Please wait a minute...
浙江大学学报(工学版)
浙江大学学报(工学版)  2018, Vol. 52 Issue (8): 1517-1525    DOI: 10.3785/j.issn.1008-973X.2018.08.011
机械工程     
机器人精镗飞机交点孔的颤振分析与识别
董辉跃1, 吴杨宝1, 郭英杰1, 李少波2, 罗水均2
1. 浙江大学 机械工程学院 浙江省先进制造技术重点研究实验室, 浙江 杭州 310027;
2. 中航成飞民用飞机有限责任公司, 四川 成都 610073
Chatter analysis and identification in robotic fine boring of aircraft intersection holes
DONG Hui-yue1, WU Yang-bao1, GUO Ying-jie1, LI Shao-bo2, LUO Shui-jun2
1. Key Laboratory of Advanced Manufacturing Technology of Zhejiang Province, College of Mechanical Engineering, Zhejiang University, Hangzhou 310027, China;
2. Chengdu Civil Aircraft Co. Ltd, Chengdu 610073, China
 全文: PDF(2762 KB)   HTML
摘要：

针对机器人精镗飞机交点孔时容易出现颤振，影响加工表面质量的问题，通过分析颤振发生时的压脚位移信号，提出基于Hilbert-Huang变换的颤振特征提取方法，实现机器人镗孔颤振的快速识别.对颤振前后的压脚位移信号进行时域分析和频域分析，获得颤振发生的频段.将压脚位移信号进行经验模态分解，得到一系列具有不同频段的固有模态函数（IMFs）.根据颤振频段筛选出与颤振相关的IMF，通过Hilbert变换得到瞬时频率.分析瞬时频率的变化规律，从中提取颤振特征以识别颤振.试验结果表明，在机器人镗孔系统中，此方法能够在颤振形成前0.5 s及时识别颤振.
Abstract:

Aiming at the chatter occurred frequently in the robotic fine boring of aircraft intersection holes and the low quality of finished surface, a feature extraction method was introduced to realize fast identification of chatter in robotic boring based on Hilbert-Huang transform (HHT) through analysis of the pressure foot displacement signal. Time and frequency domain of the pressure foot displacement signal were analyzed before and after chatter, and the chatter frequency band was obtained. The pressure foot displacement signal was decomposed by empirical mode decomposition (EMD), and a series of intrinsic mode functions (IMFs) with different frequency bands were acquired. The IMF related to chatter was selected based on the chatter frequency band, and Hilbert transform was used to get the instantaneous frequency of the IMF. The instantaneous frequency was analyzed, and the chatter feature was extracted to identify the chatter. Experimental results show that chatter can be identified in 0.5 s before the outbreak of chatter in the robotic boring system.
收稿日期: 2017-06-07 出版日期: 2018-08-23
CLC:  V262  
基金资助:

国家自然科学基金资助项目（51575479，91748204）；工信部民用飞机专项科研项目（MJZ-G-2011-07）
通讯作者: 郭英杰,男,博士后.orcid.org/0000-0002-3135-8000.     E-mail: zju_gyj@zju.edu.cn
作者简介: 董辉跃(1974-),男,研究员,从事飞机数字化装配研究.orcid.org/0000-0003-4107-2150.E-mail:donghuiyue@zju.edu.cn
服务　　
把本文推荐给朋友
加入引用管理器
E-mail Alert
作者相关文章　　

引用本文:

董辉跃, 吴杨宝, 郭英杰, 李少波, 罗水均. 机器人精镗飞机交点孔的颤振分析与识别[J]. 浙江大学学报(工学版), 2018, 52(8): 1517-1525.

DONG Hui-yue, WU Yang-bao, GUO Ying-jie, LI Shao-bo, LUO Shui-jun. Chatter analysis and identification in robotic fine boring of aircraft intersection holes. JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE), 2018, 52(8): 1517-1525.

链接本文:

http://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2018.08.011    或    http://www.zjujournals.com/eng/CN/Y2018/V52/I8/1517

[1] PAN Z, ZHANG H, ZHU Z, et al. Chatter analysis of robotic machining process[J]. Journal of Materials Processing Technology, 2006, 173(3):301-309.
[2] GUO Y, DONG H, WANG G, et al. Vibration analysis and suppression in robotic boring process[J]. International Journal of Machine Tools and Manufacture, 2016, 101:102-110.
[3] WANG G, DONG H, GUO Y, et al. Chatter mechanism and stability analysis of robotic boring[J/OL]. The International Journal of Advanced Manufacturing Technology, 2017, 91:411-421.[2017-06-05]. https://link.springer.com/article/10.1007/s00170-016-9731-9
[4] FAASSE R P H, VAN D W N, OOSTERLING J A J, et al. Prediction of regenerative chatter by modelling and analysis of high-speed milling[J]. International Journal of Machine Tools and Manufacture, 2003, 43(14):1437-1446.
[5] TOH C K. Vibration analysis in high speed rough and finish milling hardened steel[J]. Journal of Sound and Vibration, 2004, 278(1):101-115.
[6] LAMRAOUI M, THOMAS M, BADAOUI M E. Cyclostationarity approach for monitoring chatter and tool wear in high speed milling[J]. Mechanical Systems and Signal Processing, 2014, 44(1):177-198.
[7] LI X Q, WONG Y S, NEE A Y C. Tool wear and chatter detection using the coherence function of two crossed accelerations[J]. International Journal of Machine Tools and Manufacture, 1997, 37(4):425-435.
[8] THALER T, POTOCNIK P, BRIC I, et al. Chatter detection in band sawing based on discriminant analysis of sound features[J]. Applied Acoustics, 2014, 77:114-121.
[9] SCHMITZ T L. Chatter recognition by a statistical evaluation of the synchronously sampled audio signal[J]. Journal of Sound and Vibration, 2003, 262(3):721-730.
[10] 费少华, 方强, 孟祥磊, 等. 基于压脚位移补偿的机器人制孔锪窝深度控制[J]. 浙江大学学报:工学版, 2012, 46(7):1157-1161 FEI Shao-hua, FANG Qiang, MENG Xiang-lei, et al. Countersink depth control of robot drilling based on pressure foot displacement compensation[J]. Journal of Zhejiang University:Engineering Science, 2012, 46(7):1157-1161
[11] OLSSON T, HAAGE M, KIHLMAN H, et al. Cost-efficient drilling using industrial robots with high-bandwidth force feedback[J]. Robotics and Computer-Integrated Manufacturing, 2010, 26(1):24-38.
[12] HUANG P, LI J, SUN J, et al. Vibration analysis in milling titanium alloy based on signal processing of cutting force[J]. The International Journal of Advanced Manufacturing Technology, 2013, 64(5-8):613-621.
[13] 李茂月, 韩振宇, 富宏亚, 等. 基于开放式控制器的铣削颤振在线抑制[J]. 机械工程学报, 2012, 48(17):172-182 LI Mao-yue, HAN Zhen-yu, FU Hong-ya, et al. Online milling chatter suppression based on open architecture controller[J]. Journal of Mechanical Engineering, 2012, 48(17):172-182
[14] CAO H, LI B, HE Z. Chatter stability of milling with speed-varying dynamics of spindles[J]. International Journal of Machine Tools and Manufacture, 2012, 52(1):50-58.
[15] HUANG N E, SHEN Z, LONG S R, et al. The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis[J]. Proceedings of the Royal Society A:Mathematical Physical and Engineering Sciences, 1998, 454(1971):903-995.
[16] HUANG N E, SHEN Z, LONG S R. A new view of nonlinear water waves:the Hilbert Spectrum[J]. Annual Review of Fluid Mechanics, 1999, 31(1):417-457.
[17] SOUALHI A, MEDJAHER K, ZERHOUNI N. Bearing health monitoring based on Hilbert-Huang transform, support vector machine, and regression[J]. IEEE Transactions on Instrumentation and Measurement, 2015, 64(1):52-62.
[18] 唐贵基, 向玲, 朱永利. 基于HHT的旋转机械油膜涡动和油膜振荡故障特征分析[J]. 中国电机工程学报, 2008, 28(2):77-81 TANG Gui-ji, XIANG Ling, ZHU Yong-li. Fault analysis of oil whirl and oil whip based on Hilbert-Huang transform for rotor system[J]. Proceedings of the Chinese Society for Electrical Engineering, 2008, 28(2):77-81
[19] 李欣, 梅德庆, 陈子辰. 基于经验模态分解和希尔伯特-黄变换的精密孔镗削颤振特征提取[J]. 光学精密工程, 2011, 19(6):1291-1297 LI Xin, MEI De-qing, CHEN Zi-chen. Feature extraction of chatter for precision hole boring processing based on EMD and HHT[J]. Optics and Precision Engineering, 2011, 19(6):1291-1297
[20] CAO H, LEI Y, HE Z. Chatter identification in end milling process using wavelet packets and Hilbert-Huang transform[J]. International Journal of Machine Tools and Manufacture, 2013, 69:11-19.
[21] YEH L J, LAI G J. A study of the monitoring and suppression system for turning slender workpieces[J]. Proceedings of the Institution of Mechanical Engineers, Part B:Journal of Engineering Manufacture, 1995, 209(3):227-236.
[1] 董辉跃, 孙强, 郭英杰, 赵安安, 朱伟东. 机器人孔口倒角加工振动及抑制[J]. 浙江大学学报(工学版), 2018, 52(12): 2243-2252.