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Hybrid model- and signal-based chatter detection in the milling process
Authors:Liu  Meng-Kun  Tran  Minh-Quang  Chung  Chunhui  Qui  Yi-Wen
Affiliation:1.Department of Mechanical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan
;2.Center of Cyber-physical System Innovation, National Taiwan University of Science and Technology, Taipei, Taiwan
;3.Department of Mechanical Engineering, National Cheng Kung University, Tainan, Taiwan
;
Abstract:

Chatter causes machining instability and reduces productivity in the metal cutting process. It has negative effects on the surface finish, dimensional accuracy, tool life and machine life. Chatter identification is therefore necessary to control, prevent, or eliminate chatter and to determine the stable machining condition. Previous studies of chatter detection used either model-based or signal-based methods, and each of them has its drawback. Model-based methods use cutting dynamics to develop stability lobe diagram to predict the occurrence of chatter, but the off-line stability estimation couldn’t detect chatter in real time. Signal-based methods apply mostly Fourier analysis to the cutting or vibration signals to identify chatter, but they are heuristic methods and do not consider the cutting dynamics. In this study, the model-based and signal-based chatter detection methods were thoroughly investigated. As a result, a hybrid model- and signal-based chatter detection method was proposed. By analyzing the residual between the force measurement and the output of the cutting force model, milling chatter could be detected and identified efficiently during the milling process.

Keywords:
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