An online monitoring method and system for intelligent circuit breakers

Abstract

The present invention relates to the field of intelligent monitoring technology, and particularly to an online monitoring method and system for an intelligent circuit breaker. The method includes the following steps: obtaining the operating data of the circuit breaker, and generating the complete action characteristic data of the circuit breaker through feature extraction and fusion. Analyzing the complete action characteristic data to obtain the classification and status measurement data of the circuit breaker, and performing visual display, analyzing the contact separation time point and arcing time of the circuit breaker, and generating the performance data of the circuit breaker. At the same time, combining the historical operation data of the circuit breaker, estimating its future operation risks, and giving defensive optimization suggestions to realize the intelligent monitoring of the circuit breaker; the present invention realizes more efficient and comprehensive intelligent monitoring through data acquisition, feature extraction, data fusion, status analysis, performance evaluation and risk prediction.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent monitoring, and particularly to an online monitoring method and system for an intelligent circuit breaker. Background Art

[0002] In the stage of traditional monitoring methods, manual inspection and off-line testing are the main means. Manual inspection requires periodic inspection of the status of the circuit breaker, but there are problems of human negligence and subjective judgment. Manual inspection usually involves visually inspecting the circuit breaker periodically, including appearance inspection, touch detection, and identification inspection. This method relies on the experience and judgment of maintenance personnel, and there are problems of human negligence and subjective judgment. In addition, manual inspection requires power outage or disconnection of the power supply, which has a certain impact on production and operation. With the development of sensor technology, sensors have begun to be applied to monitor circuit breakers. For example, by installing current sensors and displacement sensors, the current and position parameters of the circuit breaker can be monitored in real time and transmitted to the monitoring system for analysis. However, there are problems of a large number of sensors, high installation and maintenance costs. In addition, the sensor monitoring method usually only focuses on the monitoring of specific parameters, cannot comprehensively monitor all aspects of the equipment, and cannot predict faults based on the existing circuit breaker, so that users cannot prepare in advance for the maintenance of the circuit breaker, thus increasing the maintenance cost. Summary of the Invention

[0003] Based on this, it is necessary to provide an online monitoring method and system for an intelligent circuit breaker to solve at least one of the above technical problems.

[0004] To achieve the above object, an online monitoring method for an intelligent circuit breaker includes the following steps:

[0005] Step S1: Obtain the working data of the circuit breaker; extract features from the working data of the circuit breaker to generate a working feature matrix of the circuit breaker; perform associated interleaved feature fusion on the working feature matrix of the circuit breaker to generate complete action characteristic data;

[0006] Step S2: Analyze the characteristics of the complete action characteristic data to obtain classification data of the circuit breaker; assign states to the classification data of the circuit breaker to generate measurement state data; perform visual interaction on the measurement state data to generate interface interaction data;

[0007] Step S3: Analyze the current change of the interface interaction data to obtain the contact separation time point of the circuit breaker; analyze the arcing time of the contact separation time point of the circuit breaker to generate performance data of the circuit breaker;

[0008] Step S4: Obtain the historical operation data of the circuit breaker; perform an operation risk estimation on the historical operation data of the circuit breaker and the circuit breaker performance data to obtain the estimated risk data; perform a defensive optimization prompt on the circuit breaker performance data based on the historical operation data of the circuit breaker and the estimated risk data to generate an optimization prompt for implementing the intelligent monitoring of the circuit breaker.

[0009] The present invention helps to analyze and evaluate the complete action characteristics of the circuit breaker by comprehensively obtaining the working data of the circuit breaker and extracting features. This lays a foundation for subsequent state judgment and performance analysis. Visualizing and interacting with the measured state data can intuitively display the working state of the circuit breaker, facilitating real-time monitoring and diagnosis by the operator. By analyzing the contact separation time point and arc burning time of the circuit breaker, the performance indicators of the circuit breaker can be accurately evaluated, providing a basis for subsequent risk assessment and optimization. Combining the historical operation data of the circuit breaker and the estimated risk data to perform defensive optimization on the circuit breaker performance can effectively improve the reliability and safety of the circuit breaker and achieve intelligent monitoring. It makes full use of the working data and historical operation data of the circuit breaker, combines intelligent analysis technologies, realizes the comprehensive monitoring and optimization of the circuit breaker state, and is of great significance for improving the reliability and safety of the circuit breaker. This has a positive effect on the stable operation of the power grid and the safety of power consumption.

[0010] In this specification, an intelligent circuit breaker online monitoring system is provided for implementing an intelligent circuit breaker online monitoring method as described above. The intelligent circuit breaker online monitoring system includes:

[0011] A data acquisition module, configured to obtain the working data of the circuit breaker; extract features from the working data of the circuit breaker to generate a circuit breaker working feature matrix; perform associated interleaved feature fusion on the circuit breaker working feature matrix to generate complete action characteristic data;

[0012] A data display module, configured to perform characteristic analysis on the complete action characteristic data to obtain circuit breaker classification data; assign states to the circuit breaker classification data to generate measured state data; perform visual interaction on the measured state data to generate interface interaction data;

[0013] A performance analysis module, configured to perform current change analysis on the interface interaction data to obtain the contact separation time point of the circuit breaker; perform arc burning time analysis on the contact separation time point of the circuit breaker to generate circuit breaker performance data;

[0014] A fault perception and optimization module, configured to obtain the historical operation data of the circuit breaker; perform an operation risk estimation on the historical operation data of the circuit breaker and the circuit breaker performance data to obtain the estimated risk data; perform a defensive optimization prompt on the circuit breaker performance data based on the historical operation data of the circuit breaker and the estimated risk data to generate an optimization prompt for implementing the intelligent monitoring of the circuit breaker.

[0015] The advantages of the present invention are as follows: By acquiring real-time operating data of the circuit breaker, the system can accurately capture the changes in current, voltage, and temperature parameters of the circuit breaker under different operating conditions, ensuring the accuracy and comprehensiveness of the data. Feature extraction technology is adopted to transform the original data into a feature matrix. This matrix can better represent the operating characteristics of the circuit breaker, facilitating subsequent data analysis and model establishment. By correlating and intertwining different features, the dynamic behavior of the circuit breaker can be more comprehensively described, avoiding the limitations of single features, and thus generating more comprehensive and accurate action characteristic data. Through characteristic analysis, different operating states and modes of the circuit breaker can be identified, including normal operation, abnormal operation, and potential fault states. This helps to detect potential fault signs in advance, realizing the functions of fault prediction and early warning. Presenting the measured status data in a visual manner can help operators intuitively understand the operating state and trends of the circuit breaker and make timely responses and adjustments. Arc burning time analysis is carried out based on the contact separation time point to further evaluate the response speed and safety performance of the circuit breaker under fault conditions. Combining the analysis results of current and arc burning time, detailed circuit breaker performance data is generated. These data are key indicators for evaluating the operating state and safety performance of the circuit breaker. Combining the historical operating data and performance data of the circuit breaker, the system can conduct a comprehensive assessment and prediction of operating risks, including the fault modes and impacts that occur. Based on the risk assessment results, the system can generate defensive optimization suggestions, such as proposing maintenance suggestions, adjusting operating parameters, or replacing key components, to minimize the fault risk and improve the reliability of the circuit breaker. Description of the Drawings

[0016] Figure 1 It is a schematic diagram of the step flow of an online monitoring method for an intelligent circuit breaker;

[0017] Figure 2 It is Figure 1 a schematic diagram of the detailed implementation step flow of step S2 in

[0018] Figure 3 It is Figure 1 a schematic diagram of the detailed implementation step flow of step S4 in

[0019] The realization of the object of the present invention, functional features, and advantages will be further described with reference to the embodiments and the accompanying drawings. Specific Embodiments

[0020] The technical method of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative efforts belong to the scope of protection of the present invention.

[0021] In addition, the accompanying drawings are only schematic illustrations of the present invention and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and thus repeated descriptions thereof will be omitted. Some of the block diagrams shown in the drawings are functional entities and do not necessarily correspond to physically or logically independent entities. The functional entities may be implemented in software form, or in one or more hardware modules or integrated circuits, or in different networks and / or processor methods and / or microcontroller methods.

[0022] It should be understood that although the terms "first" and "second" may be used herein to describe various units, these units should not be limited by these terms. These terms are only used to distinguish one unit from another. For example, without departing from the scope of the exemplary embodiments, the first unit may be referred to as the second unit, and similarly, the second unit may be referred to as the first unit. The term "and / or" used herein includes any and all combinations of one or more of the associated listed items.

[0023] To achieve the above object, please refer to Figures 1 to 3 , an online monitoring method for an intelligent circuit breaker, comprising the following steps:

[0024] Step S1: Obtain the operating data of the circuit breaker; extract features from the operating data of the circuit breaker to generate an operating feature matrix of the circuit breaker; perform associated interleaved feature fusion on the operating feature matrix of the circuit breaker to generate complete action characteristic data;

[0025] Step S2: Analyze the characteristics of the complete action characteristic data to obtain circuit breaker classification data; assign states to the circuit breaker classification data to generate measurement state data; perform visual interaction on the measurement state data to generate interface interaction data;

[0026] Step S3: Analyze the current change of the interface interaction data to obtain the contact separation time point of the circuit breaker; analyze the arcing time of the contact separation time point of the circuit breaker to generate circuit breaker performance data;

[0027] Step S4: Obtain the historical operation data of the circuit breaker; estimate the operation risk of the historical operation data of the circuit breaker and the circuit breaker performance data to obtain estimated risk data; perform defensive optimization prompts on the circuit breaker performance data based on the historical operation data of the circuit breaker and the estimated risk data to generate optimization prompts so as to perform intelligent monitoring of the circuit breaker.

[0028] The present invention helps to analyze and evaluate the complete operating characteristics of a circuit breaker by comprehensively acquiring the operating data of the circuit breaker and extracting features. This lays a foundation for subsequent status judgment and performance analysis. Visual interaction with the measured status data can intuitively display the operating status of the circuit breaker, facilitating real-time monitoring and diagnosis by operators. By analyzing the contact separation time point and arcing time of the circuit breaker, the performance indicators of the circuit breaker can be accurately evaluated, providing a basis for subsequent risk assessment and optimization. Combining the historical operation data and predicted risk data of the circuit breaker to perform defensive optimization on the performance of the circuit breaker can effectively improve the reliability and safety of the circuit breaker and achieve intelligent monitoring. By making full use of the operating data and historical operation data of the circuit breaker and combining intelligent analysis techniques, comprehensive monitoring and optimization of the circuit breaker status are achieved, which is of great significance for improving the reliability and safety of the circuit breaker. This has a positive effect on the stable operation of the power grid and the safety of electricity use.

[0029] In the embodiment of the present invention, referring to Figure 1 as described, it is a schematic diagram of the step flow of an online monitoring method for an intelligent circuit breaker of the present invention. In this example, the online monitoring method for the intelligent circuit breaker includes the following steps:

[0030] Step S1: Acquire the operating data of the circuit breaker; extract features from the operating data of the circuit breaker to generate an operating feature matrix of the circuit breaker; perform associated interleaved feature fusion on the operating feature matrix of the circuit breaker to generate complete operating characteristic data;

[0031] In the embodiments of the present invention, the closing and opening coil currents are collected with an accuracy of ±1% FS and a measurement range of 0 - 100A, and the energy storage motor current is collected with an accuracy of ±1% FS and a measurement range of 0 - 100A. A laser displacement sensor is used to monitor the three-phase contact travel with an accuracy of 1% FS and a measurement range of 50mm ± 15mm. The temperatures of 6 contact points and 3 cable heads are monitored with an accuracy of ±2°C and a measurement range of 0 - 120°C. The three-phase spring pressure is collected with an accuracy of 10N and a measurement range of 0 - 3000N. The 3M - 100MHz frequency band of the earth electric wave is used to detect partial discharge and collect partial discharge monitoring signals. The three-phase contact travel is collected with an accuracy of 1% FS and a measurement range of 50mm ± 15mm. A laser displacement sensor is used, and an RS485 communication channel is used for data transmission, and the power supply is AC220V / DC24V. Anti-interference measures of electrostatic discharge, fast transient, and surge severity levels are taken. Feature extraction is performed on the collected current, displacement, temperature, and spring pressure data, and the working data of the circuit breaker after feature extraction is stored in matrix form. Each row represents a circuit breaker operation, and each column represents a working parameter. Then, the principal component analysis method is used to perform feature extraction on the circuit breaker working data matrix to generate an 8-dimensional feature matrix containing the main working features. Next, the grey relational analysis method is used to perform correlation interweaving on the 8-dimensional feature matrix to fuse the internal relationships between the features, and finally a 16-dimensional complete action characteristic data is generated.

[0032] Step S2: Perform characteristic analysis on the complete action characteristic data to obtain circuit breaker classification data; assign states to the circuit breaker classification data to generate measurement state data; perform visual interaction on the measurement state data to generate interface interaction data;

[0033] In the embodiments of the present invention, an unsupervised classification is performed on the complete action characteristic data by using clustering algorithms (such as k-means, DBSCAN), the behaviors of the circuit breakers are divided into different types, the characteristics of each type are statistically analyzed, and characteristic parameters with significant differences between classes are extracted, such as current peak value and closing time. A circuit breaker classification model is established, and the new action characteristic data is classified into the existing types, and the circuit breaker classification data is output, including the type label to which each action belongs. Combining expert experience, working states are set for each circuit breaker type, such as normal, warning, and fault. According to the circuit breaker classification data, corresponding working state labels are assigned to each action, and a state transition matrix is established to describe the conversion relationship between the circuit breaker states, and the measurement state data is output, including the state label of each action. A visualization interface is developed by using Web front-end technologies (such as React, Vue) to support real-time display and interaction of circuit breaker data. The working state curve of the circuit breaker is drawn on the interface, and different states are marked with different colors. Visualization views such as state transition diagrams and statistical charts of characteristic parameters are provided to facilitate the analysis of the working characteristics of the circuit breaker, and the interface interaction data is output, including the visualization operation records of the user.

[0034] Step S3: Analyze the current change of the interface interaction data to obtain the contact separation time point of the circuit breaker; analyze the arcing time at the contact separation time point of the circuit breaker to generate circuit breaker performance data. In the embodiment of the present invention, the current waveform data of each action is extracted from the interface interaction data, and the signal processing technology (such as digital filtering, differentiation) is used to analyze the current waveform, identify the time point of the sharp drop in current, and according to the IEC 62271-100 standard, this time point is determined as the contact separation time point of the circuit breaker, calculate the contact separation time of each action, and output it as the contact separation time point data of the circuit breaker. Extract the contact separation time of each action from the contact separation time point data of the circuit breaker, combine the technical parameters of the circuit breaker (such as breaking capacity, arc chamber volume), and use the physical model to calculate the arcing time of each action. The physical model includes the arc thermodynamics equation and the arc chamber characteristic equation, and the arcing time is obtained by numerical solution, and the calculated arcing time is output as the circuit breaker performance data.

[0035] Step S4: Obtain the historical operation data of the circuit breaker; estimate the operation risk of the historical operation data of the circuit breaker and the circuit breaker performance data to obtain the estimated risk data; based on the historical operation data of the circuit breaker and the estimated risk data, give a defensive optimization prompt for the circuit breaker performance data to generate an optimization prompt to perform the intelligent monitoring of the circuit breaker.

[0036] In the embodiment of the present invention, the historical operation data of the circuit breaker is extracted from the circuit breaker monitoring system or maintenance records, including the operation time, the number of operations, and the fault records. The historical data in different time periods is summarized and standardized to ensure the consistency of the data format, establish a historical operation database of the circuit breaker, and update it regularly to ensure the integrity and timeliness of the data. The Bayesian network or Markov chain probability model is used to combine the circuit breaker performance data and the historical operation data to estimate the failure probability of the circuit breaker under different working conditions. Considering the key functional parameters of the circuit breaker (such as breaking capacity, closing time) and the fault modes, a multi-level risk estimation model is constructed, and the Monte Carlo simulation method is used to quantitatively evaluate the operation risk of the circuit breaker under different working conditions, and output the estimated risk data. Compare and analyze the estimated risk data with the circuit breaker performance data, identify the performance weaknesses and potential fault hazards of the circuit breaker, and according to the fault modes and risk factors, propose targeted optimization measures, such as adjusting parameter settings, replacing components, present the optimization measures to the user in an easy-to-understand manner, form an executable optimization prompt, and regularly push the optimization prompt through the intelligent monitoring system to support the intelligent maintenance and performance optimization of the circuit breaker.

[0037] Preferably, step S1 includes the following steps:

[0038] Step S11: Collect the operating data of the circuit breaker in real time through multiple high-precision sensors;

[0039] Step S12: Perform empirical mode decomposition on the operating data of the circuit breaker to obtain the static characteristics of the circuit breaker;

[0040] Step S13: Perform low-dimensional integration on the static characteristics of the circuit breaker to generate the operating characteristic matrix of the circuit breaker;

[0041] Step S14: Perform global correlation analysis on the operating characteristic matrix of the circuit breaker to obtain the global correlation data of the matrix;

[0042] Step S15: Perform relevant feature fusion on the operating characteristic matrix of the circuit breaker according to the global correlation data of the matrix to generate complete action characteristic data.

[0043] The advantages of the present invention are as follows: By collecting the operating data of the circuit breaker in real time through multiple high-precision sensors, more accurate and comprehensive raw data can be obtained, laying a good foundation for subsequent feature extraction and analysis. The empirical mode decomposition method is adopted, which can effectively extract the static characteristics of the circuit breaker from the original operating data and provide key information for subsequent feature fusion and analysis. Through low-dimensional integration, the extracted static characteristics are transformed into the operating characteristic matrix of the circuit breaker, providing a structured data representation for subsequent correlation analysis and feature fusion. Performing global correlation analysis on the operating characteristic matrix can fully explore the internal connections between various features and provide a basis for subsequent feature fusion. Based on the global correlation data, targeted relevant feature fusion is performed on the operating characteristic matrix, which can generate more complete and accurate circuit breaker action characteristic data, providing a reliable basis for subsequent performance analysis and risk prediction. Through data collection, feature extraction, and feature fusion methods, a complete set of circuit breaker online monitoring systems is systematically constructed, which is of great significance for realizing the intelligent monitoring of circuit breakers.

[0044] In the embodiments of the present invention, a plurality of high-precision sensors are arranged at key positions of the circuit breaker, including a closing and opening coil current sensor (±1% FS, 0-100 A range), a storage motor current sensor (±1% FS, 0-100 A range), a laser displacement sensor for monitoring the stroke of the 6-point contact and the 3-point cable head (±1% FS, 50 mm ± 15 mm range), a temperature sensor for monitoring the temperature of the 6-point contact and the 3-point cable head (±2 °C, 0-120 °C range), and a spring pressure sensor (±10 N, 0-3000 N range). A ground wave partial discharge detection sensor with a frequency band of 3M-100 MHz is used to monitor the partial discharge condition of the circuit breaker. The sampling frequency of all sensors is not less than 1 kHz, and the collected data is uploaded to the data acquisition system in real time through the RS485 communication channel. Anti-interference measures with electrostatic discharge, fast transient, and surge severity levels are taken to ensure the accuracy and reliability of data acquisition. The Hilbert-Huang transform is used to perform empirical mode decomposition (EMD) on the operating data of the circuit breaker collected in step S11. EMD can adaptively decompose the non-stationary and non-linear signals of the circuit breaker current, displacement, temperature, and spring pressure into a series of intrinsic mode functions (IMFs). The IMF components containing the key static characteristics of the circuit breaker, such as contact stroke, spring pressure, and partial discharge, are selected as the static characteristics of the circuit breaker. By analyzing the time-frequency characteristics of the IMFs, the static operating state of the circuit breaker at different action stages can be accurately reflected. The static characteristics of the circuit breaker are reduced in dimension and integrated through principal component analysis (PCA), and 8 main characteristic dimensions that can describe the key operating state of the circuit breaker are retained. An 8-column circuit breaker operating characteristic matrix is constructed, where each row of the matrix represents a circuit breaker operation, and each column represents an operating parameter, such as contact stroke, current, temperature, and spring pressure. Using the grey relational analysis method, a comprehensive correlation analysis is performed on the 8-dimensional circuit breaker operating characteristic matrix. Using the weighted average method, the selected 8 relevant characteristics are fused to generate a 16-dimensional comprehensive index matrix describing the action characteristics of the circuit breaker. This 16-dimensional action characteristic data matrix reflects the complete working process of the circuit breaker at different action stages. This action characteristic data can be used for circuit breaker state monitoring, fault diagnosis, and performance evaluation applications.

[0045] Preferably, step S2 includes the following steps:

[0046] Step S21: Perform electrical characteristic analysis on the complete action characteristic data to obtain electrical characteristic data;

[0047] Step S22: Perform action performance analysis on the complete action characteristic data to generate working performance data;

[0048] Step S23: Based on the electrical characteristic data and the working performance data, perform characteristic differentiation on the complete action characteristic data to obtain circuit breaker classification data;

[0049] Step S24: Assign states to the breaker classification data based on a preset set of state thresholds to generate measured state data, where the preset set of state thresholds includes a current waveform difference threshold and a displacement opening distance range threshold;

[0050] Step S25: Perform visual interaction on the measured state data based on the breaker classification data to generate interface interaction data.

[0051] The beneficial effects of the present invention are as follows: Electrical feature analysis and action performance analysis are carried out on the complete action characteristic data, deeply mining the key features in the working process of the breaker, providing basic data for subsequent classification and state assignment. Based on the electrical feature data and working performance data, the complete action characteristic data is distinguished by characteristics to obtain the breaker classification data, providing a basis for accurately identifying the breaker state. A preset set of state thresholds (including a current waveform difference threshold and a displacement opening distance range threshold) is used to assign states to the breaker classification data, generating measured state data, laying a foundation for subsequent state monitoring and state evaluation. Visual interaction is performed on the measured state data based on the breaker classification data to generate interface interaction data, providing intuitive data display support for human-computer interaction and intelligent decision-making. Through in-depth analysis of the complete action characteristic data, breaker classification, state threshold setting, and visual interaction methods, a complete breaker state monitoring and evaluation system is constructed, which is of great significance for realizing intelligent monitoring of the breaker.

[0052] As an example of the present invention, refer to Figure 2 As shown, in this example, step S2 includes:

[0053] Step S21: Perform electrical feature analysis on the complete action characteristic data to obtain electrical feature data;

[0054] In the embodiment of the present invention, electrical feature analysis is performed on the complete action characteristic data to obtain electrical feature data. First, current waveform data, contact opening time data, and contact insulation resistance data of the switch contacts are extracted from the complete action characteristic data. Then, filtering processing is respectively performed on these electrical parameters to remove noise interference. Next, fast Fourier transform is used to perform frequency domain analysis on the filtered current waveform data to obtain current harmonic content and main frequency component amplitude characteristic indexes. At the same time, the average value and standard deviation of the contact opening time are calculated as the contact action time characteristics. Finally, the steady-state value and transient value of the contact insulation resistance are measured, and their ratio is calculated as the contact insulation characteristic index. Combining the above three types of characteristic indexes can obtain the complete electrical feature data.

[0055] Step S22: Perform action performance analysis on the complete action characteristic data to generate working performance data;

[0056] In the embodiment of the present invention, the action performance analysis is performed on the complete action characteristic data to generate the working performance data. First, three types of action parameters, namely the contact displacement, contact velocity, and contact acceleration, are extracted from the complete action characteristic data. Among them, the contact displacement data can be directly obtained; the contact velocity is obtained by performing digital differential operation on the displacement data; and the contact acceleration is calculated by second-order differential of the velocity data. The time-domain curves of these three types of action parameters are analyzed. For the contact displacement curve, its maximum stroke and opening / closing time are measured; for the contact velocity curve, its maximum value and rise / fall time are measured; for the contact acceleration curve, its peak acceleration and duration are measured. By integrating the above action performance indicators, a complete working performance data set can be formed.

[0057] Step S23: Based on the electrical characteristic data and the working performance data, the complete action characteristic data is distinguished by characteristics to obtain the breaker classification data;

[0058] In the embodiment of the present invention, based on the electrical characteristic data and the working performance data, the complete action characteristic data is distinguished by characteristics to obtain the breaker classification data. The electrical characteristic data (such as current waveform characteristics, contact action time, insulation resistance index) and the working performance data (such as contact displacement, velocity, acceleration parameters) are combined into a high-dimensional feature vector. Then, the K-means clustering algorithm is used to perform unsupervised classification on these feature vectors, and the breakers are divided into several categories. The number of clusters K of the clustering algorithm can be set in advance according to the number of breaker models, or automatically determined using the silhouette coefficient index. On the basis of clustering, the support vector machine (SVM) supervised learning algorithm is further used to optimize the classification result. That is, the breaker model labels pre-annotated by experts are used as training samples to train the SVM model, and this model is used to finely adjust the clustering result again to obtain the final breaker classification data.

[0059] Step S24: Based on the preset state threshold set, the breaker classification data is given a state to generate the measurement state data, where the preset state threshold set includes a current waveform difference threshold and a displacement opening range threshold;

[0060] In the embodiment of the present invention, status is assigned to the circuit breaker classification data based on a preset set of status thresholds to generate measurement status data. The preset set of status thresholds includes a current waveform difference threshold and a displacement opening distance range threshold. From the electrical characteristic data, the amplitude of the main frequency component and the harmonic content index of the current waveform are extracted. Then, the current waveform difference threshold is set such that the deviation of the main frequency component amplitude does not exceed 5%, and the difference in harmonic content does not exceed 10%. For each type of circuit breaker in the classification data, it is judged whether its current waveform characteristics meet the threshold requirements. If they are met, a "good" status label is assigned; otherwise, an "abnormal" status is assigned. From the working performance data, the maximum stroke of the contact and the opening and closing time index are extracted. The displacement opening distance range threshold is set such that the maximum stroke is within ±5% of the normal value, and the opening and closing time is within ±10% of the normal value. Similarly, for each type of circuit breaker, if the threshold requirements are met, a "good" status is assigned; if not, an "abnormal" status is assigned. The current waveform status and the displacement status are subjected to a logical "AND" operation to obtain comprehensive measurement status data for subsequent circuit breaker status diagnosis.

[0061] Step S25: Based on the circuit breaker classification data, perform visual interaction on the measurement status data to generate interface interaction data.

[0062] In the embodiment of the present invention, the circuit breaker classification data is visualized as a two-dimensional scatter plot, where the abscissa is the electrical characteristic index (such as the harmonic content of the current waveform), and the ordinate is the action performance index (such as the maximum stroke of the contact). Each type of circuit breaker is represented by scatter points of different colors, and a convex hull contour is drawn around the scatter points to intuitively display the characteristic distribution areas of different types of circuit breakers. Based on this scatter plot, the preset current waveform difference threshold and displacement opening distance range threshold are superimposed and marked on the graph in the form of two straight lines. In this way, the circuit breaker status can be clearly divided into two categories: "good" and "abnormal". An interactive function is added to the visualization interface. The user can click on any circuit breaker scatter point with the mouse to pop up the detailed information of the circuit breaker, including the model, manufacturing date, and measurement status. At the same time, the user can also adjust the threshold parameters to observe the change of the circuit breaker status distribution in real time. It is implemented using HTML5+JavaScript technology, and the data interaction uses RESTful API, ensuring good cross-platform compatibility and user experience.

[0063] Preferably, step S24 includes the following steps:

[0064] Step S241: Group the circuit breaker classification data by category to obtain closing current data and closing displacement data;

[0065] Step S242: Based on a preset current waveform difference threshold, perform an upper limit state assessment on the closing current data to obtain current state data; based on a preset displacement opening range threshold, perform a displacement state assessment on the closing displacement data to generate displacement state data.

[0066] Step S243: Heterogeneously integrate the current state data and the displacement state data to generate measurement state data.

[0067] The beneficial effect of the present invention is that the classification data is further subdivided into closing current data and closing displacement data, laying a foundation for subsequent state assessment. The upper limit state assessment is performed on the closing current data using a preset current waveform difference threshold to obtain current state data, and the displacement state assessment is performed on the closing displacement data using a preset displacement opening range threshold to generate displacement state data. The state assessment method based on the preset threshold can more accurately identify the current and displacement states of the circuit breaker. The current state data and the displacement state data are heterogeneously integrated to generate comprehensive measurement state data. The integration of such heterogeneous data can more comprehensively reflect the working state of the circuit breaker, providing richer information for subsequent state monitoring and fault diagnosis. By refining the classification data, performing state assessment based on preset thresholds, and integrating heterogeneous data, a more accurate and complete circuit breaker state measurement system is constructed, which is of great significance in realizing intelligent monitoring of the circuit breaker.

[0068] In an embodiment of the present invention, according to the clustering results, the circuit breakers are divided into several categories. For each category, the current waveform characteristics of the circuit breaker of this category during the closing process are extracted from the electrical characteristic data as the closing current data. Similarly, the contact displacement parameters of the circuit breaker of this category during the closing process are extracted from the working performance data as the closing displacement data. Through this classification and statistical method, the characteristic data of different types of circuit breakers during the closing process can be obtained. For the closing current data, the set current waveform difference threshold is that the amplitude deviation of the main frequency component does not exceed 5%, and the harmonic content difference does not exceed 10%. This threshold is applied to the current data of each category of circuit breakers in turn. Those that meet the requirements are determined to be in a "good" state, and those that do not meet the requirements are determined to be in an "abnormal" state, thereby obtaining the current state data. Similarly, for the closing displacement data, the displacement opening range threshold is set to ±5% of the normal value, and the displacement state data is obtained accordingly through evaluation. A logical "AND" operation is performed on the current state and the displacement state. For the same category of circuit breakers, only when both the current state and the displacement state are "good" is its comprehensive state determined to be "good", otherwise it is determined to be "abnormal". Through such heterogeneous data integration, the actual working state of the circuit breaker can be more comprehensively evaluated, avoiding misjudgment caused by the failure of a single index.

[0069] Preferably, step S242 includes the following steps:

[0070] Obtain current reference waveform data;

[0071] Based on a preset current waveform difference threshold, perform waveform comparison on the current reference waveform data and the closing current data. When the current waveform difference between the current reference waveform data and the closing current data is greater than the preset current waveform difference threshold, define the closing current data as good current state data; when the current waveform difference between the current reference waveform data and the closing current data is less than the preset current waveform difference threshold, define the closing current data as abnormal current state data.

[0072] Perform waveform analysis on the closing displacement data and the closing current data to generate a current-displacement waveform curve;

[0073] Based on the current-displacement waveform curve, perform forward and backward displacement measurement on the displacement waveform curve to generate displacement opening distance data;

[0074] Based on a preset displacement opening distance range threshold, perform displacement range evaluation on the displacement opening distance data. When the displacement opening distance data coincides with the preset displacement opening distance range threshold, define the displacement opening distance data as good displacement state data; when the displacement opening distance data does not coincide with the preset displacement opening distance range threshold, define the displacement opening distance data as abnormal displacement state data.

[0075] The beneficial effect of the present invention is that through the waveform comparison of the current reference waveform data and the closing current data, when the difference is greater than the preset threshold, it is defined as a good current state, and when the difference is less than the threshold, it is defined as an abnormal current state. This evaluation method based on waveform difference can more accurately identify the current state, provide an important basis for subsequent fault diagnosis, and help detect the abnormal current state of the circuit breaker in a timely manner. By performing waveform analysis on the closing displacement data and the closing current data, a current-displacement waveform curve is generated, which helps to understand the relationship between the current and displacement of the circuit breaker. Based on the current-displacement waveform curve, the displacement opening distance data can be measured, providing a basis for subsequent displacement state evaluation. By comparing the displacement opening distance data with the preset threshold, when the data coincides, it is defined as a good displacement state, and when it does not coincide, it is defined as an abnormal displacement state. This evaluation method based on a preset range can more accurately identify the displacement state and provide important support for timely detecting the abnormal displacement state of the circuit breaker. By obtaining reference data, state evaluation based on preset thresholds, and the current-displacement waveform analysis method, a complete circuit breaker state monitoring system is constructed, which has important value in realizing the intelligent monitoring of the circuit breaker.

[0076] In an embodiment of the present invention, current waveform data during the closing process of a circuit breaker that has been verified to be in a normal operating state is extracted from historical operation records as current reference waveform data. This reference data should cover circuit breakers of different models and ratings to ensure broad representativeness. The current reference waveform data is stored in the form of digital signals with a sampling frequency of not less than 10 kHz to ensure the integrity of waveform characteristics. The closing current data is compared and analyzed with the current reference waveform data. The set current waveform gap threshold is: the deviation of the main frequency component amplitude does not exceed 5%, and the difference in harmonic content does not exceed 10%. This threshold is applied to the comparison process. When the gap between the closing current data and the reference waveform exceeds the threshold, it is determined as "good" current state data; when the gap is less than the threshold, it is determined as "abnormal" current state data. The closing displacement data and the closing current data are aligned according to the time series, and the interpolation method is used to map the two sets of data onto the same time axis to generate a current-displacement waveform curve, where the X-axis is the time parameter, which represents the time change during the closing process of the circuit breaker, and the unit is millisecond (ms). The x-axis value starts from the starting time of closing, and the whole process time is generally 50 - 100 ms; the Y-axis is the current and displacement data, where the current in the Y-axis represents the instantaneous current value during the closing process of the circuit breaker, and the unit is ampere (A). The current waveform curve reflects the dynamic change characteristics of the current during the closing process of the circuit breaker, including key parameters such as peak current and rising / falling edges. The displacement in the Y-axis represents the instantaneous displacement value of the circuit breaker contact during the closing process, and the unit is millimeter (mm). The displacement waveform curve reflects the movement trajectory of the circuit breaker contact during the closing process, including key parameters such as the starting position of the contact, the contact point position, and the end position. This curve intuitively reflects the dynamic change relationship between the current and displacement during the closing process of the circuit breaker. From the current-displacement waveform curve, the starting point and the ending point of the displacement waveform curve are extracted, and the displacement opening distance between the two points is measured as the displacement opening distance data. This data accurately reflects the movement stroke of the circuit breaker contact during the closing process. The set normal displacement opening distance range threshold is ±5% of the rated stroke of the contact. The displacement opening distance data is compared with this threshold. When the displacement opening distance data falls within the threshold range, it is determined as "good" displacement state data; when the displacement opening distance data exceeds the threshold range, it is determined as "abnormal" displacement state data.

[0077] Preferably, step S3 includes the following steps:

[0078] Step S31: Perform graphic change analysis on the interface interaction data to obtain graphic change data;

[0079] Step S32: Based on the graphic change data, perform current change analysis on the interface interaction data to obtain the time point of circuit breaker contact separation;

[0080] Step S33: Analyze the current waveform pattern of the interface interaction data based on the contact separation time point of the circuit breaker to generate arcing time data;

[0081] Step S34: Map the arcing time data to the device performance to generate circuit breaker performance data.

[0082] The beneficial effect of the present invention is that by analyzing the graphical changes of the interface interaction data, graphical change data is obtained. This analysis can effectively capture the dynamic change characteristics of the circuit breaker during the closing and opening processes, providing basic data for subsequent current change analysis. Based on the graphical change data, current change analysis is performed on the interface interaction data to obtain the time point of contact separation of the circuit breaker. This lays the foundation for the next arcing time analysis. Accurately obtaining the contact separation time point is the key to evaluating the performance of the circuit breaker. Analyzing the current waveform pattern of the interface interaction data based on the contact separation time point of the circuit breaker generates arcing time data. The arcing time is an important parameter of the circuit breaker performance and is of great significance for judging the breaking capacity and withstand capacity of the circuit breaker. Mapping the arcing time data to the device performance generates circuit breaker performance data. This method of mapping the arcing time parameter to the circuit breaker performance index can more intuitively reflect the overall working state of the circuit breaker, providing an important basis for subsequent fault diagnosis and performance evaluation. Through graphical change analysis, current change analysis, current waveform analysis, and performance mapping methods, key parameters related to the circuit breaker performance are extracted from the interface interaction data, providing valuable support for realizing online monitoring of intelligent circuit breakers.

[0083] As an example of the present invention, refer to Figure 3 As shown, in this example, step S3 includes:

[0084] Step S31: Analyze the graphical changes of the interface interaction data to obtain graphical change data;

[0085] In the embodiment of the present invention, interface interaction data during the closing process of the circuit breaker is collected from the human-machine interaction device, including real-time state change information of user operation buttons and sliders. This data is stored in the form of digital signals, and the sampling frequency is not less than 100 Hz to ensure that subtle changes in interface elements can be captured. The interface interaction data is input into a dedicated signal processing algorithm for time-domain and frequency-domain analysis. Specifically, it includes: extracting the change curve of the interface element state, and analyzing the amplitude, frequency, and lag time characteristic parameters of the change curve; based on these parameters, identifying the start time, maximum displacement, and oscillation characteristics of the interface element. Based on the analysis results, various change characteristic parameters of the interface element are recorded in the form of digital quantization to form complete graphical change data. This data can be used for subsequent correlation analysis with current and displacement to comprehensively evaluate the operating state of the circuit breaker.

[0086] Step S32: Perform current change analysis on the interface interaction data based on the graph change data to obtain the contact separation time point of the circuit breaker;

[0087] In the embodiment of the present invention, the graph change data and the current waveform data are synchronized and aligned in time. This requires ensuring that the sampling frequencies and time bases of the two sets of data are consistent, and performing precise matching based on characteristic parameters. Perform detailed analysis on the synchronized current waveform data to identify the key change characteristics of the current during the closing process, including the current peak time, zero-crossing time, and current drop slope. Combine the interface interaction data and compare and analyze the current characteristic parameters with the dynamic changes of the interface elements. Find the moment when the state of the interface element (such as the operation button) changes significantly, which can be determined as the time point of contact electrical separation. Organize the above analysis results in the form of a report, and record in detail the current characteristics, interface changes, and the corresponding contact separation time points of the two.

[0088] Step S33: Perform current waveform pattern analysis on the interface interaction data according to the contact separation time point of the circuit breaker to generate arc burning time data;

[0089] In the embodiment of the present invention, the contact separation time point of the circuit breaker is used as the time reference for analyzing the current waveform. This time point is the starting moment of contact mechanical separation. Taking the contact separation time point as a reference, perform detailed analysis on the collected current waveform data. Focus on the change characteristics of the current after contact separation, including the sudden rise of the current value, the fluctuations during the arc burning process, and the process of finally approaching zero value. These characteristics reflect the dynamic characteristics of arc burning. According to the analysis results of the current waveform, accurately extract the duration of arc burning. This time length is the so-called "arc burning time". The arc burning time is one of the important indicators for evaluating the breaking performance of the circuit breaker, reflecting the ability of the circuit breaker to cut off the current. Record the arc burning time parameter in digital form as an important basis for evaluating the breaking performance of the circuit breaker. This data can be correlated with other physical quantities (such as displacement, contact pressure) for comprehensive diagnosis of the operating characteristics of the circuit breaker.

[0090] Step S34: Perform device performance mapping on the arc burning time data to generate circuit breaker performance data.

[0091] In the embodiments of the present invention, according to the technical parameters provided by the circuit breaker manufacturer or through a large number of measured data, a mathematical mapping relationship is established between the arcing time and the key performance indicators of the circuit breaker (such as breaking current, mechanical life), which is described by using linear and exponential function models to obtain a mapping model. Substitute the arcing time data into the established mapping model to calculate the specific performance indicator values of the circuit breaker. These indicator values include but are not limited to: breaking current capacity, operating time, mechanical life. Integrate the performance indicators of each circuit breaker into a complete performance data set, and output the circuit breaker performance data in a structured report form, including the numerical values of each performance indicator, the calculation process, and the content of the mapping model.

[0092] Preferably, step S33 includes the following steps:

[0093] Step S331: Analyze the separating point current of the interface interaction data according to the circuit breaker contact separation time point to generate separating point electrical waveform data;

[0094] Step S332: Perform dynamic waveform analysis on the separating point electrical waveform data to obtain waveform feature data;

[0095] Step S333: Estimate the arcing duration based on the waveform feature data according to the circuit breaker contact separation time point to obtain arcing time data.

[0096] The advantages of the present invention are as follows: Analyze the separating point current of the interface interaction data according to the circuit breaker contact separation time point to generate separating point electrical waveform data. This current analysis for the separating point can more accurately capture the electrical characteristic changes at the critical moment during the opening process of the circuit breaker, providing a data basis for subsequent waveform analysis. Perform dynamic waveform analysis on the separating point electrical waveform data to obtain waveform feature data. This method of in-depth analysis of waveform data can extract the dynamic change characteristics of key parameters such as current and voltage during the opening process of the circuit breaker, laying a foundation for estimating the arcing duration. Based on the circuit breaker contact separation time point, estimate the arcing duration based on the waveform feature data to obtain arcing time data. The arcing time is an important indicator for evaluating the performance of the circuit breaker and can reflect the breaking ability and withstand ability of the circuit breaker. Through this method of estimating the arcing duration based on waveform features, the arcing time can be estimated more accurately. Through the separating point current analysis, dynamic waveform analysis, and arcing duration estimation methods, the key electrical characteristics during the opening process of the circuit breaker are deeply excavated from the interface interaction data, providing strong support for accurately evaluating the performance indicators of the circuit breaker. This is of great significance for realizing online monitoring and fault diagnosis of intelligent circuit breakers.

[0097] In the embodiments of the present invention, the time point of the breaker contact separation is used as the time reference for current waveform analysis. This time point corresponds to the starting moment of the mechanical separation of the contacts. With the contact separation time point as the reference, the current waveform within the corresponding time period is intercepted from the collected interface interaction data. This waveform reflects the entire process of the arc generation and extinction after the contact separation. For the current waveform, analyze its change characteristics after the contact separation, including the sudden rise of the current value, the fluctuations during the arc combustion process, and the process of finally tending to zero value. These characteristics are closely related to the dynamic characteristics of the arc combustion. Record and save the current waveform characteristics in a digital form as the basic data for subsequent arc burning time analysis. This data contains the entire process change information of the current after the contact separation. Conduct a detailed analysis of the current waveform data at the separation point, and extract time domain characteristic parameters such as the current value, rise / fall slope, and fluctuation frequency. These parameters reflect the dynamic changes during the arc combustion process. Use the Fourier transform method to convert the current waveform data at the separation point to the frequency domain, and extract the corresponding spectral characteristics such as the main frequency and harmonic components. These frequency domain characteristics help to further analyze the dynamic law of the arc combustion. Integrate the time domain and frequency domain characteristic parameters into a complete waveform characteristic data set. This data set comprehensively describes the dynamic change law of the current waveform at the separation point and provides a basis for subsequent arc burning time analysis. According to the mathematical correlation data between the preset waveform characteristic parameters (such as current value, slope, frequency) and the actual arc burning time, establish a mathematical mapping relationship between the waveform characteristic parameters (such as current value, slope, frequency) and the actual arc burning time. This relationship can be described by linear or exponential function models. Substitute the waveform characteristic data set into the mapping model to calculate the arc burning duration during the breaker opening process. Record and save the calculated arc burning time value as an important basis for subsequent performance evaluation. Output the arc burning time data in a structured report form, including the calculation process and the content of the mapping model.

[0098] Preferably, step S4 includes the following steps:

[0099] Step S41: Obtain the historical operation data of the breaker;

[0100] Step S42: Sort out the independent time lines of the historical operation data of the breaker to generate an independent historical operation time line;

[0101] Step S43: Conduct a structural field simulation on the breaker performance data to obtain simulated breaker data; estimate the operation risk based on the historical operation data of the breaker for the simulated breaker data to obtain estimated risk data;

[0102] Step S44: Based on the estimated risk data, perform the maximum similarity risk matching on the independent historical operation time line to generate a similar historical operation time line;

[0103] Step S45: Use the similar historical operation timeline and the estimated risk data to give a defensive optimization hint for the breaker performance data, generate an optimization hint, and perform intelligent monitoring of the breaker.

[0104] The advantages of the present invention are as follows: obtaining the historical operation data of the breaker provides a basic support for subsequent timeline sorting and risk estimation, and making full use of the historical operation data is the key to realizing intelligent monitoring. Sorting the independent timeline of the breaker historical operation data generates an independent historical operation timeline. This independent timeline sorting helps to more clearly reflect the time evolution of the breaker operation status and provides a reference for risk matching. Performing a structural field simulation on the breaker performance data obtains the simulated breaker data. And based on the historical operation data, estimating the operation risk of the simulated data generates the estimated risk data. This risk estimation method combining simulation and historical data can more accurately predict the future operation risk of the breaker and provide a basis for the optimization hint. Performing a maximum similarity risk matching on the independent historical operation timeline based on the estimated risk data generates a similar historical operation timeline. This method of finding similar historical situations through risk matching can provide valuable reference information for the breaker performance optimization. Using the similar historical operation timeline and the estimated risk data to give a defensive optimization hint for the breaker performance data generates an optimization hint. This optimization hint generated based on simulation and historical data analysis can help to timely discover and respond to the operation risks of the breaker and realize intelligent monitoring and performance optimization. Through historical data analysis, simulated risk estimation, and historical similarity matching methods, a complete intelligent breaker online monitoring system is constructed, which can effectively predict and optimize the operation status of the breaker and provide valuable support for improving the safety and reliability of the breaker.

[0105] In an embodiment of the present invention, historical operation records of the circuit breaker under various environmental conditions are collected and saved, including operation time, number of opening and closing times, and fault records. The database records the full life cycle performance of the circuit breaker in practical applications. Regularly monitor and collect the operation status data of the circuit breaker, and enter the new operation information into the database in a timely manner. Ensure that the database records the latest historical operation status of the circuit breaker. All types of operation data in the database are uniformly formatted for subsequent analysis and calculation. Including data timestamp annotation and parameter unit unified operation. From the historical operation data of the circuit breaker, identify and extract the time points of occurrence of key events, such as the time of fault occurrence, maintenance time, and operation mode change time. Based on the above key event time points, arrange the various operation status data of the circuit breaker into an independent timeline in chronological order. The timeline reflects the complete historical trajectory of the circuit breaker from being put into operation to the present. The constructed independent historical operation timeline is displayed in a graphical manner to intuitively reflect the changes in the operation status of the circuit breaker in the time dimension. Provide a basis for subsequent risk analysis and performance optimization. According to the physical structural parameters of the circuit breaker, a structural field model is constructed, which can simulate the electromagnetic field and temperature field distribution characteristics of the circuit breaker under different working conditions. Using the above structural field model, the typical working state of the circuit breaker is numerically simulated and calculated to obtain the simulation data of its key performance parameters, such as current distribution and temperature rise. The actual operation history data of the circuit breaker is compared and analyzed with the above simulation data to evaluate the operation risks of the circuit breaker under different working conditions. Based on the above evaluation results, the estimated risk data of the circuit breaker under various working conditions is formed to provide a decision-making basis for subsequent performance optimization. This data reflects the various potential failure risks that the circuit breaker will encounter. The estimated risk data is compared with the independent historical operation timeline one by one. Find the part of the historical operation timeline that is most similar to the estimated risk. According to the comparison results, extract the time period that is most consistent with the estimated risk data from the independent historical operation timeline as the similar historical operation trajectory. Extract the similar historical operation timeline separately to form a more specific similar historical operation timeline data. This data reflects the typical operating conditions that the circuit breaker will actually encounter. Combined with similar historical operation timelines and estimated risk data, the performance weaknesses of circuit breakers under critical working conditions are deeply analyzed, and corresponding defensive optimization measures are proposed for the above performance weaknesses, such as structural parameter adjustment and monitoring means enhancement. These optimization suggestions are aimed at enhancing the reliability and robustness of circuit breakers under critical working conditions. The optimization suggestions are recorded and output in a structured form to form a complete optimization prompt report. This report provides specific decision support for subsequent intelligent monitoring and performance optimization of circuit breakers. Using the information provided in the optimization prompt report, the circuit breaker is intelligently monitored and warned, and performance anomalies that will occur are discovered and responded to in a timely manner to ensure reliable and stable operation of the circuit breaker under critical working conditions.

[0106] Preferably, step S45 includes the following steps:

[0107] Step S451: Perform joint prediction-driven processing on similar historical operation timelines and predicted risk data to generate a machine life prediction model;

[0108] Step S452: Use the machine life prediction model to perform life prediction projection on the breaker performance data to obtain predicted breaker life data;

[0109] Step S453: Perform logical inversion on the predicted breaker life data to generate breaker performance defect data;

[0110] Step S454: Perform defensive prompting on the breaker performance defect data to generate optimization prompts for implementing intelligent monitoring of the breaker.

[0111] The advantages of the present invention lie in performing joint prediction-driven processing on similar historical operation timelines and predicted risk data to generate a machine life prediction model. This method of establishing a life prediction model based on historical data and predicted risks can more accurately predict the remaining service life of the breaker, providing a basis for subsequent performance analysis. Using the machine life prediction model to perform life prediction projection on the breaker performance data to obtain predicted breaker life data, this life prediction method based on the prediction model can help timely grasp the usage status and remaining service duration of the breaker, providing a basis for subsequent defect analysis. Performing logical inversion on the predicted breaker life data to generate breaker performance defect data, this method of inferring performance defects based on life prediction data helps to specifically discover the performance problems existing in the breaker, providing an analysis basis for optimization prompts. Performing defensive prompting on the breaker performance defect data to generate optimization prompts, this method of giving optimization suggestions based on performance defect analysis can help timely discover and solve the problems that occur during the use of the breaker, realizing intelligent monitoring and optimization. Through the methods of constructing the machine life prediction model, predicting the breaker life, analyzing performance defects, and generating optimization prompts, the implementation of online monitoring of intelligent breakers is further deepened. These steps can not only predict the remaining service life of the breaker but also specifically discover and propose optimization suggestions, thereby realizing more intelligent and precise operation and maintenance of the breaker.

[0112] In the embodiments of the present invention, similar historical operating time lines and predicted risk data are fused through mathematical modeling. A machine life prediction model that comprehensively considers the actual operating history and potential risk factors is established. Each parameter of the above-mentioned machine life prediction model is deeply analyzed and optimized to ensure that it can fully reflect the life characteristics of the circuit breaker in the actual application scenario. By comparing the prediction results with the actual operating data, the model parameters are continuously optimized. An independent test data set is used to comprehensively verify the optimized machine life prediction model. Ensure that its prediction accuracy and stability indicators meet the actual application requirements, laying a foundation for subsequent life prediction analysis. The performance parameters of the circuit breaker under the current operating state, such as current and temperature, are used as input data and input into the machine life prediction model. Using the above input data, through the operation of the machine life prediction model, the predicted remaining service life of the circuit breaker under the current state is obtained. This result reflects the time point when the circuit breaker will reach failure under the current working conditions. The data of the remaining service life of the circuit breaker obtained from the above prediction calculation is recorded in a standardized format to form complete predicted circuit breaker life data. Provide a basis for subsequent performance defect analysis. Deeply analyze the predicted circuit breaker life data to identify the performance degradation and failure characteristics that the circuit breaker will exhibit in future use. According to the above performance degradation characteristics, various potential performance defects existing in the circuit breaker, such as insulation aging and contact corrosion, are deduced by means of logical reasoning. The circuit breaker performance defects are recorded in a structured form to form a complete circuit breaker performance defect database. This database provides basic support for the subsequent generation of optimization tips. For the circuit breaker performance defect data, referring to expert opinions, corresponding preventive measures are proposed, such as strengthening the insulation design and optimizing the contact structure. These measures are aimed at enhancing the reliability of the circuit breaker under critical working conditions. The above preventive measures are organized in a structured form into a complete optimization suggestion, covering improvement measures for the structure design, material selection, and monitoring scheme of the circuit breaker. The organized optimization suggestion is output and saved in the form of a report, providing detailed decision-making basis and technical support for the subsequent intelligent monitoring and performance optimization of the circuit breaker. According to the information provided in the optimization tip report, the circuit breaker is subjected to intelligent condition monitoring and early warning to timely master its operating conditions, and timely discover and correct the performance defects that will occur to ensure the stable and reliable operation of the circuit breaker.

[0113] In this specification, an intelligent circuit breaker online monitoring system is provided for implementing an intelligent circuit breaker online monitoring method as described above. The intelligent circuit breaker online monitoring system includes:

[0114] A data acquisition module, configured to obtain circuit breaker operating data; extract features from the circuit breaker operating data to generate a circuit breaker operating feature matrix; perform associated interleaved feature fusion on the circuit breaker operating feature matrix to generate complete action characteristic data;

[0115] A data display module, which is used to perform characteristic analysis on the complete action characteristic data to obtain circuit breaker classification data; assign states to the circuit breaker classification data to generate measurement state data; perform visual interaction on the measurement state data to generate interface interaction data;

[0116] A performance analysis module, which is used to perform current change analysis on the interface interaction data to obtain the circuit breaker contact separation time point; perform arc burning time analysis on the circuit breaker contact separation time point to generate circuit breaker performance data;

[0117] A fault perception and optimization module, which is used to obtain the historical operation data of the circuit breaker; perform operation risk estimation on the historical operation data of the circuit breaker and the circuit breaker performance data to obtain estimated risk data; perform defensive optimization prompts on the circuit breaker performance data based on the historical operation data of the circuit breaker and the estimated risk data to generate optimization prompts for implementing intelligent monitoring of the circuit breaker.

[0118] The beneficial effects of the present invention are as follows: By obtaining real-time circuit breaker working data, the system can accurately capture the changes in current, voltage, and temperature parameters of the circuit breaker under different working conditions, ensuring the accuracy and comprehensiveness of the data. The feature extraction technology is adopted to convert the original data into a feature matrix. This matrix can better represent the working characteristics of the circuit breaker, which is helpful for subsequent data analysis and model establishment. By associating and interweaving different features, the dynamic behavior of the circuit breaker can be more comprehensively described, avoiding the limitations of single features, and thus generating more comprehensive and accurate action characteristic data. Through characteristic analysis, different working states and modes of the circuit breaker can be identified, including normal operation, abnormal operation, and potential fault states. This helps to detect potential fault signs in advance and realize the functions of fault prediction and early warning. Presenting the measurement state data in a visual way can help operators intuitively understand the working state and trend of the circuit breaker and make timely responses and adjustments. Perform arc burning time analysis based on the contact separation time point to further evaluate the response speed and safety performance of the circuit breaker in case of faults. Combine the analysis results of current and arc burning time to generate detailed circuit breaker performance data. These data are key indicators for evaluating the operation state and safety performance of the circuit breaker. Combining the historical operation data and performance data of the circuit breaker, the system can conduct a comprehensive assessment and prediction of operation risks, including the fault modes and impacts that occur. Based on the risk assessment results, the system can generate defensive optimization suggestions, such as proposing maintenance suggestions, adjusting operation parameters, or replacing key components, to minimize the fault risk and improve the reliability of the circuit breaker.

[0119] Therefore, from any perspective, the embodiments should be regarded as exemplary and non-restrictive. The scope of the present invention is defined by the appended claims rather than the above description. Therefore, it is intended to cover all changes falling within the meaning and scope of the equivalent elements of the application documents within the present invention.

[0120] The above are only specific embodiments of the present invention, enabling those skilled in the art to understand or implement the present invention. Various modifications to these embodiments will be obvious to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to these embodiments shown herein, but rather to the broadest scope consistent with the principles and novel features invented herein.

Claims

1. An online monitoring method for an intelligent circuit breaker, characterized in that: The following steps are involved: Step S1: acquiring circuit breaker working data; performing feature extraction on the circuit breaker working data to generate a circuit breaker working feature matrix; The circuit breaker operating characteristic matrix is ​​associated and intertwined to fuse the characteristics to generate complete action characteristic data; wherein step S1 includes the following steps: Step S11: collecting circuit breaker operating data in real time through multiple high-precision sensors; Step S12: performing empirical mode decomposition on the circuit breaker operating data to obtain the circuit breaker static characteristics; Step S13: performing low-dimensional integration on the static characteristics of the circuit breaker to generate a circuit breaker operating characteristic matrix; Step S14: performing global correlation analysis on the circuit breaker operating characteristic matrix to obtain matrix global correlation data; Step S15: performing relevant feature fusion on the circuit breaker operating feature matrix according to the matrix global correlation data to generate complete action characteristic data; Step S2: Perform characteristic analysis on the complete action characteristic data to obtain circuit breaker classification data; assign status to the circuit breaker classification data to generate measurement status data; perform visual interaction on the measurement status data to generate interface interaction data; wherein step S2 includes the following steps: Step S21: performing electrical characteristic analysis on the complete action characteristic data to obtain electrical characteristic data; Step S22: performing motion performance analysis on the complete motion characteristic data to generate work performance data; Step S23: distinguishing the complete action characteristic data based on the electrical characteristic data and the working performance data to obtain circuit breaker classification data; Step S24: assigning a state to the circuit breaker classification data based on a preset state threshold set to generate measurement state data, wherein the preset state threshold set includes a current waveform gap threshold and a displacement opening range threshold; wherein step S24 includes the following steps: Step S241: grouping the circuit breaker classification data into categories to obtain closing current data and closing displacement data; Step S242: Based on a preset current waveform gap threshold, the closing current data is evaluated for a gap upper limit state to obtain current state data; based on a preset displacement opening distance range threshold, the closing displacement data is evaluated for a displacement state to generate displacement state data; wherein step S242 includes the following steps: Obtain current reference waveform data; A waveform comparison is performed on the current reference waveform data and the closing current data based on a preset current waveform gap threshold value; when the current waveform gap between the current reference waveform data and the closing current data is greater than the preset current waveform gap threshold value, the closing current data is defined as good current state data; when the current waveform gap between the current reference waveform data and the closing current data is less than the preset current waveform gap threshold value, the closing current data is defined as abnormal current state data; Perform waveform analysis on closing displacement data and closing current data to generate a current-displacement waveform curve; Based on the current-displacement waveform curve, the displacement waveform curve is measured before and after, and the displacement distance data is generated; The displacement opening distance data is evaluated for a displacement range based on a preset displacement opening distance range threshold. When the displacement opening distance data coincides with the preset displacement opening distance range threshold, the displacement opening distance data is defined as good displacement state data; when the displacement opening distance data does not coincide with the preset displacement opening distance range threshold, the displacement opening distance data is defined as abnormal displacement state data; Step S243: heterogeneously integrating the current state data and the displacement state data to generate measurement state data; Step S25: Visualize and interact with the measurement status data based on the circuit breaker classification data to generate interface interaction data; Step S3: Analyze the current change of the interface interaction data to obtain the time point of the circuit breaker electric shock separation; analyze the arcing time of the circuit breaker electric shock separation time point to generate circuit breaker performance data; Step S4: acquiring historical operation data of the circuit breaker; performing operation risk estimation on the historical operation data of the circuit breaker and the performance data of the circuit breaker to obtain estimated risk data; performing defensive optimization prompts on the performance data of the circuit breaker based on the historical operation data of the circuit breaker and the estimated risk data, generating optimization prompts to perform intelligent monitoring of the circuit breaker, wherein step S4 includes the following steps: Step S41: Obtain historical operation data of the circuit breaker; Step S42: sorting out the historical operation data of the circuit breaker in an independent timeline to generate an independent historical operation timeline; Step S43: Perform structural field simulation on the circuit breaker performance data to obtain simulated circuit breaker data; perform operation risk estimation on the simulated circuit breaker data based on the historical operation data of the circuit breaker to obtain estimated risk data; wherein the operation risk estimation is specifically: Using Bayesian network or Markov chain probability model, combined with circuit breaker performance data and historical operation data, estimate the failure probability of circuit breakers under different working conditions, consider the key functional parameters and failure modes of circuit breakers, build a multi-level risk estimation model, quantitatively evaluate the operating risks of circuit breakers under different working conditions, and output estimated risk data; Step S44: performing maximum similarity risk matching on independent historical operation timelines based on the estimated risk data to generate similar historical operation timelines; Step S45: Using similar historical operation timelines and estimated risk data to perform defensive optimization prompts on circuit breaker performance data, generate optimization prompts, and perform intelligent monitoring of circuit breakers.

2. The intelligent circuit breaker online monitoring method according to claim 1, characterized in that: Step S3 includes the following steps: Step S31: performing graphic change analysis on the interface interaction data to obtain graphic change data; Step S32: analyzing the current change of the interface interaction data based on the graphic change data to obtain the time point of the circuit breaker electric shock separation; Step S33: performing current waveform mode analysis on the interface interaction data according to the time point of the circuit breaker electric shock separation to generate arcing time data; Step S34: Perform equipment performance mapping on the arcing time data to generate circuit breaker performance data.

3. The intelligent circuit breaker online monitoring method according to claim 2, characterized in that: Step S33 includes the following steps: Step S331: performing separation point current analysis on the interface interaction data according to the circuit breaker electric shock separation time point to generate separation point electrical waveform data; Step S332: Perform dynamic waveform analysis on the electrical waveform data of the separation point to obtain waveform characteristic data; Step S333: Calculate the arcing duration of the waveform characteristic data based on the time point of the circuit breaker electric shock separation to obtain arcing time data.

4. The method for online monitoring of an intelligent circuit breaker according to claim 1, characterized in that: Step S45 includes the following steps: Step S451: performing joint prediction drive processing on similar historical operation timelines and estimated risk data to generate a machine life prediction model; Step S452: using the machine life prediction model to perform life prediction projection on the circuit breaker performance data to obtain predicted circuit breaker life data; Step S453: performing logic inversion on the predicted circuit breaker life data to generate circuit breaker performance defect data; Step S454: Provide defensive prompts for circuit breaker performance defect data and generate optimization prompts to perform intelligent monitoring of the circuit breaker.

5. An intelligent circuit breaker online monitoring system, characterized in that: Used to execute the intelligent circuit breaker online monitoring method according to claim 1, the intelligent circuit breaker online monitoring system comprises: The data acquisition module is used to obtain the circuit breaker working data; extract the features of the circuit breaker working data to generate the circuit breaker working feature matrix; perform correlation and interweaving feature fusion on the circuit breaker working feature matrix to generate complete action characteristic data; The data display module is used to analyze the complete action characteristic data to obtain the circuit breaker classification data; assign status to the circuit breaker classification data to generate measurement status data; and visualize the measurement status data to generate interface interaction data; The performance analysis module is used to analyze the current change of the interface interaction data to obtain the time point of the circuit breaker electric shock separation; analyze the arcing time of the circuit breaker electric shock separation time point to generate circuit breaker performance data; The fault perception optimization module is used to obtain the historical operation data of the circuit breaker; estimate the operation risk of the historical operation data of the circuit breaker and the circuit breaker performance data to obtain the estimated risk data; based on the historical operation data of the circuit breaker and the estimated risk data, provide defensive optimization prompts for the circuit breaker performance data, generate optimization prompts, and perform intelligent monitoring of the circuit breaker.

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