摘要
针对固结磨料研磨石英晶片材料去除率难以预测的问题,提出一种基于接触力学和广义回归神经网络(GRNN)的石英晶片材料去除率模型。首先根据脆/塑材料去除机理、磨粒块与晶片微观接触简化形式,采用微积分、力平衡原理等方法,建立了理想情况下的材料去除率模型。然后采用微单元法,进行了三因素四水平正交试验,并通过GRNN分析研磨液流量、研磨液浓度、研磨盘转速与材料去除率修正系数的映射关系,进一步完善了材料去除率模型。最后为验证材料去除率模型,设定研磨盘转速为20 r/min,研磨液浓度为5 wt.%,研磨液流量为36 ml/min,仿真并测量不同研磨压强以及相对速度下,晶片材料去除率预测值与实际值。结果表明:研磨压强和相对速度的增加使晶片材料去除加快,材料去除率模型预测值与实际值变化趋势相同,模型误差为8.57%。材料去除率模型基本满足固结磨料研磨工艺中石英晶片材料去除率预测需求。
The material removal rate of a quartz wafer by fixed abrasive lapping is difficult to predict;therefore,a model of the material removal rate based on contact mechanics and a generalized regression neural network(GRNN)is proposed.First,according to the ductile–brittle material removal mechanism and the simplified form of micro-contact between the abrasive block and wafer,an ideal material removal rate model was established by using calculus and the force balance principle.Then,a three-factor four-lev⁃el orthogonal test was performed using the microelement method.The mapping relationship of the lapping fluid flow,lapping fluid concentration,lapping disk speed,and material removal rate correction coefficient was analyzed using the GRNN.The material removal rate model was further improved.Finally,to vali⁃date the material removal rate model,a lapping experiment was conducted.The lapping disk speed was set to 20 r/min,lapping fluid concentration to 5 wt.%,and lapping fluid flow rate to 36 ml/min.The predicted and actual values of the wafer material removal rate were simulated and measured under different lapping pressures and relative velocities.It was found that the increase in lapping pressure and relative ve⁃locity accelerates the removal of the wafer material.The predicted value of the material removal rate mod⁃el exhibited the same trend as the actual value,and the error of model was 8.57%.The material removal rate model meets the demand for predicting the material removal rate of quartz wafers in fixed abrasive lap⁃ping.
作者
贾玙璠
朱祥龙
杨垒
康仁科
董志刚
JIA Yufan;ZHU Xianglong;YANG Lei;KANG Renke;DONG Zhigang(State Key Laboratory of High-Performance Precision Manufacturing,Dalian University of Technology,Dalian 116024,China)
出处
《光学精密工程》
EI
CAS
CSCD
北大核心
2023年第16期2362-2371,共10页
Optics and Precision Engineering
基金
国家自然科学基金资助项目(No.U22A20198)。
关键词
固结磨料研磨
石英晶片
材料去除率
广义回归神经网络
fixed abrasive lapping
quartz wafer
material removal rate
generalized regression neural
