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Qualitative interpretation of process trends by using neural networks

Qualitative interpretation is a process to convert numerical output of sensors into symbolic representation. This process is one of the most critical path to connect intelligent systems with real world. In this paper, qualitative interpretation is realized as pattern-based classification of time-series signal by using ART2 neural networks. As an example, automatic classification of flow patterns in a pneumatic conveyor is successfully demonstrated.