Toggle Main Menu Toggle Search

Open Access padlockePrints

Detection of process model changes in PCA based performance monitoring

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

Downloads

Full text for this publication is not currently held within this repository. Alternative links are provided below where available.


Abstract

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


Share