Qualitative fault diagnosis in systems with nonintermittent concurrent faults: a subjective approach

Major approaches to automatic fault diagnosis of industrial plants are either subjective or objective. Subjective approaches imitate and synthesize the way that human experts diagnose faults. Objective approaches automate a portion of a diagnostic task which, due to cognitive limitation, humans do not handle efficiently. Currently available subjective fault diagnosis techniques suffer from certain drawbacks, such as: lack of knowledge for modeling and reasoning with the required levels of detail; inefficiency in utilization of sensory data; and inadequacy in learning experienced schemas. A subjective approach to fault diagnosis, using qualitative modeling and reasoning within the multiple view of the system, is introduced. The focus is on automation of the cognitive skills of human experts, which include utilizing conceptual models to detect inherent redundancy in system behavior qualitative reasoning to predict future states, and information selection to avoid computation overload