A Stacked Auto-Encoder Based Partial Adversarial Domain Adaptation Model for Intelligent Fault Diagnosis of Rotating Machines

IEEE Transactions on Industrial Informatics(2021)

Cited 47|Views29
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Abstract
Fault diagnosis plays an indispensable role in prognostics and health management of rotating machines. In recent years, intelligent fault diagnosis methods based on domain adaptation technology have attracted the attention of researchers. However, a more extensive application scenario of fault diagnosis − partial domain adaptation (PDA) − has not been well-resolved. In this article, for the first ...
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Key words
Informatics,Adaptation models,Rotating machines,Training,Principal component analysis,Fault diagnosis,Data models
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