Time domain vibration analysis techniques for condition monitoring of rolling element bearing: A review

Abstract

Rolling element bearings are very critical components of rotating machines and the presence of defects in the bearing may lead to failure of machines. Rolling Element Bearing (REB) fault detection, diagnosis, prognosis are the key steps of machine failure diagnostics. Under operating condition of the bearing may avoid malfunctioning and breakdown of machines. Although various methods to fault detection and diagnosis of the same have been proposed in the literature, such as the thermograph, visual inspection, ultrasonic test, motor current analysis, acoustic emission analysis, the wear-debris analysis, oil analysis, and the vibration analysis. The vibration-based analysis is proven as a popular among all non-destructive methods due to its merits over the other. Time domain vibration analysis technique is better for the online monitoring, remote area, non human intervention area, and hazard location. This paper reviews time domain vibration analysis techniques for REB fault detection. The collected vibration signals from machinery with the help of appropriate data acquisition system, which incorporates the vibration transducers are in time domain. Various statistical parameters are listed to illustrate them as time domain feature from vibration signals In order to understand various features and terminologies, REB vibration signals (Bearing Data Set) acquired from Bearing Data Center, of Case Western Reserve University (CWRU) are used.