Detection and identification of cutting chatter based on improved variational nonlinear chirp mode decomposition

摘要

During the turning process of the lathe, the cutting chatter may be generated with the increase of cutting vibration amplitude, which is harmful to machining precision of the turning process. In order to effectively avoid the influence of cutting chatter during the turning process, the improved variational nonlinear chirp mode decomposition (VNCMD) algorithm is presented for the detection and identification of cutting chatter. The wideband and weak characteristic of the vibration signal are considered by the improved algorithm, which cannot only overcome the mode mixing and pseudo-component problems of the empirical mode decomposition (EMD) algorithm but also overcome the drawbacks of the wideband signal extraction. To eliminate the influence of uncertainty of the number of signal components on the decomposition of the VNCMD algorithm, the cross-correlation coefficient method is used to determine the optimal number of signal intrinsic mode functions. And the improved algorithm is further applied to the detection of the cutting chatter, where the fourth-order cumulant, permutation entropy, and instantaneous frequency of the signal intrinsic mode functions are extracted as the multi-feature vector for the cutting chatter. As the results show, it can effectively identify the existence and extent of cutting chatter.