Semi-supervised denoising autoencoder with multiple consistency regularization for process fault classification

Process fault classification constitutes a critical component for ensuring efficient and stable industrial operations. If the collected process data is severely affected by noise or contains a lot of information unrelated to the fault, it will affect the performance of the classification model. To a...

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Veröffentlicht in:	Engineering Research Express Jg. 7; H. 3; S. 35402 - 35420
Hauptverfasser:	Guo, Xiaoping, Guo, Qingyu, Li, Yuan
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	IOP Publishing 30.09.2025
Schlagworte:	chemical process Consistency regularization fault classification fault related feature extraction stacked supervised autoencoder (SSAE)
ISSN:	2631-8695, 2631-8695
Online-Zugang:	Volltext
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