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Centrifugal pump-based predictive models for kraft black liquor viscosity / Sunday B. Alabi in Industrial & engineering chemistry research, Vol. 50 N° 17 (Septembre 2011) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 50 N° 17 (Septembre 2011) . - pp. 10320-10328 Titre : Centrifugal pump-based predictive models for kraft black liquor viscosity : an artificial neural network approach Type de document : texte imprimé Auteurs : Sunday B. Alabi, Auteur ; Chris J. Williamson, Auteur Année de publication : 2011 Article en page(s) : pp. 10320-10328 Note générale : Chimie industrielle Langues : Anglais (eng) Mots-clés : Neural  network  Viscosity  Black  liquor  Forecast  model  Centrifugal  pump Résumé : Previous investigators have shown that the Newtonian viscosity of black liquor (BL), a byproduct of kraft pulping process, can be estimated online from the performance parameters of an installed centrifugal pump (CP). Unfortunately, the existing models from which such estimates can be obtained lack the necessary robustness for process control applications and/or would require a substantial amount of data for periodic updates. This study developed a generalized artificial neural network (ANN)-based model which directly accounts for the effect of aging on the pump performance (hence the model). Simulation results show that ANN predicts BL viscosity better than the existing linear models as the former gives accurate and robust predictions at all practical operating points of the pump. Moreover, the ANN model requires just a single data point for its periodic recalibration as the pump ages significantly. The methodologies presented here can easily be adapted for use in any process industry where Newtonian process fluids are transferred by a CP. DEWEY : 660 ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=24483677 [article] Centrifugal pump-based predictive models for kraft black liquor viscosity : an artificial neural network approach [texte imprimé] / Sunday B. Alabi, Auteur ; Chris J. Williamson, Auteur . - 2011 . - pp. 10320-10328. Chimie industrielle Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 50 N° 17 (Septembre 2011) . - pp. 10320-10328 Mots-clés : Neural  network  Viscosity  Black  liquor  Forecast  model  Centrifugal  pump Résumé : Previous investigators have shown that the Newtonian viscosity of black liquor (BL), a byproduct of kraft pulping process, can be estimated online from the performance parameters of an installed centrifugal pump (CP). Unfortunately, the existing models from which such estimates can be obtained lack the necessary robustness for process control applications and/or would require a substantial amount of data for periodic updates. This study developed a generalized artificial neural network (ANN)-based model which directly accounts for the effect of aging on the pump performance (hence the model). Simulation results show that ANN predicts BL viscosity better than the existing linear models as the former gives accurate and robust predictions at all practical operating points of the pump. Moreover, the ANN model requires just a single data point for its periodic recalibration as the pump ages significantly. The methodologies presented here can easily be adapted for use in any process industry where Newtonian process fluids are transferred by a CP. DEWEY : 660 ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=24483677