一种无刷直流电动机故障诊断方法研究
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摘要
提出一种基于小波熵和SOM神经网络的无刷直流电动机故障诊断方法,以无刷直流电动机的霍尔传感器和驱动器故障为研究对象,采用小波分析对故障信号进行分析,并在此基础上通过小波熵对故障特征进行提取,作为故障诊断部分(神经网络)的输入,由训练得到的神经网络对故障进行分类和识别,最后建立无刷直流电动机仿真模型,对该故障诊断方法进行仿真验证。
A fault-detection method for brushless direct current motor was poposed based on wavelet entropy and SOM network.The research object of the fault was Hall sensor and driver of the brushless direct current motor,then the fault was analyzed by using wavelet,and the fault features were extracted by using wavelet entropy. The fault was classified and identified by SOM network. A simulation model was established and the fault-detection method was verified.
A fault-detection method for brushless direct current motor was poposed based on wavelet entropy and SOM network.The research object of the fault was Hall sensor and driver of the brushless direct current motor,then the fault was analyzed by using wavelet,and the fault features were extracted by using wavelet entropy. The fault was classified and identified by SOM network. A simulation model was established and the fault-detection method was verified.
引文
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[14]杨忠林.基于小波包分解的逆变器一相开路故障诊断.[J]电机与控制应用,2011,38(7):34-37.
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[16]王冰,刁鸣,宋凯.基于小波奇异熵和相关向量机的氢气传感器故障诊断[J].电机与控制学报,2015,19(1):96-101.
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[18]DING H,GE H,LIU J.High performance of gas identificationby wavelet transform-based fast feature extraction from temperature modulated semiconductor gas sensors[J].Sensors&Actuators B Chemical,2005,107(2):749-755.
[2]张媛,陈宏韬,赵嵩.航天用无刷直流电动机故障模式及危害性分析[J].微特电机,2015,43(2):27-30.
[3]刘冬生等.基于小波分析和神经网络的电机故障诊断方法研究[J].天津理工大学学报,2009,25(1):11-14.
[4]吕永健,李子龙,张洪林,等.基于改进遗传小波网络的电机故障诊断研究[J].微特电机,2012,40(4):19-22.
[5]江龙,秦文甫.TMS320lf2407在舵机多通道控制系统的应用研究[J].航空兵器,2009,35(2):54-57.
[6]杨明,董传洋.基于电机驱动系统的齿轮故障诊断方法对比研究[J].电工技术学报,2016,31(19):132-140.
[7]周杨,马瑞卿,李添幸,等.无刷直流电动机逆变器双管开路故障仿真研究[J].微电机,2016,49(12):70-75.
[8]杨欣荣,蒋林,王婧林,等.基于小波变换的无刷直流电动机逆变器故障诊断[J].电测与仪表,2017,54(5):113-118.
[9]程啟华,盛国良.无刷直流电动机匝间短路故障检测及识别方法[J].微特电机,2014,42(2):14-17.
[10]刘昕彤,王红艳,张冬梅,等.无刷直流电动机在转子偏心故障时的容错控制研究[J].电机与控制应用,2017,44(5):121-127.
[11]潘汉明,雷良育,王子辉.基于小波分析的电动汽车轮毂电机永磁体故障诊断[J].中国机械工程,2016,27(11):1488-1492.
[12]ZHANG Z,WANG Y,WANG K.Intelligent fault diagnosis andprognosisapproach for rotating machinery integrating wavelet transform,principal component analysis,and artificial neural networks[J].International Journal of Advanced Manufacturing Technology,2013,68(1-4):763-773.
[13]CHEN X Y,SUN S C.Research on a fault diagnosismethod based on improved wavelet Network[J].International Journal of Science,2015,2(3):37-39.
[14]杨忠林.基于小波包分解的逆变器一相开路故障诊断.[J]电机与控制应用,2011,38(7):34-37.
[15]刘锴,王宜怀,徐达.无刷直流电动机霍尔位置传感器故障处理研究[J].电力电子技术,2017,51(7):93-96.
[16]王冰,刁鸣,宋凯.基于小波奇异熵和相关向量机的氢气传感器故障诊断[J].电机与控制学报,2015,19(1):96-101.
[17]郭清,夏虹,韩文伟.基于小波熵与BP神经网络的电机故障信号研究[J].仪表技术与传感器,2014,(1):96-99.
[18]DING H,GE H,LIU J.High performance of gas identificationby wavelet transform-based fast feature extraction from temperature modulated semiconductor gas sensors[J].Sensors&Actuators B Chemical,2005,107(2):749-755.