Chatter detection in milling based on the probability distribution of cutting force signal

This paper proposes a new method for in-process detection of chatter in milling, which is based on the probability distribution of the cutting force signal. First, it is shown that under stable cutting conditions, the probability distribution of the cutting force displays the characteristics of a sinusoidal function. However, under chatter conditions, the probability distribution of the cutting force approaches that of a Gaussian white noise. Then, a monitoring strategy based on the probability distribution of the cutting forces is proposed. The strategy is investigated using computer simulations and verified experimentally under various cutting conditions. The results indicate the proposed monitoring strategy is effective in discriminating between stable and chatter conditions.