Bearing Fault Diagnosis Method Based on Self-attentional Time-frequency Feature Fusion

Aiming at the problem that the single time and frequency domain signal contains incomplete features in bearing fault diagnosis , which leads to the poor generalization ability of traditional fault diagnosis models, a bearing fault diagnosis method based on self-attention time-frequency feature fusio...

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Bibliographic Details

Published in:	Journal of Harbin University of Science and Technology
Main Authors:	LIU Jing, ZHANG Minghui, WU Jian, CHEN Erlong, JI Haipeng
Format:	Article
Language:	Chinese
Published:	Harbin University of Science and Technology Publications 2024-12-01
Subjects:	bearing fault diagnosis self-attention feature fusion deep learning multi-scale residual networks
Online Access:	https://hlgxb.hrbust.edu.cn/#/digest?ArticleID=2378