Method and device for monitoring state of air circuit breaker, computing equipment and storage medium

By using a physical information neural network model combined with the data of multiple measurement devices, the accuracy of air circuit breaker power loss and status monitoring is solved, real-time and accurate ACB status monitoring is achieved, and the reliability and efficiency of the power distribution system is improved.

CN120577684APending Publication Date: 2025-09-02SIEMENS (CHINA) CO LTD
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Patent Information

Application Number
CN202510703549.5
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-05-28
Publication Date
2025-09-02

AI Technical Summary

Technical Problem

The prior art is difficult to accurately calculate the power loss of air circuit breakers, and there are measurement errors and installation method dependencies, making it difficult to achieve accurate ACB status monitoring.

Method used

Using a physical information neural network (PINN) model, combining data and physical constraints from multiple measurement devices, the model is trained to predict the state of ACB over the entire current range, including performance under low current and high current conditions.

Benefits of technology

Real-time and accurate monitoring of ACB status is achieved, the reliability and efficiency of the system is improved, potential problems can be identified early, fault risks are reduced, and energy management is optimized.

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Abstract

The invention relates to a method and device for monitoring the state of an air circuit breaker, computing equipment and a storage medium. The method comprises the steps that measurement data related to a target ACB is received from multiple pieces of measurement equipment; inputting the received measurement data into a pre-trained physical information neural network model; and predicting the state of the target ACB in the whole current range based on the PINN model.
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