电动机故障诊断技术探讨  

Study on fault diagnosis technologies of motor

作　　者：王惠中[1,2] 効迎春 张荧 朱宏毅[1,2] 

机构地区：[1]兰州理工大学电气工程与信息工程学院,甘肃兰州730050 [2]甘肃省工业过程先进控制重点实验室,甘肃兰州730050

出　　处：《工矿自动化》2015年第1期40-44,共5页Journal Of Mine Automation

基　　金：国家自然科学基金资助项目(50967001)

摘　　要：介绍了电动机常见电气故障和机械故障的类型及产生原因,详细阐述了短时傅里叶变换、小波变换、小波包变换、经验模态分解等基于信号处理的诊断方法,以及基于专家系统、模糊理论、支持向量机、神经网络等的智能诊断方法在电动机故障诊断中的应用,指出多种诊断方法相结合以及信息融合方法是电动机故障诊断技术的发展趋势。The paper introduced types and causes of common electrical and mechanical faults of motor,and described application of signal processing methods and intelligent diagnosis methods in fault diagnosis of motor. The signal processing methods include short-time Fourier transform, wavelet transform, wavelet packet transform and empirical mode decomposition. The intelligent diagnosis methods include expert system, fuzzy theory, support vector machine and neural network. It also pointed out development trend of fault diagnosis technologies of motor is combination of multiple diagnosis methods and information fusion method.

关 键 词：电动机 故障诊断 信号处理 智能诊断 

分 类 号：TD614[矿业工程—矿山机电]