Browse by author
Lookup NU author(s): Professor Elaine Martin,
Emeritus Professor Julian Morris
Full text for this publication is not currently held within this repository. Alternative links are provided below where available.
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.
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
Publisher: American Automatic Control Council