Bearing Fault Detection Based on Multi-Scale Laplace Wavelet Transform Spectrum

Abstract:

Laplace wavelet transform is self-adaptive to non-stationary and non-linear signal, which can detect the singularity characteristic of a signal precisely under strong background noise condition. A new method of bearing fault diagnosis based on multi-scale Laplace wavelet transform spectrum is proposed. The multi scale Laplace wavelet transform spectrum technique combines the advantages of Laplace wavelet transform, envelope spectrum and three dimensions color map into one integrated technique. The bearing fault vibration signal is firstly decomposed using Laplace wavelet transform. In the end, the multi scale Laplace wavelet transform spectrum is obtained and the characteristics of the bearing fault can be recognized according to the multi-scale Laplace wavelet transform spectrum. The proposed method has been verified by vibration signals obtained from rolling bearing with inner race fault.

• Periodical: Advanced Materials Research (Volume 739)
• Pages: 413-417
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.739.413
• Online since: August 2013
• Authors: Ya Ning Wang
• Keywords: Bearing, Fault Detection, Laplace Wavelet Transform, Multi-Scale Spectrum, Signal Processing, Time Frequency Distribution

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