On-Line Prediction of a Fixed-Bed Reactor Using K-L Expansion and Neural Networks

被引：0
|
作者：
周兴贵
刘良宏
戴迎春
袁渭康
J.L.Hudson
机构：
[1] Department of Chemical Engineering
[2] VA 22903
[3] USA
[4] University of Virginia
[5] Charlottesville
来源：
Chinese Journal of Chemical Engineering | 1998年 / 04期
基金：
中国国家自然科学基金;
关键词：
fixed-bed reactor; artificial neural network. Karhunen-Loeve expansion;
D O I：
暂无
中图分类号：
TQ018 [数学模型及放大];
学科分类号：
0703 ;
摘要：
An on-line prediction scheme combining the Karhunen-Love expansion and a recurrent neural network for a wall-cooled fixed-bed reactor is presented.Benzene oxidation in a pilotscale,single tube fixed-bed reactor is chosen as a working system and a pseudo-homogeneous twodimensional model is used to generate simulation data to investigate the prediction scheme presentedunder randomly changing operating conditions.The scheme consisting of the K-L expansion andneural network performs satisfactorily for on-line prediction of reaction yield and bed temperatures.
引用
收藏
页码：21 / 27
页数：7
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