| 董浩生,杨赫然,孙兴伟,董祉序,刘 寅.基于砂带表面磨粒分布的螺杆曲面重复磨削区域
表面粗糙度预测[J].电子测量与仪器学报,2022,36(3):87-95 |
| 基于砂带表面磨粒分布的螺杆曲面重复磨削区域
表面粗糙度预测 |
| Prediction of surface roughness in repeated grinding area of screw surfacebased on abrasive particle distribution on abrasive belt surface |
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| DOI： |
| 中文关键词: 磨削 表面粗糙度 形貌预测 |
| 英文关键词:grinding surface roughness shape prediction |
| 基金项目:辽宁省自然科学基金计划指导计划(2019 ZD 0206)、辽宁省“兴辽英才计划”（XLYC1905003）、中央引导地方科技发展专项资金（2020JH6/10500048）、辽宁省博士启动项目（2019BS181）资助 |
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| Author | Institution |
| Dong Haosheng | 1. College of Mechanical Engineering, Shenyang University of technology,2. Key Laboratory of Numerical Control Manufacturing Technology for Complex Surfaces of Liaoning Province |
| Yang Heran | 1. College of Mechanical Engineering, Shenyang University of technology,2. Key Laboratory of Numerical Control Manufacturing Technology for Complex Surfaces of Liaoning Province |
| Sun Xingwei | 1. College of Mechanical Engineering, Shenyang University of technology,2. Key Laboratory of Numerical Control Manufacturing Technology for Complex Surfaces of Liaoning Province |
| Dong Zhixu | 1. College of Mechanical Engineering, Shenyang University of technology,2. Key Laboratory of Numerical Control Manufacturing Technology for Complex Surfaces of Liaoning Province |
| Liu Yin | 1. College of Mechanical Engineering, Shenyang University of technology,2. Key Laboratory of Numerical Control Manufacturing Technology for Complex Surfaces of Liaoning Province |
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| 中文摘要: |
| 为提高螺杆转子磨削效率开发螺杆同步磨削装置,分别采用不同方式对螺杆凹凸两面进行磨削,由此会在连接处产生
重复磨削区域。 为保证重复磨削区域表面质量满足螺杆使用要求,对该区域表面粗糙度进行预测。 首先基于瑞利分布建立砂
带表面磨粒分布模型;在此基础上,根据磨削去除机理及螺杆廓形对磨削后的螺杆表面形貌进行预测;其次,依据表面粗糙轮廓
度定义得到不同工艺参数下的表面粗糙度预测值。 最后通过螺杆磨削及测量实验验证提出算法的准确性。 实验结果表明提出
的算法平均误差为 6. 27%,最低误差为 0. 16%,因此提出的算法可为螺杆转子砂带磨削表面粗糙度预测提供理论依据。 |
| 英文摘要: |
| In order to improve the grinding efficiency of screw rotor, a screw synchronous grinding device is developed. Different ways are
used to grind the concave and convex sides of screw respectively, which will produce repeated grinding areas at the joints. In order to
ensure that the surface quality of the repeated grinding area meets the requirements of the screw, the surface roughness of the area is
predicted. Firstly, based on Rayleigh distribution, the abrasive particle distribution model on the surface of sand belt is established. On
this basis, the surface morphology of the ground screw is predicted according to the grinding removal mechanism and screw profile.
Secondly, according to the definition of surface roughness profile, the predicted values of surface roughness under different process
parameters are obtained. Finally, the accuracy of the proposed algorithm is verified by screw grinding and measurement experiments.
The experimental results show that the average error of the proposed algorithm is 6. 27% and the minimum error is 0. 16%. Therefore,
the proposed algorithm can provide a theoretical basis for the prediction of surface roughness in screw rotor abrasive belt grinding. |
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