A Fault Detection Method for Multi-Sensor Data of Spring Circuit Breakers Based on the RF-Adaboost Algorithm
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 t...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-07-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/18/14/3890 |
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| _version_ | 1839616094881447936 |
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| author | Chuang Wang Peijie Cong Sifan Yu Jing Yuan Nian Lv Yu Ling Zheng Peng Haoyan Zhang Hongwei Mei |
| author_facet | Chuang Wang Peijie Cong Sifan Yu Jing Yuan Nian Lv Yu Ling Zheng Peng Haoyan Zhang Hongwei Mei |
| author_sort | Chuang Wang |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-e7a25b19f95f4cc0a01f4295bb386da1 |
| institution | Matheson Library |
| issn | 1996-1073 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj-art-e7a25b19f95f4cc0a01f4295bb386da12025-07-25T13:22:01ZengMDPI AGEnergies1996-10732025-07-011814389010.3390/en18143890A Fault Detection Method for Multi-Sensor Data of Spring Circuit Breakers Based on the RF-Adaboost AlgorithmChuang Wang0Peijie Cong1Sifan Yu2Jing Yuan3Nian Lv4Yu Ling5Zheng Peng6Haoyan Zhang7Hongwei Mei8Guangzhou Power Supply Bureau of Guangdong Power Grid Co., Ltd., Guangzhou 510030, ChinaGuangzhou Power Supply Bureau of Guangdong Power Grid Co., Ltd., Guangzhou 510030, ChinaGuangzhou Power Supply Bureau of Guangdong Power Grid Co., Ltd., Guangzhou 510030, ChinaGuangzhou Power Supply Bureau of Guangdong Power Grid Co., Ltd., Guangzhou 510030, ChinaGuangzhou Power Supply Bureau of Guangdong Power Grid Co., Ltd., Guangzhou 510030, ChinaGuangzhou Power Supply Bureau of Guangdong Power Grid Co., Ltd., Guangzhou 510030, ChinaGuangzhou Power Supply Bureau of Guangdong Power Grid Co., Ltd., Guangzhou 510030, ChinaShenzhen International Graduate School, Tsinghua University, Shenzhen 518055, ChinaShenzhen International Graduate School, Tsinghua University, Shenzhen 518055, ChinaIn 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.https://www.mdpi.com/1996-1073/18/14/3890spring-operated circuit breakermulti-sensor fusionRF-Adaboostfault detectioncondition-based maintenance |
| spellingShingle | Chuang Wang Peijie Cong Sifan Yu Jing Yuan Nian Lv Yu Ling Zheng Peng Haoyan Zhang Hongwei Mei A Fault Detection Method for Multi-Sensor Data of Spring Circuit Breakers Based on the RF-Adaboost Algorithm Energies spring-operated circuit breaker multi-sensor fusion RF-Adaboost fault detection condition-based maintenance |
| title | A Fault Detection Method for Multi-Sensor Data of Spring Circuit Breakers Based on the RF-Adaboost Algorithm |
| title_full | A Fault Detection Method for Multi-Sensor Data of Spring Circuit Breakers Based on the RF-Adaboost Algorithm |
| title_fullStr | A Fault Detection Method for Multi-Sensor Data of Spring Circuit Breakers Based on the RF-Adaboost Algorithm |
| title_full_unstemmed | A Fault Detection Method for Multi-Sensor Data of Spring Circuit Breakers Based on the RF-Adaboost Algorithm |
| title_short | A Fault Detection Method for Multi-Sensor Data of Spring Circuit Breakers Based on the RF-Adaboost Algorithm |
| title_sort | fault detection method for multi sensor data of spring circuit breakers based on the rf adaboost algorithm |
| topic | spring-operated circuit breaker multi-sensor fusion RF-Adaboost fault detection condition-based maintenance |
| url | https://www.mdpi.com/1996-1073/18/14/3890 |
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