Integrating machine learning and feature analysis for predicting and managing thermal deformation in machine tools
This study develops a method to predict and compensate for thermal deformation in machine tools, focusing on selecting temperature-sensitive points, establishing a predictive model, and detecting temperature anomalies. Optimal sensing points were identified using feature ranking algorithms and Parti...
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| Format: | Article |
| Language: | English |
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Elsevier
2024-05-01
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| Series: | Case Studies in Thermal Engineering |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2214157X24003745 |