Fault diagnosis for tilting-pad journal bearing based on SVD and LMD
School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou, 510640, China
Aiming at fault diagnosis for tilting-pad journal bearing with fluid support developed recently, a new method based on singular value decomposition (SVD) and local mean decomposition (LMD) is proposed. First, the phase space reconstruction of Hankel matrix and SVD method are used as pre-filter process unit to reduce the random noises in the original signal. Then the purified signal is decomposed by LMD into a series of production functions (PFs). Based on PFs, time frequency map and marginal spectrum can be obtained for fault diagnosis. Finally, this method is applied to numerical simulation and practical experiment data. The results show that the proposed method can effectively detect fault features of tilting-pad journal bearing.
© The Authors, published by EDP Sciences, 2016
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