Failure Diagnosis of Plants in Operation

Abstract

When plants are running normally, the ordinary process controllers, which have been developed till now, act excellently, but they are almost useless in an abnormal condition. Usually, simple automatic trip systems are equipped only for emergency use. These emergency control systems are so poor that the human operator is indispensable even in fully automated plants. On the other hand, if we equip the plant with many fault detectors, the plant may frequently make unnecessary halts due to noise or troubles in detectors. The purpose of this paper is to develop a new type emergency control system which keeps the plant safe while making the down time minimum. The new system has two major actions. One is the automatic diagnosis finding the place of troubles, either in the plant side (including normal state) or in the detectors’ side. The other action is the prediction of the plant state if it goes into the dangerous state or not. This is very important, because most of the mis-downs of plants are caused by the temporary fluctuation of some controlled variables.The basic idea of the diagnosis is the combination of “maximum likelihood” and “two out of three”. The prediction is done by “simulation”. After building the emergency control system, the authors tested it with a steam plant. This experiment gave fine results. The artificial troubles caused by us were completely diagnosed and predicted.