Application of Frequency B-Spline Wavelets for Detection of Defects in Rolling Bearings

Frequency B-spline (fbsp) wavelets have been applied in the present work for detection of localized defects in the inner race of a rolling element bearing. The theoretical response from the bearing system due to an inner race defect coupled with additive noise of varying magnitude form the simulated signal. Methodology of defect detection includes three steps. Firstly, wavelet transformation of noisy vibration signal has been obtained using fbsp wavelets with appropriate parameters. Then, maximum wavelet coefficients were retained from the result of transformation on which a threshold level was applied. Finally fast Fourier transformation was applied on these retained coefficients to identify the presence of components at characteristic frequency corresponding to the defect location. The results show that the method could specifically identify bearing defects even from noisy vibration signals.