Comparison of Methods for Separating Excitation Sources in Rotating Machinery

Abstract Vibro-acoustic signatures are widely used for diagnostics of rotating machinery. Vibration based automatic diagnostics systems need to achieve a good separation between signals generated by different sources. The separation task may be challenging, since the effects of the different vibration sources often overlap. In particular, there is a need to separate between natural frequencies of the structure and excitations resulting from the rotating components (signal pre-whitening), and there is a need to separate between signals generated by asynchronous components like bearings and signals generated by cyclo-stationary components like gears. Several methods were proposed to achieve the above separation tasks. The present study compares between some of these methods. For pre-whitening the study compares between liftering of the high quefrencies and adaptive clutter separation. The method of adaptive clutter separation is suggested in this paper for the first time. For separating between the asynchronous and the cyclo-stationary signals the study compares between two methods: liftering in the quefrency domain and dephase. The methods are compared using both simulated signals and real data.