Diagnosis of Process Nonlinearities and Valve Stiction

Diagnosis of Process Nonlinearities and Valve Stiction
Author :
Publisher : Springer Science & Business Media
Total Pages : 292
Release :
ISBN-10 : 9783540792246
ISBN-13 : 3540792244
Rating : 4/5 (244 Downloads)

Book Synopsis Diagnosis of Process Nonlinearities and Valve Stiction by : Ali Ahammad Shoukat Choudhury

Download or read book Diagnosis of Process Nonlinearities and Valve Stiction written by Ali Ahammad Shoukat Choudhury and published by Springer Science & Business Media. This book was released on 2008-08-20 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: were published in the series as the contributed volume, Process Control Performance Assessment: From Theory to Implementation with Andrzej Ordys, Damian Uduehi, and Michael Johnson as Editors (ISBN 978-1-84628-623-0, 2007). Along with this good progress in process controller assessment methods, researchers have also been investigating techniques to diagnose what is causing the process or control loop degradation. This requires the use of on-line data to identify faults via new diagnostic indicators of typical process problems. A significant focus of some of this research has been the issue of valve problems; a research direction that has been motivated by some industrial statistics that show up to 40% of control loops having performance degradation attributable to valve problems. Shoukat Choudhury, Sirish Shah, and Nina Thornhill have been very active in this research field for a number of years and have written a coherent and consistent presentation of their many research results as this monograph, Diagnosis of Process Nonlinearities and Valve Stiction. The Advances in Industrial Control series is pleased to welcome this new and substantial contribution to the process diagnostic literature. The reader will find the exploitation of the extensive process data archives created by today’s process computer systems one theme in the monograph. From another viewpoint, the use of higher-order statistics could be considered to provide a continuing link to the earlier methods of the statistical process control paradigm.


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