Valve stiction detection using NLPCA
A significant number of control loops in process plants perform poorly due to control valve stiction. Stiction in control valves is the most common and long standing problem in industry, resulting in oscillations in process variables which subsequently lowers product quality and productivity. Develo...
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my.utp.eprints.37312017-01-19T08:26:29Z Valve stiction detection using NLPCA H., Zabiri A., Maulud M., Ramasamy T.D.T., Thao TP Chemical technology A significant number of control loops in process plants perform poorly due to control valve stiction. Stiction in control valves is the most common and long standing problem in industry, resulting in oscillations in process variables which subsequently lowers product quality and productivity. Developing a method to detect valve stiction in the early phase is imperative to avoid major disruptions to the plant operations. In this paper, nonlinear principal component analysis (NLPCA), which is widely known for its capability in unravelling nonlinear correlations in process data, is extended to investigate control valve stiction problems. Results from simulated case studies show that NLPCA is a promising tool for valve stiction diagnosis. 2008 Conference or Workshop Item PeerReviewed application/pdf http://eprints.utp.edu.my/3731/1/paper.pdf http://www.scopus.com/inward/record.url?eid=2-s2.0-62449306452&partnerID=40&md5=aabdc84ea31f34273bf1004f1d49ab0f H., Zabiri and A., Maulud and M., Ramasamy and T.D.T., Thao (2008) Valve stiction detection using NLPCA. In: 27th IASTED International Conference on Modelling, Identification, and Control, 11 February 2008 through 13 February 2008, Innsbruck. http://eprints.utp.edu.my/3731/ |
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TP Chemical technology H., Zabiri A., Maulud M., Ramasamy T.D.T., Thao Valve stiction detection using NLPCA |
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A significant number of control loops in process plants perform poorly due to control valve stiction. Stiction in control valves is the most common and long standing problem in industry, resulting in oscillations in process variables which subsequently lowers product quality and productivity. Developing a method to detect valve stiction in the early phase is imperative to avoid major disruptions to the plant operations. In this paper, nonlinear principal component analysis (NLPCA), which is widely known for its capability in unravelling nonlinear correlations in process data, is extended to investigate control valve stiction problems. Results from simulated case studies show that NLPCA is a promising tool for valve stiction diagnosis.
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format |
Conference or Workshop Item |
author |
H., Zabiri A., Maulud M., Ramasamy T.D.T., Thao |
author_facet |
H., Zabiri A., Maulud M., Ramasamy T.D.T., Thao |
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H., Zabiri |
title |
Valve stiction detection using NLPCA |
title_short |
Valve stiction detection using NLPCA |
title_full |
Valve stiction detection using NLPCA |
title_fullStr |
Valve stiction detection using NLPCA |
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Valve stiction detection using NLPCA |
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valve stiction detection using nlpca |
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2008 |
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http://eprints.utp.edu.my/3731/1/paper.pdf http://www.scopus.com/inward/record.url?eid=2-s2.0-62449306452&partnerID=40&md5=aabdc84ea31f34273bf1004f1d49ab0f http://eprints.utp.edu.my/3731/ |
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