智能主轴高速铣削颤振的模糊控制方法研究

doi:10.3901/JME.2021.13.055

机械工程学报 ›› 2021, Vol. 57 ›› Issue (13): 55-62.doi: 10.3901/JME.2021.13.055

• 特邀专栏：高性能电主轴技术 • 上一篇下一篇

扫码分享

智能主轴高速铣削颤振的模糊控制方法研究

曹宏瑞^1,2, 李登辉^1,2, 刘金鑫^1,2, 张兴武^1,2, 陈雪峰^1,2

1. 西安交通大学机械工程学院西安 710049;
2. 西安交通大学机械制造系统工程国家重点实验室西安 710049

收稿日期:2020-05-10 修回日期:2021-02-18 出版日期:2021-07-05 发布日期:2021-08-31
通讯作者: 曹宏瑞(通信作者),男,1982年出生,博士,教授,博士研究生导师。主要研究方向为转子-轴承系统动力学建模,智能主轴颤振监测及主动控制以及航空发动机转子振动异常监测与故障预警等。E-mail:chr@mail.xjtu.edu.cn
作者简介:李登辉,男,1992年出生,博士研究生。主要研究方向为高速铣削颤振的主动控制。E-mail:lidenghui@stu.xjtu.edu.cn;刘金鑫,男,1988年出生,博士,副教授,博士研究生导师。主要研究方向为航空发动机建模与智能容错控制,机械装备减振与振动控制。E-mail:jinxin.liu@xjtu.edu.cn;张兴武,男,1984年出生,博士,教授,博士研究生导师。主要研究方向为小波有限元动力学分析,振动优化控制与智能制造。E-mail:xwzhang@mail.xjtu.edu.cn;陈雪峰,男,1975年出生,博士,教授,博士研究生导师。主要研究方向为有限元动态分析与数字化制造,机械故障诊断、安全监测与寿命预测,大数据与智能制造。E-mail:chenxf@mail.xjtu.edu.cn
基金资助:
国家自然科学基金资助项目（51922084，11772244）

Research on Fuzzy Control for High Speed Milling Chatter of Intelligent Spindle

CAO Hongrui^1,2, LI Denghui^1,2, LIU Jinxin^1,2, ZHANG Xingwu^1,2, CHEN Xuefeng^1,2

1. School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an 710049;
2. State Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an 710049

Received:2020-05-10 Revised:2021-02-18 Online:2021-07-05 Published:2021-08-31

摘要/Abstract

摘要： 在航空叶片、整体叶盘等零件高速高效加工过程中，切削过程阻尼作用的减弱，致使颤振相比低速切削时更容易发生，严重影响了加工精度和效率的提高。而颤振监控作为智能主轴的主要功能之一，是解决高速高效加工过程中颤振难题的一种有效途径。首先，在主轴结构上集成压电作动器及位移传感器等，搭建颤振主动控制系统，并在此基础上，建立主动控制系统模型。然后，分析主轴系统动态特性，据此设计模糊控制规则，开发模糊控制器。接着，通过力锤激励试验及扫频试验辨识主轴动态系统模型，进行铣削加工及颤振控制仿真分析。最后，开展铣削颤振主动控制试验。试验结果表明，提出的颤振模糊控制方法能够有效控制铣削颤振，提升铣削加工的稳定性。

关键词: 高速铣削, 颤振, 模糊控制, 主动控制, 压电作动器

Abstract: In the process of high speed and high efficiency machining of parts such as aeronautical blades, chatter is more likely to occur than low speed cutting process due to the weakening of the damping effect in the cutting process. As one of the main functions of intelligent spindle, chatter monitoring and control is an effective way to solve the chatter problem in high speed and high efficiency machining process. First of all, an active control structure is designed by integrating piezoelectric actuators and displacement sensors into the spindle system. According to the structure, the active control system model is developed. Then, the dynamic characteristics of the active spindle structure are analyzed. Based on that, the control rules and the fuzzy controller are developed. Next, the system equation is obtained through hammer tests and sweep-frequency tests. A numerical example is also performed to analyze the chatter control effects. Finally, chatter control milling experiments are performed. The results show that the proposed active control method can effectively control milling chatter and improve the stability of the milling process.

Key words: high speed milling, chatter, fuzzy control, active control, piezoelectric actuator

中图分类号:

TG547

曹宏瑞, 李登辉, 刘金鑫, 张兴武, 陈雪峰. 智能主轴高速铣削颤振的模糊控制方法研究[J]. 机械工程学报, 2021, 57(13): 55-62.

CAO Hongrui, LI Denghui, LIU Jinxin, ZHANG Xingwu, CHEN Xuefeng. Research on Fuzzy Control for High Speed Milling Chatter of Intelligent Spindle[J]. Journal of Mechanical Engineering, 2021, 57(13): 55-62.

参考文献

[1] Kayhan M, Budak E. An experimental investigation of chatter effects on tool life[J]. Proceedings of the Institution of Mechanical Engineers, Part B:Journal of Engineering Manufacture, 2009, 223(11):1455-1463.
[2] Munoa J, Beudaert X, Dombovari Z, et al. Chatter suppression techniques in metal cutting[J]. CIRP Annals-Manufacturing Technology, 2016, 65(2):785-808.
[3] Cao H, Zhang X, Chen X. The concept and progress of intelligent spindles:A review[J]. International Journal of Machine Tools & Manufacture, 2017, 112:21-52.
[4] 陈雪峰, 张兴武, 曹宏瑞. 智能主轴状态监测诊断与振动控制研究进展[J]. 机械工程学报, 54(19):58-69. CHEN Xuefeng, ZHANG Xingwu, CAO Hongrui. Advances in condition monitoring, diagnosis and vibration control of smart spindles[J]. Journal of Mechanical Engineering, 54(19):58-69
[5] 乔晓利, 祝长生, 钟志贤. 基于主动磁轴承的切削颤振稳定性分析及控制[J]. 中国机械工程, 2016, 27(12):1632-1637. QIAO Xiaoli, ZHU Changsheng, ZHONG Zhixian. Stability and control for cutting chatter based on active magnetic bearings[J]. China Mechanical Engineering, 2016, 27(12):1632-1637.
[6] Chen F, Lu X, Altintas Y. A novel magnetic actuator design for active damping of machining tools[J]. International Journal of Machine Tools & Manufacture, 2014, 85(7):58-69.
[7] Lu X, Chen F, Altintas Y. Magnetic actuator for active damping of boring bars[J]. CIRP Annals-Manufacturing Technology, 2014, 63(1):369-372.
[8] Dijk N J M V, Wouw N V D, Doppenberg E J J, et al. Robust active chatter control in the high-speed milling process[J]. IEEE Transactions on Control Systems Technology, 2012, 20(4):901-917.
[9] Wouw N V D, Dijk N J M V, Schiffler A, et al. Experimental validation of robust chatter control for high-speed milling processes[M]. Springer International Publishing, 2017.
[10] Wu Y, Zhang H T, Huang T, et al. Robust chatter mitigation control for low radial immersion machining processes[J]. IEEE Transactions on Automation Science & Engineering, 2018, 99:1-8.
[11] 张永亮, 李郝林, 刘军, 等. 外圆车削颤振的半主动模糊控制[J]. 振动与冲击, 2012, 31(1):101-105. ZHANG Yongliang, LI Haolin, LIU Jun, et al. Semi-active fuzzy control for cylindrical turning chatter[J]. Journal of Vibration and Shock, 2012, 31(1):101-105.
[12] Pour D S, Behbahani S. Semi-active fuzzy control of machine tool chatter vibration using smart MR dampers[J]. International Journal of Advanced Manufacturing Technology, 2016, 83(1-4):421-428.
[13] Biju C, Shunmugam M. Performance of magnetorheological fluid based tunable frequency boring bar in chatter control[J]. Measurement, 2019, 140:407-415.
[14] Dohner J L, Lauffer J P, Hinnerichs T D, et al. Mitigation of chatter instabilities in milling by active structural control[J]. Journal of Sound and Vibration, 2001, 269(1):197-211.
[15] Denkena B, Gümmer O. Process stabilization with an adaptronic spindle system[J]. Production Engineering, 2012, 6(4-5):485-492.
[16] Monnin J, Kuster F, Wegener K. Optimal control for chatter mitigation in milling-Part 1:Modeling and control design[J]. Control Engineering Practice, 2014, 24(1):167-175.
[17] Monnin J, Kuster F, Wegener K. Optimal control for chatter mitigation in milling-Part 2:Experimental validation[J]. Control Engineering Practice, 2014, 24:167-175.
[18] Li D, Cao H, Liu J, et al. Milling chatter control based on asymmetric stiffness[J]. International Journal of Machine Tools and Manufacture, 2019, 147:103458.
[19] Wang C, Zhang X, Liu Y, et al. Stiffness variation method for milling chatter suppression via piezoelectric stack actuators[J]. International Journal of Machine Tools & Manufacture, 2017, 124.
[20] Shi F, Cao H, Zhang X, et al. A chatter mitigation technique in milling based on H∞-ADDPMS and piezoelectric stack actuators[J]. The International Journal of Advanced Manufacturing Technology, 2019, 101(9-12):2233-2248.
[21] Zhang X, Wang C, Liu J, et al. Robust active control based milling chatter suppression with perturbation model via piezoelectric stack actuators[J]. Mechanical Systems and Signal Processing, 2019, 120:808-835.
[22] Li D, Cao H, Zhang X, et al. Model predictive control based active chatter control in milling process[J]. Mechanical Systems and Signal Processing, 2019, 128:266-281.
[23] Driankov D, Hellendoorn H, Reinfrank M. An introduction to fuzzy control[M]. Springer Science & Business Media, 2013.
[24] 王立新, 王迎军. 模糊系统与模糊控制教程[M]. 北京:清华大学出版社. 2003. WANG Lixin, WANG Yingjun. Course of fuzzy system and fuzzy control[M]. Beijing:Tsinghua University Press, 2003.
[25] Altintas Y. Manufacturing automation:metal cutting mechanics, machine tool vibrations, and CNC design[M]. Cambridge University Press, 2012.

智能主轴高速铣削颤振的模糊控制方法研究

Research on Fuzzy Control for High Speed Milling Chatter of Intelligent Spindle

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]	刘阔, 姜业明, 黄任杰, 李明禹, 陈虎, 王永青. 虑及颤振在线抑制的机床高效自适应加工技术研究[J]. 机械工程学报, 2024, 60(6): 104-113.
[2]	唐新姿, 李可翔, 何文双, 陈睿, 彭锐涛. 多工况风电叶片颤振相关性分析与气弹优化[J]. 机械工程学报, 2024, 60(20): 300-314.
[3]	陈耿彪, 刘志文, 尹来容, 易继军, 张拓. 半主动三附气室空气弹簧吸振器特性分析[J]. 机械工程学报, 2024, 60(17): 194-207.
[4]	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.
[5]	何华, 刘全, 申屠舒展, 宫昭. 轮式多机协同搬运机器人轨迹跟踪控制器设计[J]. 机械工程学报, 2024, 60(11): 145-155.
[6]	谭志朴, 秦国华, 娄维达, 吴竹溪. 基于伯努利分布与混合驱动模型的铣削稳定性高精判断方法[J]. 机械工程学报, 2024, 60(11): 318-331.
[7]	宋阳, 曹华军, 张金, 刘磊, 张琼之. 纤维随机分布CFRP高速铣削比能模型与表面质量优化[J]. 机械工程学报, 2024, 60(1): 65-74.
[8]	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.
[9]	王晓勇, 郜志英, 辛岩莉. 基于定量递归分析的冷轧颤振状态识别与预报[J]. 机械工程学报, 2023, 59(9): 137-145.
[10]	任乔, 张济民, 张鹏. 电磁旋转涡流制动特性分析和力矩模糊控制方法研究[J]. 机械工程学报, 2023, 59(6): 255-263.
[11]	朱子俊, 朱祥龙, 董志刚, 康仁科, 鲍岩. 磨削加工颤振稳定性研究综述[J]. 机械工程学报, 2023, 59(21): 15-33.
[12]	宋兴荣, 熊尚峰, 王德顺, 李理, 胡安平, 陶以彬. 风电并网下储能参与电网一次调频控制策略^*[J]. 电气工程学报, 2023, 18(2): 260-268.
[13]	宾光富, 钟新利, 张阳演, 杨峰, 陈安华. 基于压电驱动浮环轴承间隙可调的涡轮增压器转子瞬变振动主动控制[J]. 机械工程学报, 2023, 59(18): 31-41.
[14]	娄维达, 秦国华, 王华敏, 吴竹溪. 基于复化Cotes积分和神经网络的稳定铣削工艺参数多目标优化方法[J]. 机械工程学报, 2023, 59(17): 279-290.
[15]	王攀, 周小宝, 杨欣欣, 褚志刚. 基于虚拟传感的薄板结构辐射声主动控制研究[J]. 机械工程学报, 2023, 59(15): 121-130.