Development of anomaly diagnosis method using neuro-expert for PWR monitoring system

Subekti, M.*; Kudo, Kazuhiko*; Nabeshima, Kunihiko  

The monitoring system for a huge and complex Pressurized Water Reactor (PWR) has some difficulties of monitoring task due to the dynamic system with large number of plant signals. The anomaly detection using neural networks integrated in the monitoring system improves the reactor safety to detect the anomaly faster than conventional methods. The advanced research considered the online anomaly diagnosis using expert system to complete the monitoring system tasks. The combination of neural network and expert system (neuro-expert) has been developed and tested in some anomaly conditions using PWR simulator. In simulation, the neuro-expert system could detect and diagnose the anomalies faster than the conventional alarm system.