Development of a Real-Time Thermal Performance Diagnostic Monitoring System Using Self-Organizing Neural Network for KORI-2 Nuclear Power Unit

Abstract

In this work, a PC-based thermal performance monitoring system is developed for the nuclear power plants. The system performs real-time thermal performance monitoring and diagnosis during plant operation. Specifically, a prototype for the KORI-2 nuclear power unit is developed and examined in this work. The analysis and the fault identification of the thermal cycle of a nuclear power plant is very difficult because the system structure is highly complex and the components are very much inter-related. In this study, some major diagnostic performance parameters are selected in order to represent the thermal cycle effectively and to reduce the computing time. The Fuzzy ARTMAP, a self-organizing neural network, is used to recognize the characteristic pattern change of the performance parameters in abnormal situation. By examination, this algorithm is shown to be able to detect abnormality and to identify the fault component or the change of system operation condition successfully. For the convenience of operators, a graphical user interface is also constructed in this work.