Li Xubo, Zhai Chuanmiao, Wang Canjun, Wu Ruiqin, Zang Cunqiang, Zhang Shihao, Guo Bian, Su Yuewen
College of Mechanical Engineering, Baoji University of Arts and Sciences, Baoji 721016, China.
Zhejiang Sankai Mechanical and Electrical Co., Ltd., Taizhou 317511, China.
Materials (Basel). 2024 Dec 26;18(1):56. doi: 10.3390/ma18010056.
The surface roughness of hole machining greatly influences the mechanical properties of parts, such as early fatigue failure and corrosion resistance. The boring and trepanning association (BTA) deep hole drilling with axial vibration assistance is a compound machining process of the tool cutting and the guide block extrusion. At the same time, the surface of the hole wall is also ironed by the axial large amplitude and low-frequency vibration of the guide block. The surface-forming mechanism is very complicated, making it difficult to obtain an effective theoretical analytical model of the surface roughness of the hole wall through kinematic analysis. In order to achieve accurate prediction of the surface quality of the hole wall, the chip-breaking mechanism and the hole wall formation mode of BTA deep hole vibration drilling were analyzed. The influence of drilling spindle speed, feed, amplitude, and vibration frequency on the surface roughness of the hole wall during BTA deep hole vibration drilling was illustrated by a single-factor experiment. A four-factor and three-level test scheme was designed by using the Box-Behnken design (BBD) experimental design method. A surface roughness prediction model for hole wall machining was established based on the response surface methodology. The accuracy of the prediction model was analyzed through ANOVA, and the complex correlation coefficient of the model was 0.9948, indicating that the prediction model can better reflect the mapping relationship between vibration drilling parameters and surface roughness. After optimization analysis and experimental verification, the obtained vibration drilling parameters can achieve smaller surface roughness. The error between the predicted value of the model and the experimental measurement value is 8.65%. The established prediction model is reliable and can accurately predict the surface roughness of the hole wall of BTA deep hole axial vibration drilling, providing a theoretical basis for the surface quality control of the machining hole wall. It can be applied to process optimization in practical production.
内孔加工表面粗糙度对零件力学性能影响很大,如早期疲劳失效和耐腐蚀性。轴向振动辅助的枪钻深孔钻削是刀具切削与导向块挤压的复合加工过程。同时,孔壁表面也受到导向块轴向大振幅低频振动的熨烫作用。其表面形成机理非常复杂,难以通过运动学分析获得有效的孔壁表面粗糙度理论解析模型。为实现对孔壁表面质量的准确预测,分析了枪钻深孔振动钻削的断屑机理和孔壁形成方式。通过单因素试验阐述了钻削主轴转速、进给量、振幅和振动频率对枪钻深孔振动钻削过程中孔壁表面粗糙度的影响。采用Box-Behnken设计(BBD)试验设计方法设计了四因素三水平试验方案。基于响应面法建立了孔壁加工表面粗糙度预测模型。通过方差分析(ANOVA)对预测模型的精度进行了分析,模型的复相关系数为0.9948,表明该预测模型能够较好地反映振动钻削参数与表面粗糙度之间的映射关系。经过优化分析和试验验证,所获得的振动钻削参数可实现更小的表面粗糙度。模型预测值与试验测量值之间的误差为8.65%。所建立的预测模型可靠,能够准确预测枪钻深孔轴向振动钻削孔壁的表面粗糙度,为加工孔壁的表面质量控制提供了理论依据,可应用于实际生产中的工艺优化。