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Few-Shot Learning for Fault Diagnosis With a Dual...
Journal article

Few-Shot Learning for Fault Diagnosis With a Dual Graph Neural Network

Abstract

Mechanical fault diagnosis is crucial to ensure the safe operations of equipment in intelligent manufacturing systems. Deep learning-based methods have been recently developed for fault diagnosis due to their advantages in feature representation. However, most of these methods fail to learn relations between samples and thus perform poorly without sufficient labeled data. In this article, we propose a new few-shot learning method named dual …

Authors

Wang H; Wang J; Zhao Y; Liu Q; Liu M; Shen W

Journal

IEEE Transactions on Industrial Informatics, Vol. 19, No. 2, pp. 1559–1568

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

DOI

10.1109/tii.2022.3205373

ISSN

1551-3203