东北大学学报（自然科学版）

东北大学学报:自然科学版 ›› 2020, Vol. 41 ›› Issue (1): 1-6.DOI: 10.12068/j.issn.1005-3026.2020.01.001

• 信息与控制 •    下一篇

基于案例推理的湿法冶金全流程优化设定

牛大鹏， 臧雅丽， 贾明兴   

  1. (东北大学 信息科学与工程学院， 辽宁 沈阳110819)
  • 收稿日期:2019-05-04 修回日期:2019-05-04 出版日期:2020-01-15 发布日期:2020-02-01
  • 通讯作者: 牛大鹏
  • 作者简介:牛大鹏(1980-)，男，山东高青人，东北大学副教授； 贾明兴(1972-)，男，辽宁凌源人，东北大学教授.
  • 基金资助:
    国家自然科学基金资助项目(61773101，61673092)； 中央高校基本科研业务费专项资金资助项目(N170402009).

Optimal Setting for Hydrometallurgical Whole Process Based on Case-Based Reasoning

NIU Da-peng， ZANG Ya-li， JIA Ming-xing   

  1. School of Information Science & Engineering， Northeastern University， Shenyang 110819， China.
  • Received:2019-05-04 Revised:2019-05-04 Online:2020-01-15 Published:2020-02-01
  • Contact: NIU Da-peng
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摘要： 湿法冶金全流程具有工况多变、强耦合、非线性等特点，基于机理模型的过程优化控制通常求解困难且难以适应工况变化.为此，提出一种基于案例推理的全流程优化设定方法.由于湿法冶金各生产工序之间存在紧密耦合，运行参数彼此关联，这些关联关系表现为各工况运行参数和各调整变量的优化设定值之间的关系.因此，通过对历史数据进行关联规则挖掘，寻找各运行参数和操作变量的优化设定值之间的规则，将挖掘的规则用于案例修正环节，以解决案例修正中规则难以获取的问题.仿真实验表明，该方法可以提高湿法冶金全流程的经济效益.

关键词: 湿法冶金, 优化设定, 历史数据, 案例推理, 关联规则挖掘

Abstract: The hydrometallurgical whole process has the characteristics of variable working conditions， strong coupling and non-linearity. The process optimization control based on mechanism model is usually difficult to solve， and has difficulty in adapting to changes in working conditions. Thus， a case-based reasoning(CBR)method to optimize the whole process is proposed. Due to the close coupling in hydrometallurgical the production processes， the operation parameters are related to each other， which shows the relationship between the operation parameters of each working condition and the optimal setting value of each adjustment variable. Therefore， the rules between the optimal setting values of each operation parameter and operation variables are searched by mining the association rules of historical data. The mining rules are used in the case correction to solve the problem that rules are difficult to obtain. The simulation results show that this method can improve the economic benefits of the hydrometallurgical whole process.

Key words: hydrometallurgy, optimal setting, historical data, case-based reasoning(CBR), association rule mining

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