摘要
设计了两种超声振动辅助铣磨加工试验,并与普通铣磨加工方式相对比,试验研究了三种不同加工方式下铣磨难加工复合材料C_f/SiC的加工缺陷及表面粗糙度。试验结果表明:施加了纵向振动与沿进给方向振动的两种超声振动后,C_f/SiC复合材料的纤维拔出与崩边缺陷明显减少,底面凹坑缺陷也得到了有效抑制;采用纵向超声振动辅助铣磨时加工质量要优于沿进给方向超声振动辅助铣磨的加工效果。与普通铣磨相比,两种超声振动辅助铣磨均可有效降低表面粗糙度。各磨削要素对不同铣磨加工方式下C_f/SiC材料的表面粗糙度影响关系为:表面粗糙度随主轴转速增加而降低,随进给速度、磨削深度的增加而增加,随着超声振幅增大,表面粗糙度先减小后增大。研究表明,在优化的振幅下采用纵向超声振动辅助铣磨方式可以更大幅度地改善C_f/SiC复合材料的表面质量。该研究对难加工复合材料的高性能加工具有实际指导作用。
Two kinds of ultrasonic vibration assisted mill-grinding experiments are designed and compared with the traditional mill-grinding,the machining defects and surface roughness of C f/SiC composites in the three machining methods are analyzed.The results show that after the two ultrasonic vibrations are applied in the longitudinal direction and the direction along the feed,the defects of the fiber drawing and disintegration of the C f/SiC composites are obviously reduced and the concave defect of the bottom is effectively suppressed,and the machining quality by the longitudinal ultrasonic vibration assisted mill-grinding is better than that by the ultrasonic vibration along the feed direction.Compared with traditional mill-grinding,the two ultrasonic vibration assisted mill-grinding can reduce the surface roughness effectively.The influence of the grinding factors on the surface roughness of the C f/SiC material under different mill-grinding methods is that the surface roughness decreases with the increase of the spindle speed,increases with the increase of the feed rate and grinding depth,and with the increase of the ultrasonic amplitude,the surface roughness decreases first and then increases.It is concluded that the surface quality of C f/SiC composites can be improved greatly by using the longitudinal ultrasonic vibration assisted mill-grinding method under the optimized amplitude.The study has a practical guidunce to the high-performance machining of difficult-to-machine composite materials.
作者
湛青坡
刘含莲
黄传真
朱洪涛
刘伟昊
袭建人
Zhan Qingpo;Liu Hanlian;Huang Chuanzhen;Zhu Hongtao;Liu Weihao;Xi Jianren(School of Mechanical Engineering,Shandong University,Key Laboratory of High-efficiency and Clean Mechanical Manufacture,Shandong University,Jinan 250061,China)
出处
《工具技术》
2019年第2期17-21,共5页
Tool Engineering
基金
国家重点研发计划"智能机器人"专项(2017YFB1301903)
国家自然科学基金(51675313)