Tool Wear State Identification Method with Variable Cutting Parameters Based on Multi-Source Unsupervised Domain Adaptation
Accurately identifying tool wear states with variable cutting parameters can improve machining quality and efficiency. However, existing wear state recognition methods based on unsupervised domain adaptation mostly employ the knowledge transfer learning strategy in a single source domain. They canno...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-03-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/25/6/1742 |
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