Diagnosis of Process Nonlinearities and Valve Stiction: Data Driven Approaches

byAli Ahammad Shoukat Choudhury, Sirish L. Shah, Nina F. Thornhill

Paperback | November 25, 2010

Diagnosis of Process Nonlinearities and Valve Stiction: Data Driven Approaches by Ali Ahammad Shoukat Choudhury
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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.
M. A. A. Shoukat Choudhury received his B. Sc. Engineering (Chemical) from Bangladesh University of Engineering and Technology (BUET), Dhaka, Bangladesh in 1996. He was awarded a gold medal for his outstanding results in B. Sc. Engineering. He obtained an M. Sc. Engineering (Chemical) in 1998 from the same unive...
Title:Diagnosis of Process Nonlinearities and Valve Stiction: Data Driven ApproachesFormat:PaperbackProduct dimensions:286 pages, 9.25 X 6.1 X 0 inShipping dimensions:286 pages, 9.25 X 6.1 X 0 inPublished:November 25, 2010Publisher:Springer-Verlag/Sci-Tech/TradeLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:364209810X

ISBN - 13:9783642098109

Appropriate for ages: All ages

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Table of Contents

Higher-Order Statistics.- Higher-Order Statistics: Preliminaries.- Bispectrum and Bicoherence.- Data Quality - Compression and Quantization.- Impact of Data Compression and Quantization on Data-Driven Process Analyses.- Nonlinearity and Control Performance.- Measures of Nonlinearity - A Review.- Linear or Nonlinear? A Bicoherence-Based Measure of Nonlinearity.- A Nonlinearity Measure Based on Surrogate Data Analysis.- Nonlinearities in Control Loops.- Diagnosis of Poor Control Performance.- Control Valve Stiction<- Definition, Modelling, Detection and Quantification.- Different Types of Faults in Control Valves.- Stiction: Definition and Discussions.- Physics-Based Model of Control Valve Stiction.- Data-Driven Model of Valve Stiction.- Describing Function Analysis.- Automatic Detection and Quantification of Valve Stiction.- Industrial Applications of the Stiction Quantification Algorithm.- Confirming Valve Stiction.- Plant-wide Oscillations - Detection and Diagnosis.- Detection of Plantwide Oscillations.- Diagnosis of Plant-wide Oscillations.

Editorial Reviews

From the reviews: "This monograph is aimed at researchers and practicing engineers interested in the diagnosis of closed-loop system performance. The goal is to present techniques for monitoring the performance of continuous processes in the chemical industry using process data. The material consolidates in one place some recent results concerned with the detection, diagnosis, and quantification of process nonlinearities." (IEEE Control Systems Magazine, Vol. 29, October, 2009)