Few-Shot Fault Diagnosis of Rolling Bearings Using Generative Adversarial Networks and Convolutional Block Attention Mechanisms

In modern industrial systems, diagnosing faults in the rolling bearings of high-speed rotating machinery remains a considerable challenge due to the scarcity of reliable fault samples and the inherent complexity of the diagnostic task. To address these limitations, this study proposes an intelligent...

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Bibliografische gegevens

Hoofdauteurs:	Yong Chen, Xiangrun Pu, Guangxin Li, Yunhui Bai, Lijie Hao
Formaat:	Artigo
Taal:	Inglês
Gepubliceerd in:	MDPI AG 2025-11-01
Reeks:	Lubricants
Onderwerpen:	few-shot learning generative adversarial networks (GAN) convolutional block attention module (CBAM) fault diagnosis rolling bearing
Online toegang:	https://www.mdpi.com/2075-4442/13/12/515
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