한국생산제조학회 학술지 영문 홈페이지
[ Papers ]
Journal of the Korean Society of Manufacturing Technology Engineers - Vol. 28, No. 4, pp.246-252
ISSN: 2508-5107 (Online)
Print publication date 15 Aug 2019
Received 26 Jul 2019 Revised 09 Aug 2019 Accepted 13 Aug 2019
DOI: https://doi.org/10.7735/ksmte.2019.28.4.246

통계학적 변수를 이용한 엔드밀링의 채터 검출법

김종도a ; 지양하b ; 윤문철c, *
Chatter Detection in End-milling Using Stochastic Variables
Jong-Do Kima ; Yang-Ha Jib ; Moon-Chul Yoonc, *
aCenter of industrial Cooperation, Jung-Won University, 85, Munmu-ro, Goesan-eup Goesan-gun, Chungbuk-do, 28024, Korea
bCourse-1 Team, Pusan Human Resources Development Institute, 454-20, Sinsun-ro, Namgu, Pusan 48518, Korea
cDepartment of Mechanical Design Engineering, Pukyong National University, 45, Yongso-ro, Namgu, Pusan 48513, Korea

Correspondence to: *Tel.: +82-51-629-6160 Fax: +82-51-629-6150 E-mail address: mcyoon@pknu.ac.kr (Moon-Chul Yoon)

Abstract

Chatter behavior in end-milling is both complex and closely related to the dynamic unbalanced malfunction phenomenon of the end-milling force; hence, it is difficult to clearly detect and diagnose this behavior using a cutting force. Therefore, this paper presents a new method for detecting chatter in end-milling operations using different stochastic variables such as average, residual, variance, and kurtosis variables. By comparing the histories and stochastic variables of the end-milling force using the fundamental end-milling property, the chatter characteristics can be reviewed and compared with other variables. Stochastic variable threshold values can therefore separate chatter and non-chatter states, and can be used reliably in the detection and prediction of chatter properties in end milling.

Keywords:

Chatter, Cutting force, Kurtosis, Residuals, Variance

References

  • Chin, D. H., Yoon, M. C., Son, S. K., Cho, H. D., 2007, Spectral Analysis of Malfunction Mode in End-milling, Journal of Mechanical Science and Technology, 21 1637-1643. [https://doi.org/10.1007/BF03177387]
  • Ji, Y. H., Kim, J. D., Kim, K. H., Kim. B. T., Yoon, M. C., 2015, Chatter Detection using Dynamic Property Variable, Proc. of the KSMPE Autumn conference, 41.
  • Kim, J. D., Yoon, M. C., Cho, H. D., 2011, An Analysis on the Tooth Passing Frequency using End-milling Force, Journal of the KSMPE, 10:4 1-7.
  • Kay, S. M., 1990, Modern Spectral Estimation: Theory and Application, Prentice Hall, London.
  • Pandit, S. M., Wu, S. M., 1993, Time Series and System Analysis with Applications, John Wiley and Sons, Toronto.
  • Yu, H. D., Chin, D. H., Kim, J. D., Yoon, M. C., 2018, Neural Network Application for Chatter Detection, Journal of the KSMTE, 27:3 203-210. [https://doi.org/10.7735/ksmte.2018.27.3.203]
  • Yoon, M. C., Chin, D. H., 2005, Cutting Force Monitoring in the End-milling Operation for Chatter Detection, Journal of Engineering Manufacture, 12 455-466. [https://doi.org/10.1243/095440505X32292]
  • Shin, J. H., Youn, J. W., 2018, Chatter Monitoring in Head-Tilting 5-axis Machining Centers using an Accelerometer Signal, Journal of the KSMTE, 27:2 132-139. [https://doi.org/10.7735/ksmte.2018.27.2.132]
  • Tlusty, J., Polacek, M., 1963, The Stability of Machine Tools against Self excited Vibrations in Machining, Proceedings of the International Research in Production Engineering Conference, 465-474.
  • Meritt, H. E., 1965, Theory of Self-excited Machine Tool Chatter, Transactions of the ASME, Journal of Engineering for Industry 87 447-454.