Skip to Main content Skip to Navigation
Journal articles

Bearing failure detection using matching pursuit

B. Liu 1 S.F. Ling 2 Rémi Gribonval 3 
3 METISS - Speech and sound data modeling and processing
IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires, Inria Rennes – Bretagne Atlantique
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.
Complete list of metadata

https://hal.inria.fr/inria-00576214
Contributor : Rémi Gribonval Connect in order to contact the contributor
Submitted on : Sunday, March 13, 2011 - 4:55:00 PM
Last modification on : Friday, February 4, 2022 - 3:22:09 AM

Links full text

Identifiers

Citation

B. Liu, S.F. Ling, Rémi Gribonval. Bearing failure detection using matching pursuit. NDT & E International, Elsevier, 2002, 35 (4), pp.255-262. ⟨10.1016/S0963-8695(01)00063-9⟩. ⟨inria-00576214⟩

Share

Metrics

Record views

75