Analysis of Chatter in Ball End Milling by Wavelet Transform
The chatter is one of the major limitations of the productivity in the ball end milling process. It affects the surface roughness, the dimensional accuracy and the tool life. The aim of this research is to propose the new system to detect the chatter during the ball end milling process by using the wavelet transform. The proposed method is implemented on the 5-axis CNC machining center and the new three parameters are introduced from three dynamic cutting forces, which are calculated by taking the ratio of the average variances of dynamic cutting forces to the absolute variances of themselves. It had been proved that the chatter can be easier to detect during the in-process cutting by using the new parameters which are proposed in this research. The experimentally obtained results showed that the wavelet transform can provide the reliable results to detect the chatter under various cutting conditions.
[1] Y. Altintas, "Manufacturing automation : principles of metal cutting and machine tool vibrations", Cambribge University Press, 2000.
[2] Y. Altintas, "Analytical prediction of three dimensional chatter stability
in milling", Japan society of mechanical engineers, Volume 44(3),
Pages 717-723, 2001
[3] J. Kwak, "Application of wavelet transform technique to detect tool
failure in turning operations", The International Journal of Advanced Manufacturing Technology, Volume 28, Issue 11, Pages 1078-1083,
2005
[4] K. Bickraj, B. Kaya, A. Yapici, M. Li, I. N. Tansel, B. Ozcelik, "Inspection of Chatter Damage in End Milling Operations by Using
Wavelet Transformations", 5th International Latin American and
Caribbean Conference for Engineering and Technology. Tempaco,
Mexico, 2007
[5] Z. Yao, D. Mei, Z. Chen, "On-line chatter detection and identification
based on wavelet and support vector machine" Journal of Materials
Processing Technology, Volume 210, Issue 5, Pages 713-719, 2010
[6] E. Kuljanic, G. Totis, M. Sortino, "Development of an intelligent multisensor chatter detection system in milling" Mechanical Systems and Signal Processing, Volume 23, Issue 5, Pages 1704-1718, 2009.
[7] S. Tangjitsitcharoen, N. Pongsathornwiwat, "Development of Chatter
Detection in Milling Processes", The International Journal of advanced
Manufacturing Technology, 2012.
[8] P. S. Addison, "The Illustrated Wavelet Transform Handbook, Introductory Theory and Applications in Science, Engineering, Medicine and Finance", Institute of Physics Publishing Bristol and Philadelphi,2002.
[9] A. Graps, “An Introduction to Wavelets” Computational Science &
Engineering, IEEE, Volume 2, Issue 2, Pages 50-61, 1995.
[10] L. Xiaoli, S. Dong, Y. Zhejun, “Discrete wavelet transform for tool
breakage monitoring” International Journal of Machine Tools &
Manufacture, Volume 39, Pages 1935–1944, 1999.
[11] M. C. Yoon, D. H. Chin, “Cutting force monitoring in the endmilling
operation for chatter detection”, Proceedings of the Institution of
Mechanical Engineers, Part B: Journal of Engineering Manufacture,
Volume 219, no. 6, Pages 455-465, 2005.
[12] Z. Yao, D. Mei, Z. Chen, “On-line chatter detection and identification
based on wavelet and support vector machine” Journal of Materials
Processing Technology, Volume 210, Issue 5, Pages 713-719, 2010.
[13] T. Kanungo, D. M. Mount, N. S. Netanyahu, C. D. Piatko,
R. Silverman, A. Y. Wu, “An efficient k-means clustering algorithm:
Analysis and implementation”, IEEE Trans. Pattern Analysis and
Machine Intelligence, Volume 24, Pages 881–892, 2002
[1] Y. Altintas, "Manufacturing automation : principles of metal cutting and machine tool vibrations", Cambribge University Press, 2000.
[2] Y. Altintas, "Analytical prediction of three dimensional chatter stability
in milling", Japan society of mechanical engineers, Volume 44(3),
Pages 717-723, 2001
[3] J. Kwak, "Application of wavelet transform technique to detect tool
failure in turning operations", The International Journal of Advanced Manufacturing Technology, Volume 28, Issue 11, Pages 1078-1083,
2005
[4] K. Bickraj, B. Kaya, A. Yapici, M. Li, I. N. Tansel, B. Ozcelik, "Inspection of Chatter Damage in End Milling Operations by Using
Wavelet Transformations", 5th International Latin American and
Caribbean Conference for Engineering and Technology. Tempaco,
Mexico, 2007
[5] Z. Yao, D. Mei, Z. Chen, "On-line chatter detection and identification
based on wavelet and support vector machine" Journal of Materials
Processing Technology, Volume 210, Issue 5, Pages 713-719, 2010
[6] E. Kuljanic, G. Totis, M. Sortino, "Development of an intelligent multisensor chatter detection system in milling" Mechanical Systems and Signal Processing, Volume 23, Issue 5, Pages 1704-1718, 2009.
[7] S. Tangjitsitcharoen, N. Pongsathornwiwat, "Development of Chatter
Detection in Milling Processes", The International Journal of advanced
Manufacturing Technology, 2012.
[8] P. S. Addison, "The Illustrated Wavelet Transform Handbook, Introductory Theory and Applications in Science, Engineering, Medicine and Finance", Institute of Physics Publishing Bristol and Philadelphi,2002.
[9] A. Graps, “An Introduction to Wavelets” Computational Science &
Engineering, IEEE, Volume 2, Issue 2, Pages 50-61, 1995.
[10] L. Xiaoli, S. Dong, Y. Zhejun, “Discrete wavelet transform for tool
breakage monitoring” International Journal of Machine Tools &
Manufacture, Volume 39, Pages 1935–1944, 1999.
[11] M. C. Yoon, D. H. Chin, “Cutting force monitoring in the endmilling
operation for chatter detection”, Proceedings of the Institution of
Mechanical Engineers, Part B: Journal of Engineering Manufacture,
Volume 219, no. 6, Pages 455-465, 2005.
[12] Z. Yao, D. Mei, Z. Chen, “On-line chatter detection and identification
based on wavelet and support vector machine” Journal of Materials
Processing Technology, Volume 210, Issue 5, Pages 713-719, 2010.
[13] T. Kanungo, D. M. Mount, N. S. Netanyahu, C. D. Piatko,
R. Silverman, A. Y. Wu, “An efficient k-means clustering algorithm:
Analysis and implementation”, IEEE Trans. Pattern Analysis and
Machine Intelligence, Volume 24, Pages 881–892, 2002
@article{"International Journal of Mechanical, Industrial and Aerospace Sciences:62830", author = "S. Tangjitsitcharoen", title = "Analysis of Chatter in Ball End Milling by Wavelet Transform", abstract = "The chatter is one of the major limitations of the productivity in the ball end milling process. It affects the surface roughness, the dimensional accuracy and the tool life. The aim of this research is to propose the new system to detect the chatter during the ball end milling process by using the wavelet transform. The proposed method is implemented on the 5-axis CNC machining center and the new three parameters are introduced from three dynamic cutting forces, which are calculated by taking the ratio of the average variances of dynamic cutting forces to the absolute variances of themselves. It had been proved that the chatter can be easier to detect during the in-process cutting by using the new parameters which are proposed in this research. The experimentally obtained results showed that the wavelet transform can provide the reliable results to detect the chatter under various cutting conditions.
", keywords = "Ball end milling, wavelet transform, fast fourier transform, chatter.", volume = "6", number = "11", pages = "2573-7", }
