Milling cutter breakage detection based on VMD

被引：0
|
作者：
Wang X. [1 ]
He L. [1 ]
Wang P. [1 ]
Gao Z. [1 ]
机构：
[1] School of Mechanical Science & Engineering, Huazhong University of Science and Technology, Wuhan
来源：
Zhendong yu Chongji/Journal of Vibration and Shock | 2020年 / 39卷 / 16期
关键词：
Cutting vibration signals; Support vector machine (SVM); Tool condition monitoring; Variational mode decomposition (VMD);
D O I：
10.13465/j.cnki.jvs.2020.16.019
中图分类号：
学科分类号：
摘要：
Aiming at the non-stationary characteristics of the cutting vibration signal in the end milling process, a milling cutter breakage detection method based on variational mode decomposition (VMD) was proposed. The method decomposes the cutting vibration signal into several modal components by VMD. After the milling cutter is broken, the frequency band distribution of different modal components will change, and the center frequency and energy of each modal component are extracted to construct a feature vector. The feature vector was normalized and input to the support vector machine (SVM) for milling cutter breakage detection. Milling experiments under various cutting parameters show that the method can suppress modal mixture and has higher detection accuracy than the EMD-based milling cutter damage detection method. © 2020, Editorial Office of Journal of Vibration and Shock. All right reserved.
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页码：135 / 140and162
相关论文
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