文献类型：期刊文献

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

英文题名：On-line prediction of a fixed-bed reactor using K-L expansion and neural networks

作者：Zhou, Xinggui[1]; Liu, Lianghong[1]; Dai, Yingchun[1]; Yuan, Weikang[1]; Hudson, J.L.[1]

机构：[1]E China Univ Sci & Technol, UNILAB Res Ctr Chem React Engn, Shanghai 200237, Peoples R China;[2]Univ Virginia, Dept Chem Engn, Charlottesville, VA 22903 USA

年份：1998

卷号：6

期号：4

起止页码：299

中文期刊名：Chinese Journal of Chemical Engineering

外文期刊名：CHINESE JOURNAL OF CHEMICAL ENGINEERING

收录：CSTPCD;;EI(收录号：1999124549020);Scopus;WOS:【SCI-EXPANDED(收录号:WOS:000077787300003)】；CSCD:【CSCD2011_2012】；

基金：Supported by the National Natural Science Foundation of China(No.29676014)and others.

语种：英文

中文关键词：fixed-bed;reactor;artificial;neural;network.;Karhunen-Loeve;expansion

外文关键词：fixed-bed reactor; artificial neural network; Karhunen-Loeve expansion

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.
An on-line prediction scheme combining the Karhunen-Loeve expansion and a recurrent neural network for a wall-cooled fixed-bed reactor is presented. Benzene oxidation in a pilot-scale, single tube fixed-bed reactor is chosen as a working system and a pseudo-homogeneous two-dimensional model is used to generate simulation data to investigate the prediction scheme presented under randomly changing operating conditions. The scheme consisting of the K-L expansion and neural network performs satisfactorily for on-line prediction of reaction yield and bed temperatures.