Bearing fault diagnosis based on efficient cross space multiscale CNN transformer parallelism

Bearing fault diagnosis based on efficient cross space multiscale CNN transformer parallelism

Abstract Fault diagnosis of wind turbine bearings is crucial for ensuring operational safety and reliability. However, traditional serial-structured deep learning models often fail to simultaneously extract spatio- temporal features from fault signals in noisy environments, leading to critical infor...

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Bibliographic Details
Main Authors:	Qi Chen, Feng Zhang, Yin Wang, Qing Yu, Genfeng Lang, Lixiong Zeng
Format:	Article
Language:	English
Published:	Nature Portfolio 2025-04-01
Series:	Scientific Reports
Online Access:	https://doi.org/10.1038/s41598-025-95895-x
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