| Neural Networks Based Component Content Soft－Sensor in Countercurrent Rare－Earth Extraction |
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| 引用本文： | 杨辉,谭明皓,柴天佑.Neural Networks Based Component Content Soft－Sensor in Countercurrent Rare－Earth Extraction[J].中国稀土学报(英文版),2003,21(6):691-696. |
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| 作者姓名： | 杨辉 谭明皓 柴天佑 |
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| 作者单位： | ResearchCenterofAutomation,NortheasternUniversity,Shenyang110004,China |
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| 基金项目： | ProjectsupportedbytheNationalTenthFive Year PlanofKeyTechnology (2 0 0 2BA3 15A) |
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| 摘 要： | 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 countereurrent rare earth extraction production. Simulation experiments with industrial operation data prove the effectiveness of the hybrid softsensor.
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| 关 键 词： | 稀土 反向萃取 神经网络 传感器 XRD |
Neural Networks Based Component Content Soft-Sensor in Countercurrent Rare-Earth Extraction |
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| Yang Hui ,Tan Minghao,Chai Tianyou.Neural Networks Based Component Content Soft-Sensor in Countercurrent Rare-Earth Extraction[J].Journal of Rare Earths,2003,21(6):691-696. |
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| Authors: | Yang Hui Tan Minghao Chai Tianyou |
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| Affiliation: | Yang Hui ~*,Tan Minghao,Chai Tianyou |
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| 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 effectiveness of the hybrid soft-(sensor). |
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| Keywords: | countercurrent extraction first principle model soft-sensor model neural networks rare earths |
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