转子断条与静态偏心复合故障诊断方法  

Composite Fault Diagnosis of Rotor Broken Bars and Static Eccentricity Based on Multi-Channel Adaptive Notch Filters and EEMD

作　　者：李双双[1] 田慕琴[1] 宋建成[1] 吝伶艳[1] 乔建强[2] 马兵[2] 

机构地区：[1]太原理工大学,太原030024 [2]太原重工股份有限公司,太原030024

出　　处：《微特电机》2017年第11期40-44,共5页Small & Special Electrical Machines

基　　金：国家自然科学基金项目(U1510112);国家自然科学基金项目(61472271);山西省煤基重点科技攻关项目(MJ2014-02)

摘　　要：为了探究笼型异步电动机中,转子断条和静态偏心两种故障的影响因素和耦合规律,提高转子断条与静态偏心复合故障识别的准确率,基于多通道自适应陷波和总体平均经验模态分解(ensemble empirical mode decomposition,EEMD)两种算法对转子断条与静态偏心复合故障进行诊断分析。首先采用自适应陷波技术滤除定子电流中的工频及奇次谐波,再对信号进行EEMD分解获得若干固有模态分量(intrinsic mode function,IMF)。然后对IMF分量进行包络分析,解调出故障特征频率,甄别故障类型。实验结果表明,该方法对转子断条与静态偏心复合故障能够准确识别。In order to explore the influence factors and coupling rules of the two kinds of faults on the squirrel cage in- duction motor, and to improve the identifying veracity of the composite fault of broken rotor bars and static eccentricity, a composite fault diagnosis method was presented based on the multi-channel adaptive notch filter and the ensemble average empirical mode decomposition （EEMD） algorithm. The multi-channel adaptive notch filter was used to filter out the power frequency and its odd harmonies. EEMD was applied to decompose the signal to some intrinsic mode components （IMF）. Based on that, the envelope analysis of the 1MF components was carried out, and the fault characteristic frequencies could be obtained to identify fault types. Experimental results show that the proposed method could effectively identify the com- posite fault of rotor broken bars and static eccentricity.

关 键 词：复合故障 转子断条 静态偏心 多通道自适应陷波 总体平均经验模态分解 固有模态分量 

分 类 号：TM343[电气工程—电机]