Milling chatter detection based on VMD and difference of power spectral entropy

Chatter is a kind of unstable vibration in high-speed milling process, leading to poor surface quality of workpiece, significant tool wear, and severe noise. In order to avoid these negative effects of milling chatter, the detection of chatter at early stage is highly needed. In this paper, an early-stage chatter detection method based on variational mode decomposition (VMD) and difference of power spectral entropy (ΔPSE) is presented. Considering that the existence of possible colored noise in the monitoring signals, which might lead to the misjudgment of chatter detection, the signals monitored at spindle’s idling is utilized to identify these noise components. In order to separate the needed chatter-sensitive sub-signals, VMD is utilized to decompose the original signals into a series of intrinsic mode functions (IMFs), and the chatter-sensitive sub-signals are obtained by adding the IMFs whose central frequencies are closed to the milling system’s natural frequency. After that, an adaptive filter is utilized to filter out the harmonics of spindle-speed frequency and the identified colored noise components. Then, a dimensionless indicator is designed, which is determined as the difference of power spectral entropy (ΔPSE) of signals without and with filtering. A series of experiments are also performed, and the results indicate that the presented methodology can detect the chatter at early stage and is applicable in different cutting conditions, which is very important in the practical application.