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

被引：11

作者：

YANG Hui School of Electronics and Electrical EngineeringEast China Jiaotong UniversityNanchang CHAI TianYou Rescarch Center of AutomationNortheastern UniversityShenyang ^{[330013
,110004
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机构：

来源：

自动化学报 | 2006年 / 04期

关键词：

Rare-earth; countercurrent extraction; soft-sensor; equilibrium calculation model; neural networks;

D O I：

10.16383/j.aas.2006.04.002

中图分类号：

TP212 [发送器（变换器）、传感器];

学科分类号：

080202 ;

摘要：

<正>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.

引用

页码：489 / 495

页数：7