Abstract
In vertical milling process of Ti-6Al-4V titanium alloy thin-walled workpieces, chatter as a thorny problem occurs easily, which can lead to the instability of the machining process, tool wear, and poor surface finish. It has become a focus issue to identify and avoid chatter in machining process. In this paper, the milling force signals in the direction perpendicular to the machined surface were analyzed by fast Fourier transform and wavelet transform for detecting chatter. The combination of the surface topography and the prediction theory of regenerative chatter were put forward to further verify chatter. The results show that fast Fourier transform in some cases, wavelet transform, and the combination of surface topography and the prediction theory of regenerative chatter can obtain better results for the detection and verification of chatter, and the stable cutting zone was obtained using a stability lobe diagram, which can assist in the selection of reasonable cutting parameters to avoid chatter.