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Mathematical Problems in Engineering
Volume 2015, Article ID 429185, 13 pages
Research Article

The Rolling Bearing Fault Feature Extraction Based on the LMD and Envelope Demodulation

1Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, China
2Engineering Research Center for Mineral Pipeline Transportation YN, Kunming 650500, China

Received 30 September 2014; Revised 1 January 2015; Accepted 5 January 2015

Academic Editor: Xinggang Yan

Copyright © 2015 Jun Ma et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Since the working process of rolling bearings is a complex and nonstationary dynamic process, the common time and frequency characteristics of vibration signals are submerged in the noise. Thus, it is the key of fault diagnosis to extract the fault feature from vibration signal. Therefore, a fault feature extraction method for the rolling bearing based on the local mean decomposition (LMD) and envelope demodulation is proposed. Firstly, decompose the original vibration signal by LMD to get a series of production functions (PFs). Then dispose the envelope demodulation analysis on PF component. Finally, perform Fourier Transform on the demodulation signals and judge failure condition according to the dominant frequency of the spectrum. The results show that the proposed method can correctly extract the fault characteristics to diagnose faults.