考虑力致变形影响的薄壁件铣削多点接触稳定性预测

doi:10.3901/JME.2022.17.309

机械工程学报 ›› 2022, Vol. 58 ›› Issue (17): 309-320.doi: 10.3901/JME.2022.17.309

• 制造工艺与装备 • 上一篇

扫码分享

考虑力致变形影响的薄壁件铣削多点接触稳定性预测

王志学^1,2, 刘献礼¹, 李茂月¹, 王力翚³, Steven Y. LIANG⁴, 于福航¹

1. 哈尔滨理工大学先进制造智能化技术教育部重点实验室哈尔滨 150080;
2. 哈尔滨职业技术学院哈尔滨 150076;
3. 瑞典皇家理工学院斯德哥尔摩 25175 瑞典;
4. 佐治亚理工学院乔治·W·伍德拉夫机械工程学院亚特兰大 30332 美国

收稿日期:2021-05-20 修回日期:2022-03-23 发布日期:2022-11-07
作者简介:王志学,男,1989年出生,博士研究生,讲师。主要研究方向为先进制造技术、智能加工、开放式数控。E-mail:wzxyx126@126.com;李茂月,男,1981年出生,教授,博士,博士研究生导师。主要研究方向为智能加工、开放式数控、数控插补等。E-mail:lmy0500@163.com

Multi-point Contact Stability Prediction Considering Force-induced Deformation Effect in Milling Thin-Walled Parts

WANG Zhixue^1,2, LIU Xianli¹, LI Maoyue¹, WANG Lihui³, Steven Y. LIANG⁴, YU Fuhang¹

1. Key Laboratory of Advanced Manufacturing and Intelligent Technology (Ministry of Education), Harbin University of Science and Technology, Harbin 150080;
2. Harbin Vocational & Technical College, Harbin 150076;
3. KTH Royal Institute of Technology, Stockholm 25175, Sweden;
4. George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta 30332, USA

Received:2021-05-20 Revised:2022-03-23 Published:2022-11-07
Contact: 国家自然科学基金国际(地区)合作与交流重点(51720105009)和哈尔滨职业技术学院博士创新工作室(HZYBS202009)资助项目。

摘要/Abstract

摘要： 薄壁件具有弱刚性的特点，因此在加工过程中极易诱发颤振，同时由于铣削力的存在，导致工件的变形不可避免。力致变形的存在导致径向切深的改变，从而造成切入和切出角的变化，最终影响了加工的稳定性。同时，在侧铣过程中，薄壁件动力学参数沿刀轴方向变化明显，所以在建立动力学模型时，需要同时考虑力致变形和多点接触的影响。首先，对铣削力进行了建模，并考虑了铣刀螺旋角的影响；其次，提出了一种变形量迭代提取的方法，借助Workbench软件提取了不同轴向切深处由于铣削力导致的工件变形并进行了拟合。然后，对工件进行了模态分析，提取了工件的模态振型并进行了拟合。最后，将刀-工接触域沿刀轴方向进行了离散，计算了各节点处的振型和由于铣削力导致的工件变形，综合这些因素建立了考虑力致变形的多点接触动力学模型。最后以钛合金(Ti6Al4V)为研究对象，进行了实验验证，并与未考虑力致变形的多点接触动力学模型进行了对比，证明了本文所提模型的优越性。

关键词: 铣削颤振, 力致变形, 多点接触, 薄壁件, 钛合金

Abstract: Thin wall parts have the characteristics of weak rigidity, so it is easy to induce chatter in the machining process. At the same time, the deformation of the workpiece is inevitable due to the existence of milling force. The existence of force-induced deformation leads to the change of radial cutting depth, which leads to the change of start angle and exit angle under milling, and finally affects the stability of machining. At the same time, in the process of side milling, the dynamic parameters of thin-walled parts change obviously along the direction of the cutter axis, so the influence of force-induced deformation and multi-point contact should be taken into account in the establishment of the dynamic model. Firstly, the milling force is modeled and the effect of the spiral angle of the milling cutter is considered. Secondly, an iterative extraction method of deformation is proposed. With the help of workbench software, the workpiece deformation caused by milling force at different axial cutting depths is extracted and fitted. Then, the modal analysis of the workpiece is carried out, the modal vibration mode of the workpiece is extracted and fitted. Finally, the tool-part contact zone is discretized along the tool axis, and the vibration modes and the workpiece deformation caused by milling force at each node are calculated, and a multi-point contact dynamic model considering force-induced deformation is established. Finally, taking titanium alloy (Ti6Al4V) as the research object, the experimental verification is carried out, and compared with the multi-point contact dynamic model without considering force-induced deformation, which proves the superiority of the model proposed in this paper.

Key words: milling chatter, force-induced deformation, multi-point contact, thin-walled parts, titanium alloy

中图分类号:

TH113
TG56

王志学, 刘献礼, 李茂月, 王力翚, Steven Y. LIANG, 于福航. 考虑力致变形影响的薄壁件铣削多点接触稳定性预测[J]. 机械工程学报, 2022, 58(17): 309-320.

WANG Zhixue, LIU Xianli, LI Maoyue, WANG Lihui, Steven Y. LIANG, YU Fuhang. Multi-point Contact Stability Prediction Considering Force-induced Deformation Effect in Milling Thin-Walled Parts[J]. Journal of Mechanical Engineering, 2022, 58(17): 309-320.

参考文献

[1] 王志学，刘献礼，李茂月，等. 切削加工颤振智能监控技术[J]. 机械工程学报，2020，56(24)：1-23. WANG Zhixue，LIU Xianli，LI Maoyue，et al. Intelligent monitoring and control technology of cutting chatter[J]. Journal of Mechanical Engineering, 2020,56(24)：1-23.
[2] ZHANG Z，LI H，LIU X，et al. Chatter mitigation for the milling of thin-walled workpiece[J]. International Journal of Mechanical Sciences，2018，138-139：262-271.
[3] OZKIRIMLI O，TUNC L T，BUDAK E. Generalized model for dynamics and stability of multi-axis milling with complex tool geometries[J]. Journal of Materials Processing Tech，2016，238：446-458.
[4] COMAK A，BUDAK E. Modeling dynamics and stability of variable pitch and helix milling tools for development of a design method to maximize chatter stability[J]. Precision Engineering，2017，47：459-468.
[5] 陈云，侯亮，刘文志，等. 基于时域仿真法的断续铣削颤振预测[J]. 机械工程学报，2021，57(3)：98-106. CHEN Yun，HOU Liang，LIU Wenzhi，et al. Chatter stability prediction in low immersion milling based on time-domain simulation[J]. Journal of Mechanical Engineering，2021，57(3)：98-106.
[6] WANG X J，SONG Q H，LIU Z Q. Dynamic model and stability prediction of thin-walled component milling with multi-modes coupling effect[J]. Journal of Materials Processing Technology，2020，288：116869.
[7] HUANG C，YANG W A，CAI X，et al. An efficient third-order full-discretization method for prediction of regenerative chatter stability in milling[J]. Shock and Vibration，2020，2020(1)：1-16.
[8] ZHI H Y，ZHANG T S，DU J，et al. An efficient full-discretization method for milling stability prediction[J]. The International Journal of Advanced Manufacturing Technology，2020，7(1781)：1-13.
[9] TANG X W，PENG F Y，YAN R，et al. Accurate and efficient prediction of milling stability with updated full-discretization method[J]. International Journal of Advanced Manufacturing Technology，2017，88：2357-2368.
[10] DING Y，ZHU L. Investigation on chatter stability of thin-walled parts considering its flexibility based on finite element analysis[J]. The International Journal of Advanced Manufacturing Technology，2018，94(9)：3173-3187.
[11] YANG Y，ZHANG W H，MA Y C，et al. An efficient decomposition-condensation method for chatter prediction in milling large-scale thin-walled structures[J]. Mechanical Systems and Signal Processing，2019，121：58-76.
[12] CHENG D J，XU F，XU S H，et al. Minimization of surface roughness and machining deformation in milling of al alloy thin-walled parts[J]. International Journal of Precision Engineering and Manufacturing，2020，21(9)：1597-1613.
[13] ZHANG L，MA L，ZHANG D. Dynamic milling stability of thin-walled component considering time variation of coupling deflection and dynamic characteristics of tool-workpiece system[J]. The International Journal of Advanced Manufacturing Technology，2018，94(5-8)：3005-3016.
[14] ZHANG L，HAO B，XU D P，et al. Dynamic milling stability prediction of thin-walled components based on VPC and VSS combined method[J]. Journal of the Brazilian Society of Mechanical Sciences and Engineering，2020，42(6)：336.
[15] LI H Q，SHIN，YUNG C. A comprehensive dynamic end milling simulation model[J]. Journal of Manufacturing Science and Engineering，2006，128(1)：86-95.
[16] EKSIOGLU C，KILIC Z M，ALTINTAS Y. Discrete-time prediction of chatter stability, cutting forces and surface location errors in flexible milling systems[J]. Transactions of the ASME-Journal of Manufacturing Science and Engineering，2012，134(6)：061006.
[17] YANG Y，ZHANG W H，MA Y C，et al. Chatter prediction for the peripheral milling of thin-walled workpieces with curved surfaces[J]. International Journal of Machine Tools & Manufacture，2016，109：36-48.
[18] KHOSHDARREGI M，ALTINTAS Y. Dynamics of multipoint thread turning, Part I: general formulation[J]. Journal of Manufacturing Science and Engineering，2017，140(6)：1-46.
[19] KHOSHDARREGI M，ALTINTAS Y. Dynamics of multi-point thread turning, Part II: application to thin-walled oil pipes[J]. Journal of Manufacturing Science and Engineering，2017，140：1-11.
[20] JIN X，SUN Y W，GUO Q，et al. 3D stability lobe considering the helix angle effect in thin-wall milling[J]. International Journal of Advanced Manufacturing Technology，2016，82：2123-2136.
[21] 孙启梦，李蓓智，周亚勤，等. 极大径厚比薄壁件的加工变形仿真与试验研究[J]. 东华大学学报(自然科学版)，2021. SUN Qimeng，LI Beizhi，ZHOU Yaqin，et al. Simulation and experimental research on machining deformation of thin-walled parts with large diameter to thickness[J]. Journal of Donghua University (Natural Science)，2021.
[22] 蒋宇平. 薄壁结构件铣削加工稳定性分析研究[D]. 上海：上海交通大学，2015. JIANG Yuping. Milling stability of thin-walled structure[D]. Shanghai: Shanghai Jiao Tong University，2015.
[23] 刘强，李忠群. 数控铣削加工过程仿真与优化——建模、算法与工程应用[M]. 北京：航空工业出版社，2011. LIU Qiang，LI Zhongqun. Numerical control milling process simulation and Optimization-modeling, algorithm and engineering application[M]. Beijing：Aviation Industry Press，2011.

考虑力致变形影响的薄壁件铣削多点接触稳定性预测

Multi-point Contact Stability Prediction Considering Force-induced Deformation Effect in Milling Thin-Walled Parts

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

本文评价

[1]	苏志朋, 梁志强, 李娟, 王飞, 魏正义, 刘月红, 金惟薇, 马悦, 殷振, 王西彬. 钛合金微槽超声螺线辅助铣磨加工试验研究[J]. 机械工程学报, 2024, 60(9): 5-12.
[2]	武韩强, 陈卓, 叶曦珉, 张诗博, 李偲偲, 曾江, 汪强, 吴勇波. 钛合金超声辅助等离子体氧化改性磨削基本加工特性研究[J]. 机械工程学报, 2024, 60(9): 13-25.
[3]	周京国, 张宇航, 隋天一, 行登海, 董宝昆, 付清宇, 付俊帆, 林彬. 分离-接触特征对钛合金超声振动辅助铣削加工特性影响规律研究[J]. 机械工程学报, 2024, 60(9): 97-113.
[4]	郑开魁, 赵信哲, 牟刚, 任志英. 超声波滚压强化TC11钛合金的表面质量与摩擦磨损性能[J]. 机械工程学报, 2024, 60(9): 137-151.
[5]	吴淑晶, 王大中, 谷顾全, 黄帅, 董国军, 郭国强, 安庆龙, 李长河. 多种能场高性能加工复杂曲面关键技术研究进展[J]. 机械工程学报, 2024, 60(9): 152-167.
[6]	肖贵坚, 刘振扬, 贺毅, 刘岗, 邓忠才. 激光辅助CBN砂带磨削TC4钛合金材料去除行为及表面完整性研究[J]. 机械工程学报, 2024, 60(9): 241-253.
[7]	魏荣, 徐默然, 李常平, 李树健, 李鹏南. 电火花辅助铣削钛合金多能场建模及调控优化研究[J]. 机械工程学报, 2024, 60(9): 393-409.
[8]	韩建超, 张孟非, 王斌, 国生辉, 贾燚, 王涛. 钛合金电致塑性本构方程及多物理场耦合分析[J]. 机械工程学报, 2024, 60(9): 421-433.
[9]	张禹森, 陈雷, 刘胜杰, 胡峻华, 张启飞, 崔明亮, 胡建良, 金淼. TB6钛合金模锻件低倍组织局部粗晶形成机理及预测[J]. 机械工程学报, 2024, 60(8): 121-131.
[10]	杜随更, 刘冠翔, 陈虎, 胡弘毅, 李菊. TC17(α+β)/TC17(β)线性摩擦焊接过程中焊合区组织及其织构演变[J]. 机械工程学报, 2024, 60(2): 99-106.
[11]	施壮, 李长河, 刘德伟, 张彦彬, 秦爱国, 曹华军, 陈云. 不等螺旋角立铣刀瞬时铣削力模型与验证[J]. 机械工程学报, 2024, 60(15): 393-406.
[12]	李超, 张俊, 田辉, 赵万华. 综合振动信号能量比和幅值标准差的铣削颤振实时监测方法[J]. 机械工程学报, 2024, 60(14): 11-23.
[13]	赵宇辉, 赵吉宾, 李明玥, 何振丰, 王志国, 贺晨. 激光熔化沉积TC4钛合金电涡流检测仿真及亚表面缺陷检测[J]. 机械工程学报, 2024, 60(14): 34-41.
[14]	王润琼, 宋清华, 彭业振, 刘战强. 基于特征自适应融合和集成学习的高性能铣削刀具状态监测[J]. 机械工程学报, 2024, 60(1): 149-158.
[15]	孙朝阳, 彭芳瑜, 唐小卫, 闫蓉, 辛世豪, 吴嘉伟. 基于自适应变分模态分解与功率谱熵差的机器人铣削加工颤振类型辨识[J]. 机械工程学报, 2023, 59(9): 90-100.