Abstract
Stiction is a persistent control valve problem in the process industry responsible for oscillations and, consequently, losses of productivity. Its early detection and separation from other oscillation causes is an important issue in the industrial context. One of simple and effective approaches to detect stiction has been proposed by Yamashita that employed a pattern recognition principle. While its performance is good in flow control loops, it fails to properly diagnose other types of processes.The present work details a new approach that enables the application of the Yamashita pattern recognition principle to level and other integrating process control loops. A simulation study demonstrates its capabilities in clean and noisy environments and analyzes the impact of the noise on the diagnostic performance.
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