Abstract
This article presents an efficient Intelligent Supervision System (ISS) architecture for the monitoring of a plant. The ISS detects relevant events which are later used to identify the state of the plant. The ISS layered structure implements the sliding window paradigm to detect significative events from measured signals. This methodology allows for the design of flexible ISS interfaces, that can be easily configured to detect the desired events. The behavioral model of the plant is described by an automaton, which matches event sequences to the state of the plant. Expert knowledge is used in the design of the whole ISS architecture. The ISS has been implemented in Simulink, and applied to a biotechnological process.
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