摘要
针对传统的异步电动机轴承故障诊断方法对于轴承的局部缺陷及早期故障的诊断效果不明显的问题,提出了一种采用小波包理论与EMD相结合的方式提取异步电动机轴承故障特征频率的方法。该方法先采用小波包理论对原始信号进行消噪及频带划分,接着采用EMD对小波分解重构得到的信号进行分解以获得固有内在模函数(IMF),最后将IMF经时频变换得到频谱图,根据故障特征频率得出诊断结果。实验结果证明,该方法可有效地提取出故障特征频率,并方便地判断出故障类型。
In view of the problem that diagnosis effect of traditional fault diagnosis method of bearing of asynchronous motor is bad for local defect and initial fault of bearing,the paper proposed a method of using wavelet-packet theory and EMD to extract fault characteristic frequency of bearing.The method uses wavelet-packet theory to delete noise and differentiate frequency band for original signal at first,then uses EMD to decompose the signal got by wavelet decomposition and reconstruction so as to get IMF,at last the spectrogram of each IMF is obtained through time-frequency transform and diagnosis result can be gotten according to fault characteristic frequency.The experiment result proved that the method can extract fault characteristic frequency effectively and easy to judge fault type.
出处
《工矿自动化》
2010年第6期49-53,共5页
Journal Of Mine Automation
基金
山西省科技攻关项目(2006031153-01)
山西省自然科学基金项目(2007011068)
