Outdoor intelligent power distribution circuit breaker monitoring management system and method thereof

Abstract

The invention provides an outdoor intelligent power distribution circuit breaker monitoring management system and method, and relates to the technical field of electric power automation control, and the system comprises an intelligent sensing monitoring module, an edge calculation processing module, a potential fault recognition module and a cloud acquisition optimization module. Monitoring a current working state and a real-time environment condition of the outdoor power distribution circuit breaker, and generating initial circuit breaker operation data; analyzing and filtering the initial circuit breaker operation data to obtain target circuit breaker operation data; constructing a circuit breaker potential fault diagnosis model, and performing fault identification on the target circuit breaker operation data to obtain potential circuit breaker fault points; the historical circuit breaker operation data of the outdoor power distribution circuit breaker is acquired through the cloud data center, and the circuit breaker potential fault diagnosis model is verified and optimized, so that real-time fault identification and monitoring management can be performed on the outdoor power distribution circuit breaker, the operation and maintenance efficiency of a power grid is improved, the operation cost is reduced, and the safety and continuity of power supply are guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of electric power automation control, and in particular to an outdoor intelligent distribution circuit breaker monitoring and management system and a method thereof. Background Art

[0002] With the continuous growth of electricity demand and the continuous development of smart grid technology, traditional outdoor distribution circuit breakers have problems in operation and maintenance costs and fault response speed.

[0003] At present, most outdoor power distribution circuit breakers rely on manual regular inspections and passive maintenance after failures, lacking the ability of real-time monitoring and preventive maintenance. This model not only increases operating costs, but also takes a long time to respond to sudden failures, seriously affecting the stable operation of the power grid and the quality of power supply.

[0004] Therefore, it is necessary to provide an outdoor intelligent distribution circuit breaker monitoring and management system and method thereof to solve the above technical problems. Summary of the invention

[0005] In order to solve the above technical problems, the present invention provides an outdoor intelligent distribution circuit breaker monitoring and management system and method thereof, which are used to solve the problem that most of the current outdoor distribution circuit breakers rely on manual regular inspections and passive maintenance modes after failures, lack the ability of real-time monitoring and preventive maintenance, which not only increases the operating costs, but also has a long response time when facing sudden failures, seriously affecting the stable operation of the power grid and the quality of power supply.

[0006] The present invention provides an outdoor intelligent distribution circuit breaker monitoring and management system, the monitoring and management system comprising: An intelligent sensor monitoring module is used to monitor the current working status and real-time environmental conditions of outdoor power distribution circuit breakers through embedded sensors, and generate corresponding initial circuit breaker operation data; An edge computing processing module, used for analyzing and filtering the initial circuit breaker operation data to obtain corresponding target circuit breaker operation data; A potential fault identification module is used to construct a potential fault diagnosis model for a circuit breaker, perform fault identification on the target circuit breaker operation data, and obtain a corresponding potential circuit breaker fault point; The cloud acquisition optimization module is used to obtain the historical circuit breaker operation data of the outdoor power distribution circuit breaker through the cloud data center, and verify and optimize the circuit breaker potential fault diagnosis model.

[0007] Preferably, the embedded sensor includes a temperature sensor, a current and voltage detection sensor, an ambient humidity sensor, and an ambient gas concentration sensor.

[0008] Preferably, the shell material of the outdoor power distribution circuit breaker is an IP67-level sealing material, and the outdoor power distribution circuit breaker is equipped with a temperature-controlled fan and a heat sink.

[0009] Preferably, the edge computing processing module is used to analyze and filter the initial circuit breaker operation data to obtain corresponding target circuit breaker operation data, specifically including: Cleaning and compressing the initial circuit breaker operation data to generate corresponding first circuit breaker operation data; The calculation formula for compressing the initial circuit breaker operation data based on discrete cosine transform technology is as follows: In the formula, represents the initial circuit breaker operation data after the kth compression process; represents the nth initial circuit breaker operation data; N represents the number of initial circuit breaker operation data; The first circuit breaker operation data is subjected to weighted average filtering to obtain corresponding second circuit breaker operation data. The corresponding calculation formula is as follows: In the formula, represents the kth second circuit breaker operation data; Indicates the operating data of the first circuit breaker at km; represents the mth weight coefficient; M represents the window size of the filter; Performing Fourier transform on the second circuit breaker operation data, extracting the frequency spectrum features in the second circuit breaker operation data, and obtaining the corresponding target circuit breaker operation data. The corresponding calculation formula is as follows: In the formula, represents the qth target circuit breaker operation data; K represents the number of second circuit breaker operation data; represents the kth second circuit breaker operation data; j represents an imaginary unit; e represents a natural constant; Represents the complex exponential function of the Fourier transform.

[0010] Preferably, the potential fault identification module is used to construct a potential fault diagnosis model for a circuit breaker, perform fault identification on the target circuit breaker operation data, and obtain the corresponding potential circuit breaker fault point, specifically including: The target circuit breaker operation features corresponding to the target circuit breaker operation data are extracted, and the target circuit breaker operation features are feature classified based on a support vector machine. The corresponding optimization problem is as follows: In the formula, represents the weight vector of the u-th support vector machine, which is used to determine the direction of the classification hyperplane; represents the bias term of the u-th support vector machine, which is used to determine the distance between the classification hyperplane and the origin; represents the slack variable when the vth target circuit breaker operation feature is linearly inseparable in the uth support vector machine; C represents the regularization parameter, which is used to control the trade-off between classification interval and classification error; R represents the number of target circuit breaker operation features; min represents the minimum value operation.

[0011] Preferably, the constraints corresponding to the optimization problem are as follows: In the formula, Indicates the feature category label corresponding to the vth target circuit breaker operation feature; represents the operating characteristics of the vth target circuit breaker; represents the weight vector of the u-th support vector machine, which is used to determine the direction of the classification hyperplane; represents the bias term of the u-th support vector machine, which is used to determine the distance between the classification hyperplane and the origin; represents the slack variable when the vth target circuit breaker operation feature is linearly inseparable in the uth support vector machine; R represents the number of target circuit breaker operation features; The abnormal circuit breaker operation feature and the corresponding abnormal circuit breaker operation data, namely the potential circuit breaker fault point, are determined according to the feature category label corresponding to the target circuit breaker operation feature.

[0012] Preferably, the cloud acquisition optimization module is used to obtain the historical circuit breaker operation data of the outdoor power distribution circuit breaker through the cloud data center to verify and optimize the circuit breaker potential fault diagnosis model, specifically including: Acquiring historical circuit breaker operation data of the outdoor power distribution circuit breaker through the cloud data center, extracting historical circuit breaker operation features corresponding to the historical circuit breaker operation data and inputting them into the circuit breaker potential fault diagnosis model to obtain a predicted circuit breaker fault point; Acquire historical circuit breaker fault points corresponding to the historical circuit breaker operation data, and determine a confusion matrix corresponding to the circuit breaker potential fault diagnosis model according to the predicted circuit breaker fault points and the historical circuit breaker fault points; The elements of the confusion matrix include true positive examples, false positive examples, true negative examples and false negative examples, wherein the true positive examples are the correctly identified fault points; the false positive examples are the incorrectly identified fault points; the true negative examples are the correctly identified non-fault points; and the false negative examples are the incorrectly identified non-fault points. Based on the confusion matrix, the fault identification performance index corresponding to the circuit breaker potential fault diagnosis model is calculated, wherein the fault identification performance index includes accuracy, precision, recall, F1 score and false positive rate; The calculation formula of the accuracy is: In the formula, It represents the accuracy of the circuit breaker potential fault diagnosis model; represents a true positive, i.e., the fault point is correctly identified; represents a true counterexample, i.e., correctly identifying a non-fault point; represents a false positive, i.e., a fault point is incorrectly identified; represents a false counterexample, i.e., a non-fault point is incorrectly identified; The calculation formula of the accuracy is: In the formula, It represents the accuracy rate corresponding to the potential fault diagnosis model of the circuit breaker; represents a true positive, i.e., the fault point is correctly identified; represents a false positive, i.e., a fault point is incorrectly identified; The calculation formula of the recall rate is: In the formula, represents the recall rate corresponding to the circuit breaker potential fault diagnosis model; represents a true positive, i.e., the fault point is correctly identified; represents a false counterexample, i.e., a non-fault point is incorrectly identified; The calculation formula of the F1 score is: In the formula, It represents the F1 score corresponding to the circuit breaker potential fault diagnosis model; It represents the accuracy rate corresponding to the potential fault diagnosis model of the circuit breaker; represents the recall rate corresponding to the circuit breaker potential fault diagnosis model; The calculation formula of the false positive rate is: In the formula, represents the false positive rate corresponding to the circuit breaker potential fault diagnosis model; represents a false positive, i.e., a fault point is incorrectly identified; represents a true counterexample, i.e., correctly identifying a non-fault point; The fault identification performance index corresponding to the circuit breaker potential fault diagnosis model is analyzed, and the precision and recall are weighed to verify the fault identification performance of the circuit breaker potential fault diagnosis model, and the circuit breaker potential fault diagnosis model is adjusted and optimized based on the performance verification result.

[0013] Preferably, after obtaining the potential circuit breaker failure point, the potential circuit breaker failure point is sent to the management end through the Internet of Things platform; The management end monitors the operating status of the outdoor power distribution circuit breaker in real time through the Internet of Things platform, and remotely configures the operating parameters of the outdoor power distribution circuit breaker according to the monitoring results.

[0014] A monitoring and management method for an outdoor intelligent power distribution circuit breaker, the monitoring and management method comprising: Through embedded sensors, the current working status and real-time environmental conditions of outdoor distribution circuit breakers are monitored to generate corresponding initial circuit breaker operation data; Analyzing and filtering the initial circuit breaker operation data to obtain corresponding target circuit breaker operation data; Constructing a potential fault diagnosis model for a circuit breaker, performing fault identification on the target circuit breaker operation data, and obtaining corresponding potential circuit breaker fault points; The historical circuit breaker operation data of the outdoor power distribution circuit breaker is obtained through the cloud data center to verify and optimize the circuit breaker potential fault diagnosis model.

[0015] Compared with the related art, the outdoor intelligent distribution circuit breaker monitoring and management system and method provided by the present invention have the following beneficial effects: The present invention uses an intelligent sensor monitoring module, an edge computing processing module, a potential fault identification module and a cloud acquisition optimization module to monitor the current working state and real-time environmental conditions of the outdoor distribution circuit breaker through an embedded sensor, and generate corresponding initial circuit breaker operation data; analyze and filter the initial circuit breaker operation data to obtain corresponding target circuit breaker operation data; construct a circuit breaker potential fault diagnosis model, perform fault identification on the target circuit breaker operation data, and obtain corresponding potential circuit breaker fault points; obtain historical circuit breaker operation data of the outdoor distribution circuit breaker through a cloud data center, verify and optimize the circuit breaker potential fault diagnosis model, so that real-time fault identification and monitoring management of the outdoor distribution circuit breaker can be performed, which significantly improves the operation and maintenance efficiency of the power grid, reduces operating costs, and ensures the safety and continuity of power supply.

[0016] The present invention can monitor and collect the current working status and surrounding environmental conditions of the outdoor distribution circuit breaker in real time through embedded sensors, and analyze and filter the collected data, thereby reducing the amount of data transmission and improving data processing efficiency; the system of the present invention can accurately identify the potential fault points of the outdoor distribution circuit breaker through a potential fault diagnosis model, thereby reducing the risk of unexpected power outages, ensuring the continuity and stability of power supply, improving the adaptability and flexibility of the monitoring and management system, and improving the operation and maintenance efficiency and economic benefits of the power grid, reducing the maintenance cost of the power grid. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1A system block diagram of an outdoor intelligent power distribution circuit breaker monitoring and management system of the present invention; Figure 2 is a schematic diagram of elements of the confusion matrix of the present invention; Figure 3 A schematic diagram of data transmission of the Internet of Things platform of the present invention; Figure 4 The present invention is a flow chart of a method for monitoring and managing an outdoor intelligent power distribution circuit breaker. DETAILED DESCRIPTION

[0018] The present invention will be further described below in conjunction with the accompanying drawings and implementation modes.

[0019] Embodiment 1

[0020] like Figure 1 As shown, an outdoor intelligent distribution circuit breaker monitoring and management system, the monitoring and management system comprises: An intelligent sensor monitoring module is used to monitor the current working status and real-time environmental conditions of outdoor power distribution circuit breakers through embedded sensors, and generate corresponding initial circuit breaker operation data; The initial circuit breaker operation data refers to the working state and environmental condition data of the outdoor power distribution circuit breaker at the current moment without being analyzed, filtered or processed.

[0021] It can be understood that the intelligent sensor monitoring module integrates a high-precision, high-reliability embedded sensor network, which can monitor the electrical parameters of the outdoor distribution circuit breaker in real time, such as current, voltage, and surrounding environmental conditions, such as humidity, pollution level, etc., so as to obtain the initial circuit breaker operation data that accurately reflects the current working status of the circuit breaker and the degree of environmental impact.

[0022] An edge computing processing module, used for analyzing and filtering the initial circuit breaker operation data to obtain corresponding target circuit breaker operation data; It should be noted that the target circuit breaker operation data refers to the operation data of the outdoor distribution circuit breaker after analysis and filtering. The edge computing processing module can use edge computing technology to clean, compress, extract features and filter noise from the initial operation data, effectively eliminate irrelevant or redundant information, and extract the target circuit breaker operation data for evaluating the circuit breaker status, thereby significantly reducing the amount of data transmission and improving data processing efficiency.

[0023] A potential fault identification module is used to construct a potential fault diagnosis model for a circuit breaker, perform fault identification on the target circuit breaker operation data, and obtain a corresponding potential circuit breaker fault point; It can be understood that the circuit breaker potential fault diagnosis model refers to a model used to identify fault conditions during the operation of an outdoor distribution circuit breaker; and the potential circuit breaker fault point refers to an identified circuit breaker operation data point where a fault condition may exist.

[0024] The potential fault identification module can use the circuit breaker potential fault diagnosis model to identify faults in the target circuit breaker operation data after edge computing processing, obtain early signs or abnormal patterns that may indicate faults, and accurately locate potential circuit breaker fault points, thereby helping to take measures in advance to avoid faults, and can guide the formulation of subsequent maintenance plans and reduce unplanned downtime.

[0025] The cloud acquisition optimization module is used to obtain the historical circuit breaker operation data of the outdoor power distribution circuit breaker through the cloud data center, and verify and optimize the circuit breaker potential fault diagnosis model.

[0026] The historical circuit breaker operation data refers to the operation data of the outdoor power distribution circuit breaker in the past period of time. The cloud acquisition optimization module can obtain and integrate the historical circuit breaker operation data by seamlessly connecting with the cloud data center.

[0027] Then, the module can verify the fault identification performance of the circuit breaker potential fault diagnosis model, and then continuously optimize the fault prediction capability of the circuit breaker based on the verification results, so as to achieve comprehensive monitoring and precise management of the circuit breaker status and ensure the safe and efficient operation of the power system.

[0028] In a specific implementation process, the embedded sensor includes a temperature sensor, a current and voltage detection sensor, an ambient humidity sensor, and an ambient gas concentration sensor.

[0029] It should be noted that embedded sensors include various types of sensors, including temperature sensors for monitoring temperature changes of circuit breakers, current and voltage detection sensors for real-time detection of current and voltage parameters of circuit breakers, environmental humidity sensors for evaluating environmental humidity conditions, and environmental gas concentration sensors for analyzing the concentration distribution of harmful gases or specific gases in the environment.

[0030] The shell material of the outdoor power distribution circuit breaker is an IP67 grade sealing material, and the outdoor power distribution circuit breaker is equipped with a temperature control fan and a heat sink.

[0031] It is understandable that the shell material used in outdoor distribution circuit breakers has IP67-level sealing performance, which can effectively prevent dust intrusion and can withstand short-term water immersion, thereby ensuring the stable operation of the circuit breaker in harsh outdoor environments.

[0032] At the same time, the circuit breaker is equipped with an efficient temperature-controlled fan and heat sink assembly, which can optimize the thermal management of the circuit breaker and ensure that the electrical components can maintain a suitable operating temperature during long-term high-load operation, thereby extending the service life of the circuit breaker and improving the reliability and stability of the overall monitoring and management system.

[0033] The edge computing processing module is used to analyze and filter the initial circuit breaker operation data to obtain corresponding target circuit breaker operation data, specifically including: Cleaning and compressing the initial circuit breaker operation data to generate corresponding first circuit breaker operation data; The calculation formula for compressing the initial circuit breaker operation data based on discrete cosine transform technology is as follows: In the formula, represents the initial circuit breaker operation data after the kth compression process; represents the nth initial circuit breaker operation data; N represents the number of initial circuit breaker operation data; The first circuit breaker operation data is subjected to weighted average filtering to obtain corresponding second circuit breaker operation data. The corresponding calculation formula is as follows: In the formula, represents the kth second circuit breaker operation data; Indicates the operating data of the first circuit breaker at km; represents the mth weight coefficient; M represents the window size of the filter; Performing Fourier transform on the second circuit breaker operation data, extracting the frequency spectrum features in the second circuit breaker operation data, and obtaining the corresponding target circuit breaker operation data. The corresponding calculation formula is as follows: In the formula, represents the qth target circuit breaker operation data; K represents the number of second circuit breaker operation data; represents the kth second circuit breaker operation data; j represents an imaginary unit; e represents a natural constant; Represents the complex exponential function of the Fourier transform.

[0034] Among them, the edge computing processing module can clean the initial circuit breaker operation data and remove invalid or abnormal data points to ensure data quality. Then, the module can use discrete cosine transform (DCT) technology to compress the cleaned data to generate more compact first circuit breaker operation data that retains key information, thereby effectively reducing the data dimension.

[0035] Furthermore, the first circuit breaker operation data can be subjected to weighted average filtering processing. By introducing a weight coefficient, differentiated processing can be performed according to the importance of the data to obtain smoother second circuit breaker operation data, thereby effectively reducing data noise interference and improving data accuracy.

[0036] Finally, the second circuit breaker operation data can be processed by Fourier transform (FFT), and the frequency characteristics in the data can be extracted through spectrum analysis, so as to obtain the periodic changes and potential fault characteristics in the data and obtain the target circuit breaker operation data.

[0037] The potential fault identification module is used to construct a potential fault diagnosis model for a circuit breaker, perform fault identification on the target circuit breaker operation data, and obtain the corresponding potential circuit breaker fault point, specifically including: The target circuit breaker operation features corresponding to the target circuit breaker operation data are extracted, and the target circuit breaker operation features are feature classified based on a support vector machine. The corresponding optimization problem is as follows: In the formula, represents the weight vector of the u-th support vector machine, which is used to determine the direction of the classification hyperplane; represents the bias term of the u-th support vector machine, which is used to determine the distance between the classification hyperplane and the origin; represents the slack variable when the vth target circuit breaker operation feature is linearly inseparable in the uth support vector machine; C represents the regularization parameter, which is used to control the trade-off between classification interval and classification error; R represents the number of target circuit breaker operation features; min represents the minimum value operation.

[0038] The constraints corresponding to the optimization problem are as follows: In the formula, Indicates the feature category label corresponding to the vth target circuit breaker operation feature; represents the operating characteristics of the vth target circuit breaker; represents the weight vector of the u-th support vector machine, which is used to determine the direction of the classification hyperplane; represents the bias term of the u-th support vector machine, which is used to determine the distance between the classification hyperplane and the origin; represents the slack variable when the vth target circuit breaker operation feature is linearly inseparable in the uth support vector machine; R represents the number of target circuit breaker operation features; The abnormal circuit breaker operation feature and the corresponding abnormal circuit breaker operation data, namely the potential circuit breaker fault point, are determined according to the feature category label corresponding to the target circuit breaker operation feature.

[0039] Among them, the potential fault identification module can extract key information from the target circuit breaker operation data, namely, the target circuit breaker operation characteristics, and these characteristics usually include key parameters such as current, voltage, temperature, and switching times, so as to comprehensively reflect the operating status of the circuit breaker.

[0040] Then, the extracted target circuit breaker operation features can be classified based on the support vector machine (SVM) algorithm. The SVM algorithm can divide the feature space into different category areas by constructing a classification hyperplane, thereby achieving accurate classification of features.

[0041] It should be noted that the optimization problem in the SVM algorithm can maximize the separation of feature points of different categories by determining the optimal weight vector and bias term, while minimizing the classification error. Among them, the weight vector determines the direction of the classification hyperplane, and the bias term determines the distance between the classification hyperplane and the origin.

[0042] In addition, in order to deal with the situation of linear inseparability, a slack variable can be introduced to allow some feature points to be misclassified, but they will be punished accordingly. The regularization parameter is used to balance the weight between the classification interval and the classification error to ensure the generalization ability of the circuit breaker potential fault diagnosis model.

[0043] Furthermore, the constraints of the optimization problem can ensure the accuracy and consistency of the classification results. Specifically, each target circuit breaker operation feature corresponds to a feature category label, that is, the category to which the feature belongs. The SVM algorithm can calculate the distance from the feature point to the classification hyperplane based on the weight vector and the bias term, and judge the category of the feature point based on the positive or negative value of the distance. At the same time, the slack variable allows the feature point to deviate from the classification hyperplane to a certain extent to handle the situation of linear inseparability.

[0044] Finally, the abnormal features can be determined according to the feature category labels corresponding to the target circuit breaker operation features, and the operation data corresponding to these abnormal features are the potential circuit breaker failure points.

[0045] Through the above method, the potential fault identification module can extract the operating characteristics of the target circuit breaker, classify and process them using the SVM algorithm, and determine the abnormal characteristics based on the optimization problem and constraints, so as to accurately locate the potential fault point, timely discover and deal with potential fault hazards, and ensure the safe and stable operation of the power system.

[0046] The cloud acquisition optimization module is used to obtain the historical circuit breaker operation data of the outdoor power distribution circuit breaker through the cloud data center to verify and optimize the circuit breaker potential fault diagnosis model, specifically including: Acquiring historical circuit breaker operation data of the outdoor power distribution circuit breaker through the cloud data center, extracting historical circuit breaker operation features corresponding to the historical circuit breaker operation data and inputting them into the circuit breaker potential fault diagnosis model to obtain a predicted circuit breaker fault point; Acquire historical circuit breaker fault points corresponding to the historical circuit breaker operation data, and determine a confusion matrix corresponding to the circuit breaker potential fault diagnosis model according to the predicted circuit breaker fault points and the historical circuit breaker fault points; The elements of the confusion matrix include true positive examples, false positive examples, true negative examples and false negative examples, wherein the true positive examples are the correctly identified fault points; the false positive examples are the incorrectly identified fault points; the true negative examples are the correctly identified non-fault points; and the false negative examples are the incorrectly identified non-fault points. Based on the confusion matrix, the fault identification performance index corresponding to the circuit breaker potential fault diagnosis model is calculated, wherein the fault identification performance index includes accuracy, precision, recall, F1 score and false positive rate; The calculation formula of the accuracy is: In the formula, It represents the accuracy of the circuit breaker potential fault diagnosis model; represents a true positive, i.e., the fault point is correctly identified; represents a true counterexample, i.e., correctly identifying a non-fault point; represents a false positive, i.e., a fault point is incorrectly identified; represents a false counterexample, i.e., a non-fault point is incorrectly identified; The calculation formula of the accuracy is: In the formula, It represents the accuracy rate corresponding to the potential fault diagnosis model of the circuit breaker; represents a true positive, i.e., the fault point is correctly identified; represents a false positive, i.e., a fault point is incorrectly identified; The calculation formula of the recall rate is: In the formula, represents the recall rate corresponding to the circuit breaker potential fault diagnosis model; represents a true positive, i.e., the fault point is correctly identified; represents a false counterexample, i.e., a non-fault point is incorrectly identified; The calculation formula of the F1 score is: In the formula, It represents the F1 score corresponding to the circuit breaker potential fault diagnosis model; It represents the accuracy rate corresponding to the potential fault diagnosis model of the circuit breaker; represents the recall rate corresponding to the circuit breaker potential fault diagnosis model; The calculation formula of the false positive rate is: In the formula, represents the false positive rate corresponding to the circuit breaker potential fault diagnosis model; represents a false positive, i.e., a fault point is incorrectly identified; represents a true counterexample, i.e., correctly identifying a non-fault point; The fault identification performance index corresponding to the circuit breaker potential fault diagnosis model is analyzed, and the precision and recall are weighed to verify the fault identification performance of the circuit breaker potential fault diagnosis model, and the circuit breaker potential fault diagnosis model is adjusted and optimized based on the performance verification result.

[0047] In practical applications, the cloud acquisition optimization module can efficiently obtain historical data accumulated over a long period of time from outdoor distribution circuit breakers through the data retrieval and transmission capabilities of the cloud data center, and extract key operating characteristics to input into the circuit breaker potential fault diagnosis model. Based on these characteristics, the model can predict possible fault points, that is, the location or time period where a fault may occur.

[0048] In order to evaluate the prediction accuracy of the model, the actual failure points can be determined from the historical data and compared with the failure points predicted by the model. Figure 2 As shown, the comparison result is intuitively reflected through the confusion matrix, which includes true positive examples, that is, the situation where the model correctly identifies the fault point, false positive examples, that is, the situation where the model incorrectly judges that there is a fault but there is no fault in fact, true negative examples, that is, the situation where the model correctly judges that there is no fault point, and false negative examples, that is, the situation where the model incorrectly judges that there is no fault but there is a fault in fact.

[0049] Based on the confusion matrix, key fault identification performance indicators can be further calculated, including accuracy, precision, recall, F1 score, and false positive rate. Then, each fault identification performance indicator can be deeply analyzed, and combined with the actual application scenario, the balance between precision and recall can be weighed to verify the fault identification ability of the circuit breaker potential fault diagnosis model. According to the verification results, the circuit breaker potential fault diagnosis model can be adjusted and optimized accordingly, including adjusting algorithm parameters, increasing feature dimensions, etc., so as to continuously improve the prediction accuracy and practicality of the model and ensure the safe and stable operation of the outdoor power distribution system.

[0050] After obtaining the potential circuit breaker failure point, sending the potential circuit breaker failure point to the management end through the Internet of Things platform; The management end monitors the operating status of the outdoor power distribution circuit breaker in real time through the Internet of Things platform, and remotely configures the operating parameters of the outdoor power distribution circuit breaker according to the monitoring results.

[0051] In practical applications, such as Figure 3 As shown, after the potential circuit breaker fault point is identified, the specific information of the potential circuit breaker fault point can be transmitted to the central management terminal in real time and accurately through the Internet of Things platform, and then sent to the management end in time.

[0052] At the same time, the central management terminal can remotely monitor the working status of outdoor power distribution circuit breakers based on the Internet of Things platform, including key operating indicators such as current, voltage, and temperature, and display the monitoring and management results to the management terminal. Based on these monitoring data and analysis results, the management terminal can efficiently remotely adjust and optimize the various operating parameters of outdoor power distribution circuit breakers, thereby effectively preventing circuit breaker failures and improving the stability and safety of the entire distribution system.

[0053] Embodiment 2 like Figure 4 As shown, a monitoring and management method for an outdoor intelligent distribution circuit breaker, the monitoring and management method comprising: S1, monitors the current working status and real-time environmental conditions of the outdoor distribution circuit breaker through embedded sensors, and generates corresponding initial circuit breaker operation data; S2, analyzing and filtering the initial circuit breaker operation data to obtain corresponding target circuit breaker operation data; S3, constructing a potential fault diagnosis model for a circuit breaker, performing fault identification on the target circuit breaker operation data, and obtaining a corresponding potential circuit breaker fault point; S4, obtaining historical circuit breaker operation data of the outdoor power distribution circuit breaker through the cloud data center, and verifying and optimizing the circuit breaker potential fault diagnosis model.

[0054] Through the introduction of the above embodiments, the present invention uses an outdoor intelligent distribution circuit breaker monitoring and management system and its method, through an intelligent sensor monitoring module, an edge computing processing module, a potential fault identification module and a cloud acquisition optimization module, and can monitor the current working status and real-time environmental conditions of the outdoor distribution circuit breaker through an embedded sensor, and generate corresponding initial circuit breaker operation data; analyze and filter the initial circuit breaker operation data to obtain the corresponding target circuit breaker operation data; construct a circuit breaker potential fault diagnosis model, identify faults on the target circuit breaker operation data, and obtain the corresponding potential circuit breaker fault point; obtain the historical circuit breaker operation data of the outdoor distribution circuit breaker through the cloud data center, verify and optimize the circuit breaker potential fault diagnosis model, so that the outdoor distribution circuit breaker can be real-time fault identified and monitored and managed, significantly improving the power grid operation and maintenance efficiency, reducing operating costs, and ensuring the safety and continuity of power supply.

[0055] The present invention can monitor and collect the current working status and surrounding environmental conditions of the outdoor distribution circuit breaker in real time through embedded sensors, and analyze and filter the collected data, thereby reducing the amount of data transmission and improving data processing efficiency; the system of the present invention can accurately identify the potential fault points of the outdoor distribution circuit breaker through a potential fault diagnosis model, thereby reducing the risk of unexpected power outages, ensuring the continuity and stability of power supply, improving the adaptability and flexibility of the monitoring and management system, and can improve the efficiency and economic benefits of power grid operation and maintenance, and reduce power grid maintenance costs.

[0056] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0057] Those skilled in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable storage medium, and the storage medium includes a read-only memory (ROM), a random access memory (RAM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), a one-time programmable read-only memory (OTPROM), an electronically erasable rewritable read-only memory (EEPROM), a compact disc (CD-ROM) or other optical disc storage, magnetic disk storage, magnetic tape storage, or any other computer-readable medium that can be used to carry or store data.

[0058] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

Claims

1. An outdoor intelligent distribution circuit breaker monitoring and management system, characterized in that: The monitoring management system comprises: An intelligent sensor monitoring module is used to monitor the current working status and real-time environmental conditions of outdoor power distribution circuit breakers through embedded sensors, and generate corresponding initial circuit breaker operation data; An edge computing processing module, used for analyzing and filtering the initial circuit breaker operation data to obtain corresponding target circuit breaker operation data; A potential fault identification module is used to construct a potential fault diagnosis model for a circuit breaker, perform fault identification on the target circuit breaker operation data, and obtain a corresponding potential circuit breaker fault point; The cloud acquisition optimization module is used to obtain the historical circuit breaker operation data of the outdoor power distribution circuit breaker through the cloud data center, and verify and optimize the circuit breaker potential fault diagnosis model.

2. The outdoor intelligent distribution circuit breaker monitoring and management system according to claim 1 is characterized in that: The embedded sensors include a temperature sensor, a current and voltage detection sensor, an environmental humidity sensor, and an environmental gas concentration sensor.

3. The outdoor intelligent distribution circuit breaker monitoring and management system according to claim 1 is characterized in that: The shell material of the outdoor power distribution circuit breaker is an IP67 grade sealing material, and the outdoor power distribution circuit breaker is equipped with a temperature control fan and a heat sink.

4. The outdoor intelligent distribution circuit breaker monitoring and management system according to claim 1 is characterized in that: The edge computing processing module is used to analyze and filter the initial circuit breaker operation data to obtain corresponding target circuit breaker operation data, specifically including: Cleaning and compressing the initial circuit breaker operation data to generate corresponding first circuit breaker operation data; The calculation formula for compressing the initial circuit breaker operation data based on discrete cosine transform technology is as follows: In the formula, represents the initial circuit breaker operation data after the kth compression process; represents the nth initial circuit breaker operation data; N represents the number of initial circuit breaker operation data; The first circuit breaker operation data is subjected to weighted average filtering to obtain corresponding second circuit breaker operation data. The corresponding calculation formula is as follows: In the formula, represents the kth second circuit breaker operation data; Indicates the operating data of the first circuit breaker at km; represents the mth weight coefficient; M represents the window size of the filter; Performing Fourier transform on the second circuit breaker operation data, extracting the frequency spectrum features in the second circuit breaker operation data, and obtaining the corresponding target circuit breaker operation data. The corresponding calculation formula is as follows: In the formula, represents the qth target circuit breaker operation data; K represents the number of second circuit breaker operation data; represents the kth second circuit breaker operation data; j represents an imaginary unit; e represents a natural constant; Represents the complex exponential function of the Fourier transform.

5. The outdoor intelligent distribution circuit breaker monitoring and management system according to claim 1 is characterized in that: The potential fault identification module is used to construct a potential fault diagnosis model for a circuit breaker, perform fault identification on the target circuit breaker operation data, and obtain the corresponding potential circuit breaker fault point, specifically including: The target circuit breaker operation features corresponding to the target circuit breaker operation data are extracted, and the target circuit breaker operation features are feature classified based on a support vector machine. The corresponding optimization problem is as follows: In the formula, represents the weight vector of the u-th support vector machine, which is used to determine the direction of the classification hyperplane; represents the bias term of the u-th support vector machine, which is used to determine the distance between the classification hyperplane and the origin; represents the slack variable when the vth target circuit breaker operation feature is linearly inseparable in the uth support vector machine; C represents the regularization parameter, which is used to control the trade-off between classification interval and classification error; R represents the number of target circuit breaker operation features; min represents the minimum value operation.

6. The outdoor intelligent distribution circuit breaker monitoring and management system according to claim 5, characterized in that: The constraints corresponding to the optimization problem are as follows: In the formula, Indicates the feature category label corresponding to the vth target circuit breaker operation feature; represents the operating characteristics of the vth target circuit breaker; represents the weight vector of the u-th support vector machine, which is used to determine the direction of the classification hyperplane; represents the bias term of the u-th support vector machine, which is used to determine the distance between the classification hyperplane and the origin; represents the slack variable when the vth target circuit breaker operation feature is linearly inseparable in the uth support vector machine; R represents the number of target circuit breaker operation features; The abnormal circuit breaker operation feature and the corresponding abnormal circuit breaker operation data, namely the potential circuit breaker failure point, are determined according to the feature category label corresponding to the target circuit breaker operation feature.

7. The outdoor intelligent distribution circuit breaker monitoring and management system according to claim 1 is characterized in that: The cloud acquisition optimization module is used to obtain the historical circuit breaker operation data of the outdoor power distribution circuit breaker through the cloud data center to verify and optimize the circuit breaker potential fault diagnosis model, specifically including: Acquiring historical circuit breaker operation data of the outdoor power distribution circuit breaker through the cloud data center, extracting historical circuit breaker operation features corresponding to the historical circuit breaker operation data and inputting them into the circuit breaker potential fault diagnosis model to obtain a predicted circuit breaker fault point; Acquire historical circuit breaker fault points corresponding to the historical circuit breaker operation data, and determine a confusion matrix corresponding to the circuit breaker potential fault diagnosis model according to the predicted circuit breaker fault points and the historical circuit breaker fault points; The elements of the confusion matrix include true positive examples, false positive examples, true negative examples and false negative examples, wherein the true positive examples are the correctly identified fault points; the false positive examples are the incorrectly identified fault points; the true negative examples are the correctly identified non-fault points; and the false negative examples are the incorrectly identified non-fault points. Based on the confusion matrix, the fault identification performance index corresponding to the circuit breaker potential fault diagnosis model is calculated, wherein the fault identification performance index includes accuracy, precision, recall, F1 score and false positive rate; The calculation formula of the accuracy is: In the formula, It represents the accuracy of the circuit breaker potential fault diagnosis model; represents a true positive, i.e., the fault point is correctly identified; represents a true counterexample, i.e., correctly identifying a non-fault point; represents a false positive, i.e., a fault point is incorrectly identified; represents a false counterexample, i.e., a non-fault point is incorrectly identified; The calculation formula of the accuracy is: In the formula, It represents the accuracy rate corresponding to the potential fault diagnosis model of the circuit breaker; represents a true positive, i.e., the fault point is correctly identified; represents a false positive, i.e., a fault point is incorrectly identified; The calculation formula of the recall rate is: In the formula, represents the recall rate corresponding to the circuit breaker potential fault diagnosis model; represents a true positive, i.e., the fault point is correctly identified; represents a false counterexample, i.e., a non-fault point is incorrectly identified; The calculation formula of the F1 score is: In the formula, It represents the F1 score corresponding to the circuit breaker potential fault diagnosis model; It represents the accuracy rate corresponding to the potential fault diagnosis model of the circuit breaker; represents the recall rate corresponding to the circuit breaker potential fault diagnosis model; The calculation formula of the false positive rate is: In the formula, represents the false positive rate corresponding to the circuit breaker potential fault diagnosis model; represents a false positive, i.e., a fault point is incorrectly identified; represents a true counterexample, i.e., correctly identifying a non-fault point; The fault identification performance index corresponding to the circuit breaker potential fault diagnosis model is analyzed, and the precision and recall are weighed to verify the fault identification performance of the circuit breaker potential fault diagnosis model, and the circuit breaker potential fault diagnosis model is adjusted and optimized based on the performance verification result.

8. The outdoor intelligent distribution circuit breaker monitoring and management system according to claim 1, characterized in that: After obtaining the potential circuit breaker failure point, sending the potential circuit breaker failure point to the management end through the Internet of Things platform; The management end monitors the operating status of the outdoor power distribution circuit breaker in real time through the Internet of Things platform, and remotely configures the operating parameters of the outdoor power distribution circuit breaker according to the monitoring results.

9. A monitoring and management method for an outdoor intelligent power distribution circuit breaker, applied to an outdoor intelligent power distribution circuit breaker monitoring and management system as claimed in any one of claims 1 to 8, the monitoring and management method comprising: Through embedded sensors, the current working status and real-time environmental conditions of outdoor distribution circuit breakers are monitored to generate corresponding initial circuit breaker operation data; Analyzing and filtering the initial circuit breaker operation data to obtain corresponding target circuit breaker operation data; Constructing a potential fault diagnosis model for a circuit breaker, performing fault identification on the target circuit breaker operation data, and obtaining corresponding potential circuit breaker fault points; The historical circuit breaker operation data of the outdoor power distribution circuit breaker is obtained through the cloud data center to verify and optimize the circuit breaker potential fault diagnosis model.

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