Online Monitoring for Uneven Length Batch Processes using Function Space Principal Component Analysis

Ela, Arora and Ketan, P. Detroja (2013) Online Monitoring for Uneven Length Batch Processes using Function Space Principal Component Analysis. In: Proceeding of the International Symposium on Computer Applications in Biotechnology, 16-18 december 2013, Mumbai, India,.

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Abstract

Online batch process monitoring has been a challenging task, as batch processes do not operate around a nominal steady state operating point. Various monitoring approaches where future batch trajectory is filled with average (nominal) batch trajectory have been proposed. Predicting future trajectory for a batch process is a difficult task. Recently a multiway principal component analysis (MPCA) based approach that does not involve future trajectory prediction was proposed. In this paper a new technique based on function space principal component analysis (FSPCA) is proposed for online batch process monitoring. The main advantage of the proposed FSPCA based methodology is its ability to detect incipient and small to medium magnitude faults and its relevance for uneven length batch processes. Efficiency and effectiveness of the proposed algorithm is demonstrated via a fed-batch penicillin cultivation process simulation. The diagnostic performance of the proposed approach is significantly better compared to MPCA based approaches.

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IITH Creators:
IITH CreatorsORCiD
Ketan, P. DetrojaUNSPECIFIED
Item Type: Conference or Workshop Item (Paper)
Subjects: Electrical Engineering
Divisions: Department of Electrical Engineering
Depositing User: Library Staff
Date Deposited: 09 Sep 2019 09:12
Last Modified: 09 Sep 2019 09:15
URI: http://raiith.iith.ac.in/id/eprint/6159
Publisher URL: http://doi.org/10.3182/20131216-3-IN-2044.00058
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