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Monitoring of Distillation Column Based on Indiscernibility Dynamic Kernel PCA
Joint Authors
Yu, Xiao
Gao, Qiang
Chang, Yong
Xiao, Zhen
Source
Mathematical Problems in Engineering
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-03-03
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
Aiming at complicated faults detection of distillation column industrial process, it has faced a grave challenge.
In this paper, a new indiscernibility dynamic kernel principal component analysis (I-DKPCA) method is presented and applied to distillation column.
Compared with traditional statistical techniques, I-DKPCA not only can capture nonlinear property and dynamic characteristic of processes but also can extract relevant variables from all the variables.
Applying this new method to distillation column process (a hardware-in-the-loop simulation system), the results prove the proposed method has great advantages, that is, lower missing rate and higher detection rate for the faults, compared with KPCA and DPCA.
American Psychological Association (APA)
Gao, Qiang& Chang, Yong& Xiao, Zhen& Yu, Xiao. 2016. Monitoring of Distillation Column Based on Indiscernibility Dynamic Kernel PCA. Mathematical Problems in Engineering،Vol. 2016, no. 2016, pp.1-11.
https://search.emarefa.net/detail/BIM-1112888
Modern Language Association (MLA)
Gao, Qiang…[et al.]. Monitoring of Distillation Column Based on Indiscernibility Dynamic Kernel PCA. Mathematical Problems in Engineering No. 2016 (2016), pp.1-11.
https://search.emarefa.net/detail/BIM-1112888
American Medical Association (AMA)
Gao, Qiang& Chang, Yong& Xiao, Zhen& Yu, Xiao. Monitoring of Distillation Column Based on Indiscernibility Dynamic Kernel PCA. Mathematical Problems in Engineering. 2016. Vol. 2016, no. 2016, pp.1-11.
https://search.emarefa.net/detail/BIM-1112888
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1112888