基于小波包与SVM的风电变流器故障诊断
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摘要
针对风力发电系统中背靠背式PWM变流器故障诊断问题,以整流状态为例,提出一种基于小波包分析与SVM(支持向量机)分类算法相结合的故障诊断新方法。该方法选取直流侧输出电压信号为研究对象,分析不同开路故障状态下该信号的调制情况,利用小波包分析法提取故障特征样本,最后建立SVM的故障分类器,实现变流器的故障诊断。仿真结果表明该方法可有效实现风力发电系统中变流器的故障诊断。
Aiming at the fault diagnosis of back-to-back PWM converter in wind power generation system,taking therectifier state as an example,a new fault diagnosis method was presented based on wavelet packet analysis and supportvector machine(SVM)classification algorithm. DC-side output voltage signal was studied in this method to analyze themodulation degree of signals in the different types of open circuit fault,and fault features were extracted based onwavelet packet analysis,then the SVM-fault classifier was built to implement the fault diagnosis of three-pulse PWMconverter. The simulation results show that this method can effectively realize the fault diagnosis of converter used inwind power generation system.
Aiming at the fault diagnosis of back-to-back PWM converter in wind power generation system,taking therectifier state as an example,a new fault diagnosis method was presented based on wavelet packet analysis and supportvector machine(SVM)classification algorithm. DC-side output voltage signal was studied in this method to analyze themodulation degree of signals in the different types of open circuit fault,and fault features were extracted based onwavelet packet analysis,then the SVM-fault classifier was built to implement the fault diagnosis of three-pulse PWMconverter. The simulation results show that this method can effectively realize the fault diagnosis of converter used inwind power generation system.
引文
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[17]韩晓娟,曹慧,李勇,等.基于小波变换和LSSVM的短期风速预测方法[J].太阳能学报,2011,32(10):1538—1542.[17]Cao Xiaojuan,Cao Hui,Li Yong,et al.Short term wind speed prediction based on wavelet transform and LSSVM[J].Acta Energiae Solaris Sinica,2011,32(10):1538—1542.
[18]安学利,赵明浩,蒋东翔,等.基于支持向量机和多源信息的直驱风力发电机组故障诊断[J].电网技术,2011,35(4):117—122.[18]An Xueli,Zhao Minghao,Jiang Dongxiang,et al.Direct-drive wind turbine fault diagnosis based on support vector machine and multi-source information[J].Power System Technology,2011,35(4):117—122.
[19]刘永前,王飞,时文刚.基于支持向量机的风电机组运行工况分类方法[J].太阳能学报,2010,31(9):1191—1197.[19]Liu Yongqian,Wang Fei,Shi Wengang.Operation condition classification method for wind turbine based on support vector machine[J].Acta Energiae Solaris Sinica,2010,31(9):1191—1197.
[2]程启明,程尹曼,王映斐,等.风力发电系统技术的发展综述[J].自动化仪表,2012,33(1):1-8.[2]Cheng Qiming,Cheng Yinman,Wang Mingfei,et al.Overview of the development of control technique for wind power generation system[J].Process Automation Instrumentation,2012,33(1):1-8.
[3]孟恩隆,郭东杰,王灵梅,等.风力发电机组状态监测与智能故障诊断系统的设计与实现[J].华东电力,2012,(3):507-510.[3]Meng Enlong,Guo Dongjie,Wang Mingmei,et al.Design and implementation of condition monitoring and intelligent fault diagnosis system for wind turbines[J].East China Electric Power,2012,(3):507-510.
[4]Amirat Y,Benbouzid M E H,Al-Ahmar E,et al.A brief status on condition monitoring and fault diagnosis in wind energy conversion systems[J].Renewable and Sustainable Energy,2009,13(9):2629-2636.
[5]龙泉,刘永前,杨勇平.基于粒子群优化BP神经网络的发电机组齿轮箱故障诊断方法[J].太阳能学报,2012,33(1):120-125.[5]Long Quan,Liu Yongqian,Yang Yongping.Fault diagnosis method of wind turbine gearbox based on BP neural network trained by particle swarm optimization algorithm[J].Acta Energiae Solaris Sinica,2012,33(1):120-125.
[6]陈苏声,张全成,杨涛,等.风力发电机组安全保护技术分析评价[J].电气自动化,2012,34(1):46-48.[6]Chen Susheng,Zhang Quancheng,Yang Tao,et al.Analysis on the safety protection technique of wind turbine facility[J].Electrical Automation,2012,34(1):46-48.
[7]张登峰,郝伟,郝旺身.风力发电机组的振动测试与诊断[J].大电机技术,2012,(1):10-18.[7]Zhang Dengfeng,Hao Wei,Hao Wangshen.Vibration test and diagnosis of the wind generator[J].Large Electric Machine and Hydraulic Turbine,2012,(1):10-18.
[8]王磊,赵雷霆,张钢,等.电压型PWM整流器的开关器件断路故障特征[J].电工技术学报,2010,25(7):108-116.[8]Wang Lei,Zhao Leiting,Zhang Gang,et al.Analysis of fault characteristics after the breakdown of power switches in voltage-source PWM rectifiers[J].Transactions of China Electrotechnical Society,2010,25(7):108-116.
[9]荣先亮,姚鹏,段其昌.风电变流器的开路故障诊断[J].电机与控制应用,2009,36(12):47-51.[9]Rong Xianliang,Yao Peng,Duan Qichang.Open circuit fault diagnosis of converter for wind power generation system[J].Electric Machines&Control Application,2009,36(12):47-51.
[10]于辉,邓英.变速风力发电机变流器故障诊断方法[J].可再生能源,2010,28(3):89-92.[10]Yu Hui,Deng Ying.The diagnosis method for converter fault of the variable speed wind turbine[J].Renewable Energy Resources,2010,28(3):89-92.
[11]王磊,杜永红,赵雷廷.基于标幺化均值的大功率PWM整流器故障诊断[J].北京交通大学学报,2010,34(5):48-52.[11]Wang Lei,Du Yonghong,Zhao Leiting.Fault diagnosis for large-capacity PWM rectifier based on normalizedaverage[J].Journal of Beijing Jiaotong University,2010,34(5):48—52.
[12]张晓波,张新燕,王维庆.用小波分析来判定风力发电中电力电子的故障[J].电机技术,2008,(5):47—50.[12]Zhang Xiaobo,Zhang Xinyan,Wang Weiqing.Faultanalysis of power electronic devices in wind powersystem by means of wavelet analysis[J].ElectricalMachinery Technology,2008,(5):47—50.
[13]胡昌华,李国华,周涛.基于Matlab的系统分析与设计-小波分析[M].西安:西安电子科技大学出版社,2008.[13]Hu Changhua,Li Guohua,Zhou Tao.System analysisand design based on Matlab-wavelet analysis[M].Xi’an:Xidian University Publishing House,2008.
[14]Gong Xiaoyun,Han Jie,Chen Hong,et al.Applicationof full vector wavelet packet and envelope analysismethod in gear fault diagnosis[J].Journal of Vibrationand Shock,2012,31(12):92—95.
[15]张金敏,翟玉千,王思明.小波分解和最小二乘支持向量机的风机齿轮箱故障诊断[J].传感器与微系统,2011,30(1):41—43.[15]Zhang Jinmin,Zhai Yuqian,Wang Siming.Faultdiagnosis of wind turbine gearbox based on the waveletdecomposition and least square support vector machine[J].Transducer and Microsystem Technologies,2011,30(1):41—43.
[16]周松林,峁美琴,苏建徽.基于小波分析与支持向量机的风速预测[J].太阳能学报,2012,33(3):452—456.[16]Zhou Songlin,Mao Meiqin,Su Jianhui.Wind speed forecasting based on wavelet analysis and support vector machine[J].Acta Energiae Solaris Sinica,2012,33(3):452—456.
[17]韩晓娟,曹慧,李勇,等.基于小波变换和LSSVM的短期风速预测方法[J].太阳能学报,2011,32(10):1538—1542.[17]Cao Xiaojuan,Cao Hui,Li Yong,et al.Short term wind speed prediction based on wavelet transform and LSSVM[J].Acta Energiae Solaris Sinica,2011,32(10):1538—1542.
[18]安学利,赵明浩,蒋东翔,等.基于支持向量机和多源信息的直驱风力发电机组故障诊断[J].电网技术,2011,35(4):117—122.[18]An Xueli,Zhao Minghao,Jiang Dongxiang,et al.Direct-drive wind turbine fault diagnosis based on support vector machine and multi-source information[J].Power System Technology,2011,35(4):117—122.
[19]刘永前,王飞,时文刚.基于支持向量机的风电机组运行工况分类方法[J].太阳能学报,2010,31(9):1191—1197.[19]Liu Yongqian,Wang Fei,Shi Wengang.Operation condition classification method for wind turbine based on support vector machine[J].Acta Energiae Solaris Sinica,2010,31(9):1191—1197.