From Symptoms to Faults: Temporal Reasoning Methods

Abstract

Complex systems composed of many components can operate in an inappropriate way. Information about the system is obtained in time, gradually. The assessment of casualties in such situation has challenged many researchers. The present paper provides a new compact methodology for diagnostics of faults form measurements: Space of measurements is divided into symptoms. Each symptom is able to admit some faults as possible and exclude some as impossible. This concept is based on fuzzy logic approach and provides an efficient alternative to usual probabilistic oriented methodologies. These relations between symptoms and faults are stated in the mapping table as logical rules. The diagnosis information is gathered online and aggregated on the side of symptoms or on the side of faults. This paper provides and compares a set of different methods for transformation of measured information into truth rates for each fault.