Control system and method for intelligent controller of circuit breaker

Abstract

The invention relates to the technical field of circuit breaker control, in particular to a control system and method for an intelligent circuit breaker controller, and the system comprises a data collection module, an abnormality judgment module, an abnormality determination module, a type determination module, an adjustment module and an execution module. According to the invention, the current, the contact displacement and the contact temperature are collected in real time, so that the operation state of the circuit breaker can be sensed in a multi-dimensional manner; in the hidden anomaly judgment, anomaly candidate generation and type identification process, the synchronous change trend of displacement and temperature is compared with historical anomaly characteristics, and a trigger amplitude threshold value and a delay tripping window are adjusted based on the anomaly type and the confidence coefficient; and furthermore, the peak amplitude threshold value is adjusted or the tripping action is executed according to the time distribution of the implicit anomaly judgment result in the preset correction duration, so that the problem of insufficient early warning capability caused by lack of a refined state recognition and prediction mechanism is effectively solved.

Description

Technical Field

[0001] This invention relates to the field of circuit breaker control technology, and in particular to a control system and method for an intelligent circuit breaker controller. Background Technology

[0002] As power distribution systems evolve towards higher density and greater intelligence, low-voltage circuit breakers are no longer limited to basic overload and short-circuit protection. They also need to identify potential risks early in operation and provide preventative protection. However, most existing general-purpose intelligent controllers are limited to electrical quantity measurement and over-limit alarms, lacking the ability to identify complex abnormal patterns and determine trends. This results in insufficient early warnings and difficulty in providing reliable data for subsequent safety measures, posing a significant challenge to be addressed in the intelligent application of circuit breakers.

[0003] Chinese Patent Application Publication No. CN118783375A discloses an intelligent controller applicable to general low-voltage circuit breakers and its operating method. The controller includes: a signal acquisition module, a power supply module, a metering module, a main control module, and a display / button module. The signal acquisition module is connected to the low-voltage circuit breaker, the power supply module, the main control module, and the metering module respectively. The power supply module is also connected to the metering module, the main control module, and the display / button module respectively. The metering module and the display / button module are respectively connected to the main control module.

[0004] Therefore, the intelligent controller applicable to general low-voltage circuit breakers has the following problems: the controller is mainly used for measuring and alarming electrical parameters, lacks the ability to subdivide and classify abnormal modes, and cannot achieve more refined status identification and early warning; the controller structure is biased towards the implementation of general functions, and its adaptability to complex operating scenarios is insufficient, and the protection strategy is simplistic. Summary of the Invention

[0005] To address this, the present invention provides a control system and method for a circuit breaker intelligent controller, which overcomes the problem of insufficient early warning capability in the prior art due to the lack of detailed state identification and prediction mechanisms by using abnormal feature modeling and trend analysis.

[0006] To achieve the above objectives, in one aspect, the present invention provides a control system for a circuit breaker intelligent controller, comprising: The data acquisition module is used to collect data in real time on the current, contact displacement, and contact temperature of the circuit breaker during operation with a preset trigger amplitude threshold and a preset delay trip window. An anomaly detection module, which is connected to the acquisition module, is used to determine whether a latent anomaly has occurred based on the current and a preset peak amplitude threshold, so as to obtain a latent anomaly detection result. An anomaly determination module, which is connected to the acquisition module and the determination module respectively, is used to determine an anomaly candidate list and several confidence scores based on the latent anomaly determination result, the synchronous change trend of the contact displacement and the contact temperature, and a preset historical anomaly feature template. A type determination module, connected to the anomaly determination module, is used to determine the total confidence and comparative confidence based on the anomaly candidate list and the confidence score, and to determine the anomaly type based on the total confidence, comparative confidence, and the preset historical anomaly feature template. An adjustment module, which is connected to the anomaly determination module and the type determination module respectively, is used to adjust the preset trigger amplitude threshold or the preset delay tripping window according to the anomaly candidate list, the confidence score, the anomaly type and the total confidence. An execution module, which is connected to the type determination module and the anomaly determination module respectively, is used to adjust the preset peak amplitude threshold or perform a trip based on the anomaly type and the time distribution characteristics of the latent anomaly determination results within the preset correction time after adjusting the preset trigger amplitude threshold or the preset delay tripping window.

[0007] Furthermore, the anomaly detection module includes: A current curve plotting unit is used to plot a current curve based on the current within a preset determination time period; A feature extraction unit, which is connected to the current curve plotting unit, is used to extract the peak amplitude from the current curve; An anomaly determination unit, connected to the feature extraction unit, is used to determine that a latent anomaly has occurred when the cumulative number of times the peak amplitude is greater than the preset peak amplitude threshold within the preset determination time is greater than the preset cumulative threshold, so as to obtain the latent anomaly determination result.

[0008] Furthermore, the anomaly determination module includes: The triggering unit is used to determine several characteristic parameters based on the contact displacement and the contact temperature within a preset anomaly determination time when the latent anomaly determination result is obtained, and to generate a list of triggering signals; A candidate generation unit, connected to the triggering unit, is used to generate the abnormal candidate list and the confidence score based on the feature parameters when generating the list trigger signal.

[0009] Furthermore, the triggering unit includes: The synchronization triggering subunit is used to obtain the contact displacement and the contact temperature within the preset anomaly determination time when the latent anomaly determination result is obtained, to obtain the displacement sequence and the temperature sequence, and to calculate the Pearson correlation coefficient of the normalized displacement sequence and the normalized temperature sequence to obtain the synchronization change index, and to generate a synchronization triggering signal when the synchronization change index is greater than the preset synchronization threshold. An amplitude triggering subunit, connected to the synchronization triggering subunit, is used to calculate the change amplitude of the displacement sequence and the change amplitude of the temperature sequence when generating the synchronization triggering signal, and to generate an amplitude triggering signal when the change amplitude of the displacement sequence is greater than or equal to a preset displacement change threshold and the change amplitude of the temperature sequence is greater than or equal to a preset temperature change threshold. A rate triggering subunit, connected to the amplitude triggering subunit, is used to count the duration of the synchronization triggering signal when generating the amplitude triggering signal, and to determine whether the abnormal candidate list needs to be generated when the duration is greater than a preset duration threshold, so as to generate the list triggering signal.

[0010] Furthermore, the candidate generation unit includes: The index extraction subunit is used to extract the average value of the change amplitude of the displacement sequence to obtain the average displacement amplitude when the list trigger signal is generated, and to extract the average value of the change amplitude of the temperature sequence to obtain the average temperature amplitude, and to extract the synchronization change index. A matching subunit, which is connected to the index extraction subunit, is used to perform matching based on the average displacement amplitude, the average temperature amplitude, the synchronous change index, and the preset historical anomaly feature template to obtain feature matching results; A candidate generation subunit, connected to the matching subunit, is used to determine several abnormal candidates based on the feature matching results and aggregate them into the abnormal candidate list, and to determine the confidence score based on the feature parameters corresponding to each abnormal candidate.

[0011] Furthermore, the type determination module includes: A candidate filtering unit is used to filter out abnormal candidates from the abnormal candidate list whose confidence scores are greater than a preset score threshold, thereby obtaining filtered candidates. A total confidence calculation unit, which is connected to the candidate screening unit, is used to perform a weighted summation calculation on the confidence scores of the screened candidates to obtain the total confidence score. The comparison confidence calculation unit is used to perform a weighted summation of the confidence scores of all the abnormal candidates to obtain the comparison confidence. A type determination unit is connected to the total confidence calculation unit and the comparison confidence calculation unit, respectively, to determine the anomaly type based on the total confidence, the comparison confidence, and the preset historical anomaly feature template.

[0012] Furthermore, the type determination unit includes: The deviation calculation subunit is used to calculate the relative deviation between the total confidence level and the comparison confidence level to obtain the confidence deviation; A type determination subunit, connected to the deviation calculation subunit, is used to determine the anomaly type as contact jamming when the first type in the confidence deviation and the preset historical anomaly feature template has the highest matching degree; to determine the anomaly type as overload pulse when the second type in the confidence deviation and the preset historical anomaly feature template has the highest matching degree; and to determine the anomaly type as transient anomaly when the third type in the confidence deviation and the preset historical anomaly feature template has the highest matching degree.

[0013] Furthermore, the adjustment module includes: A threshold adjustment unit is used to increase the preset trigger amplitude threshold based on the total confidence level and the minimum value of the preset total confidence range when the abnormality type is the contact jamming type and the total confidence level is less than the minimum value of the preset total confidence range. A delay adjustment unit is used to increase the preset delay tripping window based on the minimum value of the total confidence and the preset total confidence range when the anomaly type is the transient anomaly type and the total confidence is within the preset total confidence range. The tolerance convergence unit is used to reduce the preset delay tripping window based on the difference between the total confidence level and the maximum value of the preset total confidence range and the preset standard deviation when the anomaly type is the overload pulse type, the total confidence level is greater than the maximum value of the preset total confidence range, and the difference between the total confidence level and the maximum value of the preset total confidence range is less than the preset standard deviation.

[0014] Furthermore, the execution module includes: The distribution duration calculation unit is used to calculate the difference between the timestamp of the latent anomaly determination result occurring within the preset correction duration and the initial time, so as to obtain several distribution durations; A distribution fluctuation calculation unit, which is connected to the distribution duration calculation unit, is used to calculate the standard deviation of all the distribution durations to obtain the distribution fluctuation. A tripping execution unit, connected to the distribution fluctuation calculation unit, is used to determine a persistent abnormality and execute the tripping action when the distribution fluctuation is greater than the maximum value of the preset fluctuation range. A peak adjustment unit, connected to the distribution fluctuation calculation unit, is used to determine that a transient clustering anomaly has occurred when the distribution fluctuation is less than the minimum value of the preset fluctuation range, and to adjust the preset peak amplitude threshold according to the distribution fluctuation and the minimum value of the preset fluctuation range.

[0015] On the other hand, the present invention also provides a control method for a circuit breaker intelligent controller, comprising: Real-time acquisition of current, contact displacement, and contact temperature during the operation of the circuit breaker with a preset trigger amplitude threshold and a preset delay trip window; The presence or absence of a latent anomaly is determined based on the current and a preset peak amplitude threshold, in order to obtain the latent anomaly determination result. Based on the latent anomaly determination results, an anomaly candidate list and several confidence scores are determined according to the synchronous change trends of the contact displacement and the contact temperature, as well as the preset historical anomaly feature template. The total confidence and comparative confidence are determined based on the anomaly candidate list and the confidence score, and the anomaly type is determined based on the total confidence, comparative confidence, and the preset historical anomaly feature template. Adjust the preset trigger amplitude threshold or the preset delay tripping window based on the anomaly candidate list, the confidence score, the anomaly type, and the total confidence. Adjust the preset peak amplitude threshold based on the time distribution characteristics of the latent anomaly determination results within the preset correction time and the anomaly type re-determined after adjusting the preset trigger amplitude threshold or the preset delay tripping window, or execute the tripping.

[0016] Compared with existing technologies, the advantages of this invention lie in its ability to achieve multi-dimensional perception of the circuit breaker's operating status through real-time acquisition of current, contact displacement, and contact temperature. During the processes of latent anomaly determination, anomaly candidate generation, and type identification, the synchronous change trends of displacement and temperature are compared with historical anomaly characteristics to quantify the confidence level of the anomaly and generate anomaly type judgment. Based on the anomaly type and confidence level, the trigger amplitude threshold and delay tripping window can be intelligently adjusted to optimize the circuit breaker's response mechanism. Furthermore, by analyzing the time distribution of latent anomaly determination results within a preset correction period, the peak amplitude threshold can be adjusted or tripping actions can be executed, enabling timely handling of persistent anomalies. Overall, the mutual mapping and constraints between various parameters create a closed-loop control system for anomaly determination, threshold adjustment, and tripping execution. This improves the circuit breaker's sensitivity to sudden and latent anomalies while also ensuring operational safety and reliability, guaranteeing accurate and efficient protection actions under different load and fault conditions. This effectively solves the problem of insufficient early warning capabilities due to the lack of detailed state identification and prediction mechanisms.

[0017] Furthermore, by plotting the current curve of the circuit breaker within a preset judgment period in real time and extracting the peak amplitude from the curve, the frequency and amplitude of the peaks can be quantified. When the cumulative number of times the peak amplitude exceeds the preset threshold exceeds the set standard, the system automatically determines the occurrence of a latent anomaly, thereby achieving early identification of minor anomalies in the circuit breaker. It can combine current fluctuation characteristics with anomaly judgment thresholds, so that anomaly identification considers both amplitude changes and frequency of occurrence, accurately reflecting the dynamic changes in the internal electrical and mechanical state of the circuit breaker, and improving the timeliness and reliability of latent anomaly detection.

[0018] Furthermore, through the collaborative work of the triggering unit and the candidate generation unit, multi-dimensional perception and judgment of the circuit breaker's status are achieved. In the triggering unit, the system analyzes in real time the changes in contact displacement and contact temperature within a preset anomaly determination period, extracting displacement amplitude, temperature amplitude, and their synchronous change index to form quantifiable feature parameters. These feature parameters not only reflect the dynamic relationship between contact mechanical movement and temperature rise but also reveal the development trend of potential anomalies. The candidate generation unit generates an anomaly candidate list and calculates confidence scores by matching it with historical anomaly feature templates, thereby distinguishing the probability of different anomaly types, achieving early identification and accurate classification of abnormal events, and providing a reliable basis for subsequent threshold adjustments and protection actions.

[0019] Furthermore, a three-tiered judgment mechanism—synchronous triggering, amplitude triggering, and rate triggering—achieves comprehensive monitoring of contact displacement and temperature changes. The synchronous triggering subunit calculates the correlation coefficient between the displacement and temperature sequences to identify coordinated trends in displacement and temperature changes, thereby capturing initial signals of potential anomalies. The amplitude triggering subunit uses threshold judgments on the amplitude changes of displacement and temperature to filter out significant abnormal fluctuations, avoiding false alarms caused by minor fluctuations. The rate triggering subunit judges continuous abnormal signals by statistically analyzing the duration of synchronous changes, ensuring the reliability of the generated anomaly candidate list. This mechanism establishes hierarchical linkages between contact displacement, temperature, and their amplitude and duration, enabling timely and accurate identification of potential circuit breaker anomalies, improving judgment accuracy and control reliability.

[0020] Furthermore, the candidate generation unit comprehensively analyzes the displacement sequence, temperature sequence, and their synchronous change index. The index extraction sub-unit calculates the average change amplitude and synchronous change index, and the matching sub-unit compares these features with historical anomaly templates to generate an anomaly candidate list and corresponding confidence scores for the candidate generation sub-unit. This design effectively integrates the quantitative characteristics of contact displacement, temperature change, and their synchronous relationship. By matching historical anomaly patterns, the system can accurately filter and sort candidate events under different anomaly conditions, thereby improving the accuracy and reliability of anomaly identification. It also provides a scientific basis for subsequent type determination and threshold adjustment, enabling a rapid and robust response to potential circuit breaker faults.

[0021] Furthermore, by using a type determination module to filter and weight the confidence scores in the anomaly candidate list, not only can high-confidence candidates be evaluated collectively to calculate the total confidence score, but a comparative confidence score is also obtained by comparing the weighted confidence scores of all candidates, thus achieving accurate anomaly type determination. The parameters are intrinsically linked through the matching degree between the candidate's feature parameters and historical anomaly templates, ensuring that the total confidence score and comparative confidence score reflect the probability of anomaly occurrence and feature consistency. This guarantees that the determination of different anomaly types is both sensitive and robust, while providing a reliable basis for subsequent threshold adjustments and delay control, improving the accuracy and safety of the circuit breaker intelligent control system's response to latent anomalies.

[0022] Furthermore, by calculating the deviation between the total confidence score and the comparative confidence score, the overall characteristics of the anomaly candidates are matched with historical anomaly feature templates to achieve accurate differentiation between contact jamming, overload pulse, and transient anomaly types. The total confidence score reflects the concentration of high-confidence candidates, while the comparative confidence score reflects the overall candidate distribution. The deviation between the two can reveal the bias of the anomaly signal in different feature dimensions. By matching historical templates to determine the anomaly type, the anomaly judgment not only considers the amplitude of a single parameter but also integrates multi-dimensional information such as displacement, temperature, and synchronous change index, thereby improving the accuracy of judgment and the response reliability of the control system.

[0023] Furthermore, by adjusting the preset trigger amplitude threshold and delay trip window for different anomaly types, adaptive optimization of the circuit breaker's operating characteristics is achieved: when the contact jamming anomaly occurs and the total confidence level is below the threshold, increasing the trigger threshold can prevent maloperation and ensure closing stability; when the transient anomaly occurs and the total confidence level is within a reasonable range, extending the trip window can avoid unnecessary disconnection caused by short-term spikes; when the overload pulse anomaly occurs and the total confidence level deviation is small and below the standard deviation threshold, converging the delay trip window can improve the accuracy of the action response while ensuring safety. The parameters are dynamically correlated through anomaly type, confidence level, and preset range to form a closed-loop control, realizing intelligent protection and reliable operation of the circuit breaker.

[0024] Furthermore, by analyzing the time distribution of the latent anomaly determination results within a preset correction period through the execution module, and calculating the distribution volatility using the standard deviation of the distribution duration, the persistence and clustering of abnormal events can be effectively reflected. When the distribution volatility exceeds the maximum value of the preset volatility range, a persistent anomaly can be accurately determined and a tripping action can be executed in a timely manner to prevent the circuit breaker from being damaged due to prolonged anomalies. When the distribution volatility is lower than the minimum value of the preset volatility range, it can be determined as a transient clustered anomaly, and the peak amplitude threshold can be adjusted accordingly to make the determination more sensitive and avoid misjudgments. This method establishes a dynamic correlation between parameters through the time distribution characteristics of current, contact displacement, and temperature data, realizing intelligent and refined control of circuit breaker anomaly determination and protection actions.

[0025] Furthermore, by collecting current, contact displacement, and contact temperature in real time during circuit breaker operation, and combining this with multi-dimensional parameters such as preset trigger amplitude thresholds, delayed tripping windows, peak amplitude thresholds, and correction durations for hierarchical judgment and dynamic adjustment, a correspondence can be established between current peak characteristics and contact thermo-mechanical responses. Then, a candidate list is constructed using historical anomaly feature templates, and confidence levels are calculated to achieve differential analysis between total confidence and comparative confidence levels, thereby accurately distinguishing different operating conditions such as contact jamming, overload pulse, and transient anomalies. Based on this, the system adaptively adjusts the thresholds and tripping windows according to the confidence deviation, avoiding false tripping due to minor disturbances and quickly triggering tripping during persistent anomalies. This forms a dynamic coupling closed-loop control mechanism of electrical-thermal-mechanical three parameters, significantly improving the accuracy, sensitivity, and stability of circuit breaker operation. Attached Figure Description

[0026] Figure 1 This is a schematic diagram of the control system of the intelligent circuit breaker controller in this embodiment; Figure 2 This is the logic diagram for the anomaly determination unit in this embodiment to determine the occurrence of a latent anomaly; Figure 3 This is a logic diagram of the candidate filtering unit in this embodiment for determining the candidates to be filtered; Figure 4 This is a flowchart of the control method of the intelligent controller for the circuit breaker in this embodiment. Detailed Implementation

[0027] To make the objectives and advantages of the present invention clearer, the present invention will be further described below with reference to embodiments; it should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention.

[0028] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0029] Please see Figure 1 As shown, this is a schematic diagram of the control system of the intelligent circuit breaker controller in this embodiment. On one hand, this embodiment provides a control system for an intelligent circuit breaker controller, including: The data acquisition module is used to collect data in real time on the current, contact displacement, and contact temperature of the circuit breaker during operation with a preset trigger amplitude threshold and a preset delay trip window. An anomaly detection module, which is connected to the acquisition module, is used to determine whether a latent anomaly has occurred based on the current and a preset peak amplitude threshold, so as to obtain a latent anomaly detection result. An anomaly determination module, which is connected to the acquisition module and the determination module respectively, is used to determine an anomaly candidate list and several confidence scores based on the latent anomaly determination result, the synchronous change trend of the contact displacement and the contact temperature, and a preset historical anomaly feature template. A type determination module, connected to the anomaly determination module, is used to determine the total confidence and comparative confidence based on the anomaly candidate list and the confidence score, and to determine the anomaly type based on the total confidence, comparative confidence, and the preset historical anomaly feature template. An adjustment module, which is connected to the anomaly determination module and the type determination module respectively, is used to adjust the preset trigger amplitude threshold or the preset delay tripping window according to the anomaly candidate list, the confidence score, the anomaly type and the total confidence. An execution module, which is connected to the type determination module and the anomaly determination module respectively, is used to adjust the preset peak amplitude threshold or perform a trip based on the anomaly type and the time distribution characteristics of the latent anomaly determination results within the preset correction time after adjusting the preset trigger amplitude threshold or the preset delay tripping window.

[0030] In this embodiment, the data acquisition module collects the current amplitude during circuit breaker operation in real time using a high-precision current transformer to reflect load changes and potential abnormal spikes; it acquires contact displacement changes using a micro-displacement sensor or photoelectric encoder to monitor minute mechanical movements and synchronization trends of the contacts; and it collects contact temperature using a temperature sensor to reflect the contact heating state and contact condition. When the circuit breaker operates at a preset trigger amplitude threshold and a preset delay tripping window, this module continuously records current, displacement, and temperature data, ensuring that all parameters are collected synchronously and in real time, providing an accurate and reliable data foundation for subsequent anomaly detection and type analysis.

[0031] In this embodiment, the preset historical anomaly feature template refers to a standardized anomaly pattern library established based on a large amount of historical circuit breaker operation data and experimental verification results. This library records the distribution patterns of parameters such as the numerical range, amplitude, and synchronization index of contact displacement, contact temperature, and their synchronous changes under various typical anomaly conditions. This template is used to compare and match with the feature parameters collected in real time. By quantifying the similarity between each anomaly candidate and the template, a confidence score is generated, thereby accurately determining the anomaly type and providing a reference for the intelligent monitoring and early warning of the circuit breaker.

[0032] The preset trigger amplitude threshold is used to determine the trigger value of current abnormality. It depends on the rated current of the circuit breaker and the load characteristics, and is usually set between 5% and 20% of the rated current. In this embodiment, it is set to 10% of the rated current, which can identify potential latent abnormalities in a timely manner under load fluctuations. The preset delay tripping window is used to control the time window of the delay tripping action. It depends on the response speed of the circuit breaker contacts and the overload duration, and is usually set between 50 milliseconds and 200 milliseconds. In this embodiment, it is set to 100 milliseconds, which can avoid false tripping caused by transient pulses. The preset spike amplitude threshold is used to determine the amplitude of current spike abnormality. It depends on the transient overload characteristics of the circuit breaker and the system noise level, and is usually set between 15% and 40% of the rated current. In this embodiment, it is set to 25% of the rated current, which can accurately identify sudden spike signals. The preset correction duration is used to analyze the time distribution of the latent abnormality determination results. It depends on the frequency of abnormal events and the circuit breaker operating cycle, and is usually set between 0.5 seconds and 3 seconds. In this embodiment, it is set to 1 second, which can effectively capture the distribution characteristics of short-term abnormalities.

[0033] By real-time acquisition of current, contact displacement, and contact temperature, multi-dimensional perception of the circuit breaker's operating status is achieved. During the process of latent anomaly detection, anomaly candidate generation, and type identification, the synchronous change trends of displacement and temperature are compared with historical anomaly characteristics to quantify the confidence level of the anomaly and generate an anomaly type judgment. Based on the anomaly type and confidence level, the trigger amplitude threshold and delay tripping window can be intelligently adjusted to optimize the circuit breaker's response mechanism. Furthermore, by analyzing the time distribution of latent anomaly detection results within a preset correction period, the peak amplitude threshold can be adjusted or tripping actions can be executed to achieve timely handling of persistent anomalies. Overall, the mutual mapping and constraints between various parameters form a closed-loop control system for anomaly detection, threshold adjustment, and tripping execution. This improves the circuit breaker's sensitivity to sudden and latent anomalies while also ensuring operational safety and reliability, guaranteeing accurate and efficient protection actions under different load and fault conditions. This effectively solves the problem of insufficient early warning capabilities due to the lack of detailed state identification and prediction mechanisms.

[0034] Specifically, the anomaly detection module includes: A current curve plotting unit is used to plot a current curve based on the current within a preset determination time period; A feature extraction unit, which is connected to the current curve plotting unit, is used to extract the peak amplitude from the current curve; An anomaly determination unit, connected to the feature extraction unit, is used to determine that a latent anomaly has occurred when the cumulative number of times the peak amplitude is greater than the preset peak amplitude threshold within the preset determination time is greater than the preset cumulative threshold, so as to obtain the latent anomaly determination result.

[0035] The preset trigger amplitude threshold is used to determine the current amplitude required for the circuit breaker to trigger action. It depends on the circuit breaker's rated current and operating sensitivity, and is usually set between 5% and 20% of the rated current. In this embodiment, it is set to 10% of the rated current to accurately trigger the circuit breaker and avoid false tripping. The preset delay trip window is used to control the time range of the circuit breaker's delay trip. It depends on the circuit breaker's thermomechanical characteristics and load characteristics, and is usually set between 50 milliseconds and 500 milliseconds. In this embodiment, it is set to 200 milliseconds to balance transient fluctuations and actual overload protection requirements. The preset spike amplitude threshold is used to determine the amplitude of abnormal current spikes. It depends on the load fluctuation amplitude and the circuit breaker's response characteristics, and is usually set between 15% and 40% of the average current. In this embodiment, it is set to 25% of the average current to effectively identify latent abnormal spikes. The preset correction duration is used to calculate the statistical interval of the latent abnormal time distribution. It depends on the circuit breaker's action response cycle and the frequency of abnormal occurrence, and is usually set between 1 second and 10 seconds. In this embodiment, it is set to 5 seconds to fully capture the time distribution characteristics of abnormal events.

[0036] By plotting the current curve of the circuit breaker within a preset judgment period in real time and extracting the peak amplitude from the curve, the frequency and amplitude of the peaks can be quantified. When the cumulative number of times the peak amplitude exceeds the preset threshold exceeds the set standard, the system automatically determines the occurrence of a latent anomaly, thereby achieving early identification of minor anomalies in the circuit breaker. By combining current fluctuation characteristics with anomaly judgment thresholds, anomaly identification considers both amplitude changes and frequency of occurrence, accurately reflecting the dynamic changes in the internal electrical and mechanical state of the circuit breaker, and improving the timeliness and reliability of latent anomaly detection.

[0037] Specifically, the anomaly determination module includes: The triggering unit is used to determine several characteristic parameters based on the contact displacement and the contact temperature within a preset anomaly determination time when the latent anomaly determination result is obtained, and to generate a list of triggering signals; A candidate generation unit, connected to the triggering unit, is used to generate the abnormal candidate list and the confidence score based on the feature parameters when generating the list trigger signal.

[0038] The preset anomaly determination time is a time window used to monitor the displacement and temperature changes of circuit breaker contacts. It depends on the circuit breaker's operating characteristics, load type, and anomaly development speed, and is usually set between 100 milliseconds and 300 milliseconds. In this embodiment, it is set to 200 milliseconds, which can filter out short-term random fluctuations while ensuring timely capture of anomaly signals, thereby improving the accuracy and reliability of anomaly determination.

[0039] Through the collaborative work of the triggering unit and the candidate generation unit, multi-dimensional perception and judgment of the circuit breaker's status are achieved. In the triggering unit, the system analyzes in real time the changes in contact displacement and temperature within a preset anomaly determination period, extracting displacement amplitude, temperature amplitude, and their synchronous change index to form quantifiable feature parameters. These feature parameters not only reflect the dynamic relationship between contact mechanical movement and temperature rise but also reveal the development trend of potential anomalies. The candidate generation unit generates an anomaly candidate list and calculates confidence scores by matching it with historical anomaly feature templates, thereby distinguishing the probability of different anomaly types and achieving early identification and accurate classification of abnormal events. This also provides a reliable basis for subsequent threshold adjustments and protection actions.

[0040] Please see Figure 3 As shown, this is a logic diagram for determining the trigger signal generated by the trigger unit in this embodiment. In this embodiment, the trigger unit includes: The synchronization triggering subunit is used to obtain the contact displacement and the contact temperature within the preset anomaly determination time when the latent anomaly determination result is obtained, to obtain the displacement sequence and the temperature sequence, and to calculate the Pearson correlation coefficient of the normalized displacement sequence and the normalized temperature sequence to obtain the synchronization change index, and to generate a synchronization triggering signal when the synchronization change index is greater than the preset synchronization threshold. An amplitude triggering subunit, connected to the synchronization triggering subunit, is used to calculate the change amplitude of the displacement sequence and the change amplitude of the temperature sequence when generating the synchronization triggering signal, and to generate an amplitude triggering signal when the change amplitude of the displacement sequence is greater than or equal to a preset displacement change threshold and the change amplitude of the temperature sequence is greater than or equal to a preset temperature change threshold. A rate triggering subunit, connected to the amplitude triggering subunit, is used to count the duration of the synchronization triggering signal when generating the amplitude triggering signal, and to determine whether the abnormal candidate list needs to be generated when the duration is greater than a preset duration threshold, so as to generate the list triggering signal.

[0041] In this embodiment, the displacement and temperature sequences are normalized using a standardized Z-score, which involves subtracting the sequence mean from each data point and then dividing by the sequence standard deviation to obtain the normalized displacement and temperature sequences. The normalized sequences are used to calculate the Pearson correlation coefficient to obtain a synchronization change index, reflecting the degree of synchronization between contact displacement and temperature over time. When the synchronization change index is greater than a preset synchronization threshold, a synchronization trigger signal is generated. Subsequently, the amplitude trigger subunit calculates the amplitude of the displacement and temperature sequences and generates amplitude trigger signals when the amplitudes are greater than or equal to preset displacement and temperature change thresholds, respectively. The rate trigger subunit counts the duration of the synchronization trigger signals; when the duration exceeds a preset duration threshold, it determines that an anomaly candidate list needs to be generated, thus generating a list trigger signal to initiate subsequent anomaly analysis and type determination.

[0042] The preset synchronization threshold is used to determine the degree of synchronization between the displacement sequence and the temperature sequence. It depends on the normal coordination between the circuit breaker contact displacement and temperature, and is usually set between 0.6 and 0.9. In this embodiment, it is set to 0.8, which can accurately filter out abnormal events with significant synchronization changes. The preset displacement change threshold is used to determine whether the amplitude of the contact displacement change is abnormal. It depends on the amplitude of the contact mechanical action and the allowable deviation, and is usually set between 0.05 mm and 0.2 mm. In this embodiment, it is set to 0.1 mm, which can effectively identify potential faults caused by abnormal displacement. The preset temperature change threshold is used to determine whether the amplitude of the contact temperature change is abnormal. It depends on the thermal characteristics of the contact material and the temperature fluctuation of the operating environment, and is usually set between 0.5℃ and 2℃. In this embodiment, it is set to 1℃, which can promptly detect faults that may be caused by abnormal temperature rise. The preset duration threshold is used to determine the duration of the synchronization trigger signal. It depends on the duration characteristics of the abnormal contact action, and is usually set between 10 milliseconds and 100 milliseconds. In this embodiment, it is set to 50 milliseconds, which can distinguish between brief transient interference and continuous abnormal events.

[0043] A three-tiered judgment mechanism—synchronous triggering, amplitude triggering, and rate triggering—achieves comprehensive monitoring of contact displacement and temperature changes. The synchronous triggering subunit calculates the correlation coefficient between the displacement and temperature sequences to identify coordinated trends in displacement and temperature changes, thus capturing initial signals of potential anomalies. The amplitude triggering subunit uses threshold judgments on the amplitude of displacement and temperature changes to filter out significant abnormal fluctuations, avoiding false alarms caused by minor fluctuations. The rate triggering subunit judges continuous abnormal signals by statistically analyzing the duration of synchronous changes, ensuring the reliability of the generated anomaly candidate list. This mechanism establishes hierarchical linkages between contact displacement, temperature, and their amplitude and duration, enabling timely and accurate identification of potential circuit breaker anomalies, improving judgment accuracy and control reliability.

[0044] Specifically, the candidate generation unit includes: The index extraction subunit is used to extract the average value of the change amplitude of the displacement sequence to obtain the average displacement amplitude when the list trigger signal is generated, and to extract the average value of the change amplitude of the temperature sequence to obtain the average temperature amplitude, and to extract the synchronization change index. A matching subunit, which is connected to the index extraction subunit, is used to perform matching based on the average displacement amplitude, the average temperature amplitude, the synchronous change index, and the preset historical anomaly feature template to obtain feature matching results; A candidate generation subunit, connected to the matching subunit, is used to determine several anomalous candidates based on the feature matching results and aggregate them into the anomalous candidate list, and to determine the confidence score based on the feature parameters corresponding to each anomalous candidate, wherein... Ci represents the confidence score of the anomalous candidate; f ij denoted as , where is the j-th feature parameter of anomaly candidate i; wj is the weight of the j-th feature in the confidence score calculation, representing the importance of each feature to the anomaly determination. It depends on the significance of the feature's ability to distinguish circuit breaker anomaly types and is usually set between 0.1 and 1. In this embodiment, it is set to 0.5 to balance the contribution of different features to the confidence score and avoid excessive influence of a single feature on the determination result; Δj is the tolerance range, used to quantify the allowable deviation between the feature parameter and the historical anomaly template. It depends on the volatility of the feature itself and the measurement accuracy and is usually set between 5% and 20% of the feature's average value. In this embodiment, it is set to 10% to accurately reflect the degree of anomaly while considering measurement noise and equipment fluctuations.

[0045] The candidate generation unit comprehensively analyzes displacement sequences, temperature sequences, and their synchronous change indices. The index extraction subunit calculates the average change amplitude and synchronous change index. The matching subunit compares these features with historical anomaly templates to generate an anomaly candidate list and corresponding confidence scores for the candidate generation subunit. This design effectively integrates the quantitative characteristics of contact displacement, temperature changes, and their synchronous relationship. By matching historical anomaly patterns, the system can accurately filter and sort candidate events under different anomaly conditions, thereby improving the accuracy and reliability of anomaly identification. It also provides a scientific basis for subsequent type determination and threshold adjustment, enabling a rapid and robust response to potential circuit breaker faults.

[0046] Please see Figure 3 As shown, this is a logic diagram of the candidate filtering unit determining the candidates in this embodiment. In this embodiment, the type determination module includes: A candidate filtering unit is used to filter out abnormal candidates from the abnormal candidate list whose confidence scores are greater than a preset score threshold, thereby obtaining filtered candidates. A total confidence calculation unit, which is connected to the candidate screening unit, is used to perform a weighted summation calculation on the confidence scores of the screened candidates to obtain the total confidence score. The comparison confidence calculation unit is used to perform a weighted summation of the confidence scores of all the abnormal candidates to obtain the comparison confidence. A type determination unit is connected to the total confidence calculation unit and the comparison confidence calculation unit, respectively, to determine the anomaly type based on the total confidence, the comparison confidence, and the preset historical anomaly feature template.

[0047] A preset scoring threshold is used to filter out abnormal candidates, clearly identifying which candidates with low confidence levels will not participate in subsequent type determination. This threshold depends on the system's tolerance for false positives and false negatives, and is typically set between 0.5 and 0.9. In this embodiment, it is set to 0.7, which can effectively eliminate low-confidence candidates and ensure the accuracy of abnormal type determination.

[0048] The weights used to calculate the total confidence score are calculated by weighted summation of the confidence scores of the selected candidates. Each anomaly candidate's feature parameter is assigned a specific weight according to its importance. The weight depends on the influence of the feature on the anomaly type judgment and is usually set between 0 and 1 and normalized. In this embodiment, the weights are set based on historical data and feature analysis so that the total confidence score can truly reflect the contribution of the selected candidates to the anomaly judgment. In this embodiment, there are three feature parameters for the selected candidates: average displacement amplitude, average temperature amplitude, and synchronous change index, with corresponding weights of 0.4, 0.3, and 0.3, respectively. This ensures that the calculated total confidence score fully reflects the contribution ratio of each feature parameter to the anomaly judgment.

[0049] The weights calculated by weighted summation of the confidence scores of all anomaly candidates are used to calculate the comparative confidence score. All candidate feature parameters are assigned weights to reflect their importance in the overall anomaly pattern. The weights depend on the degree of matching of the candidate in the historical anomaly feature template, and are usually set between 0 and 1 and normalized. In this embodiment, the weights of each candidate are set evenly so that the comparative confidence score can fully reflect the distribution of anomaly features and provide a reference for type determination.

[0050] The type determination module filters and weights the confidence scores in the anomaly candidate list, enabling not only centralized evaluation of high-confidence candidates to calculate the total confidence score, but also comparison of the weighted confidence scores of all candidates to obtain a comparative confidence score, thus achieving accurate anomaly type determination. The parameters are intrinsically linked through the matching degree between the candidate's feature parameters and historical anomaly templates, ensuring that the total confidence score and comparative confidence score reflect the probability of anomaly occurrence and feature consistency. This guarantees both sensitivity and robustness in determining different anomaly types, while providing a reliable basis for subsequent threshold adjustments and delay control, improving the accuracy and safety of the circuit breaker intelligent control system's response to latent anomalies.

[0051] Specifically, the type determination unit includes: The deviation calculation subunit is used to calculate the relative deviation between the total confidence level and the comparison confidence level to obtain the confidence deviation; A type determination subunit, connected to the deviation calculation subunit, is used to determine the anomaly type as contact jamming when the first type in the confidence deviation and the preset historical anomaly feature template has the highest matching degree; to determine the anomaly type as overload pulse when the second type in the confidence deviation and the preset historical anomaly feature template has the highest matching degree; and to determine the anomaly type as transient anomaly when the third type in the confidence deviation and the preset historical anomaly feature template has the highest matching degree.

[0052] In this embodiment, the matching of confidence bias with preset historical anomaly feature templates is accomplished by calculating the similarity between the confidence bias and historical anomaly feature templates of each type. Specifically, the historical anomaly feature template for each anomaly type is represented as a multi-dimensional feature vector (including normalized features such as average displacement amplitude, average temperature amplitude, and synchronous change index). Then, the cosine similarity between the currently calculated confidence bias and each template vector is calculated to obtain the matching degree. The anomaly type corresponding to the historical anomaly feature template with the highest matching degree is determined as the current anomaly type, thereby accurately corresponding the real-time acquired anomaly signal with historically known anomaly patterns, achieving automation and reliability in type determination.

[0053] In this embodiment, the contact jamming type abnormality refers to the circuit breaker contacts being mechanically jammed or experiencing abnormal resistance, resulting in slow switching action or inability to fully close, manifested as slow and continuous abnormal changes in contact displacement; the overload pulse type abnormality refers to the circuit breaker experiencing short-term pulse overload when the current exceeds the rated value, with brief but unsustainable fluctuations in contact displacement and temperature; the transient abnormality type abnormality refers to the circuit breaker being affected by transient interference or brief current spikes, causing instantaneous changes in contact displacement and temperature, but recovering to normal within a very short time. These three types correspond to different mechanical or electrical abnormality characteristics and can be distinguished by the amplitude, rate of change, and duration of displacement, temperature, and current signals.

[0054] By calculating the deviation between the total confidence score and the comparative confidence score, the overall characteristics of the anomaly candidates are matched with historical anomaly feature templates, enabling accurate differentiation between contact jamming, overload pulse, and transient anomalies. The total confidence score reflects the concentration of high-confidence candidates, while the comparative confidence score reflects the overall candidate distribution. The deviation between the two reveals the bias of the anomaly signal in different feature dimensions. By matching historical templates to determine the anomaly type, anomaly judgment considers not only the amplitude of a single parameter but also multi-dimensional information such as displacement, temperature, and synchronous change index, thereby improving the accuracy of judgment and the reliability of the control system response.

[0055] Specifically, the adjustment module includes a threshold adjustment unit, used to increase the preset trigger amplitude threshold based on the total confidence level and the minimum value of the preset total confidence range when the abnormality type is the contact jamming type and the total confidence level is less than the minimum value of the preset total confidence range. Y' is the increased preset trigger amplitude threshold, Y is the original preset trigger amplitude threshold, k1 is the preset threshold adjustment coefficient, Zmin is the minimum value of the preset total confidence range, and Z is the total confidence level. The delay adjustment unit is used to increase the preset delay tripping window based on the minimum value of the total confidence level and the preset total confidence range when the anomaly type is the transient anomaly type and the total confidence level is within the preset total confidence range. in, Q' is the increased preset delay tripping window, Q is the original preset delay tripping window, and k2 is the preset window adjustment coefficient; A tolerance convergence unit is used to reduce the preset delay tripping window based on the difference between the total confidence level and the maximum value of the preset total confidence range and the preset standard deviation when the anomaly type is the overload pulse type, the total confidence level is greater than the maximum value of the preset total confidence range, and the difference between the total confidence level and the maximum value of the preset total confidence range is less than the preset standard deviation. W is the difference between the total confidence level and the maximum value of the preset total confidence range, and W' is the preset standard deviation.

[0056] The preset total confidence range is a numerical interval used to judge the overall reliability of anomaly candidates. It depends on historical anomaly data and the system's requirements for the reliability of circuit breaker operation, and is usually set between [0.5, 0.9]. In this embodiment, it is set to [0.7, 0.85], which can effectively distinguish between high-confidence and low-confidence events when screening anomaly candidates, thereby guiding the reasonable adjustment of the threshold or delayed tripping window. The preset standard deviation is a reference quantity used to measure the sensitivity of the difference fluctuation between the total confidence and the maximum value of the preset total confidence range. It depends on the stability of the historical confidence distribution of the circuit breaker under different load conditions, and is usually set between 0.05 and 0.2. In this embodiment, it is set to 0.1, which can effectively distinguish between high-confidence and low-confidence events when there is an overload pulse anomaly. The current delay trip window features rapid convergence and precise adjustment. The preset threshold adjustment coefficient controls the dynamic amplification ratio of the preset trigger amplitude threshold during contact jamming anomalies. It depends on the sensitivity of contact displacement changes to current surges and is typically set between 0.1 and 0.5. In this embodiment, it is set to 0.2 to avoid misjudgments caused by slight fluctuations and improve system robustness. The preset window adjustment coefficient controls the dynamic adjustment amplitude of the preset delay trip window during transient or overload pulse anomalies. It depends on the concentration of the current spike duration distribution and is typically set between 0.05 and 0.3. In this embodiment, it is set to 0.1 to ensure operational reliability while also considering tolerance to transient disturbances.

[0057] By adjusting the preset trigger amplitude threshold and delay trip window for different anomaly types, adaptive optimization of the circuit breaker's operating characteristics is achieved: when the contact jamming anomaly occurs and the total confidence level is below the threshold, increasing the trigger threshold can prevent maloperation and ensure closing stability; when the transient anomaly occurs and the total confidence level is within a reasonable range, extending the trip window can avoid unnecessary disconnection caused by short-term spikes; when the overload pulse anomaly occurs and the total confidence level deviation is small and below the standard deviation threshold, converging the delay trip window can improve the accuracy of the action response while ensuring safety. The parameters are dynamically correlated through anomaly type, confidence level, and preset range to form a closed-loop control, realizing intelligent protection and reliable operation of the circuit breaker.

[0058] Specifically, the execution module includes: The distribution duration calculation unit is used to calculate the difference between the timestamp of the latent anomaly determination result occurring within the preset correction duration and the initial time, so as to obtain several distribution durations; A distribution fluctuation calculation unit, which is connected to the distribution duration calculation unit, is used to calculate the standard deviation of all the distribution durations to obtain the distribution fluctuation. A tripping execution unit, connected to the distribution fluctuation calculation unit, is used to determine a persistent abnormality and execute the tripping action when the distribution fluctuation is greater than the maximum value of the preset fluctuation range. A peak adjustment unit, connected to the distribution fluctuation calculation unit, is used to determine that a transient clustering anomaly has occurred when the distribution fluctuation is less than the minimum value of the preset fluctuation range, and to adjust the preset peak amplitude threshold according to the distribution fluctuation and the minimum value of the preset fluctuation range.

[0059] The preset fluctuation range is usually determined based on the circuit breaker contact operation characteristics and current fluctuations. Its specific value is determined by the statistical results of the standard deviation of the duration of latent anomalies under normal operating conditions. It is usually set between [5ms, 20ms], and in this embodiment, it is specifically set to [6ms, 19ms], which can effectively distinguish between transient clustered anomalies and persistent anomalies, thereby accurately adjusting the tripping or peak amplitude threshold.

[0060] By analyzing the time distribution of latent anomaly detection results within a preset correction period through the execution module, and calculating the distribution volatility using the standard deviation of the distribution duration, the persistence and clustering of abnormal events can be effectively reflected. When the distribution volatility exceeds the maximum value of the preset volatility range, persistent anomalies can be accurately identified and tripping actions can be executed in a timely manner to prevent circuit breaker damage due to prolonged anomalies. When the distribution volatility is lower than the minimum value of the preset volatility range, it can be identified as a transient clustered anomaly, and the peak amplitude threshold can be adjusted accordingly to make the detection more sensitive and avoid misjudgments. This method establishes a dynamic correlation between parameters through the time distribution characteristics of current, contact displacement, and temperature data, realizing intelligent and refined control of circuit breaker anomaly detection and protection actions.

[0061] Please see Figure 4 As shown, this is a flowchart of the control method for the intelligent circuit breaker controller in this embodiment. Furthermore, this embodiment also provides a control method for the intelligent circuit breaker controller, including: Real-time acquisition of current, contact displacement, and contact temperature during the operation of the circuit breaker with a preset trigger amplitude threshold and a preset delay trip window; The presence or absence of a latent anomaly is determined based on the current and a preset peak amplitude threshold, in order to obtain the latent anomaly determination result. Based on the latent anomaly determination results, an anomaly candidate list and several confidence scores are determined according to the synchronous change trends of the contact displacement and the contact temperature, as well as the preset historical anomaly feature template. The total confidence and comparative confidence are determined based on the anomaly candidate list and the confidence score, and the anomaly type is determined based on the total confidence, comparative confidence, and the preset historical anomaly feature template. Adjust the preset trigger amplitude threshold or the preset delay tripping window based on the anomaly candidate list, the confidence score, the anomaly type, and the total confidence. Adjust the preset peak amplitude threshold based on the time distribution characteristics of the latent anomaly determination results within the preset correction time and the anomaly type re-determined after adjusting the preset trigger amplitude threshold or the preset delay tripping window, or execute the tripping.

[0062] By collecting current, contact displacement, and contact temperature data in real time during circuit breaker operation, and combining this with multi-dimensional parameters such as preset trigger amplitude thresholds, delay tripping windows, peak amplitude thresholds, and correction durations for hierarchical judgment and dynamic adjustment, a correlation is established between current peak characteristics and contact thermo-mechanical responses. Furthermore, a candidate list is constructed using historical anomaly feature templates, and confidence levels are calculated to achieve differential analysis between total confidence and comparative confidence levels. This accurately distinguishes between different operating conditions such as contact jamming, overload pulse, and transient anomalies. Based on this, the system adaptively adjusts the thresholds and tripping windows according to confidence deviations. This avoids false tripping due to minor disturbances and enables rapid tripping during persistent anomalies, forming a dynamic coupling closed-loop control mechanism of electrical, thermal, and mechanical parameters. This significantly improves the accuracy, sensitivity, and stability of circuit breaker operation.

[0063] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A control system for an intelligent circuit breaker controller, characterized in that, include: The data acquisition module is used to collect data in real time on the current, contact displacement, and contact temperature of the circuit breaker during operation with a preset trigger amplitude threshold and a preset delay trip window. An anomaly detection module, which is connected to the acquisition module, is used to determine whether a latent anomaly has occurred based on the current and a preset peak amplitude threshold, so as to obtain a latent anomaly detection result. An anomaly determination module, which is connected to the acquisition module and the determination module respectively, is used to determine an anomaly candidate list and several confidence scores based on the latent anomaly determination result, the synchronous change trend of the contact displacement and the contact temperature, and a preset historical anomaly feature template. A type determination module, connected to the anomaly determination module, is used to determine the total confidence and comparative confidence based on the anomaly candidate list and the confidence score, and to determine the anomaly type based on the total confidence, comparative confidence, and the preset historical anomaly feature template. An adjustment module, which is connected to the anomaly determination module and the type determination module respectively, is used to adjust the preset trigger amplitude threshold or the preset delay tripping window according to the anomaly candidate list, the confidence score, the anomaly type and the total confidence. An execution module, which is connected to the type determination module and the anomaly determination module respectively, is used to adjust the preset peak amplitude threshold or perform a trip based on the anomaly type and the time distribution characteristics of the latent anomaly determination results within the preset correction time after adjusting the preset trigger amplitude threshold or the preset delay tripping window.

2. The control system of the intelligent circuit breaker controller according to claim 1, characterized in that, The anomaly detection module includes: A current curve plotting unit is used to plot a current curve based on the current within a preset determination time period; A feature extraction unit, which is connected to the current curve plotting unit, is used to extract the peak amplitude from the current curve; An anomaly determination unit, connected to the feature extraction unit, is used to determine that a latent anomaly has occurred when the cumulative number of times the peak amplitude is greater than the preset peak amplitude threshold within the preset determination time is greater than the preset cumulative threshold, so as to obtain the latent anomaly determination result.

3. The control system of the intelligent circuit breaker controller according to claim 2, characterized in that, The anomaly determination module includes: The triggering unit is used to determine several characteristic parameters based on the contact displacement and the contact temperature within a preset anomaly determination time when the latent anomaly determination result is obtained, and to generate a list of triggering signals; A candidate generation unit, connected to the triggering unit, is used to generate the abnormal candidate list and the confidence score based on the feature parameters when generating the list trigger signal.

4. The control system of the intelligent circuit breaker controller according to claim 3, characterized in that, The triggering unit includes: The synchronization triggering subunit is used to obtain the contact displacement and the contact temperature within the preset anomaly determination time when the latent anomaly determination result is obtained, to obtain the displacement sequence and the temperature sequence, and to calculate the Pearson correlation coefficient of the normalized displacement sequence and the normalized temperature sequence to obtain the synchronization change index, and to generate a synchronization triggering signal when the synchronization change index is greater than the preset synchronization threshold. An amplitude triggering subunit, connected to the synchronization triggering subunit, is used to calculate the change amplitude of the displacement sequence and the change amplitude of the temperature sequence when generating the synchronization triggering signal, and to generate an amplitude triggering signal when the change amplitude of the displacement sequence is greater than or equal to a preset displacement change threshold and the change amplitude of the temperature sequence is greater than or equal to a preset temperature change threshold. A rate triggering subunit, connected to the amplitude triggering subunit, is used to count the duration of the synchronization triggering signal when generating the amplitude triggering signal, and to determine whether the abnormal candidate list needs to be generated when the duration is greater than a preset duration threshold, so as to generate the list triggering signal.

5. The control system of the intelligent circuit breaker controller according to claim 4, characterized in that, The candidate generation unit includes: The index extraction subunit is used to extract the average value of the change amplitude of the displacement sequence to obtain the average displacement amplitude when the list trigger signal is generated, and to extract the average value of the change amplitude of the temperature sequence to obtain the average temperature amplitude, and to extract the synchronization change index. A matching subunit, which is connected to the index extraction subunit, is used to perform matching based on the average displacement amplitude, the average temperature amplitude, the synchronous change index, and the preset historical anomaly feature template to obtain feature matching results; A candidate generation subunit, connected to the matching subunit, is used to determine several abnormal candidates based on the feature matching results and aggregate them into the abnormal candidate list, and to determine the confidence score based on the feature parameters corresponding to each abnormal candidate.

6. The control system of the intelligent circuit breaker controller according to claim 5, characterized in that, The type determination module includes: A candidate filtering unit is used to filter out abnormal candidates from the abnormal candidate list whose confidence scores are greater than a preset score threshold, thereby obtaining filtered candidates. A total confidence calculation unit, which is connected to the candidate screening unit, is used to perform a weighted summation calculation on the confidence scores of the screened candidates to obtain the total confidence score. The comparison confidence calculation unit is used to perform a weighted summation of the confidence scores of all the abnormal candidates to obtain the comparison confidence. A type determination unit is connected to the total confidence calculation unit and the comparison confidence calculation unit, respectively, to determine the anomaly type based on the total confidence, the comparison confidence, and the preset historical anomaly feature template.

7. The control system of the intelligent circuit breaker controller according to claim 6, characterized in that, The type determination unit includes: The deviation calculation subunit is used to calculate the relative deviation between the total confidence level and the comparison confidence level to obtain the confidence deviation; A type determination subunit, connected to the deviation calculation subunit, is used to determine the anomaly type as contact jamming when the first type in the confidence deviation and the preset historical anomaly feature template has the highest matching degree; to determine the anomaly type as overload pulse when the second type in the confidence deviation and the preset historical anomaly feature template has the highest matching degree; and to determine the anomaly type as transient anomaly when the third type in the confidence deviation and the preset historical anomaly feature template has the highest matching degree.

8. The control system of the intelligent circuit breaker controller according to claim 7, characterized in that, The adjustment module includes: A threshold adjustment unit is used to increase the preset trigger amplitude threshold based on the total confidence level and the minimum value of the preset total confidence range when the abnormality type is the contact jamming type and the total confidence level is less than the minimum value of the preset total confidence range. A delay adjustment unit is used to increase the preset delay tripping window based on the minimum value of the total confidence and the preset total confidence range when the anomaly type is the transient anomaly type and the total confidence is within the preset total confidence range. The tolerance convergence unit is used to reduce the preset delay tripping window based on the difference between the total confidence level and the maximum value of the preset total confidence range and the preset standard deviation when the anomaly type is the overload pulse type, the total confidence level is greater than the maximum value of the preset total confidence range, and the difference between the total confidence level and the maximum value of the preset total confidence range is less than the preset standard deviation.

9. The control system of the intelligent circuit breaker controller according to claim 8, characterized in that, The execution module includes: The distribution duration calculation unit is used to calculate the difference between the timestamp of the latent anomaly determination result occurring within the preset correction duration and the initial time, so as to obtain several distribution durations; A distribution fluctuation calculation unit, which is connected to the distribution duration calculation unit, is used to calculate the standard deviation of all the distribution durations to obtain the distribution fluctuation. A tripping execution unit, connected to the distribution fluctuation calculation unit, is used to determine a persistent abnormality and execute the tripping action when the distribution fluctuation is greater than the maximum value of the preset fluctuation range. A peak adjustment unit, connected to the distribution fluctuation calculation unit, is used to determine that a transient clustering anomaly has occurred when the distribution fluctuation is less than the minimum value of the preset fluctuation range, and to adjust the preset peak amplitude threshold according to the distribution fluctuation and the minimum value of the preset fluctuation range.

10. A control method for a circuit breaker intelligent controller, applied to the control system of the circuit breaker intelligent controller according to any one of claims 1-9, characterized in that, include: Real-time acquisition of current, contact displacement, and contact temperature during the operation of the circuit breaker with a preset trigger amplitude threshold and a preset delay trip window; The presence or absence of a latent anomaly is determined based on the current and a preset peak amplitude threshold, in order to obtain the latent anomaly determination result. Based on the latent anomaly determination results, an anomaly candidate list and several confidence scores are determined according to the synchronous change trends of the contact displacement and the contact temperature, as well as the preset historical anomaly feature template. The total confidence and comparative confidence are determined based on the anomaly candidate list and the confidence score, and the anomaly type is determined based on the total confidence, comparative confidence, and the preset historical anomaly feature template. Adjust the preset trigger amplitude threshold or the preset delay tripping window based on the anomaly candidate list, the confidence score, the anomaly type, and the total confidence. Adjust the preset peak amplitude threshold based on the time distribution characteristics of the latent anomaly determination results within the preset correction time and the anomaly type re-determined after adjusting the preset trigger amplitude threshold or the preset delay tripping window, or execute the tripping.

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