A Comparison of Wavelet Packet, Wavelet Leaders Multifractal, and p-Leader Multifractal Method in Chatter Detection.

An efficient stability analysis contributes to the improvement of machining stability and chatter suppression. First, this paper presents three chatter detection approaches that were developed on the application of wavelet transforms. Second, the feasibility of the methods for chatter detection is verified by combining numerical simulations and experimental research. Finally, the recognition performance of the three methods is compared. The analysis results indicate that the proposed three methods can distinguish different machining states. The p-leader multifractal method (PLMM) provides the best recognition performance but takes the longest time, the wavelet leader multifractal method (WLMM) comes second, and the wavelet packet method (WPM) is the worst but takes the shortest amount of time. Therefore, the PLMM can be used for identifying signals with high accuracy requirements, whereas the WLMM or WPM can be used otherwise.Highlights: Three methods for judging the stability of micro milling process are proposed by using wavelet packet method (WPM), wavelet leaders multifractal method (WLMM) and p-leader multifractal method (PLMM). The feasibility of WPD, WLMM, and PLMM in stability analysis was preliminarily verified through numerical simulation. The recognition performance of WPD, WLMM, and PLMM for chatter detection is compared. [ABSTRACT FROM AUTHOR]