单磨粒金刚石微切削碳化硅晶体仿真与实验研究

杨宇飞; 李翔; 何艳; 刘铭; 徐子成; 高兴军

doi:10.13394/j.cnki.jgszz.2023.0158

单磨粒金刚石微切削碳化硅晶体仿真与实验研究

doi: 10.13394/j.cnki.jgszz.2023.0158

辽宁石油化工大学机械工程学院, 辽宁抚顺 113001

基金项目: 辽宁省博士科研启动基金计划项目（2022-BS-292）；辽宁省教育厅科学技术研究项目（LJKZ0383）；辽宁石油化工大学引进人才科研启动基金（2020XJJL-012）；省级大学生创新创业训练计划项目（S202310148031）。

详细信息

通讯作者:
高兴军，男，1979年生，硕士、副教授。主要研究方向：精密磨削、纳米制造。E-mail：gaoxingjun@lnpu.edu.cn

中图分类号: TG74; TG58
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出版历程
- 收稿日期: 2023-08-03
- 修回日期: 2023-10-12
- 录用日期: 2023-11-07
- 网络出版日期: 2023-11-07
- 刊出日期: 2024-08-20

Simulation and experimental study on micro-cutting silicon carbide crystal with single grain diamond

School of Mechanical Engineering, Liaoning Petrochemical University, Fushun 113001, Liaoning, China

摘要

摘要: 采用有限元软件Abaqus建立金刚石锥形磨粒微切削碳化硅晶体的模型，通过预仿真模型确定切削深度和切削速度的选择范围，分析影响切削力的主、次要因素，研究单一切削参数对碳化硅晶体切削效果的影响；并借助赫兹接触理论，验证加载力对摩擦力、切削边缘形貌、切削深度的影响。结果表明：切削深度是影响切削力的显著因素，预仿真模型确定的切削深度不超过1.50 μm；碳化硅晶体切削的最优方案为切削深度取0.50 μm、切削速度取76 m/s、磨料切削刃角度取60°。通过控制切削深度可以提高切削稳定性，且在保证切削质量的前提下适当提高切削速度可以提高切削效率。金刚石探针压入晶体的深度与摩擦系数、摩擦力和切削力呈正相关，获得的碳化硅晶体切削边缘的三维轮廓相对平整、光滑。
- 碳化硅晶体 /
- 金刚石磨粒 /
- 金刚石探针 /
- 切削力 /
- 切削边缘质量
Abstract: Objectives The hardness of silicon carbide is second only to those of diamond, cubic boron nitride, and boron carbide, making its processing very difficult. Compared with plastic metal materials, the brittle and hard nature of silicon carbide makes it prone to brittle fracture and edge fragmentation during processing, greatly affecting its superior performance. Therefore, it is crucial to carefully select appropriate cutting methods and establish reasonable cutting process conditions. Methods The finite element software Abaqus was used to establish a model of micro-cutting silicon carbide crystal with a diamond conical grain, and the selection range of micro-cutting depth and speed was determined by the pre-simulation model. Then, the main and secondary factors affecting the cutting force were analyzed, and the influence of a single cutting parameter on the cutting effect was studied. In addition, with the help of Hertzian contact stress, the influence of the loading force on the friction force, the morphology of the cutting edge, and the cutting depth was verified by the tip scratching experiment. Results (1) The cutting depth is a crucial factor that greatly impacts the quality of the cutting process. When the cutting depth is less than 1.50 μm, the removal of silicon carbide material primarily occurs through plastic removal. However, when the cutting depth exceeds 1.50 μm, cracks of varying lengths and pits of different sizes gradually form at the cutting edge of the workpiece. As the cutting depth increases, the length of cracks and the number of pits also increase. This type of removal is known as brittle removal. To ensure the integrity of the cutting edge and minimize damage to the silicon carbide workpiece, it is essential to control the cutting depth of the abrasive particles during stages I and III, keeping it below 1.50 μm. (2) Through variance and range analysis of the main cutting force, the relationship between the three factors and the magnitude of the main cutting force is V > W > U, meaning that cutting depth is the most important factor affecting cutting force. The optimal solution V₁W₁U₂ and cutting parameters have been determined, namely a diamond abrasive cutting depth of 0.50 μm, a diamond abrasive cutting edge angle of 60°, and a cutting speed of 76 m/s. Cutting depth is the main factor affecting the magnitude of cutting force, while cutting speed and cutting edge angle are secondary factors. (3) As the cutting depth increases, the affected area surrounding the cut also expands, causing an increase in equivalent stress even in areas where the abrasive particles do not come into contact with the workpiece. This phenomenon is responsible for the development of cutting edge cracks and pits. Additionally, as the cutting depth increases, the main cutting force experiences greater fluctuations. To maintain cutting stability, it is important to control the cutting depth. In the high-speed cutting range of 60-106 m/s, the impact of cutting speed on cutting force is minimal. Therefore, increasing the cutting speed can be an effective method for improving cutting efficiency and ensuring high-quality cuts. For optimal results, a cutting depth of 0.50 μm and a cutting speed of 76 m/s are recommended. (4) The coefficient of friction is not only affected by the properties of the two materials in contact, but also by the depth of the diamond probe pressing into the workpiece. The greater the depth of pressing, the higher the coefficient of friction and the greater the frictional force. The surface of the microgrooves is clear and tidy, with relatively smooth edges. Under the same Hertz contact stress, the simulated depth values and experimental depth values show a consistent trend with the change in loading force. Conclusions Finite element simulation has become a valuable tool for studying the interaction and removal of materials in the precision machining of crystal materials. The purpose of this article is to investigate the removal characteristics of silicon carbide and determine the optimal range of cutting parameters. The study analyzes cutting force, stress distribution, and removal mechanisms, and proposes effective methods for enhancing cutting efficiency. The findings of this research can contribute to improving the smoothness of the cutting edge and reducing subsurface damage to the workpiece. Furthermore, this research has significant implications for understanding the impact of process parameters on cutting accuracy and the removal mechanism of hard and brittle materials during cutting.
- silicon carbide crystal /
- diamond grain /
- diamond tip /
- cutting force /
- cutting edge quality

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图 1 单颗磨粒运动轨迹示意图

Figure 1. Schematic diagram of movement track of single grain diamond in ultra-thin grinding wheel

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图 2 磨粒切削工件运动轨迹示意图

Figure 2. Schematic diagram of diamond grain cutting workpiece

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图 3 预仿真模型

Figure 3. Pre-simulation model

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图 4 3种不同锥角磨粒的模型

Figure 4. Three models of grains with different cone angles

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图 5 单磨粒金刚石切削碳化硅工件仿真模型

Figure 5. Simulation model of single grain diamond cutting silicon carbide workpiece

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图 6 碳化硅工件的状态云图

Figure 6. State nephogram of silicon carbide workpiece

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图 7 不同切削速度切削碳化硅工件的状态云图

Figure 7. State nephograms of cutting silicon carbide workpiece at different cutting speeds

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图 8 不同切削速度下的最大切缝宽度和最大切缝深度

Figure 8. Maximum slit width W_max and maximum slit depth H_max at different cutting speeds

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图 9 不同切削参数组合下碳化硅工件应力云图

Figure 9. Stress nephograms of silicon carbide workpiece with different combinations of cutting parameters

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图 10 不同切削深度切削碳化硅工件的应力云图

Figure 10. Stress nephograms of silicon carbide workpiece with different cutting depth

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图 11 不同切削深度下的切削力

Figure 11. Cutting forces with different cutting depths

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图 12 不同切削速度切削碳化硅工件的应力云图

Figure 12. Stress nephograms of silicon carbide workpiece with different cutting speeds

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图 13 不同切削速度下的切削力

Figure 13. Cutting forces with different cutting speeds

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图 14 金刚石探针划擦碳化硅工件原理

Figure 14. Schematic diagram of diamond tip scratching silicon carbide crystal

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图 15 不同加载力下的摩擦系数与摩擦力

Figure 15. Friction coefficients and frictional forces with different load forces

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图 16 碳化硅工件划痕形貌及截面轮廓

Figure 16. Scratched morphologies and cross-sectional profiles of silicon carbide workpieces

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图 17 碳化硅工件压痕深度对比

Figure 17. Comparison of indentation depths of silicon carbide workpiece

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表 1 金刚石和碳化硅的物理性能参数

Table 1. The physical properties of diamond and SiC

材料	密度 ρ' / (kg·m⁻³)	弹性模量 E / GPa	泊松比 ε
金刚石	3523	1050	0.07
碳化硅	3215	196	0.21

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表 2 碳化硅JH-2本构模型参数

Table 2. JH-2 constitutive model parameters of SiC

参数	取值
A	0.96
B	0.35
C	0
M	1.00
N	0.65

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表 3 正交试验的因素及水平

Table 3. Factors and level of orthogonal test

水平	切削速度 v / (m·s⁻¹)	切削深度 a_p / μm	磨粒锥角 θ / (°)
水平	U	V	W
1	60	0.5	60
2	76	1.0	90
3	85	1.5	120

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表 4 极差分析表

Table 4. Range analysis results

No.	U	V	W	空列	主切削力 F_c/ mN
1	1	1	1	1	0.08
2	1	2	2	2	0.39
3	1	3	3	3	0.95
4	2	1	2	3	0.31
5	2	2	3	1	0.52
6	2	3	1	2	0.49
7	3	1	3	2	0.30
8	3	2	1	3	0.43
9	3	3	2	1	0.68
K₁	1.42	0.70	1.00	1.29
K₂	1.32	1.34	1.38	1.18
K₃	1.41	2.12	1.78	1.68
k₁	0.47	0.23	0.33	0.43
k₂	0.44	0.45	0.46	0.39
k₃	0.47	0.71	0.59	0.56
R	0.03	0.47	0.26	0.17

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表 5 方差分析结果

Table 5. Variance analysis results

差异源	SS	df	MS	F	P-value	显著性
U	0.002	2	0.001	0.08	6.94
V	0.337	2	0.168	13.75	6.94	*
W	0.100	2	0.050	4.12	6.94
误差e	0.047	2	0.023
误差e^Δ	0.049	4	0.012
总和	0.536	12

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