Title :
Weak fault signal detection of rolling bearing
Author_Institution :
Coll. of Mech. Eng., Changchun Univ., Changchun, China
Abstract :
The characteristics of local singularity of vibration signal under the wavelet transform are studied, and quantitative analysis of the noise reduction features of wavelet transform methods is carried out. Based on that the modulus maxima of the local singularity of fault vibration signal and noise of rolling bearing under wavelet transform has different propagation characteristics in different scales, the wavelet decomposition and reconstruction algorithms are used to conduct decomposition, noise reduction, re-structure and spectral analysis on vibration signals of the bearing. Experiment show that the wavelet noise reduction method is very suitable for fault frequency detection of weak vibration signal of rolling bearing in low SNR cases.
Keywords :
acoustic noise; acoustic signal processing; fault diagnosis; mechanical engineering computing; rolling bearings; signal reconstruction; spectral analysis; vibrations; wavelet transforms; SNR; fault frequency detection; local singularity; modulus maxima; noise reduction features; quantitative analysis; rolling bearing; spectral analysis; vibration signal; wavelet decomposition algorithms; wavelet noise reduction method; wavelet reconstruction algorithms; wavelet transform methods; weak fault signal detection; Frequency domain analysis; Noise; Noise reduction; Rolling bearings; Vibrations; Wavelet analysis; Wavelet transforms; fault diagnosis; rolling bearing; wavelet denoising; weak signal;
Conference_Titel :
Transportation, Mechanical, and Electrical Engineering (TMEE), 2011 International Conference on
Conference_Location :
Changchun
Print_ISBN :
978-1-4577-1700-0
DOI :
10.1109/TMEE.2011.6199260