Recently, in Japan and abroad, information related to abnormal events occurring in nuclear power plants is being exchanged by utilities and international organizations. The information contains a variety of knowledge which may be useful for prevention of similar events.
With this background, an expert system which incorporates the above knowledge into its knowledge base, and offers suggestions about potential abnormal events and preventive know-how, has been developed. The mode of the system utilization mostly recommended by the authors is to infer the potential for abnormal events from newly experienced ones at other plants, evaluate countermeasure priorities, and then consider preventive measures for identified potential events. The system provides six fundamental inference functions for such mode. Among which, the “similar event prediction” function with respect to plant components and the “significance evaluation” function for given event sequences are the main featurings of the system.
This paper discusses the system design/construction philosophies focusing on their unique points, presents the inference algorithms and the knowledge data structure going into details of “similar event prediction” and “significance evaluation”, and demonstrates some system operation examples.
The knowledge base is now being enhanced in order to put the system into operation in the near future.
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