Research on Tool Wear Monitoring Based on ET-GD and K-nearest Neighbor Algorithm
Aiming at the problem of tool wear monitoring in milling process , a tool wear monitoring method based on extreme random tree and Gaussian distribution and K-nearest neighbor is proposed. In this method ,truncation method and Hampel filtering method are used to eliminate outliers and singular point...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Harbin University of Science and Technology Publications
2023-02-01
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| Series: | Journal of Harbin University of Science and Technology |
| Subjects: | |
| Online Access: | https://hlgxb.hrbust.edu.cn/#/digest?ArticleID=2171 |
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