PHYSICALLY ACCURATE NONLINEAR MODELS FOR FAULT-DETECTION AND DIAGNOSIS - THE CASE OF A POWER-PLANT

This paper deals with two main contributions. The first is the definit ion of an accurate nonlinear model of a section of a real 320 MW power plant. Within the framework of this global method, the second contrib ution is the modelling of the most common faults that may occur in pla nts like the one considered in the paper. All these models allow the s imulation of the system both under normal working conditions and under anomalous conditions due to the occurrence of one of the faults model led. The simulated model can be integrated with the automation system of the plant and used in real time, thus providing the plant technicia ns with crucial information on the plant behaviour; for instance, faul t detection and diagnosis can be accomplished in a natural way. Simula tion results and comparisons with real data show the effectiveness of the proposed approach. (C) 1997 Elsevier Science Ltd. All rights reser ved.