Early chatter identification based on optimized VMD with multi-band information fusion and compression method in robotic milling process  

作　　者：Sichen CHEN Zhiqiang LIANG Yuchao DU Zirui GAO Haoran ZHENG Zhibing LIU Tianyang QIU Xibin WANG 

机构地区：[1]School of Mechanical Engineering,Beijing Institute of Technology,Beijing 100081,China [2]Beijing Institute of Technology Chongqing Innovation Center,Chongqing 401120,China

出　　处：《Chinese Journal of Aeronautics》2024年第6期464-484,共21页中国航空学报（英文版）

基　　金：supported by the Civil Aircraft Project(No.MJZ4-1N22),National Natural Science Foundation of China(No.51975053);Inversion and Application Project of Outcome(Nos.D44F9A65 and 2B0188E1);Key R&D Program of Inner Mongolia(No.2022YFHH0121);the Basic Research Fund of Beijing Institute of Technology(No.2021CX01023).

摘　　要：Undesirable self-excited chatter has always been a typical issue restricting the improvement of robotic milling quality and efficiency.Sensitive chatter identification based on processing signals can prompt operators to adjust the machining process and prevent chatter damage.Compared with the traditional machine tool,the uncertain multiple chatter frequency bands and the band-moving of the chatter frequency in robotic milling process make it more challenging to extract chatter information.This paper proposes a novel method of chatter identification using optimized variational mode decomposition(OVMD)with multi-band information fusion and compression technology(MT).During the robotic milling process,the number of decomposed modes k and the penalty coefficient a are optimized based on the dominant component of frequency scope partition and fitness of the mode center frequency.Moreover,the mayfly optimization algorithm(MA)is employed to obtain the global optimal parameter selection.In order to conquer information collection about the uncertain multiple chatter frequency bands and the band-moving of the chatter frequency in robotic milling process,MT is presented to reduce computation and extract signal characteristics.Finally,the cross entropy of the image(CEI)is proposed as the final chatter indicator to identify the chatter occurrence.The robotic milling experiments are carried out to verify the proposed method,and the results show that it can distinguish the robotic milling condition by extracting the uncertain multiple chatter frequency bands and overcome the band-moving of the chatter frequency in robotic milling process.

关 键 词：Robotic milling Chatter detection Variational mode decomposition Information fusion and compression Chatter featur 

分 类 号：V26[航空宇航科学与技术—航空宇航制造工程] V46