基于模糊操作模式的砷盐除钴过程操作参数协同优化

伍铁斌; 阳春华; 李勇刚; 朱红求; 桂卫华

doi:10.3724/SP.J.1004.2014.01690

基于模糊操作模式的砷盐除钴过程操作参数协同优化

doi: 10.3724/SP.J.1004.2014.01690

1.
中南大学信息科学与工程学院长沙 410083;
2.
湖南人文科技学院机电工程系娄底 417000

基金项目:

国家自然科学基金（61174133，61273159，61273185），国家杰出青年科学基金（61025015），国家''十二五''科技支撑计划项目（2012BAF03B05）资助

详细信息

作者简介:
伍铁斌中南大学信息科学与工程学院博士研究生. 主要研究方向为复杂工业过程建模、控制与优化.E-mail：wutiebin81@163.com

通讯作者:
阳春华博士，中南大学信息科学与工程学院教授. 主要研究方向为复杂工业过程建模与优化控制，智能自动化控制系统.E-mail：ychh@mail.csu.edu.cn

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出版历程
- 收稿日期: 2013-06-17
- 修回日期: 2013-12-31
- 刊出日期: 2014-08-20

Fuzzy Operational-pattern Based Operating Parameters Collaborative Optimization of Cobalt Removal Process with Arsenic Salt

1.
School of Information Science and Engineering, Central South University, Changsha 410083;
2.
Department of electrical and Mechanical Engineering, Hunan University of Humanities, Science and Technology, Loudi 417000

Funds:

Supported by National Natural Science Foundation (61174133, 61273159, 61273185), National Science Fund for Distinguished Young Scholars of China (61025015), and National “Twelfth Five-Year” Plan for Science & Technology Support (2012BAF03B05)

摘要

摘要: 针对湿法炼锌砷盐除钴过程工况变化频繁和操作参数之间具有强耦合关系，导致操作参数优化困难的问题，提出了一种基于模糊操作模式的操作参数协同优化方法.根据大量的砷盐除钴工业运行数据，提炼初始操作模式库，根据入口工况参数，采用模糊匹配方法检索出相似操作模式，在操作模式重用时综合考虑系统参数缓慢变化和资源消耗的特点，然后采用灰色模糊最小二乘支持向量机（Least squares support vector machine，LSSVM）评估操作模式重用后的操作参数的可行性，并根据评估结果采用模糊专家规则修正操作参数.在工况发生变化时，系统能自动优化设定操作参数.工业验证结果表明，本文提出的操作参数协同优化方法保证了生产稳定，可有效提高净化后溶液中钴离子浓度的合格率和降低锌粉的消耗.
- 操作模式 /
- 操作参数 /
- 协同优化 /
- 模糊 /
- 评估
Abstract: In the process of cobalt removal with arsenic salt in zinc hydrometallurgy, since the work conditions change frequently and the operating parameters couple strongly, it is difficult to optimize the operating parameters. To solve the problem, a method of operating parameters collaborative optimization based on fuzzy operational-pattern is proposed. The initial operational-pattern library is abstracted from the abundant industrial operating data of the cobalt removal process. A fuzzy matching method is adopted to search for similar operational-patterns according to the entrance working parameters. When the operational-pattern is reused, the slow change of system parameters and the characteristics of energy consumption should be considered comprehensively. Then the gray fuzzy least squares support vector machine (LSSVM) is used to evaluate the feasibility of operation parameter after reusing, and the operating parameters will be modified by fuzzy expert rules according to the evaluation result. When the working conditions change, the system can optimize and set the operating parameters automatically. The industrial test results show that the proposed operating parameters collaborative optimization method can ensure a stable production process running increase the qualified rate of outlet cobalt concentration, and help reduce zinc consumption effectively.
- Operational-pattern /
- operating parameters /
- collaborative optimization /
- fuzzy /
- evaluation

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参考文献(16)

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[2]	[2] Tozawa K, Nishimura T, Akahori M, Malaga M A. Comparison between purification processes for zinc leach solutions with arsenic and antimony trioxides. Hydrometallurgy, 1992, 30(1-3): 445-461
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基于模糊操作模式的砷盐除钴过程操作参数协同优化

doi: 10.3724/SP.J.1004.2014.01690

作者简介:
伍铁斌中南大学信息科学与工程学院博士研究生. 主要研究方向为复杂工业过程建模、控制与优化.E-mail：wutiebin81@163.com

通讯作者:
阳春华博士，中南大学信息科学与工程学院教授. 主要研究方向为复杂工业过程建模与优化控制，智能自动化控制系统.E-mail：ychh@mail.csu.edu.cn

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Fuzzy Operational-pattern Based Operating Parameters Collaborative Optimization of Cobalt Removal Process with Arsenic Salt

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留言板

基于模糊操作模式的砷盐除钴过程操作参数协同优化

doi: 10.3724/SP.J.1004.2014.01690

作者简介: 伍铁斌 中南大学信息科学与工程学院博士研究生. 主要研究方向为复杂工业过程建模、控制与优化.E-mail：wutiebin81@163.com

通讯作者: 阳春华 博士，中南大学信息科学与工程学院教授. 主要研究方向为复杂工业过程建模与优化控制，智能自动化控制系统.E-mail：ychh@mail.csu.edu.cn

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出版历程

Fuzzy Operational-pattern Based Operating Parameters Collaborative Optimization of Cobalt Removal Process with Arsenic Salt

计量

出版历程

目录

作者简介:
伍铁斌中南大学信息科学与工程学院博士研究生. 主要研究方向为复杂工业过程建模、控制与优化.E-mail：wutiebin81@163.com

通讯作者:
阳春华博士，中南大学信息科学与工程学院教授. 主要研究方向为复杂工业过程建模与优化控制，智能自动化控制系统.E-mail：ychh@mail.csu.edu.cn