Feature extraction of chatter for precision hole boring processing based on EMD and HHT

LI Xin; MEI De-qing; CHEN Zi-chen

doi:10.3788/OPE.20111906.1291

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Feature extraction of chatter for precision hole boring processing based on EMD and HHT

Article | 更新时间：2020-08-12

- Feature extraction of chatter for precision hole boring processing based on EMD and HHT
- Optics and Precision Engineering Vol. 19, Issue 6, Pages: 1291-1297(2011)
- 作者机构：
  
  浙江大学现代制造工程研究所浙江省先进制造技术重点实验室,浙江杭州 310027
- 作者简介：
- 基金信息：
- DOI：10.3788/OPE.20111906.1291
  CLC： TG53;TP391.4
- Received：14 July 2010，
  
  Revised：27 October 2010，
  
  Published Online：25 June 2011，
  
  Published：25 June 2011
- 稿件说明：
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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]. Editorial Office of Optics and Precision Engineering, 2011,19(6): 1291-1297
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 DOI： 10.3788/OPE.20111906.1291.

LI Xin, MEI De-qing, CHEN Zi-chen. Feature extraction of chatter for precision hole boring processing based on EMD and HHT[J]. Editorial Office of Optics and Precision Engineering, 2011,19(6): 1291-1297 DOI： 10.3788/OPE.20111906.1291.

摘要

针对精密孔镗削加工过程中容易出现颤振现象

影响精密孔的表面质量问题

建立了镗削加工的监测系统

对镗削颤振信号进行特征提取

以实现对镗削颤振的快速预报。首先

根据颤振信号的时频特点

将经验模态分解(EMD)和希尔伯特-黄变换(HHT)引入颤振特征提取过程

并介绍了其基本原理及具体实现过程。然后

在线拾取镗杆的振动信号

并对振动信号进行EMD分解和HHT变换。最后

通过对各本征模态函数分量的Hilbert谱分析

提取出了颤振发生的征兆特征。实验结果表明

利用EMD和HHT对镗削振动信号进行特征提取

可以在颤振形成之前0.5 s得到颤振爆发的征兆

为后续的颤振抑制工作赢取时间

进而确保精密孔的表面加工质量。

Abstract

For the chatter occured frequently in precise hole boring processing and resulted in low quality of finished surface

a chatter monitoring system was established to finish the feature extraction of the chatter to predict the chatter and gain the precious time for chatter suppression. Firstly

according to the characteristics of chatter signals

Empirical Mode Decomposition(EMD) and Hilbert-Huang Transform(HHT) were introduced to extract the chatter feature

and their basic theories were investigated. Then

the vibration of boring bar was picked up online during the process

and the vibration signal was decomposed by EMD and then transformed by HHT. Finally

the feature of chatter symptom was extracted by analyzing the Hilbert spectrum of each Intrinsic Mode Function(IMF). The experimental results show that extracting chatter feature from vibration of boring bar by EMD and HHT can gain the chatter symptom by 0.5 s ahead of the chatter outbreak

which can provide sufficient guarantee for follow-up chatter suppression and can provide the high quality surface for workpieces.

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Keywords

references

HUANG N E, ZHENG SH, STEVEN R L, et al.. The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis[J]. Pro Royal Society London A, 1998:903-995.[2] Better algorithms for analyzing nonlinear, nonstationary data . http://tco.gsfc.nasa.gov, 2005-07-10.[3] HUANG N E, WU M L, QU W D, et al.. Applications of Hilbert-Huang transform to non-stationary financial time series analysis[J]. Applied Stochastic Models in Business and Industry, 2003,19(3):245-268.[4] 杨永锋,任兴民,秦卫阳,等. 基于EMD方法的混沌时间序列预测[J]. 物理学报,2008, 57(10):6139-6144. YANG Y F, REN X M, QIN W Y, et al.. Prediction of chaotic time series based on EMD method[J]. Acta Physica Sinica, 2008,57(10):6139-6144. (in Chinese)[5] MARCUS D, TORSTEN S. Performance and limitations of the Hilbert-Huang transformation (HHT) with an application to irregular water waves[J].Ocean Engineering, 2004,31(9):1783-1834.[6] LIANG H L, BRESSLER S L, BUFFALO E A, et al.. Empirical mode decomposition of field potentials from macaque V4 in visual spatial attention[J]. Biological Cybernetics, 2005,92:380-392.[7] SENROY N, SURYANARAYANAN S, RIBEIRO P F. An improved Hilbert-Huang method for analysis of time-varying waveforms in power quality[J]. IEEE Transactions on Power Systems, 2007,22(4):1843-1850.[8] 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 G J, XIANG L, ZHU Y L. Fault analysis of oil whirl and oil whip based on hilbert-huang transform for rotor system[J]. Proceedings of the CSEE, 2008,28(2):77-81. (in Chinese)[9] 杨世锡,胡劲松,吴昭同,等. 基于高次样条插值的经验模态分解方法研究[J]. 浙江大学学报(工学版),2004,38(4):267-270. YANG SH X, HU J S, WU ZH T, et al.. Study on empirical mode decomposition based on high-order spline interpolation[J]. Journal of Zhejiang University (Engineering Science), 2004,38(4):267-270. (in Chinese)[10] 孔天荣,梅德庆,陈子辰. 基于变结构刚度抑制精密孔镗削加工的颤振[J]. 光学精密工程,2009,17(12):3040-3046. KONG T R, MEI D Q, CHEN Z CH. Suppression of chatter for precision hole boring based on variable structural stiffness [J]. Opt. Precision Eng., 2009,17(12):3040-3046. (in Chinese)[11] MEI D Q, YAO Z H, KONG T R, et al.. Parameter optimization of time-varying stiffness method for chatter suppression based on magnetorheological fluid controlled boring bar[J]. Int. J. Adv. Manuf. Technol., 2010,46:1071-1083.

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