Timely Chatter Detecting Method in Milling with Integrated Energy Ratio and Amplitude Standard Deviation of Vibration Signal
LI Chao1, ZHANG Jun1, TIAN Hui2, ZHAO Wanhua1
1. State Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an 710054; 2. AVIC Xi'an Aircraft Industry Group Company Limited, Xi'an 710089
LI Chao, ZHANG Jun, TIAN Hui, ZHAO Wanhua. Timely Chatter Detecting Method in Milling with Integrated Energy Ratio and Amplitude Standard Deviation of Vibration Signal[J]. Journal of Mechanical Engineering, 2024, 60(14): 11-23.
[1] CALISKAN H,KILIC Z M,ALTINTAS Y. On-line energy-based milling chatter detection[J]. Journal of Manufacturing Science and Engineering,Transactions of the ASME,2018,140(11):111012. [2] ZHENG Q Z,CHEN G S,JIAO A L. Chatter detection in milling process based on the combination of wavelet packet transform and PSO-SVM[J]. The International Journal of Advanced Manufacturing Technology,2022,120(1-2):1237-1251. [3] 张奇. 铣削加工颤振稳定性分析和颤振辨识研究[D]. 上海:上海交通大学,2020. ZHANG Qi. Study on stability analysis and identification and detection of chatter in milling process[D]. Shanghai:Shanghai Jiao Tong University,2020. [4] WANG B Q,WEI Y,LIU S L,et al. Intelligent chatter detection for CNC machine based on RFE multi-feature selection strategy[J]. Measurement Science and Technology,2021,32(9):095904. [5] CHEN H G,SHEN J Y,CHEN W H,et al. Grinding chatter detection and identification based on BEMD and LSSVM[J]. Chinese Journal of Mechanical Engineering,2019,32(1):90-102. [6] FU Y,ZHANG Y,ZHOU H M,et al. Timely online chatter detection in end milling process[J]. Mechanical Systems and Signal Processing,2016,75(1):668-688. [7] LI K,HE S P,LUO B,et al. Online chatter detection in milling process based on VMD and multiscale entropy[J]. The International Journal of Advanced Manufacturing Technology,2019,105(4):5009-5022. [8] MOU W P,ZHU S W,JIANG Z X,et al. Vibration signal-based chatter identification for milling of thin-walled structure[J]. Chinese Journal of Aeronautics,2022,35(1):204-214. [9] LIU X L,WANG Z X,LI M Y,et al. Feature extraction of milling chatter based on optimized variational mode decomposition and multi-scale permutation entropy[J]. The International Journal of Advanced Manufacturing Technology,2021,114(1):2849-2862. [10] YANG K,Wang G F,Dong Y,et al. Early chatter identification based on an optimized variational mode decomposition[J]. Mechanical Systems and Signal Processing,2019,115(1):238-254. [11] ZHANG P F,GAO D,LU Y,et al. Online chatter detection in milling process based on fast iterative VMD and energy ratio difference[J]. Measurement,2022,194(1):111060. [12] NIU J C,Ning G C,Shen Y J,et al. Detection and identification of cutting chatter based on improved variational nonlinear chirp mode decomposition[J]. The International Journal of Advanced Manufacturing Technology,2019,104(5-8):2567-2578. [13] 侯慧杰. 基于傅里叶分解方法和径向基神经网络的铣削颤振检测研究[D]. 武汉:华中科技大学,2020. HOU Huijie. Research on milling chatter detection based on fourier decomposition method and rbf neural network[D]. Wuhan:Huazhong University of Science and Technology,2020. [14] YAO Y C,CHEN Y H,LIU C H,et al. Real-time chatter detection and automatic suppression for intelligent spindles based on wavelet packet energy entropy and local outlier factor algorithm[J]. The International Journal of Advanced Manufacturing Technology,2019,103(1-4):297-309. [15] PERRELLI M,COSCO F,GAGLIARDI F,et al. In-process chatter detection using signal analysis in frequency and time-frequency domain[J]. Machines,2021,10(1):24-24. [16] LIU C F,GAO X J,CHI D X,et al. On-line chatter detection in milling using fast kurtogram and frequency band power[J]. European Journal of Mechanics / A Solids,2021,90(1):104341. [17] CHEN D,ZHANG X J,ZHAO H,et al. Development of a novel online chatter monitoring system for flexible milling process[J]. Mechanical Systems and Signal Processing,2021,159(1):107799. [18] RAHIMI M H,HUYNH H N,ALTINTAS Y. On-line chatter detection in milling with hybrid machine learning and physics-based model[J]. CIRP Journal of Manufacturing Science and Technology,2021,35(1):25-40. [19] 张磊,郑侃,孙连军,等. 基于小波包敏感频带选择的复材铣边颤振监测研究[J]. 机械工程学报,2022,58(3):140-148. ZHANG Lei,ZHENG Kan,SUN Lianjun,et al. Investigation on chatter monitoring of composite milling edge based on the selection of sensitive frequency band of wavelet packet[J]. Journal of Mechanical Engineering,2022,58(3):140-148. [20] YAN S C,SUN Y W. Early chatter detection in thin-walled workpiece milling process based on multi-synchrosqueezing transform and feature selection[J]. Mechanical Systems and Signal Processing,2022,169(1):108622-108622. [21] 韩振宇,金鸿宇,富宏亚. 基于ESPRIT频谱估计和隐马尔可夫模型的铣削颤振辨识系统建模[J]. 计算机集成制造系统,2016,22(8):1938-1944. HAN Zhenyu,JIN Hongyu,FU Hongya. Modeling of chatter recognition system in CNC milling based on ESPRIT and hidden Markov model[J]. Computer Integrated Manufacturing Systems,2016,22(8):1938-1944. [22] CHEN K H,ZHANG X,ZHAO Z,et al. Milling chatter monitoring under variable cutting conditions based on time series features[J]. The International Journal of Advanced Manufacturing Technology,2021,113(1):2595-2613. [23] YEH L J,LAI G J. A study of the monitoring and suppression system for turning slender workpieces[J]. Proceedings of the Institution of Mechanical Engineers,Part B:Journal of Engineering Manufacture,1995,209(3):227-236. [24] SENER B,GUDELEK M U,OZBAYOGLU A M,et al. A novel chatter detection method for milling using deep convolution neural networks[J]. Measurement,2021,182(1):109689.