An integrated approach for fault diagnosis with learning

Abstract This paper presents an integrated approach for diagnostic reasoning that combines the strengths of both shallow reasoning and deep reasoning, and incorporates two different forms of learning into the diagnostic system. This new diagnostic approach should be widely applicable to a range of complex, computer-controlled systems. A case study is presented for a pumping system in a chemical process plant, in which several fault situations are simulated and correctly diagnosed by the diagnostic system and the system learning capability is demonstrated.

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