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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
