[article] 
inIndustrial & engineering chemistry research > Vol. 48 N°2 (Janvier 2009) . - p.837–843

Titre :	Two-dimensional dynamic principal component analysis with autodetermined support region
Type de document :	texte imprimé
Auteurs :	Yuan Yao, Auteur ; Yinghu Diao, Auteur ; Ningyun Lu, Auteur ; Junde Lu, Auteur ; Furong Gao, Auteur
Année de publication :	2009
Article en page(s) :	p.837–843
Note générale :	chemical engineering
Langues :	Anglais (eng)
Mots-clés :	Dynamics--Principal Component Analysis
Résumé :	Dynamics are inherent characteristics of batch processes. In some cases, such dynamics exist not only within a particular batch, but also from batch to batch. In previous work, two-dimensional dynamic principal component analysis (2-D-DPCA) has been developed to monitor 2-D dynamics. Support region determination is a key step in 2-D-DPCA modeling and monitoring of a batch process. A proper support region can ensure modeling accuracy, monitoring efficiency, and reasonable fault diagnosis. In this work, an automatic method for support region determination is developed. This data-based method can be applied on different batch processes without prior process knowledge. Simulation shows that the developed method has good application potentials for both monitoring and fault diagnosis.
En ligne :	http://pubs.acs.org/doi/abs/10.1021/ie800825m

[article] Two-dimensional dynamic principal component analysis with autodetermined support region [texte imprimé] / Yuan Yao, Auteur ; Yinghu Diao, Auteur ; Ningyun Lu, Auteur ; Junde Lu, Auteur ; Furong Gao, Auteur . - 2009 . - p.837–843.
chemical engineering
Langues : Anglais (eng)
in Industrial & engineering chemistry research > Vol. 48 N°2 (Janvier 2009) . - p.837–843

Mots-clés :	Dynamics--Principal Component Analysis
Résumé :	Dynamics are inherent characteristics of batch processes. In some cases, such dynamics exist not only within a particular batch, but also from batch to batch. In previous work, two-dimensional dynamic principal component analysis (2-D-DPCA) has been developed to monitor 2-D dynamics. Support region determination is a key step in 2-D-DPCA modeling and monitoring of a batch process. A proper support region can ensure modeling accuracy, monitoring efficiency, and reasonable fault diagnosis. In this work, an automatic method for support region determination is developed. This data-based method can be applied on different batch processes without prior process knowledge. Simulation shows that the developed method has good application potentials for both monitoring and fault diagnosis.
En ligne :	http://pubs.acs.org/doi/abs/10.1021/ie800825m