经验模态分解在密封轴承故障诊断中的应用

应用Labview直观的图形化界面将采集到的有缺陷的轴承信号转换为数字信号,在labview中调用matlab函数程序.将经验模态分解(EMD)引入到轴承的振动特征信号提取中,再从若干个包括故障的IMF分量中提取能量特征参数以判别故障产生的部位。试验结果表明,经验模态分解的分析方法在判断轴承故障的部位时具有很高的准确性,是一种有效的轴承故障诊断方法。

Sealed Bearing Fault Diagnosis Method Based on Empirical Mode Decomposition

Using Labview graphical user interface the defective bearing signals were collected and converted into digital signals,then called Matlab function in Labview.Applying the Matlab powerful data processing capabilities,the empirical mode decomposition(EMD) is introduced into the extraction of bearing vibration feature signal,then the energy feature parameters are extracted from a number of IMFs with main fault information which can be served as distinguishing the location of fault.The results indicate that EMD...