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Bearing failure detection using matching pursuit
Authors:B Liu  S F Ling  R Gribonval
Affiliation:a Department of Mathematics, Centre for Wavelets, Approximation and Information Processing, National University of Singapore, Singapore, Singapore 117543;b School of Mechanical and Production Engineering, Nanyang Technological University, Singapore, Singapore 639798;c IRISA–INRIA, Campus DE Beaulieu, 35042 Rennes Cedex, France
Abstract:In this paper, a new approach to the detection of localized defects of rolling element bearings is proposed. It employs matching pursuit with time–frequency atoms to analyze bearing vibration and extract vibration signatures. In particular, this approach utilizes not only the temporal and spectral but also the scale characteristics of the vibration generated due to the presence of a defect for the detection. This leads to a high signal-to-noise ratio and facilitates considerably the detection at the early stage of failure development. Experimental results show that the proposed approach is sensitive and reliable and works better than continuous wavelet transform and envelope detection.
Keywords:Rolling element bearing  Vibration  Fault diagnosis  Matching pursuit  Wavelet
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