A review on identification of defects in the rolling element bearings

Rolling element bearings are crucial for supporting rotating parts in machinery, enabling efficient power transmission. Any faults in these bearings can cause significant machine damage, potentially causing catastrophic failures if left unnoticed. Therefore, early detection of bearing damage and its severity is crucial to avoiding abrupt equipment malfunctions. Defects in bearing components generate vibrations, which intensify with the defect’s size. These vibrations can be measured using various signal analysis techniques for fault identification in the bearing elements. Numerous researchers have employed various signal-analysing approaches for bearing condition monitoring purposes under various conditions. This paper discusses diverse approaches researchers use to identify bearing faults and their corresponding models. It aims to comprehensively understand recent developments in defect identification techniques for bearings.

Authors

Publication Details

Journal
Noise & Vibration Worldwide
Published
2026-02-16
DOI
https://doi.org/10.1177/09574565261419831
Primary Topic
Machine Fault Diagnosis Techniques
Type
article
Field-Weighted Citation Impact
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article

A review on identification of defects in the rolling element bearings

Shravan Kumar Chandrasekaran, Prabu Jayachandran
Noise & Vibration Worldwide
Machine Fault Diagnosis Techniques
article

A review on identification of defects in the rolling element bearings

Shravan Kumar Chandrasekaran, Prabu Jayachandran
article en

Abstract

Rolling element bearings are crucial for supporting rotating parts in machinery, enabling efficient power transmission. Any faults in these bearings can cause significant machine damage, potentially causing catastrophic failures if left unnoticed. Therefore, early detection of bearing damage and its severity is crucial to avoiding abrupt equipment malfunctions. Defects in bearing components generate vibrations, which intensify with the defect’s size. These vibrations can be measured using various signal analysis techniques for fault identification in the bearing elements. Numerous researchers have employed various signal-analysing approaches for bearing condition monitoring purposes under various conditions. This paper discusses diverse approaches researchers use to identify bearing faults and their corresponding models. It aims to comprehensively understand recent developments in defect identification techniques for bearings.

Noise & Vibration Worldwide
Openalex Percentile: Top 55%
Machine Fault Diagnosis Techniques
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A review on identification of defects in the rolling element bearings — Shravan Kumar Chandrasekaran, Prabu Jayachandran · Noise & Vibration Worldwide (2026) | TGRS Research Map | TGRS