Table of contents
About this book
In this book, Higher Order Statistical (HOS) theory is used to develop indices for detecting and quantifying signal non-Gaussianity and nonlinearity. These indices, together with specific patterns in the mapping of process output and controller output are used to diagnose the causes of poor control loop performance.
Often valve stiction is the main cause of poor control performance. A generalized definition of valve stiction based on the investigation of real plant data is proposed. A simple data-driven model of valve stiction is developed. The model is simple, yet powerful enough to properly simulate the complex valve stiction phenomena. Both open and closed loop results have been presented and validated to show the capability of the model.
Conventional invasive methods such as the valve travel test can detect stiction easily. However, they are expensive, time consuming and tedious to use for examining thousands of valves in a typical process industry. A non-invasive method that can simultaneously detect and quantify control valve stiction is presented. The method requires only routine operating data from the process. Over a dozen industrial case studies have demonstrated the wide applicability and practicality of this method.
In chemical industrial practice, data are often compressed for archival purposes, using various techniques. Compression degrades data quality and induces nonlinearity in the data. The issues of data quality degradation and nonlinearity induction due to compression are investigated in this book. An automatic method for detection and quantification of the compression present in the archived data is discussed. Compelling and quantitative analyses have been recommended to end the practice of process data compression.
- Book Title Diagnosis of Process Nonlinearities and Valve Stiction
- Book Subtitle Data Driven Approaches
- Series Title Advances in Industrial Control
- Series Abbreviated Title Advances in Industrial Control
- DOI https://doi.org/10.1007/978-3-540-79224-6
- Copyright Information Springer Berlin Heidelberg 2008
- Publisher Name Springer, Berlin, Heidelberg
- eBook Packages Engineering Engineering (R0)
- Hardcover ISBN 978-3-540-79223-9
- Softcover ISBN 978-3-642-09810-9
- eBook ISBN 978-3-540-79224-6
- Series ISSN 1430-9491
- Series E-ISSN 2193-1577
- Edition Number 1
- Number of Pages XX, 286
- Number of Illustrations 198 b/w illustrations, 115 illustrations in colour
Control and Systems Theory
Quality Control, Reliability, Safety and Risk
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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)