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Review Article | Open Access

Condition monitoring of journal bearings based on acoustic emissions: A state-of-the-art review

Jiaojiao Ma1Jiefei Yu1Xianwen Zhou1Fengshou Gu2Lingli Jiang1( )Xuejun Li1
School of Mechatronic Engineering and Automation, Foshan University, Foshan 528000, China
Centre for Efficiency and Performance Engineering, University of Huddersfield, Queensgate HD1 3DH, UK
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Abstract

This article provides a thorough review of the advancements in acoustic emission (AE) technology used for monitoring journal bearings. First, the AE sources generated from journal bearings under different lubrication regimes are classified and discussed. Next, a comparative analysis of parametric analysis, waveform, and artificial intelligence recognition methods for bearing AE signal analysis is conducted, highlighting their respective principles, pros and cons, and applications. Additionally, an overview of physical models representing AE waves on relatively sliding surfaces is provided from the wave generation mechanism perspective, and each model’s applicable conditions are compared. Finally, an in-depth discussion is presented, and future research directions are highlighted.

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Article number: 9441080

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Review Status: {{reviewData.commendedNum}} Commended , {{reviewData.revisionRequiredNum}} Revision Required , {{reviewData.notCommendedNum}} Not Commended Under Peer Review

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Cite this article:
Ma J, Yu J, Zhou X, et al. Condition monitoring of journal bearings based on acoustic emissions: A state-of-the-art review. Friction, 2026, 14(1): 9441080. https://doi.org/10.26599/FRICT.2025.9441080

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Received: 25 February 2024
Revised: 30 December 2024
Accepted: 17 February 2025
Published: 12 January 2026
© The Author(s) 2026.

This is an open access article under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0, http://creativecommons.org/licenses/by/4.0/).