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American Chemical Society, Industrial & Engineering Chemistry Research, 2(48), p. 837-843, 2008

DOI: 10.1021/ie800825m

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Two-Dimensional Dynamic Principal Component Analysis with Autodetermined Support Region

Journal article published in 2008 by Yuan Yao ORCID, Yinghu Diao, Ningyun Lu, Junde Lu, Furong Gao
This paper is available in a repository.
This paper is available in a repository.

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Abstract

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.