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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Vydané v:	Canadian journal of chemical engineering Ročník 101; číslo 10; s. 5858 - 5873
Hlavní autori:	Ye, Zhenyu, Wu, Ping, He, Yuchen, Pan, Haipeng
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Hoboken, USA John Wiley & Sons, Inc 01.10.2023 Wiley Subscription Services, Inc
Predmet:	Fault detection Kernels KPLS Least squares Monitoring Nonlinearity process monitoring Process variables quality‐related SSAE
ISSN:	0008-4034, 1939-019X
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