%D 2008
%C Innsbruck
%T Valve stiction detection using NLPCA
%O cited By 0; Conference of 27th IASTED International Conference on Modelling, Identification, and Control ; Conference Date: 11 February 2008 Through 13 February 2008; Conference Code:75517
%K Control loops; Control valves; In controls; In process; Non-linear correlations; Nonlinear principal component analysis; Plant operations; Product qualities; Standing problems, Identification (control systems); Nonlinear analysis; Process control; Safety valves; Stiction, Principal component analysis
%L scholars366
%A H. Zabiri
%A A. Maulud
%A M. Ramasamy
%A T.D.T. Thao
%X 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.
%J Proceedings of the IASTED International Conference on Modelling, Identification, and Control, MIC