Fault Detection and Isolation of Industrial Fermentation Process Based on Semi-supervised Convex Nonnegative Matrix Factorizations-Reference-Cited by-同舟云学术

Fault Detection and Isolation of Industrial Fermentation Process Based on Semi-supervised Convex Nonnegative Matrix Factorizations

Published:2022-12-20 Issue:12 Volume:55 Page:358-364
ISSN:0021-9592
Container-title:JOURNAL OF CHEMICAL ENGINEERING OF JAPAN
language:en
Short-container-title:J. Chem. Eng. Japan

Author:

Zhai Lirong¹,Zhai Jiabao²,Xie Ying³

Affiliation:

1. College of Light Industry, Liaoning University

2. China-UK Low Carbon College, Shanghai Jiao Tong University

3. College of Information Engineering, Shenyang University of Chemical Technology

Publisher

Society of Chemical Engineers, Japan

Subject

General Chemical Engineering,General Chemistry

Link

https://www.jstage.jst.go.jp/article/jcej/55/12/55_22we053/_pdf

Reference16 articles.

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2. Birol, G., C. Undey and A. Cinar; “A Modular Simulation Package for Fed-Batch Fermentation Pencilillin Production,” Comput. Chem. Eng., 26, 1553–1565 (2002)

3. Chen, J. and R. J. Patton; “Robust Model-Based Fault Diagnosis for Dynamic Systems,” Volume 3, The International Series on Asian Studies in Computer and Information Science, Springer Science & Business Media, Germany (2012)

4. Ding, C. H. Q., T. Li and M. I. Jordan; “Convex and Semi-Nonnegative Matrix Factorizations,” IEEE Trans. Pattern Anal. Mach. Intell., 32, 44–55 (2010)

5. Ge, Z., Z. Song and F. Gao; “Review of Recent Research on Data-Based Process Monitoring,” Ind. Eng. Chem. Res., 52, 3543–3562 (2013)

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