Predicting the coefficient of friction in a sliding contact by applying machine learning to acoustic emission data
Abstract It is increasingly important to monitor sliding interfaces within machines, since this is where both energy is lost, and failures occur. Acoustic emission (AE) techniques offer a way to monitor contacts remotely without requiring transparent or electrically conductive materials. However, ac...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Tsinghua University Press
2024-02-01
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| Series: | Friction |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s40544-023-0834-7 |
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