Abstract
After Fukushima nuclear accident, there has been increasing concern regarding monitoring and management of severe accident. When transients or accidents happened in nuclear power plant, plant operator will try to identify transients by observing the trend of some important parameters. However, under the accident scenario, operator will face with hundreds of alarms and warning information, which might cause confusion and raise the risk of operational error. Therefore, accurately and fast classification of the initiating event is an important and valuable information to successfully manage the severe accident. With the result of classification, plant operators can follow the consequence to find out the sequence of management from emergency operating procedure (EOP). In order to classify loss of coolant accident (LOCA), present research employs the rule-based classification system and artificial intelligence (AI) techniques to diagnose accidents. Taipower Lungmen nuclear power station (LNPS), an advanced boiling water reactor (ABWR), is chosen as the target plant. The AI approach is to construct the database of operators’ knowledge and then make classification based on the value and trend of important operation parameters. Demonstration has shown that the present technique is a feasible approach for events classification.