Centrifugal Pump-Based Predictive Models for Kraft Black Liquor Viscosity: An Artificial Neural Network Approach

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• 作者：Sunday B. Alabi ; Chris J. Williamson
• 刊名：Industrial & Engineering Chemistry Research
• 出版年：2011
• 出版时间：September 7, 2011
• 年：2011
• 卷：50
• 期：17
• 页码：10320-10328
• 全文大小：937K
• 年卷期：v.50,no.17(September 7, 2011)
• ISSN：1520-5045

文摘

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.