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Type: Artigo de periódico
Title: ANN-based soft-sensor for real-time process monitoring and control of an industrial polymerization process
Author: Gonzaga, JCB
Meleiro, LAC
Kiang, C
Maciel, R
Abstract: This paper presents the development and the industrial implementation of a virtual sensor (soft-sensor) in the polyethylene terephthalate (PET) production process. This soft-sensor, based on a feed-forward artificial neural network (ANN), was primarily used to provide on-line estimates of the PET viscosity, which is necessary for process control purposes. The ANN-based soft-sensor (ANN-SS) was also used for providing redundant measurements of the viscosity that could be compared to the results obtained from the process viscometer. It was shown that the proposed ANN-SS was able to adequately infer the polymer viscosity, in such a way so as this soft-sensor could be used in the real-time process control strategy. The proposed control system has Successfully been applied in servo and regulatory problems, thus allowing an effective and feasible operation of the industrial plant. (C) 2008 Elsevier Ltd. All rights reserved.
Subject: soft-sensor
Artificial neural networks
Polymerization process
Polyethylene terephthalate
Process control
Distributed control system
Country: Inglaterra
Editor: Pergamon-elsevier Science Ltd
Rights: fechado
Identifier DOI: 10.1016/j.compchemeng.2008.05.019
Date Issue: 2009
Appears in Collections:Artigos e Materiais de Revistas Científicas - Unicamp

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