Pattern modeling and fault detection based on dynamic controlled autoencoder

Industrial processes often exhibit significant nonlinear and dynamic characteristics. To effectively monitor these processes, this paper proposes a dynamic controlled autoencoder (DCAE) model for pattern extraction, which primarily consists of an autoencoder and dynamic mapping components. It is cap...

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Veröffentlicht in:	Chemometrics and intelligent laboratory systems Jg. 263; S. 105422
Hauptverfasser:	Guo, Wei, Luan, Xiaoli, Liu, Fei
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 15.08.2025
Schlagworte:	Dynamic causality Dynamic controlled autoencoder Fault detection Nonlinear process Pattern extraction Fault detection Dynamic controlled autoencoder Dynamic causality Pattern extraction Nonlinear process
ISSN:	0169-7439
Online-Zugang:	Volltext
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