Neural Networks Based Component Content Soft-Sensor in Countercurrent Rare-Earth Extraction
来源期刊：JOURNAL OF RARE EARTHS2003年第6期
论文作者：谭明皓 杨辉 柴天佑
Key words：countercurrent extraction; first principle model; soft-sensor model; neural networks; rare earths;
Abstract: The equilibrium model for multicomponent rare earth extraction is developed using neural networks, which combined with the material balance model could give online prediction of component content in countercurrent rare earth extraction production. Simulation experiments with industrial operation data prove the effect iveness of the hybrid soft- sensor.
谭明皓1，杨辉1，柴天佑1
(1.Research Center of Automation, Northeastern University, Shenyang 110004, China)
Abstract:The equilibrium model for multicomponent rare earth extraction is developed using neural networks, which combined with the material balance model could give online prediction of component content in countercurrent rare earth extraction production. Simulation experiments with industrial operation data prove the effect iveness of the hybrid soft- sensor.
Key words:countercurrent extraction; first principle model; soft-sensor model; neural networks; rare earths;
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