EXPERIENCE WITH THE HIERARCHICAL METHOD FOR DIAGNOSIS OF FAULTS IN NUCLEAR-POWER-PLANT SYSTEMS

Expert systems to aid nuclear power plant operators detect and diagnose abnormal conditions have been under development at The Ohio State University over the past eight years. These systems, generically called operator advisors (OA), are designed to continuously monitor plant parameters and when an abnormality is detected, trigger a diagnostic module. Methods of diagnosis used by these OAs have employed variations of hierarchical classification. Hierarchical classification as a tool for diagnosis of complex systems is described and three systems using different methods for decomposing the hierarchy are presented. Decomposition of the hierarchy by both system and function is introduced and it is shown that a hybrid of the two methods is the optimum if there is good accessibility to operators and system designers, and if the goal is to emulate the operator's approach to diagnosis. In the case of systems operating in different modes it is shown that the most direct method for applying hierarchical diagnosis is by developing a generic function based hierarchy and by incorporating multiple knowledge groups into the nodes in the hierarchy.