Abstract
In this paper, we propose a topology-based, message-passing Diagnostic Agent (DA) architecture. The diagnostic agents in charge of each process unit perform local diagnoses, exchange related information with other diagnostic agents, and cooperatively solve the global diagnostic problem of the whole process plant just like human experts would do. For their better sharing of process knowledge and information, we also suggest a way of remodeling processes taking into account semantic abstracts of process information or data. The benefits of the suggested collaborative problem solving approach are demonstrated by solving the diagnostic problem of a CSTR system with recycle and a first order irreversible reaction.
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