文献类型：期刊文献

英文题名：Modeling on hydrocyclone separation performance by neural network

作者：He, Fengqin[1,2]; Zhou, Ping[1]; Wang, Jiangang[1]

机构：[1] Research Institute of Process Equipment and Pressure Vessels, East China University of Science and Technology, 200237, Shanghai, China; [2] College of Information, Mechanical and Electrical Engineering, Shanghai Normal University, 200234, Shanghai, China

年份：2012

卷号：105-107

起止页码：185

外文期刊名：Applied Mechanics and Materials

收录：EI(收录号：20114214438323)

语种：英文

外文关键词：Computational fluid dynamics - Cyclone separators - Separation

摘要：A 17-27-5 type BP neural network model was built, whose sampled data was got by hydrocyclone separation experiments; another 6-30-5 type BP neural network was also built, whose sampled data came from the simulation results of the LZVV of a hydrocyclone with CFD code FLUENT. The two neural network models also have good predictive validity aimed at hydrocyclone separation performance. It demonstrates LZVV structural parameters can embody hydrocyclone separation performance and reduce input parameter numbers of neural network model. It also indicates that the predictive model of hydrocyclone separation performance can be built by neural network. ? (2012) Trans Tech Publications.