| 引用本文: | 贾文君, 柴天佑.稀土串级萃取分离过程元素组分含量的多模型软测量[J].控制理论与应用,2007,24(4):569~573.[点击复制] |
| JIA Wen-jun, CHAI Tian-you.Soft-sensor of element component content based on multiple models for the rare earth cascade extraction process[J].Control Theory and Technology,2007,24(4):569~573.[点击复制] |
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| 稀土串级萃取分离过程元素组分含量的多模型软测量 |
| Soft-sensor of element component content based on multiple models for the rare earth cascade extraction process |
| 摘要点击 1552 全文点击 1909 投稿时间：2005-10-13 修订日期：2006-07-17 |
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| DOI编号 |
| 2007,24(4):569-573 |
| 中文关键词 稀土串级萃取 多模型 参数辨识 减法聚类算法 |
| 英文关键词 rare earth cascade extraction multiple models parameter identification subtraction clustering algorithm |
| 基金项目 国家重点基础研究发展计划(973)项目(2002CB312201); 国家自然科学基金重点资助项目(60534010); 国家创新研究群体科学基金资助项目(60521003); 长江学者和创新团队发展计划资助项目(IRT0421). |
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| 中文摘要 |
| 针对稀土串级萃取分离过程中元素组分含量在线测量难的问题, 提出了一种多模型软测量方法, 用于在线预测元素的组分含量. 首先, 以物料平衡方程为基础, 在多个工作点附近建立了描述萃取过程的局部线性模型. 引入减法聚类算法对样本数据进行分类, 用得到的分类数据对局部模型参数进行离线辨识. 每一时刻根据积分性能指标选择最优模型, 同时在线修正局部模型参数. 利用某La,Ce,Pr,Nd 4组分串级萃取分离Ce／Pr生产线的实测数据进行了仿真研究, 结果表明所提出的多模型方法有效、预测精度较高. |
| 英文摘要 |
| To solve the on-line measurement problem for the rare earth cascade extraction process, a multiple models based on soft-sensor is proposed in this paper. Local linear models are obtained around multiple operating points, based on the material balance equations. By introducing the subtraction clustering algorithm, the sample data are classified and the local model parameters are identified off-line using the corresponding data set. At every instant the optimal model is chosen by a suitably defined performance index, and then the parameter of the local model is updated. The soft-sensor is conducted on a certain Ce/Pr extraction production line of La,Ce,Pr,Nd tetra-component system. By comparing with the measured data, the simulation results show the effectiveness and veracity of the soft-sensor. |
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