A Chatter Monitoring Method for Robotic Machining Using Synchro-Squee-ed Transform and Energy Entropy

doi:10.7652/xjtuxb201908004

您当前的位置：

首页 >

文章列表页 >

A Chatter Monitoring Method for Robotic Machining Using Synchro-Squee-ed Transform and Energy Entropy

更新时间：2025-07-09

- A Chatter Monitoring Method for Robotic Machining Using Synchro-Squee-ed Transform and Energy Entropy
- Vol. 53, Issue 8, Pages: 24-30+89(2019)
- 作者机构：
  
  上海飞机制造有限公司,上海,200240
- 作者简介：
- 基金信息：
- DOI：10.7652/xjtuxb201908004
  CLC： TH17;TP181
- Online First：10 August 2019，
  
  Published：2019
- 稿件说明：
移动端阅览
A Chatter Monitoring Method for Robotic Machining Using Synchro-Squee-ed Transform and Energy Entropy[J]. 2019, 53(8): 24-30+89.
DOI：

A Chatter Monitoring Method for Robotic Machining Using Synchro-Squee-ed Transform and Energy Entropy[J]. 2019, 53(8): 24-30+89. DOI： 10.7652/xjtuxb201908004.

摘要

为避免机器人加工过程中颤振给加工质量及刀具寿命带来不利影响

提出了一种基于同步压缩变换和能量熵的机器人加工颤振监测方法。首先

利用同步压缩变换获取主轴振动信号高分辨率时频谱

并将获得的时频谱均分为有限个频带; 然后

对各频带对应的时域子信号进行重构并求取其能量值; 最后

采用能量熵作为表征颤振能量分布变化的特征量

通过计算所有子信号的能量熵之和对颤振进行在线监测。在库卡工业机器人加工实验平台上

开展了机器人制孔加工实验验证

实验结果表明:在不同的机器人加工条件下

所提方法均能在颤振发生前22 ms左右有效地将其检测出来; 计算一次能量熵的时长约为20 ms

能够基本满足颤振在线监测的实时性要求。

Abstract

A chatter monitoring method of robotic machining process based on synchro-squee-ed transform and energy entropy is proposed to avoid the adverse effects of chatter on machining quality and tool life during robotic machining. Firstly

the synchro-squee-ed transform is applied to obtain the high-resolution time-frequency description of the spindle vibration signal

and then the time-frequency description is equally divided into a finite number of frequency bands. Secondly

the time-domain sub-signal corresponding to each frequency band is reconstructed and the energy value of the sub-signal is calculated. Finally

the energy entropy is utili-ed to characteri-e the energy distribution of the chatter. The chatter is monitored online by calculating the sum of energy entropy of all sub-signals. Robotic drilling experiments are conducted on a KUKA industrial robot machining experimental platform to verify the proposed chatter monitoring method. Results show that the proposed algorithm effecti

关键词

Keywords

references

CHEN Y, DONG F. Robot machining: recent development and future research issues [J]. International Journal of Advanced Manufacturing Technology, 2013, 66(9/10/11/12): 1489-1497.

曲巍崴, 侯鹏辉, 杨根军, 等. 机器人加工系统刚度性能优化研究 [J]. 航空学报, 2013, 34(12): 2823-2832.

QU Weiwei, HOU Penghui, YANG Genjun, et al. Research on the stiffness performance for robot machining systems [J]. Acta Aeronautica et Astronautica Sinica, 2013, 34(12): 2823-2832.

方强, 李超, 费少华, 等. 机器人镗孔加工系统稳定性分析 [J]. 航空学报, 2016, 37(2): 727-737.

FANG Qiang, LI Chao, FEI Shaohua, et al. Stability analysis of robot boring system [J]. Acta Aeronautica et Astronautica Sinica, 2016, 37(2): 727-737.

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.

YUAN L, PAN Z, DING D, et al. A review on chatter in robotic machining process regarding both regenerative and mode coupling mechanism [J]. IEEE/ASME Transactions on Mechatronics, 2018, 23(5): 2240-2251.

王战玺, 张晓宇, 李飞飞, 等. 机器人加工系统及其切削颤振问题研究进展 [J]. 振动与冲击, 2017, 36(14): 147-155.

WANG Zhanxi, ZHANG Xiaoyu, LI Feifei, et al. Review on the research developments of robot machining systems and cutting chatter behavior [J]. Journal of Vibration and Shock, 2017, 36(14): 147-155.

WANG G, DONG H, GUO Y, et al. Early chatter identification of robotic boring process using measured force of dynamometer [J]. International Journal of Advanced Manufacturing Technology, 2013, 94(1/2/3/4): 1243-1252

THALER T, POTOACˇUNIK P, BRIC I, et al. Chatter detection in band sawing based on discriminant analysis of sound features [J]. Applied Acoustics, 2014, 77: 114-121.

LIU Y, WANG X, LIN J, et al. Early chatter detection in gear grinding process using servo feed motor current [J]. International Journal of Advanced Manufacturing Technology, 2016, 83(9/10/11/12): 1801-1810.

LIU H Q, CHEN Q H, Li B, et al. On-line chatter detection using servo motor current signal in turning [J]. Science China: Technological Sciences, 2011, 54: 3119-3129.

SHAO Y, DENG X, YUAN Y, et al. Characteristic recognition of chatter mark vibration in a rolling mill based on the non-dimensional parameters of the vibration Signal [J]. Journal of Mechanical Science Technology, 2014, 28(6): 2075-2080.

QIN C, TAO J, WANG M, et al. A novel approach for the acquisition of vibration signals of the end effector in robotic drilling [C]∥IEEE International Conference on Aircraft Utility Systems. Piscataway, NJ, USA: IEEE, 2016: 522-526.

YAO Z, MEI D, CHEN Z. On-line chatter detection and identification based on wavelet and support vector machine [J]. Journal of Materials Processing Technology, 2010, 210(5): 713-719.

LIU C, ZHU L, NI C. Chatter detection in milling process based on VMD and energy entropy [J]. Mechanical Systems Signal Processing, 2018, 105: 169-182.

DAUBECHIES I, LU J, WU H T. Synchro-squeezed wavelet transforms: an empirical mode decomposition-like tool [J]. Applied Computational Harmonic Analysis, 2011, 30(2): 243-261.

TAO J, QIN C, LIU C. A synchroextracting-based method for early chatter identification of robotic drilling process [J]. International Journal of Advanced Manufacturing Technology, 2019, 100: 273-285

董辉跃, 吴杨宝, 郭英杰, 等. 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 Huiyue, WU Yangbao, GUO Yingjie, et al. Chatter analysis and identification in robotic fine boring of aircraft intersection holes [J]. Journal of Zhejiang University(Engineering Science), 2018, 52(8): 1517-1525.

YANG Y, YU D, CHENG J. A roller bearing fault diagnosis method based on EMD energy entropy and ANN [J]. Journal of Sound Vibration, 2006, 294(1): 269-277.

ZHANG Z, LI H, MENG G, et al. Chatter detection in milling process based on the energy entropy of VMD and WPD [J]. International Journal of Machine Tools Manufacture, 2016, 108: 106-112.

张智, 刘成颖, 刘辛军, 等. 采用小波包能量熵的铣削振动状态分析方法研究 [J]. 机械工程学报, 2018, 54(21): 57-62.

ZHANG Zhi, LIU Chengying, LIU Xinjun, et al. Analysis of milling vibration state based on the energy entropy of WPD [J]. Journal of Mechanical Engineering, 2018, 54(21): 57-62.

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Key Technologies and System Development of Intelligent Electric Spindles

Analysis and Implementation for Technique for Cutting Chatter Monitoring

Faulty Line Identification in Distribution Network Based on Combined Modulus and S-Transform Energy Entropy

I/O Performance Modeling and Prediction Method for Large-Scale Parallel Applications Using Machine Learning

Integrated and Joint Design Optimization of Centrifugal Compressor Impeller and Casing Treatment at Multiple Working Points

Related Author

LI Xiaohu

WAN Shaoke

HONG Jun

吕凯波

景敏卿

张永强

刘恒

李猛

Related Institution

西安交通大学机械工程学院，710049，西安School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an 710049, China

School of Mechanical Engineering, Xi'an Jiaotong University

School of Electrical and Control Engineering, Xi'an University of Science and Technology

⁰