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过程工程学报 ›› 2021, Vol. 21 ›› Issue (6): 680-686.DOI: 10.12034/j.issn.1009-606X.220161

• 流动与传递 • 上一篇    下一篇

基于立磨选粉机颗粒分级过程的数学建模研究

耿鹏浩, 陈延信* 姚艳飞, 博,   

  1. 西安建筑科技大学材料科学与工程学院,陕西 西安 710055
  • 收稿日期:2020-05-25 修回日期:2020-07-22 出版日期:2021-06-28 发布日期:2021-06-28
  • 通讯作者: 陈延信 yx_ch@126.com
  • 基金资助:
    国家重点计划研发项目

Research on mathematical modeling of particle classification process based on vertical mill separator

Penghao GENG,  Yanxin CHEN*,  Yanfei YAO,  Bo ZHAO,  Ding HAN   

  1. School of Material Science and Engineering, Xi'an University of Architecture and Technology, Xi'an, Shaanxi 710055, China
  • Received:2020-05-25 Revised:2020-07-22 Online:2021-06-28 Published:2021-06-28
  • Contact: CHEN Yan-xin yx_ch@126.com

摘要: 通过立磨粉磨中试试验平台开展试验,对比分析不同系统风量和选粉机转速条件下选粉机分级性能的变化规律。利用正态分布的累积分布函数,将选粉机操作参数与不同粒径颗粒的捕集概率关联。采用系统风量和选粉机转速工况变化的试验数据拟合出模型中的均值和方差,建立可定量分析系统风量、选粉机转速与颗粒部分分级效率之间关系的数学模型。经验证回归的拟合标准差RMSE=0.0046,预测值与真实值偏差较小,可决系数R-square=0.9863,接近1,模型可信度较高。在已知系统风量和选粉机转速的工况下,选粉机部分分级效率的模型预测曲线与试验曲线基本重合,模型预测效果较好。

关键词: 系统风量, 选粉机转速, 部分分级效率, 曳力系数, 数学模型

Abstract: In this work, the experiment was carried out through the pilot test platform for vertical mill, and the change rule of the classification performance of the classifier under different system air volumes and classifier speeds were compared and analyzed. The cumulative distribution function of the normal distribution was used to correlate the operating parameters of the classifier with the collection probability of particles of different particle sizes. The test data of the system air volume and the speed change condition of the powder separator were used to fit the mean and variance in the model. A mathematical model can be established to quantitatively analyze the relationship between the system air volume, the speed of the separator and the particle classification efficiency. The fitted standard deviation of the verified regression was RMSE=0.0046, the deviation between the predicted value and the true value was small, and the coefficient of determination R-square=0.9863, which was close to 1, the model had higher credibility. Under the conditions of known system air volume and separator speed, the model prediction curve of the classification efficiency of the separator basically coincided with the test curve, and the model prediction effect was good.

Key words: air volume, speed of the separator, classification efficiency, drag coefficient, mathematical model