Chatter is the major factor affecting the efficiency of high-speed milling.Chatter signal in milling has obvious nonlinear and non-stationary properties.It is difficult for the conventional signal analysis method to deal with signals in such category.This paper presented a multi-component signal decomposition method based on instantaneous frequency estimation and the Vold-Kalman filter.And the signal decomposition method was applied to chatter detection.First, the instantaneous frequency parameters of the signals were estimated based on the spectral concentration index.Then, the Vold-Kalman filter was applied to extract the signal components corresponding to the estimated parameters.Since the energy distribution of the milling force signal changed in the frequency domain as a result of chatter, the definition of energy entropy was introduced.Finally, chatter was identified by the change of energy entropy of the sub-signal.The experimental results show that the method is effective and feasible.
汪晓姗，彭志科，陈是扦. 基于瞬时频率估计与Vold-Kalman滤波的铣削颤振识别[J]. 振动与冲击, 2018, 37(16): 70-76.
WANG Xiaoshan，PENG Zhike，CHEN Shiqian. Chatter detection in milling process based on instantaneous frequency estimation and the Vold-Kalman filter. JOURNAL OF VIBRATION AND SHOCK, 2018, 37(16): 70-76.
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