Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.compchemeng.2008.11.014
Title: An adjoined multi-model approach for monitoring batch and transient operations
Authors: Ng, Y.S. 
Srinivasan, R. 
Keywords: Clustering
Fault detection
Model overlap
Multi-state operations
Process transitions
Issue Date: 21-Apr-2009
Source: Ng, Y.S., Srinivasan, R. (2009-04-21). An adjoined multi-model approach for monitoring batch and transient operations. Computers and Chemical Engineering 33 (4) : 887-902. ScholarBank@NUS Repository. https://doi.org/10.1016/j.compchemeng.2008.11.014
Abstract: Most process monitoring techniques are suitable for steady-state operation but inadequate for these multiphase transient operations with complex dynamics. Specifically, statistical approaches do not function adequately since the basic assumptions that the statistics are developed upon - normal distribution, stationarity - are violated. Consequently, they become prone to false positives and false negatives. Multi-model approaches overcome this by using several local models; however these perform inadequately in the interregnum between models. In this paper, we propose a method, called adjoined principal component analysis that overcomes this. The key characteristic of AdPCA is that the different models are not disjoint; rather they overlap at the edges of their regime and thus ensure smooth evolution of the monitoring. A fuzzy c-means algorithm is used to identify suitable regimes for the constituent models. The applications of the proposed methodology to a distillation unit startup and a fed-batch penicillin cultivation process illustrate the method's efficacy. © 2008 Elsevier Ltd. All rights reserved.
Source Title: Computers and Chemical Engineering
URI: http://scholarbank.nus.edu.sg/handle/10635/63460
ISSN: 00981354
DOI: 10.1016/j.compchemeng.2008.11.014
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