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| 钴湿法冶炼萃取过程中的组分含量软测量 | |
| 引用本文： | 贾润达,毛志忠,常玉清,周俊武.钴湿法冶炼萃取过程中的组分含量软测量[J].控制与决策,2009,24(4). |
| 作者姓名： | 贾润达 毛志忠 常玉清 周俊武 |
| 作者单位： | 1. 东北大学信息科学与工程学院,沈阳,110004 2. 东北大学信息科学与工程学院,沈阳,110004;东北大学教育部暨辽宁省流程工业综合自动化重点实验室,沈阳,110004 3. 北京矿冶研究总院,信息技术与自动化研究设计所,北京,100044 |
| 基金项目： | 国家高技术研究发展计划(863计划) |
| 摘 要： | 提出了一种钴湿法冶炼萃取组分含量混合建模方法.该模型由基于物料衡算关系的动态机理模型与基于萃取平衡实验数据的RBF神经网络模型组成.机理模型作为描述过程动态行为的整体框架,RBF神经网络用来辨识机理模型中的未知函数关系.在上述混合模型的基础上,还提出了一种模型校正策略,进一步提高了模型的精确性.将所建立的混合模型应用于实际湿法冶炼生产过程中,结果表明该方法具有良好的估计性能. |
| 关 键 词： | 湿法冶炼 萃取 混合模型 RBF神经网络 软测量 |
Soft sensing for component content in cobalt hydrometallurgy extraction process |
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| JIA Run-da,MAO Zhi-zhong,CHANG Yu-qing,ZHOU Jun-wu.Soft sensing for component content in cobalt hydrometallurgy extraction process[J].Control and Decision,2009,24(4). | |
| Authors: | JIA Run-da MAO Zhi-zhong CHANG Yu-qing ZHOU Jun-wu |
| Affiliation: | 1a.College of Information Science and Engineering;1b.Key Laboratory of Process Industry Automation of Ministry of Education;Northeastern University;Shenyang 110004;China;2.Sub-institute for IT and Automation;Beijing General Research Institute of Mining and Metallurgy;Beijing 100044;China. |
| Abstract: | A hybrid modeling scheme is presented in this paper for component content in cobalt hydrometallurgy extraction process, which is composed of first principle model based on material balance and RBF neural networks models based on the data of extraction balance experiment. First principle model describes dynamic behavior of process as the rough framework. RBF neural networks are employed to identify the unknown function relationship. Based on the hybrid model above, a model correction strategy is also propose... |
| Keywords: | Hydrometallurgy Extraction Hybrid model RBF neural networks Soft sensor |
| 本文献已被 CNKI 万方数据 等数据库收录！ | |
