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 definition of an accurate nonlinear model of a section of a real 320 MW power plant. Within the framework of this global method, the second contribution is the modelling of the most common faults that may occur in plants like the one considered in the paper. All these models allow the simulation of the system both under normal working conditions and under anomalous conditions due to the occurrence of one of the faults modelled. The simulated model can be integrated with the automation system of the plant and used in real time, thus providing the plant technicians with crucial information on the plant behaviour; for instance, fault detection and diagnosis can be accomplished in a natural way. Simulation results and comparisons with real data show the effectiveness of the proposed approach.