Wavelet Based Signal Demodulation Technique for Bearing Fault Detection

Diagnostics of rolling elements under varying operational conditions, where disturbances and other rotating elements have strong influence on correctness of analysis, requires engagement of advanced signal processing techniques. Extraction of signal components generated by bearing faults has been proven to be an exceptionally promising method for rolling element bearing fault detection. In this paper, wavelet signal demodulation diagnostic techniques is presented. The method is based on the wavelet transform as a method of signal demodulation. Properties of time–frequency representation of the signal enables extraction of typical damage signatures from the signal. First step of this method is a wavelet filtration, which uses Continuous Wavelet Transform (CWT). For this transformation, the Morlet wavelet function has been used. Next, the envelope function of a decoupled frequency component is estimated from wavelet coefficients. Finally, the Discrete Wavelet Transform (DWT) has been used as a post–processing method.