The Feature Extraction of Rolling Bearing Fault Based on Wavelet Packet-EMD Energy Distribution


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The new signal analysis method based on the combination of wavelet packet and empirical mode decomposition (EMD) energy distribution was proposed for rolling bearing vibration signal presenting modulating characteristic, non-stationary characteristics and containing a lot of noise characteristics. In this method, initial vibration signal was decomposed first by wavelet packet to extract the resonance signal with obvious modulating characteristics. Then the resonance signal was decomposed by EMD method and energy distribution of each Intrinsic Mode Function (IMF) was obtained. Finally the IMF component, which can reflect the vibration condition, was processed by Hilbert envelope demodulation to extract rolling bearing fault characteristics information. The application analysis of the simulation signal and fault signal of inner race, outer race and rolling element of rolling bearing shows that this method can effectively analyze rolling bearing fault information and realize the fault diagnosis.



Edited by:

Xiong Zhou and Zhenzhen Lei




C. Wen and C. D. Zhou, "The Feature Extraction of Rolling Bearing Fault Based on Wavelet Packet-EMD Energy Distribution", Applied Mechanics and Materials, Vol. 233, pp. 234-238, 2012

Online since:

November 2012




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