Methodological approach of selecting a vibration indicator in monitoring bearings

Abstract

A rolling bearing is an important element in a rotating machine. Whatever the operating conditions, it is subject to fatigue which causes spalling. In aiming to obtain the most possible real fatigue curve, the vibration level is shown according to different statistical indicators such as the RMS (Root Mean Square), the kurtosis, the crest value, the crest factor and the peak ratio, then to choose the best of them that is able to show the evolution of the bearing degradation. In this work, through the experimental vibratory follow up of the thrust bearing spall using different statistical indicators, we present an optimization methodology in order to find a most significant indicator that is able to characterize the damage evolution