SSAE‐KPLS: A quality‐related process monitoring via integrating stacked sparse autoencoder with kernel partial least squares

Kernel partial least squares (KPLS) is widely employed to address the issue of nonlinearity inherent in complex industrial processes. However, KPLS can only extract shallow features from process measurements. This paper proposes a new quality‐related process monitoring method via integrating stacked...

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Veröffentlicht in:	Canadian journal of chemical engineering Jg. 101; H. 10; S. 5858 - 5873
Hauptverfasser:	Ye, Zhenyu, Wu, Ping, He, Yuchen, Pan, Haipeng
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Hoboken, USA John Wiley & Sons, Inc 01.10.2023 Wiley Subscription Services, Inc
Schlagworte:	Fault detection Kernels KPLS Least squares Monitoring Nonlinearity process monitoring Process variables quality‐related SSAE
ISSN:	0008-4034, 1939-019X
Online-Zugang:	Volltext
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