Accident diagnosis system based on real-time decision tree expert system

Safety is one of the most studied topics when referring to power stations. For that reason, sensors and alarms develop an important role in environmental and human protection. When abnormal event happens, it triggers a chain of alarms that must be, somehow, checked by the control room operators. In this case, diagnosis support system can help operators to accurately identify the possible root-cause of the problem in short time. In this article, we present a computational model of a generic diagnose support system based on artificial intelligence, that was applied on the dataset of two real power stations: Angra1 Nuclear Power Plant and Santo Antônio Hydroelectric Plant. The proposed system processes all the information logged in the sequence of events before a shutdown signal using the expert's knowledge inputted into an expert system indicating the chain of events, from the shutdown signal to its root-cause. The results of both applications showed that the support system is a potential tool to help the control room operators identify abnormal events, as accidents and consequently increase the safety.