Abstract

In metal cutting processes, the chatter may cause fast wear of tools and poor surface quality of the processed parts; it can happen on different cutting parameters, but how do we identify the chatter and how do we select suitable cutting parameters to avoid chatter at high material removal rate (MRR). In this paper, the signal processing methods such as time domain, frequency domain, and time–frequency domain analysis are introduced. The signals of cutting force that were collected in milling titanium alloy Ti–6Al–4V at variable cutting speeds varied from 80 to 360 m/min; signal analysis methods such as time domain, frequency domain, and time–frequency domain were put forward. Further analysis results reveal that the chatter occur when cutting speeds are 240 and 360 m/min, when the maximum value of cutting forces increase by 61.9–66.8%, the standard deviation increase by 84.1–86.1%, and the surface roughness increase by 34.2–40.5% compared with that of at 80 m/min. Detail signal d2 is employed to monitor cutting stability state from the result of wavelet analysis.

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