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Erschienen in:
2011 | OriginalPaper | Buchkapitel
A Way to Diagnose the Rolling Bearing Fault Dealt with Wavelet-Packet and EMD
verfasst von : Xiao-Feng Liu, Shu-Hua Wang, Yong-Wei Lv, Xuan Lin
Erschienen in: Emerging Research in Artificial Intelligence and Computational Intelligence
Verlag: Springer Berlin Heidelberg
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The way to diagnose the rolling bearing fault in advance is a key to safe production and avoids serious accidents in technology. This paper puts forward a update way to diagnose the fault in which the wavelet deletes the noises by the original signals handed out and differentiates the originals by frequency, and then use EMD to resolve the low-frequency signals got by wavelet decomposition and reconstruction to get a number of inherent IMF, each function of which is analyzed by time-frequency to know the fault frequency from spectrogram and compare Fourier transform and wavelet transform with strengths and weakness of the way to diagnose. This experiment has shown by the diagnosis we can pick up the fault frequency effectually and easy to judge and diffentiate fault types.