Data-based modeling and monitoring for multimode processes using local tangent space alignment

Authors:
Yingwei Zhang;Hailong Zhang
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 online monitoring approach is proposed for handling the multimode monitoring problem in the industrial batch processes. Compared to conventional method, the contributions are as follows: 1) The LTSA algorithm is applied to the multi-mode batches process. And a common subspace is extracted via the new method proposed instead of extracting the common subspaces of each mode. 2) After those 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.