光学玻璃磨削亚表面损伤预测模型及DOE实验设计
Prediction Model for Subsurface Damage in Grinding of Optical Glass and Doe Experiment Design
杨晓辉 1周凌宇 2刘宁 1孟宪宇3
作者信息
- 1. 长春职业技术学院机电学院,长春 130022
- 2. 纬湃汽车电子(长春)有限公司,长春 130022
- 3. 长春职业技术学院机电学院,长春 130022;纬湃汽车电子(长春)有限公司,长春 130022;长春理工大学机电工程学院,长春 130022
- 折叠
摘要
为了掌握光学玻璃材料杯型砂轮研磨与表面粗糙度(SR)和亚表面损伤(SSD)机理,本文建立BK7 光学玻璃杯型砂轮研磨表面粗糙度的预测模型,通过改变磨削参数来研究对表面粗糙度的影响.设计DOE试验,研究影响SR与SSD的显著性特征因子,并分析了各因子的交互作用.实验结果表明预测模型的可靠性,得到表面粗糙度的预测模型数据与实验数据的平均误差为 5.47%.采用角抛光法,通过电子显微镜观测表面裂纹,并测量裂纹的深度.最后,基于Li的模型,建立基于磨削工艺参数的亚表面损伤的新预测模型.实验结果表明:实验和预测模型结果具有很好的一致性,模型数据与实验数据的平均误差为 6.19%,并且新预测模型结果要优于Li的模型.
Abstract
In order to master the optical glass cup wheel grinding and surface roughness(SR)and subsurface damage(SSD)mechanism,the prediction model for surface roughness of BK7 optical glass in grinding of cup wheel is established,and the influence on the surface roughness is studied by changing the grinding parameters.The DOE experiment is designed to study the significant characteristic factors affecting the SR and SSD,and the interaction among the different factors has been analyzed.The experimental results have shown that the prediction model is reliable,and the average error between the prediction and the experimental results of surface roughness obtained is 5.47%.The surface crack is observed and its depth is measured via electron microscope by using the angle polishing method.Finally,a novel prediction model for subsurface damage by using the grinding parameters is established based on the Li model.The results have shown that the results of experiment model are in a good agreement with those results by using the prediction model,the average error between the predicted and experimental results is 6.19%,and the results via the novel prediction model are better than that via Li model.
关键词
表面粗糙度/亚表面损伤/BK7光学玻璃/预测模型/杯形砂轮磨削/DOE实验设计Key words
surface roughness/subsurface damage/BK7 optical glass/prediction model/cup wheel grinding/DOE experiment design引用本文复制引用
基金项目
国家重点基础研究发展计划(973计划)(2017YFD0701103)
国家自然科学基金(51705189)
吉林省教育厅科研项目(JJKH20241782KJ)
吉林省职业教育与成人教育教学改革项目(2023ZCY294)
吉林省高教科研一般课题(JGJX2022D714)
出版年
2024
国家科技期刊平台
NSTL
万方数据