Component Content Soft-sensor Based on Neural Networks in Rare-earth Countercurrent Extraction Process  

作　　者：YANG Hui CHAI Tian-You 

机构地区：[1]School of Electronics and Electrical Engineering, East China Jiaotong University, Nanchang 330013 [2]Research Center of Automation, Northeastern University, Shenyang 110004

出　　处：《自动化学报》2006年第4期489-495,共7页Acta Automatica Sinica

基　　金：Supported by National Natural Science Foundation of P.R.China(50474020,60534010,60504006)

摘　　要：Throught fusion of the mechanism modeling and the neural networks modeling,a compo- nent content soft-sensor,which is composed of the equilibrium calculation model for multi-component rare earth extraction and the error compensation model of fuzzy system,is proposed to solve the prob- lem that the component content in countercurrent rare-earth extraction process is hardly measured on-line.An industry experiment in the extraction Y process by HAB using this hybrid soft-sensor proves its effectiveness.Throught fusion of the mechanism modeling and the neural networks modeling, a component content soft-sensor, which is composed of the equilibrium calculation model for multi-component rare earth extraction and the error compensation model of fuzzy system, is proposed to solve the problem that the component content in countercurrent rare-earth extraction process is hardly measured on-line. An industry experiment in the extraction Y process by HAB using this hybrid soft-sensor proves its effectiveness.

关 键 词：RARE-EARTH countercurrent extraction soft-sensor equilibrium calculation model neural networks 

分 类 号：TP[自动化与计算机技术]