Yongjian Ji

TL;DR: In this paper, the acceleration signals acquired by sensor were decomposed into a series of intrinsic mode functions (IMFs) by the adaptive analysis method named ensemble empirical mode decomposition (EEMD), and the IMFs which contain the feature information of milling process were selected as the analyzed signals.

TL;DR: The results of milling experiment show that the proposed chatter identification method can recognize early milling chatter effectively and a support vector machine chatter identification model is obtained based on the multi-indicators.

TL;DR: Based on third-order Newton interpolation polynomial and direct integration scheme (DIS), a method to generate stability lobe diagram in milling process is proposed and proved to be an accurate and efficient method by the comparison results.

TL;DR: An updated full-discretization milling stability prediction method which based on the third-order Hermite-Newton interpolation polynomial approximation is proposed in this paper and results indicate that the proposed method show a faster convergence rate than that of other methods, and its SLD is more close to the ideal ones with small number of time intervals.

TL;DR: In this paper, a new five-axis ball-end machining dynamical model which considers the multiple interactions between the tool and workpiece is established for the first time, and the effects of regenerative effect, structural mode coupling and process damping on the dynamic characteristics of 5-axis milling are investigated.