混凝土布料机输送量影响因素研究
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  • 英文篇名:Research on the Influencing Factors of the Conveying Capacity of Concrete Distributor
  • 作者:周鹏 ; 郭菁菁 ; 李冬 ; 邹德芳
  • 英文作者:ZHOU Peng;GUO Jingjing;LI Dong;ZOU Defang;School of Traffic Engineering,Shenyang Jianzhu University;Department of Science and Technology,Shenyang Jianzhu University;School of Mechanical Engineering,Shenyang Jianzhu University;
  • 关键词:混凝土布料机 ; 螺旋输送量 ; 影响因素 ; 数值仿真
  • 英文关键词:concrete distributor;;conveying capacity of spiral;;influencing factors;;numerical simulation
  • 中文刊名:SYJZ
  • 英文刊名:Journal of Shenyang Jianzhu University(Natural Science)
  • 机构:沈阳建筑大学交通工程学院;沈阳建筑大学科学技术研究院;沈阳建筑大学机械工程学院;
  • 出版日期:2019-07-15
  • 出版单位:沈阳建筑大学学报(自然科学版)
  • 年:2019
  • 期:v.35;No.181
  • 基金:“十三五”国家重点研发计划项目(2017YFC0704003);; 辽宁省自然科学基金指导计划项目(20180551119);; 辽宁省教育厅基金项目(LJZ2017031);; 沈阳建筑大学计划基金项目(2017016)
  • 语种:中文;
  • 页:SYJZ201904019
  • 页数:8
  • CN:04
  • ISSN:21-1578/TU
  • 分类号:153-160
摘要
目的研究混凝土布料机螺旋输送量影响因素,为人工神经网络输送量智能预报模型的输入量确定提供合理依据.方法从混凝土布料机的布料机理出发,推导布料机输送量的计算公式;采用单一变量分析方法,使用MATLAB以及离散元软件进行数值仿真,研究螺旋输送量影响因素对输送量的影响效果.结果随着螺旋叶片直径、填充系数的增加,布料机输送量增加;随着螺旋叶片的摩擦系数、螺旋轴直径增加,布料机输送量减小;螺旋升角与螺旋转速都存在一个最佳值,使得输送量最大;影响因素对输送量的影响灵敏度从大到小为螺旋升角1.32 t/h、螺旋转速1.1 t/h、螺旋叶片直径0.99 t/h、填充系数0.91 t/h、摩擦系数0.59 t/h,螺旋轴直径0.382 t/h.结论影响因素中的螺旋叶片直径、螺旋升角、螺旋转速、填充系数及摩擦系数更适合作为神经网络输送量智能预报模型的输入量.
        The influencing factors of screw conveying capacity of concrete distributor are investigated to provide the basis for the determine the input layer of artificial neural network model for prediction the conveying capacity.The distribution mechanism of the concrete distributor and the formula for calculating the conveying capacity of the distributor were derived,and the single variable analysis method was used to study effect of the influence factors on the conveying capacity by simulation with MATLAB and discrete element software.The results showed that the conveying capacity was increased with the increasing of screw blade diameter and filling coefficient,and decreased with increasing the friction coefficient and screw shaft diameter increase.There is an optimal value for spiral lift angle and spiral speed to maximize the conveying capacity.The sensitivity of influence factors to conveying capacity from large to small is spiral lift angle(1.32 t/h),screw blade diameter(0.99 t/h),filling coefficient(0.91 t/h),friction coefficient(0.59 t/h),screw shaft diameter(0.382 t/h).The screw blade diameter,spiral lift angle,screw spiral speed,filling coefficient and friction coefficient are the main influencing factors of the conveying capacity,which can be used as the input of the neural network intelligent prediction model.
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