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

YANG Hui; CHAI Tian-You

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

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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.

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来源
《自动化学报》 |2006年第4期|489-495|共7页
作者
YANG Hui; CHAI Tian-You;
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作者单位

School of Electronics and Electrical Engineering;

East China Jiaotong University;

Nanchang 330013;

Research Center of Automation;

Northeastern University;

Shenyang 110004;

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原文格式 PDF
正文语种 chi
中图分类自动化技术、计算机技术;
关键词
Rare-earth; countercurrent extraction; soft-sensor; equilibrium calculation model; neural networks;

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1. Neural Networks Based Component Content Soft-Sensor in Countercurrent Rare-Earth Extraction [J] . 杨辉 ,谭明皓 ,柴天佑 . 稀土学报：英文版 . 2003,第6期
2. Component Content Soft-Sensor Based on Hybrid Models in Countercurrent Rare Earth Extraction Process [J] . 杨辉 ,王欣 . 稀土学报：英文版 . 2005,第S1期
3. The Prediction of Weight Unevenness of Ring Spinning Cotton Yarn from Processing Parameters by Using Neural Network and Regression Analysis [C] . Zhao Bo . 第三届全国社会计算会议、平行控制会议、平行管理会议 . 2011
4. Research on Relation Extraction Based on Deep Neural Networks [A] . Zhe Cao . 2020

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

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