Expert system for nuclear power plant accident diagnosis using a fuzzy inference method

Huge and complex systems such as nuclear power generating stations are likely to cause the operators to make operational mistakes for a variety of inexplicable reasons and to produce ambiguous and complicated symptoms in the case of an emergency. Therefore, a safety protection system to assist the operators in making proper decisions within a limited time is required. In this paper, we develop a reliable and improved diagnosis system using the fuzzy inference method so that the system can classify accident symptoms and identify the most probable causes of accidents in order for appropriate actions to be taken to mitigate the consequences. In the computer simulation, the proposed system proved to be able to classify accident types within only 20-30 seconds. Therefore, the corresponding operation guidelines can be determined in a very short time to put the nuclear power plant in a safe state immediately after the accident.