Title :
The processing of the rolling bearing´s fault signal based on wavelet analysis
Author_Institution :
Zhejiang Univ. of Media & Commun., Hangzhou, China
Abstract :
A key problem of a rolling bearing´s fault diagnosis is the feature extraction of the fault signal. Wavelet analysis can accomplish local analysis in the time-domain and frequency-domain, which is widely used in many different fields, such as signal processing, image processing and fault diagnosis. In this paper, we analyze the fault signal of a rolling bearing under different rotation rates, and analyze the vibration signal with damage in the inner ring, with damage in the outer ring and with damage in the ball. Basing on the wavelet analysis, signals are separated and reconstructed and a new method to figure out the characteristic parameter of the AE signal of rolling bearings is studied.
Keywords :
fault diagnosis; frequency-domain analysis; rolling bearings; signal reconstruction; time-domain analysis; vibrations; wavelet transforms; feature extraction; frequency domain; image processing; rolling bearing fault diagnosis; rolling bearing fault signal; rotation rates; signal processing; signal reconstruction; signal separation; time domain; vibration signal analysis; wavelet analysis; Cepstrum; Rolling bearings; Time domain analysis; Vibrations; Wavelet analysis; Wavelet transforms; fault signal; rolling bearings; wavelet analysis;
Conference_Titel :
Image Analysis and Signal Processing (IASP), 2012 International Conference on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4673-2547-9
DOI :
10.1109/IASP.2012.6425012