高电压技术2025，Vol.51Issue(2)：660-668,9.DOI:10.13336/j.1003-6520.hve.20232219
基于多源传感器数据融合的断路器故障诊断方法
Fault Diagnosis Method of Circuit Breaker Based on Multi-source Sensor Data Fusion
张国宝 1王朝廷 2黄伟民 1杨为 1袁欢 2王小华2
作者信息
- 1. 国网安徽省电力有限公司电力科学研究院,合肥 230601
- 2. 西安交通大学电气工程学院,西安 710049
- 折叠
摘要
Abstract
To solve the problems of few identifiable fault types and low diagnosis accuracy of single-source sensor fault diagnosis,by utilizing current and vibration sensor data,we proposed a multi-source feature selection and fusion method based on the sequential forward selection(SFS)and fuzzy C-means(FCM)clustering.This method evaluates the cluster-ing performance by adjusting the Adjusted Rand Index(ARI),and selects and fuses the extracted multi-source sensor features to obtain the optimal feature set.Based on this,nine types of circuit breaker faults are simulated and divided into three classes.Support vector machine(SVM)is used to classify the single-source sensor features and the multi-source fu-sion features separately so as to verify the effectiveness of the proposed method.Moreover,three other common classifiers are used for comparison experiments.The results show that the multi-source fusion features have significantly higher recognition accuracy than the single-source features,reaching 95.0%,92.5%,and 96.5%,respectively,in the three classes of faults,and they can achieve similar results under multiple classifiers,which is effective and universal.The pro-posed method provides a new approach for circuit breaker fault diagnosis in the context of multi-source sensors.关键词
断路器/多源传感器/数据融合/特征筛选/模糊C均值聚类/故障诊断Key words
circuit breaker/multi-source sensors/data fusion/feature selection/fuzzy C-means clustering/fault diagnosis引用本文复制引用
张国宝,王朝廷,黄伟民,杨为,袁欢,王小华..基于多源传感器数据融合的断路器故障诊断方法[J].高电压技术,2025,51(2):660-668,9.
