CAJ | 학술논문

电机轴承损伤会导致电机定子电流产生相应的电流谐波，电流谐波频率包含轴承故障特征频率。为了有效评估定子电流信号的复杂性(即电流谐波出现概率)，采用总体平均经验模态分解( EEMD)结合样本熵来实现，该方法先用EEMD将定子电流信号分解为若干个内禀模态分量，再计算分量的样本熵。通过比较得出在评估损伤轴承定子电流信号复杂性时EEMD样本熵的效果较样本熵更好，并且 EEMD样本熵增大-减小-增大的变化趋势与轴承损伤逐渐加大时定子电流的变化趋势一致。根据上述结论该方法可应用于封闭结构中电机轴承运行状态的监测和预判，也可以作为智能故障识别的信号源。
전궤축승손상회도치전궤정자전유산생상응적전류해파，전류해파빈솔포함축승고장특정빈솔。위료유효평고정자전류신호적복잡성(즉전류해파출현개솔)，채용총체평균경험모태분해( EEMD)결합양본적래실현，해방법선용EEMD장정자전류신호분해위약간개내품모태분량，재계산분량적양본적。통과비교득출재평고손상축승정자전류신호복잡성시EEMD양본적적효과교양본적경호，병차 EEMD양본적증대-감소-증대적변화추세여축승손상축점가대시정자전류적변화추세일치。근거상술결론해방법가응용우봉폐결구중전궤축승운행상태적감측화예판，야가이작위지능고장식별적신호원。
Damaged motor bearing may cause its stator current to generate the corresponding current harmonics.The bearing fault characteristic frequencies exist in the current harmonic frequencies. In order to effectively evaluate the complexity of the stator current signal( current harmonic generation probability), EEMD sample entropy is used to decompose the stator current into several intrinsic mode components, then the sample entropy of each component is calculated.comparison, in the stator current signal complexity as-sessment, it is gained that the effects of EEMD sample extropy are better than ones of the sample entropy. The EEMD sample entro-py variation is increase-decrease-increase trend which is consistented with the stator current variation trend when bearing damage gradual y increases. According to the above conclusions, this method can be used for monitoring and anticipating the motor bearing condition in enclosed structure and this signal source can be applied to the intel igent fault identification.