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 2021, Vol.70, p.1-11 |
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Sprache: | eng |
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