DEVELOPMENT OF THE ONLINE OPERATOR AID SYSTEM OASYS USING A RULE-BASED EXPERT-SYSTEM AND FUZZY-LOGIC FOR NUCLEAR-POWER-PLANTS

The On-line Operator Aid SYStem (OASYS) has been developed to support the operator's decision making process and to ensure the safety of a n uclear power plant by providing operators with proper guidelines in a timely manner, according to the plant operation mode. The OASYS consis ts of four systems such as a signal validation and management system ( SVMS), a plant monitoring system (PMS), an alarm filtering and diagnos tic system (AFDS), and a dynamic emergency procedure tracking system ( DEPTS). The SVMS and the PMS help operators to maintain a plant in a c ondition to withstand the adverse-events during a normal operation con dition. The AFDS covers the abnormal events until it exceeds the limit range of reactor trip signals, while after a reactor trip, the DEPTS aids operators with proper guidelines so as to shut down safely. The O ASYS uses a rule-based expert system and fuzzy logic. The rule-based e xpert system is used to classify the predefined events and track the e mergency operating procedures (EOPs) through data processing, and the fuzzy logic is used to generate the conceptual high-level alarms for t he prognostic diagnosis and to evaluate the qualitative fuzzy criteria used in the EOPs. Evaluation results show that the OASYS is capable o f diagnosing plant abnormal conditions and providing operators appropr iate guidelines with fast response time and consistency. The proposed system is implemented on a SUN-4/75 workstation using C language and Q uintus prolog language. Currently, the OASYS is installed in the real- time full scope simulator for validation. After sufficient validation, the OASYS will be installed in the main control room for the unit one nuclear power plant at Young Gwang.