Model-based nuclear power plant monitoring and fault detection: Theoretical foundations

The theoretical basis and validation studies of a real-time, model-based process monitoring and fault detection system is presented. Through use of a non-linear state estimation technique coupled with a probabilistically-based statistical hypothesis test, it is possible to detect and identify sensor, component and process faults at extremely early times from changes in the stochastic characteristics of measured signals. Data from an experimental fast reactor and a commercial PWR are used to demonstrate functional capabilities of the monitoring system.