Surface Morphology Characteristics and Effectiveness Analysis of Ultrasonic Longitudinal Torsion Assisted Milling of Titanium Alloys

doi:10.3969/j.issn.1004-132X.2023.06.006

Abstract

Abstract: In order to solve the problems that the surface quality of difficult-to-cut titanium alloy materials was difficult to be controlled in milling， a combination of ultrasonic longitudinal-torsional vibration and milling was proposed， and the experimental platform of ultrasonic longitudinal-torsional milling system was built. A single factor test was carried out from four aspects of cutting speed， feed per tooth， cutting depth， and ultrasonic amplitude， and the surface textures and roughnesses of ultrasonic longitudinal-torsional milling and ordinary milling were compared and analyzed. It is found that the surface textures produced by ultrasonic longitudinal-torsional milling were uniform， while the common milling has obvious adhesion phenomena accompanied by scale-spikes. The surface roughness values of ultrasonic longitudinal-torsional milling are obviously lower than that of ordinary milling， and it is concluded that the higher the speed， the larger the amplitude and the smaller the surface roughness value during ultrasonic longitudinal-torsional milling. The simulation and experiments were contrasted and effectively analysed for the feed per tooth， which has a great influence on the surface topography. The results show that the trends of experiment and simulation are consistent and have a high degree of agreement with the theoretical analysis， and the relative errors of ultrasonic longitudinal-torsional milling are lower than that of ordinary milling， and the quality of ultrasonic surface milling is obviously higher than that of ordinary milling.

Key words: , ultrasonic longitudinal torsional vibration, milling, surface morphology, effectiveness analysis

摘要： 针对钛合金难加工材料在铣削加工过程中表面质量难以控制的问题，提出将超声纵扭复合振动与铣削加工相复合，搭建超声纵扭铣削系统试验平台。从切削速度、每齿进给量、切削深度、超声振幅4个方面进行单因素试验，对比分析超声纵扭铣削和普通铣削加工表面纹理和表面粗糙度，发现超声纵扭铣削产生的表面纹理规则均匀，而普通铣削存在明显的粘连现象并伴有鳞刺产生，超声纵扭铣削时表面粗糙度值明显低于普通铣削加工时表面粗糙度值，进而得出超声纵扭铣削时速度越大、振幅越大，表面粗糙度值越小的结论。重点对表面形貌影响比较大的每齿进给量进行了仿真与试验的对比及有效性分析，结果表明，试验结果与仿真结果趋势一致，与理论分析结果具有较高吻合度，超声纵扭铣削加工的相对误差低于普通铣削加工相对误差，表面加工质量明显高于普通铣削加工表面质量。

关键词: 超声纵扭振动, 铣削, 表面形貌, 有效性分析

CLC Number:

TG146

LI Fengqin, ZHAO Bo, HAO Wangshen, WANG Xiaobo. Surface Morphology Characteristics and Effectiveness Analysis of Ultrasonic Longitudinal Torsion Assisted Milling of Titanium Alloys[J]. China Mechanical Engineering, 2023, 34(06): 677-684，693.

李凤琴, 赵波, 郝旺身, 王晓博. 超声纵扭铣削钛合金表面形貌特性及有效性分析[J]. 中国机械工程, 2023, 34(06): 677-684，693.

References

［1］姜增辉，王琳琳，石莉，等. 硬质合金刀具切削Ti-6Al-4V的磨损机理及特征［J］. 机械工程学报， 2014， 50（1）：178-184.
JIANG Zenghui， WANG Linlin， SHI Li， et al. Study on Tool Wear Mechanism and Characteristics of Carbide Tools in Cutting Ti6Al4V［J］. Journal of Mechanical Engineering， 2014， 50（1）：178-184.
［2］童景琳，封志彬，焦锋，等. 超声纵-扭复合铣削钛合金刀具磨损特性研究［J］. 表面技术， 2019， 48（3）：297-303.
TONG Jinglin， FENG Zhibin， JIAO Feng， et al. Tool Wear in Longitudinal-torsional Ultrasonic Vibration Milling of Titanium Alloys［J］. Surface Technology， 2019， 48（3）：297-303.
［3］MALY＇ M. CHRISTIAN H， SKALON M， et al. Effect of Process Parameters and High-temperature Preheating on Residual Stress and Relative Density of Ti6Al4V Processed by Selective Laser Melting［J］. Materials， 2019， 12（6）：1-13.
［4］SODKI B， ZEBALA W， STRUZIKIEWICZ G. Turning Titanium Alloy， Grade 5 ELI， with the Implementation of High Pressure Coolant［J］. Materials， 2019， 12（5）：1-14.
［5］POLINI W， TURCHETTA S. Cutting Force， Tool Life and Surface Integrity in Milling of Titanium Alloy Ti-6Al-4V with Coated Carbide Tools［J］. Proceedings of the Institution of Mechanical Engineers Part B， Journal of Engineering Manufacture， 2016， 230：694-700.
［6］SHOKRANI A， NEWMAN S T. A New Cutting Tool Design for Cryogenic Machining of Ti-6Al-4V Titanium Alloy［J］. Materials， 2019， 12（3）：1-14.
［7］叶洪涛，张军，杨金发，等. 航空难加工材料切削加工中的关键应用技术［J］. 航空制造技术， 2012， 406：44-46.
YE Hongtao， ZHANG Jun， YANG Jinfa， et al. Key Application Technology of Cutting for Aircraft Difficult-to-machine Material［J］. Aeronautical Manufac-turing Technology， 2012， 406：44-46.
［8］闫明鹏. 超声振动辅助钻削钛合金的机理和工艺研究［D］. 上海：上海交通大学， 2011.
YAN Mingpeng. Study of Machanism and Craft of Ultrasonic Vibration Aided Drilling Ti Alloys［D］. Shanghai：Shanghai Jiao Tong University， 2011.
［9］WANG M， LI S， ZHENG Y. Surface Roughness of Titanium Alloy under Ultrasonic Vibration Milling［J］. Transactions of the Chinese Society for Agricultural Machinery， 2014， 45（6）：340-341.
［10］喻宏庆，高延峰，王顺钦. 钛合金径向超声振动铣削表面粗糙度研究［J］. 航空制造技术， 2016（4）：58-62.
YU Hongqing， GAO Yanfeng， WANG Shunqin. Study on Surface Roughness of Titanium Alloy under Radial Ultrasonic Vibration Milling［J］. Aeronautical Manufacturing Technology， 2016（4）：58-62.
［11］CHEN G， REN C， ZOU Y， et al. Mechanism for Material Removal in Ultrasonic Vibration Helical Milling of Ti-6Al-4V Alloy［J］. International Journal of Machine Tools and Manufacture， 2019， 138：1-13.
［12］XIANG Daohui. Ultrasonic Longitudinal-torsional Vibration-assisted Cutting of Nomex（R） Honeycomb-core Composites［J］， The International Journal of Advanced Manufacturing Technology， 2018， 100（5/8）：1521-1530.
［13］GINTING A， NOUARI M. Surface Integrity of Dry Machined Titanium Alloys［J］. International Journal of Machine Tools and Manufacture， 2009， 49（3/4）：325-332.
［14］ZOU B， CHEN M， HUANG C， et al. Study on Surface Damages Caused by Turning NiCr20TiAl Nickel-based Alloy［J］. Journal of Materials Processing Technology， 2009， 209 （17）：5802-5809.
［15］王素玉，于涛，王文超. 基于弹塑性理论的高速铣削表面粗糙度力学建模［J］. 工具技术， 2011， 45（5）：25-27.
WANG Suyu， YU Tao， WANG Wenchao. Mechanical Modeling of Surface Roughness in HSM Based on Thermo-elastic-plastic Theory［J］. Chengdu：Tool Engineering， 2011， 45（5）：25-27.
［16］杨桂通. 弹性力学［M］. 北京：高等教育出版社， 2005.
YANG Guitong. Elastic Mechanics［M］. Beijing：Higher Education Press， 2005.
［17］浮宗霞. 超声振动铣削BK7光学玻璃表面形貌研究［D］. 焦作：河南理工大学， 2014.
FU Zongxia. Research on Ultrasonic Vibration Milling of BK7 Optical Glass Surface Morphology［D］. Jiaozuo：Henan Polytechnic University， 2014.
［18］钟鑫. 钛合金加工过程中晶粒细化与织构研究［D］. 济南：山东大学， 2018.
ZHONG Xin. Study on Grain Refinement and Texture of Machined Surface Layer of Titanium Alloy［D］. Jinan：Shandong University， 2018.

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