A deep learning model for online prediction of in-process dynamic characteristics of thin-walled complex blade machining
Author:
Funder
National Natural Science Foundation of China
National Key R &D Program of China
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s10845-024-02369-4.pdf
Reference63 articles.
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4. Bravo, U., Altuzarra, O., De Lacalle, L. L., Sánchez, J., & Campa, F. (2005). Stability limits of milling considering the flexibility of the workpiece and the machine. International Journal of machine tools and manufacture, 45(15), 1669–1680.
5. Cao, L., Huang, T., Shi, D.-M., Zhang, X.-M., & Ding, H. (2020). Active chatter suppression in low immersion intermittent milling process. Journal of Manufacturing Science and Engineering, 142(10), 101005.
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