A Method for Detection of Stiction in Control Valves

Abstract

There has been an increasing interest in automatic control performance monitoring in recent years. The aim of such monitoring tools is to detect deterioration such as increased variability, oscillating behaviour, saturation or off-sets. Easy and efficient methods have been presented in the literature. After having detected a deteriorated control performance, one would like a monitoring tool to give hints of the possible cause of the deterioration. We will in this contribution suggest a method which allows automatic classification of one important reason for a detected control performance deterioration, namely static friction (stiction) in control valves. The suggested approach uses methodology from the fault-detection field and involves a model-based nonlinear observer and statistical hypothesis testing using a likelihood ratio test. Only little process knowledge, as time-delay, measurements of control signal and process output and some usually known valve parameters are needed. The method is evaluated on industrial data.