基于多参量的高压断路器分/合闸线圈的故障诊断
|
摘要
由于分/合闸线圈电流信号和振动信号的变化均可以反映操动机构的运行状态,因此文中阐述了根据多参量来诊断高压断路器分/合闸线圈故障的一种新方法,以提高高压断路器故障诊断的准确率。文中首先介绍了操动机构电磁铁的动作状态,并分析操动机构电流信号与运行状态的关系,其次设计了一套以NI数据采集卡和实时控制器为核心的硬件电路,最后运用多层小波包分解与重构算法对信号进行滤波,结合极值法对信号进行特征值提取,并采用粒子群优化算法与支持向量机相结合的方法进行状态分类。实验结果表明,文中提出的算法能够及时发现高压断路器运行过程中存在的安全隐患,有效提高高压断路器的运行可靠性。
Because the change of tripping/closing coil current(CC)and the vibration signal can reflect the run-ning state of an operating mechanism,a new method based on multiple parameters is presented for fault diagno-sis of tripping/closing coil of the high-voltage circuit breakers(HVCBs)and for improving the accuracy of the fault diagnosis. First,the operation state of the actuator electromagnet is introduced,and the relationship be-tween the signals and the operating states of the actuator is analyzed. Second, a hardware circuit taking the NI data acquisition card and the real-time controller as the core is designed. Third, the multi-layer wavelet packet(WP)decomposition and reconstruction algorithm is used to filter the signals,and the extreme value method is used to extract the eigen-values. Finally,the particle swarm optimization(PSO)method is combined with the support vector machine(SVM)to classify the states of HVCBs. Experimental results show that the present algo-rithm can detect the hidden failure of HVCBs in operation and improve their reliability.
Because the change of tripping/closing coil current(CC)and the vibration signal can reflect the run-ning state of an operating mechanism,a new method based on multiple parameters is presented for fault diagno-sis of tripping/closing coil of the high-voltage circuit breakers(HVCBs)and for improving the accuracy of the fault diagnosis. First,the operation state of the actuator electromagnet is introduced,and the relationship be-tween the signals and the operating states of the actuator is analyzed. Second, a hardware circuit taking the NI data acquisition card and the real-time controller as the core is designed. Third, the multi-layer wavelet packet(WP)decomposition and reconstruction algorithm is used to filter the signals,and the extreme value method is used to extract the eigen-values. Finally,the particle swarm optimization(PSO)method is combined with the support vector machine(SVM)to classify the states of HVCBs. Experimental results show that the present algo-rithm can detect the hidden failure of HVCBs in operation and improve their reliability.
引文
[1]徐国政,张节容,钱家骊,等.高压断路器原理和应用[M].北京:清华大学出版社,2000.XU Guozheng,ZHANG Jierong,Qian Jiali,et al.Principies highvoltage circuit breakers[M].Beijing:Tsinghua University Press,2000.
[2]HOIDALEN H K,RUNDE M.Continuous monitoring of circuit breakers using vibration analysis[J].IEEE Transactions on Power Delivery,2005,20(4):2458-2465.
[3]STRACHAN S,MCARTHUR S,MCDONALD J.Providing decision support for the condition-based maintenance of circuit breakers through data mining of trip coil current signatures[J].IEEE Transactions on Power Delivery,2007:22(1):178-186.
[4]STRACHAN S,STEPHEN M.Trip coil signature analysis and interpretation for distributed circuit breaker condition assessment[C]//Eighteenth International Conference and Exhibition on Electricity Distribution.Turin,Italy:[s.n.],2005:559-563.
[5]宋锦刚,许长青,朱统亮.基于波形辨识技术的SF6断路器分/合闸线圈电路监测[J].电力建设,2011,32(3):65-68.ONG Jingang,XU Changqing,ZHU Tongliang.Coil current monitoring of SF6 circuit breakers based on waveform identification[J].Electric Power Construction,2011,32(3):65-68.
[6]袁金丽,李奎,郭志涛.基于SVM与分/合闸线圈电流参数的高压断路器机械故障诊断[J].高压电器,2011,47(3):26-30.YUAN Jinli,LI Kui,GUO Zhitao.Mechanical failure diagnosis of high voltage circuit breaker based on SVM and opening/closing coil current parameters[J].High Voltage Apparatus,2011,47(3):26-30.
[7]黄建,胡晓光,巩玉楠.高压断路器机械故障诊断专家系统设计[J].电机与控制学报,2011,15(10):43-49.HUANG Jian,HU Xiaoguang,GONG Yunan.Machinery fault diagnosis expert system for high voltage circuit breaker[J].Electric Machines and Control,2011,15(10):43-49.
[8]胡晓光,孙来军,纪延超.基于线圈电流和触点状态的断路器故障分析[J].电力自动化设备,2006,26(8):5-11.HU Xiaoguang,SUN Laijun and JI Yanchao.Circuit breaker fault analysis based on coil currents and contact states[J].Electric Power Automation Equipment,2006,26(8):5-11.
[9]曹志彤,何国光,陈宏平.电机故障特征值的倍频小波分析[J].中国电机工程学报,2003,23(7):112-116.CAO Zhitong,HE Guoguang,CHEN Hongping.Multiple bandwidth wavelet analysis for fault diagnosis eigenvalue in squirrel-cage induction motor[J].Proceedings of the CSEE,2003,23(7):112-116.
[10]MENG Y P,JIA S L.Condition monitoring of vacuum circuit breakers using vibration analysis[C]//International Symposium on Discharges and Electrical Insulation in Vacuum.Yalta,Ukraine:[s.n.],2004:341-344.
[11]孙来军,胡晓光.一种基于振动信号的高压断路器故障诊断新方法[J].中国电机工程学报,2006,26(6):157-161.SUN Laijun,HU Xiaoguang.A new method of fault diagnosis for high-voltage circuit breakers based on vibration signals[J].Proceeding of the CSEE,2006,26(6):157-161.
[12]黄建,胡晓光,巩玉楠.基于经验模态分解的高压断路器机械故障诊断方法[J].中国电机工程学报,2011,31(12):108-113.HUANG Jian,HU Xiaoguang,GONG Yunan.Machinery fault diagnosis of high voltage circuit breaker based on empirical mode decomposition[J].Proceeding of the CSEE,2011,31(12):108-113.
[13]薛蕙,杨仁刚.小波包变换(WPT)频带划分特性的分析[J].电力系统及其自动化学报,2003,15(2):5-8.XUE Hui,YANG Rengang.Analysis of frequency band division of wavelet packet transform[J].Automation of Electric Power Systems,2003,15(2):5-8.
[14]孙来军,胡晓光.改进的小波包-特征熵在高压断路器故障诊断中的应用[J].中国电机工程学报,2007,27(12):103-108.SUN Laijun,HU Xiaoguang.Application of improved wavelet packet-feature entropy in fault diagnosis of highvoltage circuit breakers[J].Proceeding of the CSEE,2007,27(12):103-108.
[15]THELAIDJIA T,CHENIKHER S.A new approach of preprocessing with PSO and SVM for bearing fault diagnosis[C]//13th International Conference on Hybrid Intelligent Systems,Gammarth,Tunisia:[s.n.],2014:319-324.
[16]HUANG C L,WANG C J.A GA-based feature selection and parameters optimization for support vector machines[J].Expert Systems with Applications,2006,31(2):231-240.
[17]LIU Z W,CAO H R.Multi-fault classification based on wavelet SVM with PSO algorithm to analyze vibration signals from rolling element bearings[J].Neurocomputing,2013(99):399-410.
[18]马强,荣命哲.基于振动信号小波包提取和短时能量分析的高压断路器合闸同期性的研究[J].中国电机工程学报,2005,25(13):149-154.MA Qiang,RONG Mingzhe.Study of switching synchronization of high-voltage circuit breakers based on the wavelet packets extraction algorithm and short time analysis method[J].Proceedings of the CSEE,2005,25(13):149-154.
[19]李恒真,谢志杨,王继锋.基于K-S检验法和SVM的高压断路器分合闸线圈回路故障诊断[J].电气应用,2016(9):53-58.LI Hengzhen,XIE Zhiyang,WANG Jifeng.Fault diagnosis of high-voltage circuit breaker closing coil circuit based on K-S test method and SVM[J].Electrical application,2016(9):53-58.
[20]SILVA M S,JARDINI J A,MAGRINI L C.Determination of the circuit breaker operation times using the wavelet transform[C]//IEEE Power Engineering Society General Meeting,Denver,Co.,United States:IEEE,2004:1214-1219.
[21]HOU Pingyin,BAI Shijun,GE Yun.Research on expert diagnosis system for mechanical fault of high voltage circuit breaker based on fuzzy matrix and neural network[C]//CMD2016-International Conference on Condition Monitoring and Diagnosis.Xian,China:[s.n.],2016:139-143.
[22]LIU Z W,CAO H R.Multi-fault classification based on wavelet SVM with PSO algorithm to analyze vibration signals from rolling element bearings[J].Neurocomputing,2013(99):399-410.233
[2]HOIDALEN H K,RUNDE M.Continuous monitoring of circuit breakers using vibration analysis[J].IEEE Transactions on Power Delivery,2005,20(4):2458-2465.
[3]STRACHAN S,MCARTHUR S,MCDONALD J.Providing decision support for the condition-based maintenance of circuit breakers through data mining of trip coil current signatures[J].IEEE Transactions on Power Delivery,2007:22(1):178-186.
[4]STRACHAN S,STEPHEN M.Trip coil signature analysis and interpretation for distributed circuit breaker condition assessment[C]//Eighteenth International Conference and Exhibition on Electricity Distribution.Turin,Italy:[s.n.],2005:559-563.
[5]宋锦刚,许长青,朱统亮.基于波形辨识技术的SF6断路器分/合闸线圈电路监测[J].电力建设,2011,32(3):65-68.ONG Jingang,XU Changqing,ZHU Tongliang.Coil current monitoring of SF6 circuit breakers based on waveform identification[J].Electric Power Construction,2011,32(3):65-68.
[6]袁金丽,李奎,郭志涛.基于SVM与分/合闸线圈电流参数的高压断路器机械故障诊断[J].高压电器,2011,47(3):26-30.YUAN Jinli,LI Kui,GUO Zhitao.Mechanical failure diagnosis of high voltage circuit breaker based on SVM and opening/closing coil current parameters[J].High Voltage Apparatus,2011,47(3):26-30.
[7]黄建,胡晓光,巩玉楠.高压断路器机械故障诊断专家系统设计[J].电机与控制学报,2011,15(10):43-49.HUANG Jian,HU Xiaoguang,GONG Yunan.Machinery fault diagnosis expert system for high voltage circuit breaker[J].Electric Machines and Control,2011,15(10):43-49.
[8]胡晓光,孙来军,纪延超.基于线圈电流和触点状态的断路器故障分析[J].电力自动化设备,2006,26(8):5-11.HU Xiaoguang,SUN Laijun and JI Yanchao.Circuit breaker fault analysis based on coil currents and contact states[J].Electric Power Automation Equipment,2006,26(8):5-11.
[9]曹志彤,何国光,陈宏平.电机故障特征值的倍频小波分析[J].中国电机工程学报,2003,23(7):112-116.CAO Zhitong,HE Guoguang,CHEN Hongping.Multiple bandwidth wavelet analysis for fault diagnosis eigenvalue in squirrel-cage induction motor[J].Proceedings of the CSEE,2003,23(7):112-116.
[10]MENG Y P,JIA S L.Condition monitoring of vacuum circuit breakers using vibration analysis[C]//International Symposium on Discharges and Electrical Insulation in Vacuum.Yalta,Ukraine:[s.n.],2004:341-344.
[11]孙来军,胡晓光.一种基于振动信号的高压断路器故障诊断新方法[J].中国电机工程学报,2006,26(6):157-161.SUN Laijun,HU Xiaoguang.A new method of fault diagnosis for high-voltage circuit breakers based on vibration signals[J].Proceeding of the CSEE,2006,26(6):157-161.
[12]黄建,胡晓光,巩玉楠.基于经验模态分解的高压断路器机械故障诊断方法[J].中国电机工程学报,2011,31(12):108-113.HUANG Jian,HU Xiaoguang,GONG Yunan.Machinery fault diagnosis of high voltage circuit breaker based on empirical mode decomposition[J].Proceeding of the CSEE,2011,31(12):108-113.
[13]薛蕙,杨仁刚.小波包变换(WPT)频带划分特性的分析[J].电力系统及其自动化学报,2003,15(2):5-8.XUE Hui,YANG Rengang.Analysis of frequency band division of wavelet packet transform[J].Automation of Electric Power Systems,2003,15(2):5-8.
[14]孙来军,胡晓光.改进的小波包-特征熵在高压断路器故障诊断中的应用[J].中国电机工程学报,2007,27(12):103-108.SUN Laijun,HU Xiaoguang.Application of improved wavelet packet-feature entropy in fault diagnosis of highvoltage circuit breakers[J].Proceeding of the CSEE,2007,27(12):103-108.
[15]THELAIDJIA T,CHENIKHER S.A new approach of preprocessing with PSO and SVM for bearing fault diagnosis[C]//13th International Conference on Hybrid Intelligent Systems,Gammarth,Tunisia:[s.n.],2014:319-324.
[16]HUANG C L,WANG C J.A GA-based feature selection and parameters optimization for support vector machines[J].Expert Systems with Applications,2006,31(2):231-240.
[17]LIU Z W,CAO H R.Multi-fault classification based on wavelet SVM with PSO algorithm to analyze vibration signals from rolling element bearings[J].Neurocomputing,2013(99):399-410.
[18]马强,荣命哲.基于振动信号小波包提取和短时能量分析的高压断路器合闸同期性的研究[J].中国电机工程学报,2005,25(13):149-154.MA Qiang,RONG Mingzhe.Study of switching synchronization of high-voltage circuit breakers based on the wavelet packets extraction algorithm and short time analysis method[J].Proceedings of the CSEE,2005,25(13):149-154.
[19]李恒真,谢志杨,王继锋.基于K-S检验法和SVM的高压断路器分合闸线圈回路故障诊断[J].电气应用,2016(9):53-58.LI Hengzhen,XIE Zhiyang,WANG Jifeng.Fault diagnosis of high-voltage circuit breaker closing coil circuit based on K-S test method and SVM[J].Electrical application,2016(9):53-58.
[20]SILVA M S,JARDINI J A,MAGRINI L C.Determination of the circuit breaker operation times using the wavelet transform[C]//IEEE Power Engineering Society General Meeting,Denver,Co.,United States:IEEE,2004:1214-1219.
[21]HOU Pingyin,BAI Shijun,GE Yun.Research on expert diagnosis system for mechanical fault of high voltage circuit breaker based on fuzzy matrix and neural network[C]//CMD2016-International Conference on Condition Monitoring and Diagnosis.Xian,China:[s.n.],2016:139-143.
[22]LIU Z W,CAO H R.Multi-fault classification based on wavelet SVM with PSO algorithm to analyze vibration signals from rolling element bearings[J].Neurocomputing,2013(99):399-410.233