Advance in chatter detection in ball end milling process by utilizing wavelet transform

This paper presents an advance in chatter detection in ball end milling process. The dynamic cutting forces are monitored by utilizing the wavelet transform. The new three parameters are introduced to classify the chatter and the non-chatter by taking the ratio of the average variances of dynamic cutting forces to the absolute variances of themselves. The Daubechies wavelet is employed in this research to analyze the chatter. The experimental results showed that the chatter frequency occurred in the different levels of wavelet transform due to the different cutting systems. The new algorithm is developed to detect the chatter during the in-process cutting. The experimentally obtained results showed that the chatter can be easier to detect referring to the proposed parameters under various cutting conditions.