Xiuyu, Li and Shirley Johnathan, Tanjong (2025) Classification of Bearing Degradation Stage Based on Automatic Label Assignment and Multi-scale Channel-attention Network. Pertanika Journal of Science and Technology, 33 (1). pp. 261-282. ISSN 0128-7680
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Abstract
Predicting bearing degradation is crucial for precise maintenance. However, accurately predicting the degradation stages of bearings to achieve appropriate maintenance has always been challenging. To address this problem, we propose a network architecture based on automatic label assignment called FAEK and a multi-scale channel-attention classification (MCC) prediction model to predict the degradation stage of bearings at a given time. Our method achieved outstanding performance on the FEMTO dataset with an accuracy of 0.9665. This approach provides an efficient and reliable solution for the predictive maintenance of bearings.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Automatic label assignment, bearing degradation prediction, classification prediction model, deep learning, predictive maintenance. |
| Subjects: | T Technology > T Technology (General) T Technology > TJ Mechanical engineering and machinery |
| Divisions: | Academic Faculties, Institutes and Centres > Faculty of Engineering Faculties, Institutes, Centres > Faculty of Engineering |
| Depositing User: | Johnathan Tanjong |
| Date Deposited: | 13 Mar 2025 03:14 |
| Last Modified: | 13 Mar 2025 03:14 |
| URI: | http://ir.unimas.my/id/eprint/47772 |
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