MARNet: Multi-head attention residual network for rolling bearing fault diagnosis under noisy condition
Linfeng Deng,
Guojun Wang,
Cheng Zhao
et al.
Abstract:Rolling bearings are crucial components of rotating machinery, and their health states directly affect the overall performance of the machinery. Therefore, it is exceedingly necessary to detect and diagnose bearing faults. Numerous bearing fault diagnosis methods have been successfully used for ensuring the safe operation of rotating machinery. However, in practical working environments, there is a considerable amount of noise, resulting in traditional methods incapable of achieving accurate fault diagnosis. T… Show more
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