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高压电器  2015 

特征评估高压断路器机械故障诊断方法的研究

DOI: 10.13296/j.1001-1609.hva.2015.12.016, PP. 89-95

Keywords: 高压断路器, 能量熵, 支持向量机, 故障诊断

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Abstract:

分析断路器的机械振动信号的特性,针对采用单一性质故障特征难以实现整个故障状态空间上准确诊断的局限性,提出了一种基于改进的距离评估技术和多类支持向量机相结合的诊断高压断路器机械故障的方法,该方法由3部分构成首先从高压断路器机械振动信号中提取时域统计特征、频域统计特征、经验模态分解能量熵及小波包能量特征信息;接着采用改进的距离评估技术从原始特征集合中选取最优特征,实现对原始特征空间的降维处理;最后选取的最优特征量作为“次序二叉树”策略方式的多类支持向量机的输入向量,实现对断路器3种机械故障模式的识别。实验结果表明,该方法诊断高压断路器机械故障能取得良好的效果。

References

[1]  POLYCARPOU A A,SOOM A,PETER J W,et al. Event timing and shape analysis of vibration bursts from power circuit breakers[J]. IEEE Trans. on Power Delivery,1996,11(2):848?鄄857.
[2]  HOIDALEN H K,RUNDE M.Continuous monitoring of circuit breakers using vibration analysis[J]. IEEE Transactions on Power Delivery,2005:20(4):2458?鄄2465.
[3]  DENNIS S S L,LITHGOW B J,MORRISON R E.New fault diagnosis of circuit breakers[J]. IEEE Trans. on Power Delivery,2003,18(2):454?鄄459.
[4]  LANDRY M,LONARD F,BEAUCHEMIN R. An improved vibration analysis algorithm as a diagnostic tool for detecting mechanical anomalies on power circuit breakers[J]. IEEE Transactions on Power Delivery,2008,23(4):1986?鄄1994.
[5]  RUNDE M,OTTESEN G E, SKVBERG B. Vibration analysis for diagnostic testing of circuit breakers[J]. IEEE Trans. on Power Delivery,1996,11(4):1816?鄄1823.
[6]  沈 力,黄瑜珑,钱家骊. 高压断路器机械状态监测的研究[J]. 中国电机工程学报,1997,17(2):113?鄄117. SHEN Li,HUANG Yulong,QIAN Jiali. Research on mechanical condition monitoring for HV circuit breakers[J].Proceedings of the CSEE,1997,17(2):113?鄄117.
[7]  齐 贺,赵智忠. 基于多传感器振动信号融合的真空断路器故障诊断[J]. 高压电器,2013,49(2):43?鄄47 QI He,ZHAO Zhizhong. Fault diagnosis of vacuum circuit breaker based on multi?鄄sensor for vibration signals of fusion[J]. High Voltage Apparatus,2013,49(2):43?鄄47.
[8]  赵 洋,刘汉宇. 基于机械振动信号的高压真空断路器故障诊断研究[J]. 高压电器,2010,46(2):46?鄄49. ZHAO Yang,LIU Hanyu. Study on fault diagnosis of high voltage vacuum circuit breaker based on mechanical vibration signal[J]. High Voltage Apparatus,2010,46(2):46?鄄49.
[9]  潘 微,宋政湘.基于振动的断路器状态检测系统的设计与开发[J]. 高压电器,2014,50(12):83?鄄87. PAN Hui,SONG Zhengxiang. Design and development of condition monitoring system for circuit breaker based on vibration signal[J]. High Voltage Apparatus,2014,50(12):83?鄄87.
[10]  桂中华,韩凤琴. 小波包特征熵神经网络在尾水管故障诊断中的应用[J]. 中国电机工程学报,2005,25(4):99?鄄102. GUI Zhonghua,HAN Fengqin. Neural network based on wavelet packet characteristic entropy for fault diagnosis of draft tube[J]. Proceeding of the CSEE,2005,25(4):99?鄄102.
[11]  HUANG Jian,HU Xiaoguang. Support vector machine with genetic algorithm for machinery fault diagnosis of high voltage circuit breaker[J]. Measurement,2011,44:1018?鄄1027.
[12]  HUANG Jian,HU Xiaoguang,GENG Xin. An intelligent fault diagnosis method of high voltage circuit breaker based on improved EMD energy entropy and multi?鄄class support vector machine[J]. Electrical Power System Research,2011,81(2),400?鄄407.
[13]  孙来军,胡晓光,纪延超,等. 基于支持向量机的高压断路器机械状态分类[J]. 电工技术学报,2006,21(8)53?鄄58. SUN Laijun,HU Xiaoguang,JI Yanchao,et al. Fault classification of high voltage circuit breakers based on support vector machine[J]. Proceeding of the CSEE,2006,21(8):53?鄄58.
[14]  胡 清,王荣杰,詹宜巨. 基于支持向量机的电力电子电路故障诊断技术[J]. 中国电机工程学报,2005,28(12):107?鄄111. HU Qing,WANG Rongjie,ZHANG Yiju.Fault diagnosis technology based on SVM in power electronics circuit[J]. Proceeding of the CSEE,2008,28(12):107?鄄111.
[15]  张国钢,王宏伟. 基于EMD方法的高压断路器液压机构振动信号分析[J]. 高压电器,2008,44(3):193?鄄197. ZHANG Guogang,WANG Hongwei. Vibration signal analysis of hydraulic operating mechanism for voltage circuit breaker based on EMD method[J]. High Voltage Apparatus,2008,44(3):193?鄄197.
[16]  陈伟根,邓帮飞. 基于振动信号经验模态分解及能量熵的高压断路器故障识别[J]. 高压电器,2009,45(2):90?鄄93. CHEN Weigen,DENG Bangfei. Fault recognization for high voltage breaker based on emd of vibration signal and energy entropy chaeacteristic[J]. High Voltage Apparatus,2009,45(2):90?鄄93.
[17]  YANY Y, YU D J,CHENG J S. A roller bearing fault diagnosis method based on EMD energy entropy and ANN [J]. Journal of Sound and Vibration,2006,29(4):269?鄄277.
[18]  唐发明,王仲东,陈绵云.支持向量机多类分类算法研究[J]. 控制与决策,2005,20(7):746?鄄749. TANG Faming,WANG Zhongdong,CHEN Mianyun. On multiclass classification methods for support vector machines[J]. Control and Decision,2005,20(7):746?鄄749.
[19]  HUANG N E,SHEN Z, LONG S R,et al. The empirical mode decomposition and the hilbert spectrum for nonlinear and non?鄄stationary time series analysis[J]. Proceedings of the Royal Society of London Series,1998(454):903?鄄995.

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