Reliability prediction method and device of circuit breaker spring operating mechanism and electronic equipment

By preprocessing and extracting the displacement, torque, and temperature characteristics of the spring operating mechanism of GIS circuit breakers, and using machine learning models to identify faults, the problems of omission and lack of timeliness in fault detection in existing technologies are solved, thereby improving the reliability of circuit breakers and the safety of power systems.

CN121090934APending Publication Date: 2025-12-09GUANGZHOU POWER SUPPLY BUREAU GUANGDONG POWER GRID CO LTD
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Patent Information

Application Number
CN202510927953.0
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-07-07
Publication Date
2025-12-09

AI Technical Summary

Technical Problem

In the existing technology, the fault detection of the spring operating mechanism of GIS circuit breaker has problems of omission and insufficient timeliness, which makes it impossible to accurately identify potential faults, affecting the reliability of the circuit breaker and the safety of the power system.

Method used

By acquiring displacement, torque, and temperature characteristic data of the spring operating mechanism, inputting them into a preset fault prediction model, performing data signal preprocessing and feature extraction, and combining machine learning algorithms such as the GBT model or LSTM model, the system can accurately and promptly identify faults and send early warning signals to monitoring equipment.

Benefits of technology

This improved the accuracy and timeliness of identifying faults in spring-operated mechanisms, reduced the failure rate of circuit breakers, and enhanced the safety and reliability of the power system.

✦ Generated by Eureka AI based on patent content.

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Abstract

The invention relates to a reliability prediction method and device for a circuit breaker spring operating mechanism and electronic equipment, and the method comprises the steps: inputting obtained displacement characteristic data, moment characteristic data and temperature characteristic data of the spring operating mechanism into a preset spring operating mechanism fault prediction model, and determining a fault prediction result of the spring operating mechanism according to the output of the preset spring operating mechanism fault prediction model. Furthermore, the fault prediction result of the spring operating mechanism is sent to the monitoring equipment, so that the monitoring equipment can display and / or output an early warning signal. Visibly, according to the embodiment of the invention, the fault state and the potential fault state of the spring operating mechanism can be accurately and timely identified, so that operation and maintenance personnel can timely check and maintain the spring operating mechanism, and the safety and the reliability of a power system can be improved.
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