电工技术学报  2023, Vol. 38 Issue (1): 26-36    DOI: 10.19595/j.cnki.1000-6753.tces.220639
数字化技术在输变电设备状态评估中的应用(特约主编:谢 庆教授 汲胜昌教授等) |
面向高压断路器故障分类的电流-振动信号类聚几何敏感特征优选方法
刘会兰1, 许文杰1, 赵书涛1, 裘实2, 刘教民1
1.河北省输变电设备安全防御重点实验室(华北电力大学) 保定 071003;
2.国网河北省电力有限公司保定供电分公司 保定 071000
Optimization Method of Clustering Geometric Sensitive Features of Current Vibration Signals for Fault Classification of High Voltage Circuit Breakers
Liu Huilan1, Xu Wenjie1, Zhao Shutao1, Qiu Shi2, Liu Jiaomin1
1. Hebei Provincial Key Laboratory of Power Transmission Equipment Security Defense North China Electric Power University Baoding 071003 China;
2. Baoding Power Supply Company State Grid Hebei Electric Power Co. Ltd Baoding 071000 China
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摘要 针对利用电流-振动信号联合进行高压断路器故障分类过程中原始特征集维数较高,因而造成识别率低、分类性能退化的问题,该文提出一种适用于高维小样本的类聚几何敏感特征优选方法。首先,利用广义维数谱和敏感维数定量刻画经魏格纳-威尔分布处理的振动信号时频图,结合线圈电流信号的突变信息,构建断路器完整动作过程的电-振联合多征兆域原始特征集;其次,通过定义“变异系数”细致描绘特征在样本类内和类间的波动性,由“赏函数”对类间发散性强的特征予以加权,根据特征敏感因子优选得到不同故障类型下的类聚几何最优特征集;最后,采用支持向量机和其他识别方法进行故障分类。试验结果表明采用最优特征集识别准确率明显提高,具有工程应用价值。
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刘会兰
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裘实
刘教民
关键词 高压断路器电流-振动信号联合类聚几何特征优选敏感维数    
Abstract:High voltage circuit breaker is the key safety control equipment of power system, and the loss caused by its failure is far more than its own value. The action of the circuit breaker involves the secondary electrical circuit control and the energy transmission process between mechanical components. Its complex structure and harsh operating environment are easy to cause electrical or mechanical failures. The control coil current and the vibration signal in the transmission process are effective characteristics for analyzing the abnormal operating state of the circuit breaker. In the process of fault classification of high-voltage circuit breakers using current vibration signals, the dimension of the original feature set is high, resulting in low recognition rate and degradation of classification performance. This paper proposes a clustering geometric sensitive feature optimization method suitable for high-dimensional and small samples.
Firstly, the time-frequency diagram of vibration signal processed by Wigner-Ville Distribution (WVD) is quantitatively characterized by generalized dimension spectrum and sensitive dimension. The time-frequency diagram reflects the energy difference of the circuit breaker vibration signal in the form of color scale. The generalized dimension spectrum and sensitive dimension quantitatively depict the local characteristics of the time-frequency diagram, and carefully capture the time-frequency changes. Secondly, using the mutation information of the coil current signal decomposed by singular value decomposition to extend the time history of the vibration signal, the original feature set of the electrical vibration joint multi symptom domain for the complete action process of the circuit breaker is constructed. Finally, the "coefficient of variation" is defined to describe the volatility of the characteristics in the samples within and between classes, the "reward function" is used to weight the characteristics of strong divergence between classes, and the optimal collection of clustering geometry under different fault types is obtained according to the optimization of feature sensitivity factors. The corresponding relationship between the fault types and the optimal feature set is clarified.
Taking ZN63-12 high-voltage circuit breaker as the research object, a fault simulation experiment platform is built. The experimental platform is used to simulate nine states of the circuit breaker, including normal, electrical fault, mechanical fault and compound fault. For each type of target state group, the feature sensitivity factor of a specific state group is calculated respectively, and the support vector machine (SVM) method is used to classify faults, and finally the optimal feature set under a specific fault type is selected. The experiment shows that: ①The original feature set of electrical vibration combined multi symptom domain in the complete action process of the circuit breaker can fully reflect the electrical fault, mechanical fault and compound fault of the circuit breaker. ②The optimization method of clustered geometric sensitive features is proposed to solve the problem of high-dimensional small samples of fault classification, and the optimal feature set for different fault types is scientifically screened through more comprehensive "rewards and punishments". ③The SVM method based on clustering geometric optimization feature set gives consideration to the accuracy of fault classification and computational performance, and has engineering application value.
Key wordsHigh voltage circuit breaker    current-vibration combination    aggregation geometry    feature optimization    sensitive dimension   
收稿日期: 2022-04-23     
PACS: TM561  
基金资助:中央高校基本科研业务费专项资金资助项目(2021MS064)
通讯作者: 刘会兰,女,1986年生,博士研究生,工程师,研究方向为电力设备故障诊断、智能电器监测技术及分布式电源并网技术。E-mail:liuhuilan111@163.com   
作者简介: 许文杰,男,1997年生,硕士研究生,研究方向为电力设备在线监测与故障诊断。E-mail: xuwenjie19784624@126.com
引用本文:   
刘会兰, 许文杰, 赵书涛, 裘实, 刘教民. 面向高压断路器故障分类的电流-振动信号类聚几何敏感特征优选方法[J]. 电工技术学报, 2023, 38(1): 26-36. Liu Huilan, Xu Wenjie, Zhao Shutao, Qiu Shi, Liu Jiaomin. Optimization Method of Clustering Geometric Sensitive Features of Current Vibration Signals for Fault Classification of High Voltage Circuit Breakers. Transactions of China Electrotechnical Society, 2023, 38(1): 26-36.
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