Fault detection in chemical processes using discriminant analysis and control chart

Abstract

This paper presents a fault detection methodology based on the Fisher discriminant analysis (FDA) and individuals control charts (XmR control charts). As the first step, FDA is used to find the optimal discriminant direction between the normal operation data and the fault data. In the next step, XmR control charts on the discriminant direction are used to monitor the process. To reduce the amount of false alarms, we also used a variable selection technique based on the contribution plot of FDA. The performance of the proposed technique is demonstrated through application to the monitoring of the Tennessee Eastman challenge process. Copyright © 2008 The Society of Chemical Engineers, Japan.