A Review of Dynamic Modeling and Fault Identifications Methods for Rolling Element Bearing

The rolling elements bearings are widely used in industrial and domestic machines. The existence of even tiny defects on the mating surfaces of the bearing components can lead to failure through passage of time. Their failure leads to economical and personal losses. The vibration monitoring technique is mostly used in the industries for health monitoring of bearings. Significant studies are available in open literature for vibration analysis of healthy and defective rolling elements bearings. Various researchers have studied the vibrations generated by bearings through theoretical model and experimentations. The researchers have developed the dynamic model of shaft bearing systems for the theoretical studies. This paper reviews different dynamic models for rolling bearing in presence and absence of local and distributed defects. Moreover, the techniques used for the improvement of fault detection have also been summarized. The signal processing techniques like wavelet transform, high frequency resonance technique (HFRT), envelope analysis and cyclic autocorrelation have improved the fault detection.