Bearing condition monitroing: A review of feature extraction in temporal and spectral, and joint temporal-spectraldomain

Rolling element bearings are critical components in rotating machinery.Their failure can lead to catastrophic consequences.Therefore, effective condition monitoring is very necessary to avoid the occurrence of such unexpected breakdowns and ensure safety.This review focuses on the recent advances in vibration-based feature extraction techniques for bearing fault diagnosis.More than 70 peer-reviewed journal articles published since 2019 are analysed.The analysis covers feature extraction techniques in the temporal domain, spectral domain, and joint temporal-spectral domain.Then, the reviewed features are critically assessed in terms of their diagnostic sensitivity, robustness to noise, and applicability under different operating conditions.The review aims to adopt a featurecentric and decision-oriented perspective and provides guidance for selecting suitable health indicators.It can serve as a useful reference for researchers and practitioners working in rolling element bearing fault diagnosis.