Data-Driven Prediction of Plunge Milling Force Using Stochastic Differential Equations-Reference-Cited by-同舟云学术

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Data-Driven Prediction of Plunge Milling Force Using Stochastic Differential Equations

Published:2024-05-12 Issue: Volume: Page:1-6
ISSN:
Container-title:2024 IEEE 7th International Conference on Industrial Cyber-Physical Systems (ICPS)
language:
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Author:

Hua Feng¹,Wang Yasen¹,Zhou Ziheng²,Yang Zhanpeng²,Wang Zhihui³,Cheng Cheng²

Affiliation:

1. Huazhong University of Science and Technology,School of Mechanical Science and Engineering,Wuhan,China

2. Huazhong University of Science and Technology,School of Artificial Intelligence and Automation,Wuhan,China

3. HUST-Wuxi Research Institute,Institute of Industrial Data Analysis,Wuxi,China

Funder

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10639954/10639940/10640008.pdf?arnumber=10640008

Reference17 articles.

1. Modelling cutting forces in milling on torus cutters

2. Method for rapid characterisation of cutting forces in end milling considering runout

3. Optimum orientation of a torus milling cutter: Method to balance the transversal cutting force

4. A new ternary-mechanism model for the prediction of cutting forces in flat end milling

5. On time-domain methods for milling stability analysis

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