范立维,梁忠伟,刘晓初,吴俊,吴子轩,耿晨,谢鑫成.基于正态分布的GCr15轴承钢强化研磨残余应力场数值模拟[J].表面技术,2022,51(3):242-253.
FAN Li-wei,LIANG Zhong-wei,LIU Xiao-chu,WU Jun,WU Zi-xuan,GENG Chen,XIE Xin-cheng.Numerical Simulation of Residual Stress Field in Strengthened Grinding of GCr15 Bearing Steel Based on Normal Distribution[J].Surface Technology,2022,51(3):242-253 |
| 基于正态分布的GCr15轴承钢强化研磨残余应力场数值模拟 |
| Numerical Simulation of Residual Stress Field in Strengthened Grinding of GCr15 Bearing Steel Based on Normal Distribution |
| 投稿时间：2021-05-18 修订日期：2021-08-18 |
| DOI：10.16490/j.cnki.issn.1001-3660.2022.03.026 |
| 中文关键词: 强化研磨 残余应力场 正态分布 数值模拟 GCr15轴承钢 |
| 英文关键词:strengthened grinding residual stress field normal distribution numerical simulation GCr15 bearing steel |
| 基金项目:国家自然科学基金项目(51975136，51575116);广东省科技计划项目(2017A010102014，2016A010102022);国家重点研发计划(2018YFB2000501);广州大学全日制研究生基础创新项目资助(2020GDJC-M18);广东省高等学校科技创新团队项目(2017KCXTD025);广州市教育系统创新学术团队项目(1201610013);广东省高校重点领域专项(2019KZDZX1009);广州市科技计划项目(201707010293) |
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| Author | Institution |
| FAN Li-wei | School of Mechanical & Electric Engineering,Guangzhou 510006, China;Guangzhou Key Laboratory for Strengthened Grinding and High Performance Machining of Metal Material,Guangzhou 510006, China ;Guangdong Engineering and Technology Research Centre for Strengthen Grinding and High Performance Micro-nanomachining, Guangzhou University, Guangzhou 510006, China |
| LIANG Zhong-wei | School of Mechanical & Electric Engineering,Guangzhou 510006, China;Guangzhou Key Laboratory for Strengthened Grinding and High Performance Machining of Metal Material,Guangzhou 510006, China ;Guangdong Engineering and Technology Research Centre for Strengthen Grinding and High Performance Micro-nanomachining, Guangzhou University, Guangzhou 510006, China |
| LIU Xiao-chu | School of Mechanical & Electric Engineering,Guangzhou 510006, China;Guangzhou Key Laboratory for Strengthened Grinding and High Performance Machining of Metal Material,Guangzhou 510006, China ;Guangdong Engineering and Technology Research Centre for Strengthen Grinding and High Performance Micro-nanomachining, Guangzhou University, Guangzhou 510006, China |
| WU Jun | School of Mechanical & Electric Engineering,Guangzhou 510006, China;Guangzhou Key Laboratory for Strengthened Grinding and High Performance Machining of Metal Material,Guangzhou 510006, China ;Guangdong Engineering and Technology Research Centre for Strengthen Grinding and High Performance Micro-nanomachining, Guangzhou University, Guangzhou 510006, China |
| WU Zi-xuan | School of Mechanical & Electric Engineering,Guangzhou 510006, China;Guangzhou Key Laboratory for Strengthened Grinding and High Performance Machining of Metal Material,Guangzhou 510006, China ;Guangdong Engineering and Technology Research Centre for Strengthen Grinding and High Performance Micro-nanomachining, Guangzhou University, Guangzhou 510006, China |
| GENG Chen | School of Mechanical & Electric Engineering,Guangzhou 510006, China;Guangzhou Key Laboratory for Strengthened Grinding and High Performance Machining of Metal Material,Guangzhou 510006, China ;Guangdong Engineering and Technology Research Centre for Strengthen Grinding and High Performance Micro-nanomachining, Guangzhou University, Guangzhou 510006, China |
| XIE Xin-cheng | School of Mechanical & Electric Engineering,Guangzhou 510006, China;Guangzhou Key Laboratory for Strengthened Grinding and High Performance Machining of Metal Material,Guangzhou 510006, China ;Guangdong Engineering and Technology Research Centre for Strengthen Grinding and High Performance Micro-nanomachining, Guangzhou University, Guangzhou 510006, China |
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| 中文摘要: |
| 目的 探索强化研磨不同工艺参数下定点喷射对GCr15轴承钢残余应力场的影响规律。方法 采用图像处理技术分析了不同工艺参数下强化研磨定点喷射表面覆盖率的分布特征。采用二维正态分布函数描述强化研磨定点喷射下钢珠的分布特征，运用Python/Opencv确定了在不同工艺参数下有限元模型所需的钢珠数量，基于Abaqus/Python构建出强化研磨正态分布有限元模型。运用所建立的正态分布模型分析不同喷射速度、钢珠直径及覆盖率对残余应力场的影响。结果 当喷射速度从45 m/s增加到70 m/s时，表面残余压应力从‒683.5 MPa增加到‒902.4 MPa，最大残余压应力从‒981.6 MPa增加到‒1330.6 MPa，残余压力层厚度从89 µm增加到151 µm，最大残余压应力深度从30 µm移动到70 µm。当钢珠直径从0.4 mm增加到1.0 mm时，表面残余压应力先增大后减小，最大残余压应力从‒1063.5 MPa增加到‒1240.7 MPa，最大残余压应力深度从30 µm增加到60 µm，残余压应力层厚度从103 µm增加到147 µm，其中钢珠直径从0.8 mm增加到1.0 mm，最大残余压应力保持不变。当喷射覆盖率从100%到300%时，表面残余压应力、最大残余压应力及最大残余压应力深度略有增加，残余压应力层厚度几乎保持不变。将正态分布模型、随机分布模型仿真值与实验值进行比较，发现三者的表面残余压应力、最大残余压应力深度及残余压应力厚度几乎一致，最大残余压应力随机分布模型的仿真值比实验值高32.1%，正态分布模型的仿真值比实验值高18.9%。结论 强化研磨正态分布有限元模型能够较为准确地预测残余应力变化过程，能够为强化研磨工艺参数优化提供一定的指导。 |
| 英文摘要: |
| This paper aims to explore the influence of fixed point injection on residual stress field of GCr15 bearing steel under different process parameters of strengthening grinding. Image processing technology was used to analyze the distribution characteristics of the surface coverage along the width direction of the strengthening grinding fixed point injection under different process parameters. The two-dimensional normal distribution function was used to describe the distribution characteristics of steel ball coordinates under the fixed point injection of strengthening grinding. Python/Opencv was used to determine the number of steel balls required by the finite element model under different process parameters. Based on Abaqus/ Python, the finite element model with normal distribution of strengthening grinding was constructed. Using the established normal distribution model, the influence of different injection velocity, ball diameter and coverage rate on the residual stress field was analyzed. When the injection velocity increased from 45 m/s to 70 m/s, the surface residual compressive stress increased from ‒683.5 MPa to ‒902.4 MPa, the maximum residual compressive stress increased from ‒981.6 MPa to ‒1330.6 MPa, and the thickness of residual pressure layer increased from 89 μm to 151 μm. The maximum residual compressive stress depth was moved from 30 μm to 70 μm. When the diameter of the steel ball increased from 0.4 mm to 1.0 mm, the surface residual compressive stress increased first and then decreased, the maximum residual compressive stress increased from ‒1063.5 MPa to ‒1240.7 MPa, and the maximum residual compressive stress depth increased from 30 μm to 60 μm. The thickness of residual compressive stress layer increased from 103 μm to 147 μm, and the diameter of steel ball increased from 0.8 mm to 1.0 mm, and the maximum residual compressive stress almost remained unchanged. When the injection coverage rate was from 100% to 300%, the surface residual compressive stress, the maximum residual compressive stress and the maximum residual compressive stress depth increased slightly, and the residual compressive stress layer thickness almost remained unchanged. The simulation values of the normal distribution model and the random distribution model were compared with the experimental values, and it was found that the surface residual compressive stress, maximum residual compressive stress depth and residual compressive stress thickness of the three models were almost the same. The simulation values of the random distribution model and the normal distribution model were 32.1% and 18.9% higher than the experimental values of the maximum residual compressive stress. The finite element model with normal distribution can accurately predict the change process of residual stress, which can provide some guidance for the optimization of process parameters of strengthening grinding. |
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