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The chatter phenomenon shows the dynamic characteristics of tool vibration in the endmilling process and will change according to the irregular dynamic characteristics of that tool vibration. This chatter produces an adverse effect on tool life, machining integrity, surface quality of the workpiece, and other geometric accuracy. Chatter behaviour in endmilling is a complex, non-linear phenomenon, which is very difficult to detect and diagnose. It is therefore necessary to suggest a new method for analysing chatter mechanics. This paper presents a new method for the detection of chatter in the endmilling operation based on the wavelet transform. This wavelet transform method provides various ways to determine chatter characteristics. The fundamental coefficient property of the wavelet transform is reviewed. The reliability of the wavelet transform method is verified by comparing the spectra using the fast Fourier transform (FFT). The behaviour of the detail coefficients obtained by wavelet transform reveals the possibility to detect and analyse chatter and other malfunction states using tool dynamometer cutting force. Because wavelets are closely related to filter, the method presented in this paper can be applied to other real-time cutting force monitoring and analysis in a range of endmilling processes.

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