Title :
Bearing fault diagnosis using Wavelet analysis
Author :
Chen, Kang ; Li, Xiaobing ; Wang, Feng ; Wang, Tanglin ; Wu, Cheng
Author_Institution :
Sch. of Mechatron. of Eng., Univ. of Electron. Sci. & Technol. of China, Chengdu, China
Abstract :
One-dimensional discrete wavelet transform is used to process the bearing fault signal in this paper. Firstly, the bearing fault data is decomposed to multi-layer. Then the fault feature signal is reconstructed. In order to detect the bearing failure and determine the area of it, the reconstructed signal is processed by the Hilbert transform demodulation and spectrum refining. The results show that the frequency of failure point matches well with theoretical one using this method. This method is simple and reliable and thus provides a scientific method for early warning and exclusion of failure.
Keywords :
Hilbert transforms; acoustic signal processing; demodulation; discrete wavelet transforms; failure analysis; fault diagnosis; machine bearings; signal reconstruction; Hilbert transform demodulation; bearing fault data; bearing fault diagnosis; bearing fault signal processing; early warning; failure exclusion; failure point frequency; fault feature signal reconstruction; one-dimensional discrete wavelet transform; spectrum refining; Discrete wavelet transforms; Fault diagnosis; Rolling bearings; Time frequency analysis; Wavelet analysis; bearing; fault diagnosis; wavelet analysis;
Conference_Titel :
Quality, Reliability, Risk, Maintenance, and Safety Engineering (ICQR2MSE), 2012 International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4673-0786-4
DOI :
10.1109/ICQR2MSE.2012.6246326
