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清华大学学报(自然科学版)  2017, Vol. 57 Issue (3): 324-330    DOI: 10.16511/j.cnki.qhdxxb.2017.26.017
  机械工程 本期目录 | 过刊浏览 | 高级检索 |
面向机器人喷涂的多变量涂层厚度分布模型
王国磊1, 伊强1, 缪东晶1, 陈恳1, 王力强2
1. 清华大学 机械工程系, 北京 100084;
2. 成都飞机工业(集团)有限责任公司, 成都 610091
Multivariable coating thickness distribution model for robotic spray painting
WANG Guolei1, YI Qiang1, MIAO Dongjing1, CHEN Ken1, WANG Liqiang2
1. Department of Mechanical Engineering, Tsinghua University, Beijing 100084, China;
2. Chengdu Aircraft Industrial(Group) Co., Ltd., Chengdu 610091, China
全文: PDF(1408 KB)  
输出: BibTeX | EndNote (RIS)      
摘要 为了解决传统机器人喷涂模型在喷涂工艺参数改变时会失效的问题,该文将喷涂工艺参数作为模型变量,研究多变量喷涂模型的建模方法。首先,提出了一种基于β分布的涂层生长速率函数,并通过对其进行积分推导出涂层厚度分布方程;其次,通过分析、拟合喷涂实验数据,分别建立喷枪流量、喷涂距离与涂层生长率最大值的关系式,以及喷枪流量、空气压力与喷幅宽度的关系式,并将其代入到涂层厚度分布方程中,建立了以5种常变喷涂工艺参数为自变量的涂层厚度分布泛化模型;最后,通过实验对模型进行验证。结果表明:该模型能够根据工艺参数的变化预测相应的涂层厚度分布,且平均预测误差小于4.3%。
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王国磊
伊强
缪东晶
陈恳
王力强
关键词 工业机器人机器人喷涂涂层生长速率涂层厚度分布可变喷涂参数多变量模型    
Abstract:A multivariable robotic spray painting model was developed for a range of painting parameters to improve the restricted traditional model. A β distribution based coating growth rate function was used with a coating thickness distribution formula then deduced from the integral of the growth rate function. The maximum coating growth rate was related to the paint flow rate and painting distance with the paint flow rate related to the painting air pressure and painting width from experimental data. Then, a generalized coating thickness distribution model was developed with five painting parameters as independent variables by substituting these relations into the coating thickness distribution equations. The model was validated through experiments with the results showing that it can predict the coating thickness distribution for various painting parameters with an average forecasting error of less than 4.3%.
Key wordsindustrial robot    robotic spray painting    coating growth rate    coating thickness distribution    variable painting parameter    multivariable model
收稿日期: 2016-12-13      出版日期: 2017-03-15
ZTFLH:  TP242.2  
通讯作者: 陈恳,教授,E-mail:kenchen@tsinghua.edu.cn     E-mail: kenchen@tsinghua.edu.cn
引用本文:   
王国磊, 伊强, 缪东晶, 陈恳, 王力强. 面向机器人喷涂的多变量涂层厚度分布模型[J]. 清华大学学报(自然科学版), 2017, 57(3): 324-330.
WANG Guolei, YI Qiang, MIAO Dongjing, CHEN Ken, WANG Liqiang. Multivariable coating thickness distribution model for robotic spray painting. Journal of Tsinghua University(Science and Technology), 2017, 57(3): 324-330.
链接本文:  
http://jst.tsinghuajournals.com/CN/10.16511/j.cnki.qhdxxb.2017.26.017  或          http://jst.tsinghuajournals.com/CN/Y2017/V57/I3/324
  表1 影响涂层厚度分布的因素
  图1 喷涂实验
  图2 喷涂实验照片
  图3 涂层生长速率分布
  图4 X向雾锥角预测曲线与实测数据
  图5 Y向雾锥角预测曲线与实测数据
  图6 上漆率与喷涂距离关系
  表2 实验参数取值及测量数据点
  图7 K'与E的关系
  图8 预测涂层厚度分布与实测数据对比
  表3 实验参数取值及测量数据点
  表4 模型预测结果与实测数据对比
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