NDLI: An independent component analysis and mutual information based non-Gaussian pattern matching method for fault detection and diagnosis of complex cryogenic air separation process

Content Provider	IEEE Xplore Digital Library
Author	Jingyan Chen Jie Yu Mori, J. Rashid, M.M. Gangshi Hu Honglu Yu Flores-Cerrillo, J. Megan, L.
Copyright Year	2013
Description	Author affiliation: Process & Syst. R&D, Praxair, Inc., Tonawanda, NY, USA (Gangshi Hu; Honglu Yu; Flores-Cerrillo, J.; Megan, L.) \|\| Dept. of Chem. Eng., McMaster Univ., Hamilton, ON, Canada (Jingyan Chen; Jie Yu; Mori, J.; Rashid, M.M.)
Abstract	The conventional principal component analysis (PCA) based pattern matching methods have been applied to dynamic process monitoring. However, they do not take into account the non-Gaussian features in industrial processes and are also more focused on fault detection instead of fault diagnosis. In this paper, an independent component analysis and mutual information based non-Gaussian pattern matching approach is developed for fault detection and diagnosis of complex chemical processes. The presented approach is applied to a simulated cryogenic air separation process and the application study demonstrates that the developed non-Gaussian pattern matching method can effectively monitor the complex air separation process with strong capability of fault detection and diagnosis.
Starting Page	2797
Ending Page	2802
File Size	259230
Page Count	6
File Format	PDF
ISBN	9781479901777
ISSN	07431619
e-ISBN	9781479901784
DOI	10.1109/ACC.2013.6580258
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-06-17
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	American Automatic Control Council(AACC)
Subject Keyword	Monitoring Pattern matching Fault detection Benchmark testing Mutual information Indexes Integrated circuits
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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