Fault Detection for Industrial Processes
Joint Authors
Zhang, Lingjun
Zhang, Hailong
Zhang, Yingwei
Source
Mathematical Problems in Engineering
Issue
Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-18, 18 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2012-12-11
Country of Publication
Egypt
No. of Pages
18
Main Subjects
Abstract EN
A new fault-relevant KPCA algorithm is proposed.
Then the fault detection approach is proposed based on the fault-relevant KPCA algorithm.
The proposed method further decomposes both the KPCA principal space and residual space into two subspaces.
Compared with traditional statistical techniques, the fault subspace is separated based on the fault-relevant influence.
This method can find fault-relevant principal directions and principal components of systematic subspace and residual subspace for process monitoring.
The proposed monitoring approach is applied to Tennessee Eastman process and penicillin fermentation process.
The simulation results show the effectiveness of the proposed method.
American Psychological Association (APA)
Zhang, Yingwei& Zhang, Lingjun& Zhang, Hailong. 2012. Fault Detection for Industrial Processes. Mathematical Problems in Engineering،Vol. 2012, no. 2012, pp.1-18.
https://search.emarefa.net/detail/BIM-1029749
Modern Language Association (MLA)
Zhang, Yingwei…[et al.]. Fault Detection for Industrial Processes. Mathematical Problems in Engineering No. 2012 (2012), pp.1-18.
https://search.emarefa.net/detail/BIM-1029749
American Medical Association (AMA)
Zhang, Yingwei& Zhang, Lingjun& Zhang, Hailong. Fault Detection for Industrial Processes. Mathematical Problems in Engineering. 2012. Vol. 2012, no. 2012, pp.1-18.
https://search.emarefa.net/detail/BIM-1029749
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1029749