NDLI: Performance Monitoring of Chemical Process Based on Multivariable Statistical Technology

Content Provider	IEEE Xplore Digital Library
Author	Li Xiong Jun Liang Jixin Qian
Copyright Year	2006
Description	Author affiliation: Inst. of Syst. Eng., Zhejiang Univ., Hangzho (Li Xiong; Jun Liang; Jixin Qian)
Abstract	Principal component analysis (PCA) can be effectively used to eliminate system noise and correlation between process variables but to reserve enough original data information. Based on principal component model, performance monitoring and analysis was carried out on control system with multivariate statistical index, such as Q residuals, Hotelling $T^{2}$ and principal scores. This method with multivariable statistical technologies gives explicit knowledge about control system: whether the system is in-control or out-control, how disturbance and system variables influence the performance and how the control strategy work. Control system then could be evaluated with these knowledges. Application to two typical chemical processes shows the example of the method practical function
Starting Page	5539
Ending Page	5542
File Size	122466
Page Count	4
File Format	PDF
ISBN	1424403324
DOI	10.1109/WCICA.2006.1714133
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-06-21
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Chemical technology Monitoring Chemical processes Principal component analysis Control systems Educational technology Performance analysis Control system synthesis Parameter estimation Statistical analysis Chemical process Performance monitoring PrincipalComponent Analysis Multi variate statistical index
Content Type	Text
Resource Type	Article

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