硬脆性材料用柔性磨具研磨的加工表面粗糙度建模

doi:10.3969/j.issn.1004-132X.2022.07.010

中国机械工程 ›› 2022, Vol. 33 ›› Issue (07): 834-841.DOI: 10.3969/j.issn.1004-132X.2022.07.010

硬脆性材料用柔性磨具研磨的加工表面粗糙度建模

章玉强1,2;胡中伟1,2;朱泽朋1,2;崔长彩1,2;陈铭欣3;谢斌晖3;李瑞萍3

1.华侨大学制造工程研究院，厦门，361021
2.脆性材料产品智能制造国家地方联合工程中心，厦门，361021
3.福建晶安光电有限公司，泉州，362411

出版日期:2022-04-10 发布日期:2022-05-04
通讯作者: 胡中伟（通信作者），男，1979年生，副教授。研究方向为硬脆性材料精密磨削/研磨加工机理与工艺。E-mail:huzhongwei@hqu.edu.cn。
作者简介:章玉强，男，1995年生，硕士研究生。研究方向为硬脆性材料精密磨削/研磨加工机理与工艺。
基金资助:
国家自然科学基金（U1805251,51675192）;
福建省区域发展项目（2019H4014）

Surface Roughness Modeling for Lapping Hard and Brittle Materials by Flexible Abrasive Tools

ZHANG Yuqiang1,2 ;HU Zhongwei1,2;ZHU Zepeng1,2;CUI Changcai1,2;CHEN Mingxin3;XIE Binhui3;LI Ruiping3#br#

1.Institute of Manufacturing Engineering,Huaqiao University,Xiamen,Fujian,361021
2.National Engineering Research Center for the Intelligent Manufacturing Technology of Brittle Materials and Products,Xiamen,Fujian,361021
3.Fujian JingAn Opto. Electronics Co.,Ltd.,Quanzhou,Fujian,362411

Online:2022-04-10 Published:2022-05-04

摘要/Abstract

摘要： 通过分析磨粒与工件表面的作用过程，建立了硬脆性材料柔性磨具加工表面粗糙度的理论预测模型。以橡胶结合剂金刚石研磨盘为柔性磨具、蓝宝石衬底为工件，在不同弹性模量、磨粒浓度、磨粒粒度和研磨压力下开展研磨试验，将不同研磨条件下的表面粗糙度试验值与理论预测值进行比较，发现试验结果与理论模型预测结果的趋势一致，且预测误差为7.71%~10.1%，验证了所建立理论模型的可靠性。

关键词: 研磨, 表面粗糙度, 柔性磨具, 蓝宝石衬底

Abstract: By analyzing the interaction processes between abrasive particles and the surface of the workpiece, a theoretical prediction model for surface roughness of the hard and brittle materials by flexible abrasive tool was established herein. The rubber bond diamond lapping disc was selected as the flexible abrasive tool, and the sapphire substrate was selected as the workpiece. The lapping experiments were carried out under different elastic modulus, abrasive particle concentration, abrasive particle size, and different lapping pressures. And then, the experimental values of the surface roughness were compared with the theoretical predicted values under different lapping conditions, which shows that the experimental values are consistent with the predicted results of the theoretical model. The prediction errors are as 6.32%~11.76%, which proves that the established theoretical prediction model of surface roughness is reliable for lapping hard and brittle materials by flexible abrasive tools.

Key words: lapping, surface roughness, flexible abrasive tool, sapphire substrate

中图分类号:

TH16

章玉强, 胡中伟, 朱泽朋, 崔长彩, 陈铭欣, 谢斌晖, 李瑞萍. 硬脆性材料用柔性磨具研磨的加工表面粗糙度建模[J]. 中国机械工程, 2022, 33(07): 834-841.

ZHANG Yuqiang, , HU Zhongwei, ZHU Zepeng, CUI Changcai, CHEN Mingxin, XIE Binhui, LI Ruiping. Surface Roughness Modeling for Lapping Hard and Brittle Materials by Flexible Abrasive Tools[J]. China Mechanical Engineering, 2022, 33(07): 834-841.

参考文献

［1］PISHCHIK V , LYTVYNOV L A, DOBROVINSKAYA E R. Sapphire［M］. Boston:Springer, 2009:01-493.
［2］王增泽. 碳化硅材料特性及其应用浅析［J］. 新材料产业，2018(1)：47-51.
WANG Zengze. Analysis of the Characteristics and Application of Silicon Carbide Materials［J］. New Materials Industry, 2018(1):47-51.
［3］考政晓，叶大千，于璇，等. 蓝宝石衬底材料的研究及应用进展［J］. 人工晶体学报，2018，47(1)：102-107.
KAO Zhengxiao, YE Daqian, YU Xuan, et al. Research and Application Progress of Sapphire Substrate Materials［J］. Journal of Synthetic Crystals, 2018, 47(1):102-107.
［4］NAKASUJI T, KODER S, HARA S, et al. Diamond Turning of Brittle Materials for Optical Components［J］. CIRP Annals—Manufacturing Technology, 1990, 39(1):89-92.
［5］王慧敏. 固结磨料研磨硬脆材料表面粗糙度模型［D］. 南京：南京航空航天大学，2015.
WANG Huimin. Surface Roughness Model for Lapping Hard and Brittle Materials with Fixed Abrasives［D］. Nanjing:Nanjing University of Aeronautics and Astronautics, 2015.
［6］詹昕，姚奔，金诚，等. 一种基于主成分回归的线损率成因分析方法研究［J］. 机电信息，2020(18)：130-131.
ZHAN Xin, YAO Ben, JIN Cheng, et al. A Study on the Cause Analysis Method of Line Loss Rate Based on Principal Component Regression［J］. Electromechanical Information, 2020(18):130-131.
［7］甄婷婷，王盛，王映，等. 单向碳纤维复合材料平面磨削粗糙度模型研究［J］. 机械设计， 2019，36(S1)：125-128.
ZHEN Tingting, WANG Sheng, WANG Ying, et al. Research on Surface Lapping Roughness Model of Unidirectional Carbon Fiber Composites［J］. Machine Design, 2019, 36(S1):125-128.
［8］TIAN Xinli, WANG Jianquan, ZHANG Baoguo, et al. Research on Predicting Model of Surface Roughness for Ground Engineering Ceramics［J］. Advanced Materials Research, 2012, 1672:1036-1040.
［9］JOSHI K, PATIL B. Prediction of Surface Roughness by Machine Vision Using Principal Components Based Regression Analysis［J］. Procedia Computer Science, 2020, 167：382-391.
［10］SHAO Yamin, LI Beizhi, LIANG S Y. Predictive Modeling of Surface Roughness in Lapping of Ceramics［J］. Machining Science and Technology, 2015, 19(2):325-338.
［11］WU Chongjun, LI Beizhi, LIU Yao, et al. Surface Roughness Modeling for Lapping of Silicon Carbide Ceramics Considering Co-existence of Brittleness and Ductility［J］. International Journal of Mechanical Sciences, 2017, 133:167-177.
［12］WU Jun, CHENG Jun, GAO Chunchun, et al. Research on Predicting Model of Surface Roughness in Small-scale Lapping of Brittle Materials Considering Lapping Tool Topography［J］. International Journal of Mechanical Sciences, 2020, 166:105263.
［13］NGUYEN D, YIN Shaohui, TANG Qingchun, et al. Online Monitoring of Surface Roughness and Lapping Wheel Wear When Lapping Ti-6Al-4V Titanium Alloy Using ANFIS-GPR Hybrid Algorithm and Taguchi Analysis［J］. Precision Engineering, 2018, 55:275-292.
［14］GOPAN V, LEO DEV WINS K, SURENDRAN A. Integrated ANN-GA Approach for Predictive Modeling and Optimization of Lapping Parameters with Surface Roughness as the Response［J］. Materials Today:Proceedings, 2018, 5(5):12133-12141.
［15］SIZEMORE N E, NOGUEIRA M L, GREIS N P, et al. Application of Machine Learning to the Prediction of Surface Roughness in Diamond Machining［J］. Procedia Manufacturing, 2020, 48：1029-1040.
［16］凌顺志，墨洪磊，汪忠喜，等. 磨料尺寸对固结金刚石聚集体磨料垫研磨石英玻璃加工性能的影响［J］. 金刚石与磨料磨具工程， 2017，37(5)：12-18.
LING Shunzhi, MO Honglei, WANG Zhongxi, et al. The Influence of Abrasive Size on the Processing Performance of Cemented Diamond Aggregate Abrasive Pad for Lapping Quartz Glass［J］. Diamond and Abrasive Engineering, 2017, 37(5):12-18.
［17］李军，王慧敏，王文泽，等. 固结磨料研磨K9玻璃表面粗糙度模型［J］. 机械工程学报，2015，51(21)：199-205.
LI Jun, WANG Huimin, WANG Wenze, et al. Surface Roughness Model of K9 Glass Polished by Fixed Abrasives［J］. Journal of Mechanical Engineering, 2015, 51(21):199-205.
［18］何玉辉，万荣桥，周剑杰，等. 轴向超声振动磨削硬脆性材料表面粗糙度建模研究［J］. 振动与冲击，2017，36(23)：194-200.
HE Yuhui, WAN Rongqiao, ZHOU Jianjie, et al. Research on Surface Roughness Modeling of Hard and Brittle Materials in Axial Ultrasonic Vibration Grinding［J］. Vibration and Shock, 2017, 36(23):194-200.
［19］罗睿，许黎明，查体建，等. 球面磨削表面粗糙度的仿真研究［J］. 上海交通大学学报，2013，47(5)：709-714.
LUO Rui, XU Liming, ZHA Tijian, et al. Simulation Study of Spherical Grinding Surface Roughness［J］. Journal of Shanghai Jiaotong University, 2013, 47(5):709-714.
［20］YOUNIS M A, ALAWI H. Probabilistic Analysis of the Surface Grinding Process ［J］. Transactions of the Canadian Society for Mechanical Engineering, 1984, 8(4):208-213.
［21］BULSARA V H, AHN Y, CHANDRASEHAR S, et al. Mechanics of Polishing［J］. Journal of Applied Mechanics, 1998, 65(2):410-416.
［22］TROMAS C, GIRARD J C, AUDURIER V, et al. Study of the Low Stress Plasticity in Single-crystal MgO by Nanoindentation and Atomic Force Microscopy［J］. Journal of Materials Science, 1999, 34(21):5537-5342.
［23］ZHANG Zhenzhong, YAO Peng, WANG Jun, et al. Analytical Modeling of Surface Roughness in Precision Lapping of Particle Reinforced Metal Matrix Composites Considering Nanomechanical Response of Material［J］. International Journal of Mechanical Sciences, 2019, 157/158:243-253.

[1]	马廉洁, 李红双. 脆性材料机械加工表面粗糙度模型的研究进展[J]. 中国机械工程, 2022, 33(07): 757-768.
[2]	张晓博, 朱栋. 长窄型薄壁叶片的套料电解加工[J]. 中国机械工程, 2022, 33(07): 797-803，810.
[3]	雷勇, 赵威, 何宁, 李亮. TC17钛合金低温铣削表面粗糙度预测[J]. 中国机械工程, 2022, 33(05): 583-588.
[4]	李聪波, 龙云, 崔佳斌, 赵希坤, 赵德. 基于多源异构数据的数控铣削表面粗糙度预测方法[J]. 中国机械工程, 2022, 33(03): 318-328.
[5]	时强胜, 张小俭, 陈巍, 杨泽源, 严思杰, . 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[J]. 中国机械工程, 2021, 32(24): 2967-2974.
[6]	侯想, 刘熠新, 钟梦洁, 林赛, 刘杨, 罗荣煌, 罗学涛, 张飒, . 图形化蓝宝石衬底干法刻蚀工艺研究[J]. 中国机械工程, 2021, 32(24): 3001-3007.
[7]	何庆顺, 何春雷, 陈光, 刘伟峰, 邓晓帆, 任成祖. 双盘直槽研磨圆柱滚子稳定自转条件分析与试验[J]. 中国机械工程, 2021, 32(21): 2625-2634.
[8]	易怀安, 赵欣佳, 唐乐, 陈永伦. 基于彩色图像奇异值熵指标的磨削表面粗糙度视觉测量方法[J]. 中国机械工程, 2021, 32(13): 1577-1583.
[9]	董晓星, 鲁聪达, 金明生, 文东辉, 计时鸣, 王礼明, , 朱栋杰, . 梯度功能研抛盘力学模型与材料均匀去除试验[J]. 中国机械工程, 2021, 32(13): 1600-1607.
[10]	刘念聪, 吴圣红, 谢京良, 杨程文, 刘保林, 蒋浩, 陈云. 车削奥氏体不锈钢时冷却参数对刀具振动和表面粗糙度的影响[J]. 中国机械工程, 2021, 32(11): 1321-1329.
[11]	尹龙, 赵波, 郭星晨, 赵重阳. 超声辅助内圆磨削40Cr15Mo2VN轴承套圈的试验研究#br#[J]. 中国机械工程, 2021, 32(10): 1172-1180.
[12]	林志树1,2;黄辉2. 多线往复摇摆线锯切割水晶玻璃的试验研究[J]. 中国机械工程, 2021, 32(02): 132-140.
[13]	陈景强1;马廉洁1,2;孟博1;周云光2. 氟金云母表面形成机理及表面粗糙度理论模型[J]. 中国机械工程, 2020, 31(24): 2918-2923.
[14]	罗戈山;邹莱;黄云;龚明旺. 氧化铝空心球砂带磨削钛合金的材料去除及表面质量研究[J]. 中国机械工程, 2020, 31(19): 2363-2370.
[15]	原路生, 赵波, 王毅, 赵重阳. 椭圆振动辅助车削7075铝合金表面微织构及其特性[J]. 中国机械工程, 2020, 31(15): 1831-1838.

硬脆性材料用柔性磨具研磨的加工表面粗糙度建模

Surface Roughness Modeling for Lapping Hard and Brittle Materials by Flexible Abrasive Tools

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics