Digital Twin and Data-Driven Remaining Useful Life Prediction of Gearbox
Traditional approaches for predicting the remaining useful life (RUL) of gearboxes often face challenges in integrating physical and virtual data, leading to reduced prediction accuracy and an increased risk of system failure. To realize reliable RUL prediction of gearbox, this paper proposes a nove...
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| Главные авторы: | , , |
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| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
IEEE
2025-01-01
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| Серии: | IEEE Access |
| Предметы: | |
| Online-ссылка: | https://ieeexplore.ieee.org/document/11052307/ |
| Метки: |
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