Chatter stability prediction and detection during high-speed robotic milling process based on acoustic emission technique

Chatter as a common and thorny problem occurs easily during robotic milling process, leading to the instability, severe tool wear and poor surface finish. In this work, an acoustic emission technique was employed to analyze a chatter phenomenon using root mean square (RMS) value and fast Fourier transform method during high-speed robotic milling of aluminum alloys (with cutting speed up to 678 m/min). A stability lobe diagram was proposed to predict the occurrence of chatter with various spindle speeds, which was considered as the most effective tool for chatter analysis. The underline mechanism and theoretical analysis were also presented to provide physical understanding of chatter stability. The cutting force model and robot structure model were firstly established to study chatter mechanism. The stability of a robotic milling system was then analyzed using a zero-order approximation method. Results showed that fast Fourier transform and the time-domain root mean square (RMS) value of acoustic emission signals could be effectively used for detection and verification of chatter in the robotic milling process. The stable cutting zone in the stability lobe diagram was in agreement with experimental results, which can help for the selection of reasonable cutting parameters to avoid chatter and improve efficiency during the high-speed robotic milling process.