煤炭工程 ›› 2021, Vol. 53 ›› Issue (2): 164-169.doi: 10.11799/ce202102032

• 研究探讨 • 上一篇    下一篇

速率常数在浮选过程中的变化机制研究进展

霍怡屹1,祖伟2,姜帆1,马嘉成1,赵慧洁1,李金雨1,常甜1,马力强1,李吉辉1   

  1. 1. 中国矿业大学(北京)化学与环境工程学院
    2. 宜章宏源化工有限公司
  • 收稿日期:2020-10-30 修回日期:2020-12-25 出版日期:2021-02-20 发布日期:2021-05-10
  • 通讯作者: 李吉辉 E-mail:lijihuimail@sina.com

Progress on the Mechanism of Change of Rate Constant in Flotation

  • Received:2020-10-30 Revised:2020-12-25 Online:2021-02-20 Published:2021-05-10
  • Contact: Jihui Li E-mail:lijihuimail@sina.com

摘要: 浮选动力学模型对描述浮选过程具有重要意义,浮选速率常数是模型构建的关键参数。深入研究速率常数与不同变量之间的数学关系,可以增加模型的精度和适用性|在不同操作条件下比较速率常数大小、观察其变化,为评价或优化浮选工艺、操作条件、药剂种类及用量、浮选设备性能等提供更有力的工具。文章介绍了浮选动力学模型随着速率常数的深入研究而不断发展的进程,论述了浮选速率常数K值的研究进展,简述了浮选速率常数的时间函数与分布函数的规律和发展以及K值在实践应用中发挥的作用。对推动浮选动力学不断发展的方向提出展望,深入探索浮选速率常数与微观变量的关系,建立新模型,并且优化拟合算法,精确求解模型中的主要参数,有助于精确地表达浮选过程。

关键词: 浮选, 动力学, 速率常数, 动力学模型

Abstract: The flotation kinetic model has guiding significance for describing the flotation process, and the flotation rate constant is the key parameter for model construction. In-depth study of the mathematical relationship between the rate constant and different variables can increase the accuracy and applicability of the model; compare the size of the rate constant under different operating conditions and observe its changes, and you can select better operating conditions to evaluate or optimize the flotation process , The type and amount of reagents, and the performance of flotation equipment provide more powerful tools. This paper introduces the continuous development of the flotation kinetic model along with the in-depth study of the rate constant, discusses the research progress of the flotation rate constant K value, and briefly describes the law and development of the time function and distribution function of the flotation rate constant And the role of K value in practical application. Put forward prospects for the continuous development of flotation kinetics, deeply explore the relationship between flotation rate constants and microscopic variables, establish new models, optimize fitting algorithms, and accurately solve the main parameters in the model, which will help to accurately express the float The selection process.