MATEC Web of Conferences
Volume 54, 20162016 7th International Conference on Mechanical, Industrial, and Manufacturing Technologies (MIMT 2016)
|Number of page(s)||5|
|Section||Signal analysis and processing|
|Published online||22 April 2016|
Rotating Machinery Vibration Signal Processing And Fault Diagnosis Based on LMD
Department of Electronic and Information EngineeringInner Mongolia University, Hohhot, 10126 China
There are abundant of fault information in rotating machinery vibration signal. On account of the nonlinearity and non-stationarity, the paper first does pre-process to the vibration signal using wavelet threshold denoising method and this method can bring a smooth signal. Then it decomposes the vibration signal using local mean decomposition(LMD), which is effective to the vibration signal. The LMD decomposes the signal into many PFs as the frequency from high to low. These PFs are composed of the production of envelop signal and pure frequency modulated signal. Finally, it takes most use of the kurtosis which is sensitive to the fault impact. By calculating the kurtosis of PF, it can assess the distribution of fault impact signal in every frequency band, consequently distinguishing the operating state of bearing and recognizing the fault mode according to the growth of turtosis. The experiment of actual bearing vibration signal demonstrates that the methods this paper proposed can effectively diagnose the vibration fault and has good performance.
Key words: LMD / wavelet threshold method / kurtosis / fault diagnosis
© Owned by the authors, published by EDP Sciences, 2016
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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