A Hybrid Generalization Network for Intelligent Fault Diagnosis of Rotating Machinery Under Unseen Working Conditions

The data-driven methods in machinery fault diagnosis have become increasingly popular in the past two decades. However, the wide applications of this scheme are generally compromised in real-world conditions because of the discrepancy between the training data and testing data. Although the recently...

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Veröffentlicht in:IEEE transactions on instrumentation and measurement Jg. 70; S. 1 - 11
Hauptverfasser: Han, Te, Li, Yan-Fu, Qian, Min
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York IEEE 2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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ISSN:0018-9456, 1557-9662
Online-Zugang:Volltext
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