JERAJournal of Electronic Research and Application2208-35022208-3510Bio-Byword Scientific Publishing Pty. Ltd.10.26689/jera.v9i1.9474ArticleResearch on Bearing Fault Diagnosis Method based on Deep Learninghttps://artdesignp.com/journal/JERA/9/1/10.26689/jera.v9i1.9474ZhengTing2025912025-02-14Bearing is an indispensable key component in mechanical equipment, and its working state is directly related to the stability and safety of the whole equipment. In recent years, with the rapid development of artificial intelligence technology, especially the breakthrough of deep learning technology, it provides a new idea for bearing fault diagnosis. Deep learning can automatically learn features from a large amount of data, has a strong nonlinear modeling ability, and can effectively solve the problems existing in traditional methods. Aiming at the key problems in bearing fault diagnosis, this paper studies the fault diagnosis method based on deep learning, which not only provides a new solution for bearing fault diagnosis but also provides a reference for the application of deep learning in other mechanical fault diagnosis fields.

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