Development of Fault Diagnosis System Using Principal Component Analysis for Intelligent Operation Support System

In this paper, it is proposed to develop the fault diagnosis system using the principal component analysis (PCA) for the intelligent operation support system that calculates the effect of fault propagation in abnormalities situation and gives appropriate information to plant operators. This proposed system using PCA discriminates a failure of equipment based on process variables. The proposed method deals with process variables in steady condition and only one type warning alarm condition that is occurred by several different failures. A set of process variables on each failure is shown as the points on 2dimensional data space by PCA. This system judges as a failure of the equipment when a set of current process variables is closed to the point of a failure of equipment on the data space. The proposed fault diagnosis system is applied to process on a simulator and is confirm its validity.