A Fault Detection Method for Multi-Sensor Data of Spring Circuit Breakers Based on the RF-Adaboost Algorithm

Chuang Wang, Peijie Cong (), Sifan Yu, Jing Yuan, Nian Lv, Yu Ling, Zheng Peng, Haoyan Zhang and Hongwei Mei ()
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Chuang Wang: Guangzhou Power Supply Bureau of Guangdong Power Grid Co., Ltd., Guangzhou 510030, China
Peijie Cong: Guangzhou Power Supply Bureau of Guangdong Power Grid Co., Ltd., Guangzhou 510030, China
Sifan Yu: Guangzhou Power Supply Bureau of Guangdong Power Grid Co., Ltd., Guangzhou 510030, China
Jing Yuan: Guangzhou Power Supply Bureau of Guangdong Power Grid Co., Ltd., Guangzhou 510030, China
Nian Lv: Guangzhou Power Supply Bureau of Guangdong Power Grid Co., Ltd., Guangzhou 510030, China
Yu Ling: Guangzhou Power Supply Bureau of Guangdong Power Grid Co., Ltd., Guangzhou 510030, China
Zheng Peng: Guangzhou Power Supply Bureau of Guangdong Power Grid Co., Ltd., Guangzhou 510030, China
Haoyan Zhang: Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China
Hongwei Mei: Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China

Energies, 2025, vol. 18, issue 14, 1-17

Abstract: In the context of increasing the complexity and intelligence of modern power systems, traditional maintenance approaches for circuit breakers have shown limitations in meeting both reliability and economic requirements. This paper proposes a multi-sensor data fusion fault detection method based on the RF-Adaboost algorithm for spring-operated circuit breakers. By integrating pressure, speed, coil current, and energy storage motor sensors into the mechanism, multi-source operational data are acquired and processed via denoising and feature extraction techniques. A fault detection model is then constructed using the RF-Adaboost classifier. The experimental results demonstrate that the proposed method achieves over 96% accuracy in identifying typical fault states such as coil voltage deviation, reset spring fatigue, and closing spring degradation, outperforming conventional approaches. These results validate the model’s effectiveness and robustness in diagnosing complex mechanical failures in circuit breakers.

Keywords: spring-operated circuit breaker; multi-sensor fusion; RF-Adaboost; fault detection; condition-based maintenance (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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