Chatter Detection in a Tapered Workpiece During Turning Process Using Acoustic Signals

Self-excited vibrations, also termed as chatter, is present almost in every metal removing process such as turning, milling, and drilling, etc. The chatter limits the desired productivity, and results in part surface finish. Regenerative chatter is the most predominant type of chatter in any machining process which causes excessive vibration between the cutting tool and workpiece. An early detection of chatter can help to achieve high productivity with better surface finish and high metal removal rate. Accurate detection of the chatter is a challenging task, given its reliance on various factors such as cutting conditions and the dynamic characteristics of both the tool and workpiece. The constant fluctuation of these properties during machining operations makes it arduous to forecast chatter during production. In this work, chatter detection using acoustic signal has been explored and compared with the vibration signals during the turning operation on tapered workpieces. The findings reveal that acoustic signals are more effective in detecting chatter as compared to vibration signals.