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Detection of process model changes in PCA based performance monitoring

Lookup NU author(s): Professor Elaine Martin, Emeritus Professor Julian Morris


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The detection of process changes through a principal component analysis based monitoring scheme can be achieved through the interrogation of two metrics, Hotelling's T2 and the Q-statistic. The Q-statistic has been shown to be insensitive to small changes in the process model parameters. In this paper, a modified statistic based on the local approach is proposed to detect changes in model parameters in a principal component analysis monitoring scheme. The performance of the more traditional Q-statistic is compared with the modified statistic through their application to fault detection in a continuous stirred tank reactor.

Publication metadata

Author(s): Kumar S, Martin EB, Morris J

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: Proceedings of the American Control Conference

Year of Conference: 2002

Pages: 2719-2724

ISSN: 0743-1619

Publisher: American Automatic Control Council