Spacecraft Intelligent Fault Diagnosis under Variable Working Conditions via Wasserstein Distance-Based Deep Adversarial Transfer Learning

In recent years, deep learning methods which promote the accuracy and efficiency of fault diagnosis task without any extra requirement of artificial feature extraction have elicited the attention of researchers in the field of manufacturing industry as well as aerospace. However, the problems that d...

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Bibliographic Details
Main Authors: Gang Xiang, Kun Tian
Format: Article
Language:English
Published: Wiley 2021-01-01
Series:International Journal of Aerospace Engineering
Online Access:http://dx.doi.org/10.1155/2021/6099818
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