RESEARCH ARTICLE

Identification of faults through wavelet transform vis-à-vis fast Fourier transform of noisy vibration signals emanated from defective rolling element bearings

  • Deepak PALIWAL ,
  • Achintya CHOUDHURY ,
  • T. GOVANDHAN
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  • Department of Mechanical Engineering, Sir Padampat Singhania University, Udaipur 313601, Rajasthan, India

Received date: 10 Feb 2014

Accepted date: 25 Mar 2014

Published date: 22 May 2014

Copyright

2014 Higher Education Press and Springer-Verlag Berlin Heidelberg

Abstract

Fault diagnosis of rolling element bearings requires efficient signal processing techniques. For this purpose, the performances of envelope detection with fast Fourier transform (FFT) and continuous wavelet transform (CWT) of vibration signals produced from a bearing with defects on inner race and rolling element, have been examined at low signal to noise ratio. Both simulated and experimental signals from identical bearings have been considered for the purpose of analysis. The bearings have been modeled as spring-mass-dashpot systems and the simulated signals have been obtained considering transfer functions for the bearing systems subjected to impulsive loads due to the defects. Frequency B spline wavelets have been applied for CWT and a discussion on wavelet selection has been presented for better effectiveness. Results show that use of CWT with the proposed wavelets overcomes the short coming of FFT while processing a noisy vibration signals for defect detection of bearings.

Cite this article

Deepak PALIWAL , Achintya CHOUDHURY , T. GOVANDHAN . Identification of faults through wavelet transform vis-à-vis fast Fourier transform of noisy vibration signals emanated from defective rolling element bearings[J]. Frontiers of Mechanical Engineering, 2014 , 9(2) : 130 -141 . DOI: 10.1007/s11465-014-0298-6

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