Milling Cutter Wear Prediction Based on Feature Extraction and LongShort-term Memory Neural Networks
The wear of milling cutters during high-speed milling processes affects the quality of the work-piece, productivity and manufacturing costs. Accurate tool wear prediction can therefore optimize production decisions and avoid losses due to tool wear. To improve the prediction precision, this paper pr...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Editorial Office of Control and Information Technology
2021-01-01
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| Series: | Kongzhi Yu Xinxi Jishu |
| Subjects: | |
| Online Access: | http://ctet.csrzic.com/thesisDetails#10.13889/j.issn.2096-5427.2021.04.100 |
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