光学玻璃磨削亚表面损伤预测模型及DOE实验设计

杨晓辉; 周凌宇; 刘宁; 孟宪宇

doi:10.13433/j.cnki.1003-8728.20220242

光学玻璃磨削亚表面损伤预测模型及DOE实验设计

doi: 10.13433/j.cnki.1003-8728.20220242

杨晓辉^1,,
周凌宇²,
刘宁¹,
孟宪宇^{1, 2, 3, ,}

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.
长春理工大学机电工程学院，长春　130022

基金项目: 国家973重点基础研究发展计划（2017YFD0701103）、国家自然科学基金项目（51705189）、吉林省教育厅科学研究项目（JJKH20241782KJ）、吉林省职业教育与成人教育教学改革项目（2023ZCY294）及吉林省高教科研一般课题（JGJX2022D714）

详细信息

作者简介:
杨晓辉，副教授，451842973@qq.com

通讯作者:
孟宪宇，副教授，博士，54262932@qq.com

中图分类号: TG58; TQ164
计量
- 文章访问数: 26
- HTML全文浏览量: 9
- PDF下载量: 1
- 被引次数: 0
出版历程
- 收稿日期: 2020-08-27
- 刊出日期: 2024-03-25

Prediction Model for Subsurface Damage in Grinding of Optical Glass and Doe Experiment Design

YANG Xiaohui^1
,,
ZHOU Lingyu²,
LIU Ning¹,
MENG Xianyu^{1, 2, 3
, ,}

1.
College of Electrical and Mechanical, Changchun Vocational Institute of Technology, Changchun 130022, China
2.
Vitesco Technologies Electronics (Changchun) Co., Ltd., Changchun 130022, China
3.
Changchun University Of Science And Technology, Changchun 130022, China

摘要

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。
- 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
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.
- surface roughness /
- subsurface damage /
- BK7 optical glass /
- prediction model /
- cup wheel grinding /
- DOE experiment design

HTML全文

图 1 亚表面损伤模型

Figure 1. Subsurface damage model

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图 2 样品及实验设备准备

Figure 2. Preparation of samples and experimental equipment

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图 3 实验流程图

Figure 3. Experimental flow chart

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图 4 角抛光法测量SSD

Figure 4. Angle polishing method to measure SSD

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图 5 不同抛光深度的BK7表面形貌

Figure 5. BK7 surface topography with different polishing depths

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图 6 SR和SSD与切削工艺参数的Pareto图

Figure 6. Pareto plot of SR and SSD versus cutting process parameters

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图 7 SR和SSD DOE实验分析结果

Figure 7. Experimental analysis results of SRSSD DOE

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图 8 SSD的测量值与预测值的对比

Figure 8. Comparison of measured and predicted SSD

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表 1 BK7玻璃的性能参数表

Table 1. Performance parameters of BK7 glass

α/（°）	E/GPa	H/GPa	K_c/（${\mathrm{MPa}} \cdot {\mathrm{m}}^{\tfrac 1 2} $）	M	β_k
46 ~ 62	85	7.7	0.82	0.33	0.027

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表 2 磨削的工艺参数及等级

Table 2. Process parameters and grades of grinding

参数	1级	2级	3级	4级
切削速度/（m·s⁻¹）	15	20	25	30
进给速度/（mm·r⁻¹）	0.005	0.01	0.015	0.02
切削深度/μm	20	40	80	100
转盘速度/（r·min⁻¹）	100	200	300	500

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表 3 正交试验表

Table 3. Orthogonal tests

编号	v/ （m·s⁻¹）	f /（mm·r⁻¹）	a_e/μm	n/（r·min⁻¹）	SR/μm
1	15	0.005	100	500	14.36
2	15	0.005	100	100	19.23
3	30	0.005	100	100	21.73
4	15	0.02	100	500	15.71
5	30	0.005	20	100	21.44
6	30	0.005	20	500	35.49
7	30	0.02	20	100	32.58
8	15	0.005	20	500	21.37
9	30	0.02	20	500	41.22
10	30	0.02	100	100	42.67
11	15	0.02	20	500	26.11
12	15	0.005	20	100	12.15
13	15	0.02	100	100	22.14
14	30	0.02	100	500	34.18
15	30	0.005	100	500	72.35
16	15	0.02	20	100	45.56

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表 4 SR预测模型验证实验参数及结果

Table 4. Experimental parameters and results of SR prediction model validation

编号	切削速度/ （m·s⁻¹）	进给速度/ （mm·r⁻¹）	切削深度/ μm	转盘转速/ （r·min⁻¹）	SR/μm	SR预测模型/μm	SR误差/%	SSD/μm
1	35	0.010	40	200	6.33	6.93	8.66	50.45
2	5	0.010	40	100	10.23	11.47	10.81	70.68
3	5	0.010	20	200	9.86	10.48	5.91	57.38
4	35	0.010	20	100	5.98	6.34	5.67	36.71
5	35	0.005	20	200	5.87	6.21	5.47	37.15
6	5	0.005	20	100	11.34	11.08	2.35	92.87
7	35	0.005	40	100	8.91	9.63	7.48	65.31
8	5	0.005	40	200	13.53	13.82	2.1	108.91

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