application;

[0018] Figure 2 This is a schematic diagram of the execution flow of the strong impact environment indicator determination module in the capacitor lead wire status monitoring system based on optical fiber sensing provided in an embodiment of the present application.

[0019] Explanation of the accompanying reference numerals: strong impact environment index determination module 10, optical fiber sensing module acquisition module 20, lead-out line status monitoring module 30, working environment monitoring module 40, lead-out line status early warning module 50. DETAILED DESCRIPTION

[0020] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below.

[0021] In order to make the purpose, technical solutions and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings. The described embodiments should not be regarded as limiting this application. All other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0022] In the following description, reference is made to “some embodiments”, which describes a subset of all possible embodiments, but it will be understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict, and the terms “first\second” involved are merely used to distinguish similar objects and do not represent a specific ordering of the objects. The terms “including” and “having” and any variations are intended to cover non-exclusive inclusions. For example, a process, system, product, or server that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or modules that are not clearly listed or that are inherent to these processes, products, or devices. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this application belongs. The terms used herein are for the purpose of describing the embodiments of this application only.

[0023] The embodiment of the present application provides a capacitor lead wire status monitoring system based on optical fiber sensing, such as Figure 1 As shown, the system includes:

[0024] The strong impact environment index determination module 10 is used to analyze and determine the strong impact environment index based on the basic environmental attributes of the workplace of the target capacitor, and match the optical fiber sensor type with high adaptability according to the strong impact environment index.

[0025] Preferably, the target capacitor's operating environment is analyzed to identify basic environmental parameters that may affect the condition of the capacitor's lead wires, such as temperature, humidity, electromagnetic interference, vibration, dust concentration, and gas composition. This is followed by the identification of highly influential environmental indicators. Specifically, from these basic environmental parameters, the indicators with the greatest impact on the capacitor lead wire condition and monitoring accuracy (i.e., highly influential environmental indicators) are selected. For example, in a high-temperature environment, temperature may be the primary influencing factor, while in a chemical plant environment, gas corrosion may be a key indicator. Finally, based on the identified highly influential environmental indicators, fiber optic sensors suitable for specific environmental conditions are selected. For example, for high-temperature environments, high-temperature-resistant fiber optic sensors such as fiber Bragg grating sensors (FBGs) are selected; for wide-range temperature and vibration monitoring, distributed optical fiber sensors (DTS / DASs) are selected; and for temperature-sensitive environmental temperature monitoring, Raman scattering fiber optic sensors are selected. Through analysis and matching, the most appropriate sensor type is selected for each environment, ensuring accurate and reliable monitoring.

[0026] The optical fiber sensing module acquisition module 20 is used to extract the key monitoring points of the lead wires of the target capacitor, and arrange the optical fiber sensing equipment in sequence according to the optical fiber sensor type to obtain the optical fiber sensing module. At the same time, the environmental monitoring module is arranged according to the spatial structure layout of the workplace of the target capacitor.

[0027] Preferably, the areas on the capacitor lead wires that are most prone to problems or are critical to the operation of the equipment are extracted as key monitoring points, which may include connection parts (the connection between the lead wire and the capacitor body), bending or turning points (stress concentration areas of the lead wire), high temperature areas or areas with strong electromagnetic interference, and terminal connection points (the ends of the loads connected are prone to loosening or oxidation due to vibration or temperature changes). According to the key monitoring points, the sensors are placed in the areas that need to be monitored most to ensure that the most representative and critical capacitor lead wire status data can be collected; then the monitoring points are arranged according to the selected fiber optic sensor type (such as FBG or distributed fiber optic sensor), that is, the sensors are applied, wrapped or fixed to the predetermined position according to the physical structure of the lead wire to ensure the sensor Optical fiber can cover all key monitoring points, forming a fiber optic sensing module. A fiber optic sensing module refers to a monitoring unit consisting of deployed fiber optic sensors and their supporting equipment (such as signal demodulators and data acquisition equipment). This module can accurately and real-timely collect data on the status of capacitor lead wires. Furthermore, environmental monitoring equipment (modules that monitor the working environment parameters of the capacitors) is rationally arranged based on the spatial structure of the target capacitor's workplace (e.g., indoors, outdoors, equipment density, etc.). These include temperature sensors (e.g., monitoring corners with poor heat dissipation), humidity sensors, electromagnetic field monitoring equipment (in areas near capacitors or lead wires to monitor electromagnetic interference), and vibration monitoring sensors (installed on the foundation or capacitor body near the equipment to monitor the effects of external mechanical vibration). By combining spatial structure design with layout, the environmental monitoring module can comprehensively collect environmental data from the workplace, ensuring the safety and stability of the target capacitor lead wires and their working environment.

[0028] The lead wire status monitoring module 30 is used to use the optical fiber sensing module to perform real-time status monitoring of the lead wires of the target capacitor and obtain real-time status data of the lead wires.

[0029] Preferably, the real-time status monitoring of the target capacitor lead wire is performed through the optical fiber sensing module, which may include but is not limited to temperature status, stress / tension status, vibration status and current overload status. Specifically, the optical fiber sensing module converts physical quantities (such as temperature, stress, vibration) into optical signals through optical fiber sensors, and generates real-time status data of the lead wire after demodulation and processing. Specifically, the optical fiber sensor is placed at a key position of the capacitor lead wire to continuously collect real-time information of temperature, vibration or stress. The collected data is transmitted to the demodulation device through the optical fiber sensor, and the signal transmission is completed in a high-speed, low-interference manner. The fiber demodulator converts optical signals into electrical signals, which are analyzed and organized in the data processing unit to generate clear, usable status data. This includes temperature status (monitoring the real-time temperature of the lead wire to prevent insulation aging or melting due to excessive temperature rise), stress / tension status (detecting whether the lead wire is subjected to excessive mechanical tension or stress to avoid breakage or connection failure), vibration status (monitoring whether the lead wire is subjected to abnormal vibration during operation to promptly detect external mechanical shock or environmental interference), and current overload status (indirectly reflected through temperature changes. When the lead wire current is overloaded, it will cause overheating, and the fiber optic sensor can promptly detect it through temperature measurement). Through real-time status data analysis, not only can abnormal problems with the lead wire be identified, but potential faults can also be predicted based on data trends, thereby ensuring the safe and stable operation of power equipment.

[0030] The working environment monitoring module 40 is used to use the environmental monitoring module to perform real-time working environment monitoring and obtain real-time working environment data.

[0031] Preferably, an environmental monitoring module (including environmental sensors, data acquisition units, communication modules and data analysis modules) is used to perform real-time working environment monitoring, that is, to obtain real-time workplace environmental data of the target capacitor to help evaluate the working status of the capacitor under specific environmental conditions and predict the state changes of its lead wires. The real-time working environment data obtained may include temperature data, humidity data, pH data, electromagnetic interference data, gas composition data, vibration data, air pressure data, etc., which reflects the changes in the environment in which the capacitor is located, and is combined with the capacitor status data to provide support for capacitor status assessment, fault prediction and risk warning, thereby ensuring the stability and safety of the power system.

[0032] The lead wire status warning module 50 is used to perform real-time status assessment based on the lead wire real-time status data, and extract the strong impact environment indicator value to predict the status trend in combination with the real-time working environment data, and issue a lead wire status warning based on the prediction result.

[0033] Preferably, a real-time status assessment is performed based on the real-time status data of the lead wire, that is, calculation and evaluation are performed through the collected sensor data (such as temperature exceeding the limit, excessive stress, vibration amplitude, etc.) to determine whether the lead wire is in a safe working state. For example, if the temperature exceeds the safety threshold, it means that the lead wire may be overloaded or at risk of failure; if the stress is too large, it may cause the capacitor lead wire to be damaged or aged; then combined with the real-time working environment data, the values ​​of strong environmental indicators are extracted to predict the status trend. Specifically, the real-time status data of the lead wire (such as temperature, stress) and the environmental monitoring data (such as temperature, humidity, electromagnetic interference, etc.) are combined to analyze how these environmental factors affect the health status of the lead wire, and extract the environmental indicators that have the greatest impact on the lead wire status. For example, environmental factors such as high temperature, high humidity, and strong electromagnetic interference may accelerate the aging or corrosion of the capacitor lead wire, thereby increasing the risk of failure. Based on machine learning and data Mining and other methods are used to conduct time series analysis on historical data such as temperature, stress, and vibration of the lead wires, identify the correlation between the status and environmental factors, build a prediction model to determine the impact of environmental changes on the lead wires, and predict the future state change trend of the lead wire status based on real-time status and environmental data. As a prediction result, for example, if the current temperature continues to rise and the humidity gradually increases, it may be predicted that the lead wire will enter an overheating state or the insulation performance will deteriorate. Finally, a lead wire status warning is issued based on the prediction results. That is, when the prediction results show that the status of the lead wire tends to an unsafe range, for example, parameters such as temperature, stress, and vibration exceed the preset safety thresholds, and the environmental conditions (such as high temperature or high humidity) show a significant negative correlation with the health status of the lead wire, the trend prediction model shows that the equipment will enter a fault state in a short period of time, and an early warning is automatically triggered, thereby effectively preventing the failure of the capacitor lead wire and ensuring the stability and safety of the equipment.

[0034] The fiber-optic sensing-based capacitor lead wire status monitoring system according to an embodiment of the present invention addresses the technical issues of existing technologies, such as the lack of real-time capacitor lead wire monitoring and the inability to effectively address the impact of complex operating environments, resulting in poor capacitor fault warning capabilities and safety. This system implements real-time, high-precision capacitor lead wire status monitoring, achieving the technical effect of improving capacitor fault warning capabilities and operational safety. The fiber-optic sensing-based capacitor lead wire status monitoring system includes a module 10 for determining highly influential environmental indicators, a module 20 for obtaining a fiber-optic sensing module, a lead wire status monitoring module 30, a working environment monitoring module 40, and a lead wire status warning module 50.

[0035] The specific configuration of the strong impact environment index determination module 10 will be described in detail below. Figure 2As shown, the strong impact environment indicator determination module 10 may further include: obtaining basic environmental attributes of the workplace of the target capacitor, wherein the basic environmental attributes include at least temperature, humidity, pH, electromagnetic interference and vibration interference; based on the basic environmental attributes, performing monitoring interference analysis and lead wire performance impact analysis respectively, and performing fusion analysis and sorting to generate an environmental impact indicator sequence; based on the environmental impact indicator sequence, extracting strong impact environment indicators, and matching highly adaptable optical fiber sensor types according to the strong impact environment indicator types.

[0036] Preferably, the basic environmental properties of the workplace of the target capacitor are obtained, that is, the environmental parameters in the capacitor workplace that affect the performance of the capacitor and its lead wires, mainly including temperature (high temperature accelerates material aging, and low temperature may affect the responsiveness and stability of the equipment), humidity (excessive humidity may cause condensation or corrosion on the lead wires and capacitor surfaces), pH (different pH values ​​may corrode the material, which may accelerate the aging of the lead wires and the corrosion of the capacitor), electromagnetic interference (affecting the stability and accuracy of the sensor signal, a strong electromagnetic field may affect the optical fiber sensor signal, affecting the monitoring results) and vibration interference (mechanical equipment, earthquakes or external vibrations may have a physical impact on the capacitor and lead wires, causing fatigue or mechanical damage to the material).

[0037] Preferably, monitoring interference analysis and lead wire performance impact analysis are performed separately based on basic environmental attributes and then fused and sorted. The monitoring interference analysis is to evaluate how various environmental factors affect the monitoring accuracy and stability of the optical fiber sensor, including electromagnetic interference analysis, which evaluates how electromagnetic interference (EMI) in the environment affects the signal transmission and data acquisition accuracy of the optical fiber sensor; the vibration interference analysis is to evaluate the impact of vibration in the working environment on the optical fiber sensor; the lead wire performance impact analysis is to analyze how environmental factors affect the performance of the capacitor lead wire, including temperature and humidity analysis, pH analysis, vibration analysis, etc. Then, based on the monitoring interference analysis results and the lead wire performance impact analysis results, a fusion analysis is performed to combine all environmental factors to evaluate their comprehensive impact on the lead wire, and these environmental factors are sorted according to the degree of impact of different environmental factors on the lead wire status and sensor performance to generate an environmental impact index sequence. Finally, based on the environmental impact index sequence, the environmental factors with the greatest impact on the lead wire status, namely the strong impact environmental indicators, are extracted. Based on the extracted strong impact environmental indicators, a highly adaptable optical fiber sensor type is selected for each environmental factor to ensure that the sensor can perform optimally in a specific working environment and provide accurate and reliable monitoring data.

[0038] The specific configuration of the fiber optic sensing module acquisition module 20 will be described in detail below. The fiber optic sensing module acquisition module 20 may further include: performing centralized analysis based on fault record data of the target capacitor lead wires, and extracting key monitoring points of the target capacitor lead wires in combination with conventional weak point locations; obtaining the environmental change interval of the target location; and configuring daily operation equipment and emergency activation equipment for each fiber optic sensor type based on the environmental change interval, and deploying them at corresponding key monitoring nodes to obtain the fiber optic sensing module.

[0039] Preferably, the fault record data of the target capacitor lead wire (fault type, fault time, cause, fault location, etc. that occurred during the operation of the equipment) is obtained from the historical data, and centralized analysis is performed to identify common failure modes of the capacitor lead wire, such as overheating, mechanical damage, aging, poor contact, etc. Based on the fault data analysis and the common weak point locations of the lead wire, key monitoring points are extracted as the key monitoring points of the target capacitor lead wire, such as the connection end, corner, vibration-prone area or part with high temperature of the capacitor lead wire; based on the environmental data of the workplace where the capacitor lead wire is located (such as temperature, humidity, electromagnetic Interference, vibration, etc.), obtain the range (interval) of changes in environmental factors within a certain period, that is, the environmental change interval; then, according to the characteristics of the target environment and the adaptability of the sensor, the fiber optic sensor equipment for daily operation is configured. Different types of fiber optic sensors are suitable for different environmental change intervals. For situations where extreme environmental conditions or sudden failures may occur, emergency fiber optic sensor equipment is configured. Finally, according to the extracted key monitoring points, fiber optic sensors are deployed at weak parts or key areas of the lead wires of the target capacitor. All deployed fiber optic sensor equipment is connected through an appropriate network to form a fiber optic sensing module for real-time monitoring of the status of the lead wires.

[0040] The specific configuration of the lead wire status warning module 50 will be described in detail below. The lead wire status warning module 50 may further include: receiving the real-time status data of the lead wire, extracting multiple lead wire status indicators, performing single indicator status assessment and comprehensive indicator status assessment, and generating a real-time status assessment result; performing anomaly determination based on the real-time status assessment result, and directly issuing a status warning if an anomaly is determined; if no anomaly is determined, extracting the values ​​of highly influential environmental indicators in combination with the real-time working environment data to predict status trends.

[0041] Preferably, the real-time status data of the lead wire is received and multiple lead wire status indicators are extracted, and single indicator status evaluation and comprehensive indicator status evaluation are performed respectively. Specifically, single indicator status evaluation refers to evaluating each status indicator (temperature, stress, vibration, etc.) separately to determine whether it is within the normal range, that is, comparing the real-time data with the preset safety threshold, such as whether the temperature exceeds the specified working range, whether the stress exceeds the elastic limit of the material, analyzing the short-term trend (such as a sudden increase in temperature or increased vibration), and if a single indicator exceeds the normal range, it is marked as abnormal; comprehensive indicator status evaluation refers to evaluating the overall health status of the lead wire through comprehensive analysis of multiple indicators, such as assigning weights to different indicators, comprehensively calculating the health index, and then combining the two evaluation results to generate a real-time status evaluation result; then, an abnormality judgment is made based on the real-time status evaluation result. If a single indicator or comprehensive evaluation result is exceeded, the health status of the lead wire is abnormal. If the evaluation results show an abnormality, a status warning will be triggered directly. If all indicators are within the normal range or the overall health status is good, the real-time working environment data will be combined to extract the values ​​of strong-impact environmental indicators to predict the status trend. Specifically, the real-time working environment data (such as temperature, humidity, electromagnetic interference, and vibration) will be combined with the lead-out line status data to analyze whether environmental factors may cause status changes. The environmental factors that have the greatest impact on the lead-out line (strong-impact environmental indicators) will be extracted from the environmental data, and a time series model will be constructed to analyze the data change trend. That is, based on the current status of the lead-out line and the environmental impact indicators, its future health status will be predicted. If the trend shows normal, continue monitoring and no emergency measures are needed. If the trend shows potential abnormalities, an early warning will be issued to prompt the impending problems, thereby improving the accuracy and foresight of monitoring and improving the safety and reliability of power equipment operation.

[0042] The specific configuration of the lead wire status warning module 50 will be described in detail below. The lead wire status warning module 50 may further include: extracting a strong impact environment indicator value based on the real-time working environment data, wherein the strong impact environment indicator value includes multiple strong impact environment indicator sequences, including a temperature change sequence, a humidity change sequence, a pH change sequence, an electromagnetic interference change sequence, and a vibration interference change sequence; and performing lead wire status trend prediction and risk assessment based on the multiple strong impact environment indicator sequences in combination with the real-time lead wire status data to generate a lead wire risk assessment result.

[0043] Preferably, strongly influencing environmental indicator values ​​are extracted from the real-time working environment data, that is, multiple strongly influencing environmental indicator sequences of different types, including temperature change sequences (recording changes in temperature in the working environment), humidity change sequences (changes in environmental humidity, such as the impact of increases or decreases in humidity on equipment insulation, corrosion, etc.), pH change sequences (changes in pH in the environment), electromagnetic interference change sequences (changes in electromagnetic field strength), and vibration interference change sequences (vibration conditions in the environment). The real-time working environment data are combined with the real-time status data of the lead wire (such as temperature, stress, vibration, strain, etc.) to more comprehensively understand the working status of the lead wire, and then the lead wire status trend is predicted, that is, the historical data is modeled using an event sequence analysis model to analyze the relationship between the lead wire status and environmental changes. By analyzing the historical data of multiple strongly influencing environmental indicator sequences (such as temperature, humidity, vibration, etc.), potential trends are identified. Based on the current real-time data and its change trends (such as continued increase in temperature, increase in humidity, etc.), the possible future status of the lead wire is predicted, and potential risks are identified in advance.

[0044] Preferably, a risk assessment is performed based on the results of the status trend prediction and the current health status of the lead wire, that is, an assessment of its risk level in the future period, including dividing the risk level of the lead wire into different levels based on the prediction results and the assessment model, such as low risk, environmental conditions and lead wire status are within the normal range, and the future trend is stable; medium risk, certain environmental factors may cause the lead wire performance to degrade, and close attention is required; high risk, the lead wire status and environmental factors show signs of impending failure, and measures need to be taken to intervene; and then a risk assessment result of the lead wire is generated, including possible problems that may arise in the future for the lead wire, such as excessive temperature, excessive stress, humidity impact, etc., so that potential failure risks can be identified in advance and timely measures can be taken to ensure the safety and stability of power equipment.

[0045] The specific configuration of the lead wire status warning module 50 will be described in detail below. The lead wire status warning module 50 may further include: using the multiple sequences of strong environmental indicators to predict environmental trend changes, and generating multiple environmental impact factors according to the predicted direction of the change, wherein the environmental impact factors include positive impact factors and negative impact factors; extracting multiple lead wire status indicator values ​​based on the real-time status data of the lead wire, normalizing them, constructing a basic decision matrix, and calibrating the basic decision matrix using the multiple environmental impact factors to generate a risk decision matrix; defining ideal solutions and negative ideal solutions for the multiple key monitoring nodes; and performing a lead wire status risk assessment based on the risk decision matrix and combining the ideal solution and the negative ideal solution to generate a lead wire risk assessment result.

[0046] Preferably, by analyzing multiple sequences of strongly influencing environmental indicators (such as temperature changes, humidity changes, pH changes, electromagnetic interference, vibration interference, etc.), the direction of environmental changes is predicted. For example, temperature and humidity may continue to rise in the next few hours, electromagnetic interference may gradually weaken, or vibration interference may have an increasing trend, thereby generating multiple environmental influencing factors, including positive influencing factors and negative influencing factors, wherein positive influencing factors are environmental factors that have a favorable impact on the performance of the lead wire, and negative influencing factors are environmental factors that have an adverse impact on the performance of the lead wire; multiple lead wire status indicator values ​​are extracted based on the real-time status data of the lead wire, and normalized so that different types of status data (temperature, vibration, stress, etc.) have the same dimension, that is, the values ​​of all indicators are standardized to the same range (for example, 0 to 1), and then a basic decision matrix is ​​constructed using the normalized lead wire status indicator values, wherein each column represents a status indicator, each row represents a monitoring node or monitoring time, and the values ​​in the matrix represent the specific health status of the lead wire.

[0047] Preferably, the basic decision matrix is ​​modified by introducing environmental impact factors (positive impact factors and negative impact factors), that is, the original values ​​in the basic decision matrix are adjusted according to the impact of environmental impact factors on the risk assessment of the lead line. The calibrated matrix is ​​called the risk decision matrix, which comprehensively considers the lead line status data and environmental impact factors, and generates a corresponding risk score for each lead line status; for each key monitoring node, an ideal solution and a negative ideal solution are defined respectively, where the ideal solution represents the most ideal state of the lead line, usually when all the lead line status indicator values ​​reach the optimal level (for example, temperature, stress, vibration, etc. are all within the optimal range, and the environmental impact factor is zero or positive), and the negative ideal solution represents The worst state of the lead wire is usually when all the lead wire state index values ​​reach the worst level (for example, the temperature is too high, the stress is too large, the vibration is too strong, and the negative effects of environmental factors are serious). Finally, according to the risk decision matrix, combined with the ideal solution and the negative ideal solution, the lead wire state risk assessment is performed to evaluate the risk level of the lead wire, including the use of decision models such as multi-attribute decision analysis (MCDM) and TOPSIS method (approximate ideal solution method). According to the distance between each lead wire monitoring point and the ideal solution / negative ideal solution, the risk assessment result of the lead wire is calculated to generate the final lead wire risk assessment result, which reflects the risk status of each monitoring point of the lead wire and is helpful for subsequent preventive maintenance and risk management.

[0048] The specific configuration of the lead wire status warning module 50 will be described in detail below. The lead wire status warning module 50 may further include: extracting multiple sample lead wire status index values ​​for each key monitoring point based on the risk decision matrix; calculating the relative distances to the ideal solution and the negative ideal solution based on the multiple sample lead wire status index values, and calculating the relative proximity of each key monitoring point based on the relative distances; and performing a comprehensive assessment of the overall risk of the lead wire based on the relative proximity of each key monitoring point to generate a lead wire risk assessment result.

[0049] Preferably, for each key monitoring point (such as the connection point of the capacitor lead wire, the corner point, the vibration high-incidence area, etc.), a plurality of sample data points are extracted from the lead wire status data collected in real time based on the risk decision matrix, and then the relative distances to the ideal solution and the negative ideal solution are calculated respectively according to the extracted multiple sample lead wire status index values, for example, using Euclidean method to perform relative distance calculation; then the relative proximity of each monitoring point is calculated based on the two relative distances, that is, the proximity of the key monitoring point to the ideal solution, ranging from 0 to 1, where a value close to 1 indicates that the key monitoring point is closer to the ideal solution, and a value close to 0 indicates that the key monitoring point is closer to the negative ideal solution; then, combined with each The relative proximity of each key monitoring point is used to comprehensively evaluate the overall risk of the lead-out line and generate the lead-out line risk assessment result. Specifically, the changing trend of the lead-out line status is judged according to the relative proximity of each key monitoring point. For example, if most of the monitoring points are close to the ideal solution (i.e., close to 1), it means that the lead-out line is in good condition; if most of the monitoring points are close to the negative ideal solution (i.e., close to 0), it means that the lead-out line has a high risk; finally, according to the value of relative proximity, the overall risk of the lead-out line is evaluated. If the relative proximity of some monitoring points is lower than the set threshold, it means that the point has a high risk and needs timely warning.

[0050] The specific configuration of the lead-out line status warning module 50 will be described in detail below. The lead-out line status warning module 50 may further include: constructing a basic decision matrix, which is represented as:

[0051] ;

[0052] Among them, m is the number of key monitoring points, n is the number of monitoring indicators, It shows the value of the mth monitoring point on the nth indicator.

[0053] Preferably, What is stored is the measurement value of monitoring point m on indicator n. The status of each monitoring point at different times will be recorded to form the corresponding status data. For example, at monitoring point For example, at the connection point of the capacitor lead wire, there may be multiple monitoring indicators, such as temperature, stress, vibration, etc. The value of each monitoring indicator (such as temperature 45°C, stress 20N) is filled in the corresponding position in the basic decision matrix.

[0054] Although the present application makes various references to certain modules in the system according to the embodiments of the present application, any number of different modules may be used and run on the user terminal and / or server, and the various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of distinguishing each other and are not used to limit the scope of protection of the present invention.

[0055] The above specific embodiments do not constitute a limitation on the scope of protection of this application. Those skilled in the art should understand that various modifications, combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application shall be included within the scope of protection of this application.

Claims

1. A capacitor lead wire status monitoring system based on optical fiber sensing, characterized in that: The system comprises: A module for determining strongly impacted environmental indicators, which is used to analyze and determine strongly impacted environmental indicators based on the basic environmental properties of the target capacitor's workplace, and to match highly adaptable optical fiber sensor types according to the strongly impacted environmental indicators; A fiber optic sensing module acquisition module is used to extract key monitoring points of the lead wires of the target capacitor, and to sequentially deploy fiber optic sensing equipment according to the fiber optic sensor type to obtain a fiber optic sensing module. At the same time, an environmental monitoring module is deployed according to the spatial structure layout of the target capacitor's workplace; A lead wire status monitoring module is used to use the optical fiber sensing module to perform real-time status monitoring of the lead wires of the target capacitor and obtain real-time status data of the lead wires; A working environment monitoring module is used to use the environmental monitoring module to perform real-time working environment monitoring and obtain real-time working environment data; The lead wire status warning module is used to perform real-time status assessment based on the real-time status data of the lead wire, and extract the values ​​of strong impact environmental indicators in combination with the real-time working environment data to predict the status trend, and issue a lead wire status warning based on the prediction results; The lead-out line status warning module includes: An environmental impact factor generation unit is used to use multiple sequences of strong environmental indicators to predict environmental trend changes respectively, and generate multiple environmental impact factors according to the predicted direction of change, wherein the environmental impact factors include positive impact factors and negative impact factors; A basic decision matrix construction unit is used to extract multiple lead status index values ​​based on the real-time status data of the lead wires, construct a basic decision matrix after normalization, and calibrate the basic decision matrix using the multiple environmental influencing factors to generate a risk decision matrix; A solution definition unit is used to define ideal solutions and negative ideal solutions for multiple key monitoring nodes; A lead state risk assessment unit, configured to perform lead state risk assessment based on the risk decision matrix and in combination with the ideal solution and the negative ideal solution, and generate a lead risk assessment result; The lead-out line status warning module also includes: a sample lead state index value extraction unit, configured to extract a plurality of sample lead state index values ​​for each key monitoring point based on the risk decision matrix; a relative distance calculation unit, configured to calculate relative distances from the plurality of sample lead state index values ​​to an ideal solution and a negative ideal solution, respectively, and calculate relative proximity of each key monitoring point according to the relative distances; The comprehensive risk assessment unit is used to comprehensively assess the overall risk of the lead-out line by combining the relative proximity of each key monitoring point and generate the lead-out line risk assessment result; The lead-out line status warning module includes: An indicator status evaluation unit is used to receive the real-time status data of the lead wire, extract multiple lead wire status indicators, perform single indicator status evaluation and comprehensive indicator status evaluation respectively, and generate a real-time status evaluation result; An abnormality determination unit is used to determine abnormalities based on the real-time status assessment results. If abnormalities are determined, a status warning is directly issued. If no abnormalities are determined, the unit extracts strongly influencing environmental indicators based on the real-time working environment data to predict status trends. The lead-out line status warning module includes: a strongly-influenced environment indicator value extraction unit, configured to extract a strongly-influenced environment indicator value based on the real-time working environment data, wherein the strongly-influenced environment indicator value includes a plurality of strongly-influenced environment indicator sequences, including a temperature change sequence, a humidity change sequence, a pH change sequence, an electromagnetic interference change sequence, and a vibration interference change sequence; The lead-out line risk assessment result generating unit is used to perform lead-out line state trend prediction and risk assessment based on the multiple strong impact environment indicator sequences and the real-time state data of the lead-out line to generate a lead-out line risk assessment result.

2. The capacitor lead wire status monitoring system based on optical fiber sensing according to claim 1, characterized in that: The strong impact environmental index determination module includes: A basic environmental attribute acquisition unit, which acquires basic environmental attributes of a target capacitor's workplace, wherein the basic environmental attributes include at least temperature, humidity, pH, electromagnetic interference, and vibration interference; An environmental impact indicator sequence generation unit is used to perform monitoring interference analysis and lead-out line performance impact analysis based on the basic environmental attributes, and perform fusion analysis and sorting to generate an environmental impact indicator sequence; The strong impact environment indicator extraction unit is used to extract the strong impact environment indicator based on the environmental impact indicator sequence, and match the optical fiber sensor type with high adaptability according to the type of the strong impact environment indicator.

3. The capacitor lead wire status monitoring system based on optical fiber sensing according to claim 1, characterized in that: The optical fiber sensing module acquisition module includes: A key monitoring point extraction unit is used to perform centralized analysis based on the fault record data of the target capacitor lead wire and extract the key monitoring points of the target capacitor lead wire in combination with the conventional weak point locations; An environmental change interval acquisition unit, used to acquire the environmental change interval of a target location; The equipment configuration unit is used to configure daily operation equipment and emergency activation equipment for each fiber optic sensor type based on the environmental change interval, and deploy them at corresponding key monitoring nodes to obtain the fiber optic sensing module.

4. The capacitor lead wire status monitoring system based on optical fiber sensing according to claim 1, characterized in that: The lead-out line status warning module also includes: The construction basic decision matrix is ​​expressed as: ； Among them, m is the number of key monitoring points, n is the number of monitoring indicators, Indicates the value of the mth monitoring point on the nth indicator.

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