eprintid: 734
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/00/07/34
datestamp: 2023-11-09 15:48:53
lastmod: 2023-11-09 15:48:53
status_changed: 2023-11-09 15:23:04
type: conference_item
metadata_visibility: show
creators_name: Zabiri, H.
creators_name: Ramasamy, M.
creators_name: Teh, I.S.Y.
title: Quantification analysis for NLPCA-based stiction diagnostic tool
ispublished: pub
keywords: Control loops; Control valves; Diagnostic tools; In controls; In process; Nonlinear principal component analysis; Plant operations; Product qualities; Quantification analysis; Standing problems, Computer control; Diagnostic products; Safety valves; Stiction, Principal component analysis
note: cited By 2; Conference of International Conference on Advanced Computer Control, ICACC 2009 ; Conference Date: 22 January 2009 Through 24 January 2009; Conference Code:75859
abstract: 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)-based stiction diagnostic tool is presented. Results from simulated case studies show that with proper quantification analysis, NLPCA shows a very promising capability for stiction diagnosis. © 2008 IEEE.
date: 2009
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-64949126466&doi=10.1109%2fICACC.2009.132&partnerID=40&md5=752cc8fd3261a9a96797c2935e9aa651
id_number: 10.1109/ICACC.2009.132
full_text_status: none
publication: Proceedings - International Conference on Advanced Computer Control, ICACC 2009
place_of_pub: Singapore
pagerange: 468-472
refereed: TRUE
isbn: 9780769535166
citation:   Zabiri, H. and Ramasamy, M. and Teh, I.S.Y.  (2009) Quantification analysis for NLPCA-based stiction diagnostic tool.  In: UNSPECIFIED.