CNC Interpolator Parameter Optimization using Deep Learning-Reference-Cited by-同舟云学术

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CNC Interpolator Parameter Optimization using Deep Learning

Published:2022-10-28 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE 4th Eurasia Conference on IOT, Communication and Engineering (ECICE)
language:
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Author:

Lin Jian-An¹,Lin Ming-Tsung²,Li Yong-Zhong³,Wang Ya-Hsuan³

Affiliation:

1. National Formosa University,Dept. of Mechanical Design Engineering,Yunlin,Taiwan

2. National Formosa University,Dept. of Mechanical Design Engineering & Smart Machine and Intelligent Manufacturing Research Center,Yunlin,Taiwan

3. National Formosa University,Dept. of Precision Mechanical Engineering,Yunlin,Taiwan

Funder

Ministry of Science and Technology

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10042470/10042811/10042898.pdf?arnumber=10042898

Reference20 articles.

1. A fully real-time spline interpolation algorithm with axial jerk constraint based on FIR filtering

2. Global tool-path smoothing for CNC machine tools with uninterrupted acceleration

3. A G3 continuous tool path smoothing method for 5-axis CNC machining

4. Kinematic corner smoothing for high speed machine tools

5. Optimization of Computer Numerical Control Interpolation Parameters Using a Backpropagation Neural Network and Genetic Algorithm with Consideration of Corner Vibrations

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. CNC Interpolator Tuning based on Digital Twin of Five-axis Machines;2023 IEEE 5th Eurasia Conference on IOT, Communication and Engineering (ECICE);2023-10-27

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