Tool condition monitoring for cavity milling based on bispectrum analysis and Bayesian optimized SVM
Author:
Funder
National Key Research and Development Program of China
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s00170-024-13849-5.pdf
Reference41 articles.
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2. Han X, Tang L (2015) Precise prediction of forces in milling circular corners. Int J Mach Tools Manuf 88:184–193. https://doi.org/10.1016/j.ijmachtools.2014.09.004
3. Zhang C, Zhang J (2013) On-line tool wear measurement for ball-end milling cutter based on machine vision. Comput Ind 64:708–719. https://doi.org/10.1016/j.compind.2013.03.010
4. Yang X, Yuan R, Lv Y, Li L, Song H (2022) A novel multivariate cutting force-based tool wear monitoring method using one-dimensional convolutional neural network. Sensors 22:8343. https://doi.org/10.3390/s22218343
5. Ertunc HM, Oysu C (2004) Drill wear monitoring using cutting force signals. Mechatronics 14:533–548. https://doi.org/10.1016/j.mechatronics.2003.10.005
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