Morphological Undecimated Wavelet Decomposition for Fault Feature Extraction of Rolling Element Bearing

Based on morphological undecimated wavelet decomposition (MUWD), a novel method was proposed to extract rolling element bearing fault feature. MUWD possesses both the characteristic of morphological filter in morphology and multi-resolution in wavelet transform. Signal length was maintained invariable and information loss could be avoided in MUWD. Multi-scale MUWD was developed based on the characteristic of impulse feature extraction in difference morphological filter. This method was used to extract impulse feature in bearing fault signal. Simulation and practical example show that this method could achieve better performance than traditional wavelet package. It is suitable for on-line monitoring and fault diagnosis of bearing.