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

Jiaojiao Ma, Jiefei Yu, Xianwen Zhou, Fengshou Gu, Lingli Jiang, Xuejun Li

Research output: Contribution to journalReview articlepeer-review

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.

Original languageEnglish
Article number9441080
Number of pages22
JournalFriction
Volume14
Issue number1
Early online date12 Jan 2026
DOIs
Publication statusPublished - 12 Jan 2026

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 9 - Industry, Innovation, and Infrastructure
    SDG 9 Industry, Innovation, and Infrastructure

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