This paper presents a model-based computationally efficient method for detecting milling chatter in its incipient stages. Based on a complex exponentials model for the dynamic chip thickness, the chip regeneration effect is amplified and isolated from the cutting force signal for early chatter detection. The proposed method is independent of the cutting conditions. With the aid of a one tap adaptive filter, the proposed method is also found to be able to distinguish between chatter and the dynamic transients in the cutting forces due to sudden changes in workpiece geometry and tool entry/exit. The proposed method is experimentally validated.

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