High Resonance Component of Resonance-Based Sparse Decomposition Application in Extraction of Rolling Bearing Fault Information

Wen Tao Huang; Yin Feng Liu; Pei Lu Niu; Wei Jie Wang

doi:10.4028/www.scientific.net/AMR.753-755.2290

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 753-755High Resonance Component of Resonance-Based Sparse...

High Resonance Component of Resonance-Based Sparse Decomposition Application in Extraction of Rolling Bearing Fault Information

Abstract:

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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Periodical:

Advanced Materials Research (Volumes 753-755)

Pages:

2290-2296

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.753-755.2290

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Online since:

August 2013

Authors:

Wen Tao Huang*, Yin Feng Liu, Pei Lu Niu, Wei Jie Wang

Keywords:

Constant-Q Transform, Fault Diagnosis, Resonance Decomposition, Rolling Bearing, Wavelet Analysis, Weak Fault Information

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