China Mechanical Engineering ›› 2021, Vol. 32 ›› Issue (24): 2967-2974.DOI: 10.3969/j.issn.1004-132X.2021.24.009

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Prediction of Surface Roughness of Rubber Soft Die End Face Polishing Based on GRA-RSM

SHI Qiangsheng1,2;ZHANG Xiaojian1,2;CHEN Wei3;YANG Zeyuan1,2;YAN Sijie1,2   

  1. 1.School of Mechanical Science and Engineering,Huazhong University of Science and Technology,Wuhan,430074
    2.State Key Laboratory of Digital Manufacturing Equipment and Technology,Wuhan,430074
    3.Wuxi CRRC Times Intelligent Equipment Co.,Ltd.,Wuxi,Jiangsu,214174
  • Online:2021-12-25 Published:2022-01-11

基于灰色关联度分析响应面法的橡胶软模端面抛磨表面粗糙度预测

时强胜1,2;张小俭1,2;陈巍3;杨泽源1,2;严思杰1,2   

  1. 1.华中科技大学机械科学与工程学院,武汉,430074
    2.数字制造装备与技术国家重点实验室,武汉,430074
    3. 无锡中车时代智能装备有限公司,无锡,214174
  • 通讯作者: 张小俭(通信作者),男,1982年生,副教授。研究方向为数控加工过程动力学建模、过程稳定性分析和加工工艺参数优化。E-mail:xjzhang@hust.edu.cn。
  • 作者简介:时强胜,男,1997年生,硕士研究生。研究方向为机器人磨抛技术、有限元仿真技术。
  • 基金资助:
    国家自然科学基金(51775211);
    国家重点研发计划(2019YFB1707404)

Abstract: In order to solve the problems of uneven fitting clearance between rib strip and skin on the composite reinforced siding plates, a rubber soft die should be pasted on the surface of rigid die. The rubber soft die should be polished to eliminate fitting clearance. However, if polishing parameters were not proper, the surface of rubber soft mold was easy to get hairy, and the roughness value was too large, which was easy to absorb polishing dusts. Aiming at the above problems, a set of robot-based polishing and dust removal system was built for end face polishing of rubber materials. The influences of polishing parameters, such as abrasive particle size, polishing rotation speed, polishing pressure and edging distance on the surface roughness were explored. A method was proposed to predict the surface roughness of rubber polishing by robot based on GRA-RSM, which might be used to establish the prediction model of roughness(Ra) of the rubber materials after polishing. The fitting coefficient R2 value of the model is as 0.9878, which indicates that the model fits well. The root mean square error between the predicted value of Ra calculated by the model and the observed value is as 0.014 47, which verify the validity of the prediction model. Based on the prediction model, the parameter combination with the minimum roughness Ra value(3.3 μm) is obtained(polishing rataion speed 4158.9 r/min, polishing pressure 38.4 N, and edging distance 30 mm).

Key words: grey relational analysis(GRA), response surface methodology(RSM), end face polishing, surface roughness, rubber mold

摘要: 为解决复合材料加筋壁板上筋条与蒙皮配合间隙不均匀的问题,需在刚模表面上粘贴橡胶软模,并通过抛磨橡胶软模来消除配合间隙,然而,若打磨参数选择不当,则橡胶软模表面易起毛,致使粗糙度值过大,易吸附磨屑粉尘。针对上述问题,搭建了一套基于机器人的橡胶材料除尘端面打磨系统,探究了磨粒粒度、磨头转速、打磨压力、离边距离等打磨参数对表面粗糙度的影响规律。提出一种基于灰色关联度分析响应面法的机器人橡胶垫抛磨表面粗糙度预测方法,建立了橡胶材料打磨后粗糙度Ra值的预测模型,该模型的拟合系数R2值为0.9878,表明模型拟合效果好。使用该模型计算出的Ra预测值与观测值的均方根误差为0.014 47,验证了模型预测的有效性。基于预测模型,获得粗糙度Ra值最小(3.3 μm)的参数组合为:磨头转速4158.9 r/min、抛磨压力38.4 N、离边距离30 mm。

关键词: 灰色关联度分析, 响应面法, 端面抛磨, 表面粗糙度, 橡胶软模

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