Journal
MATERIALS PROCESSING AND MANUFACTURING III, PTS 1-4
Volume 753-755, Issue -, Pages 2290-2296Publisher
TRANS TECH PUBLICATIONS LTD
DOI: 10.4028/www.scientific.net/AMR.753-755.2290
Keywords
rolling bearing; fault diagnosis; resonance decomposition; weak fault information; wavelet analysis; constant-Q transform
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In the early fault diagnosis of rolling bearing, the vibration signal is mixed with a lot of noise, resulting in the difficulties in analysis of early weak fault signal. This article introduces resonance-based signal sparse decomposition (RSSD) into rolling bearing fault diagnosis, and studies the fault information contained in high resonance component and low resonance component. This article compares the effect of the two resonance components to extract rolling bearing fault information in four aspects: the amount of fault information, frequency resolution of subbands, sensitivity to noise and immunity to autocorrelation processing. We find that the high resonance component has greater advantage in extraction of rolling bearing fault information, and it is able to indicate rolling bearing failure accurately.
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