Modeling and monitoring of multimodes process

Authors:
Yingwei Zhang;Chuang Wang
Affiliations:
State Laboratory of Synthesis Automation of Process Industry, Northeastern University, Shenyang, Liaoning, P.R. China;State Laboratory of Synthesis Automation of Process Industry, Northeastern University, Shenyang, Liaoning, P.R. China
Venue:
ISNN'12 Proceedings of the 9th international conference on Advances in Neural Networks - Volume Part I
Year:
2012

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Abstract

In the paper, a new monitoring approach is proposed for handling the dynamic problem in the industrial batch process. Compared to conventional method, the contributions are as follows:1) Multimodes are separated correctly since the cross-mode correlations are considered and the common information is extracted.2) a manifold learning approach(LLE) is implemented to extract the common information.3)after that two different subspaces are separated, the common and specific subspace models are built and analyzed respectively. The monitoring is carried out in subspace. The corresponding confidence regions are constructed according to their models respectively.