Prediction of fault evolution and remaining useful life for rolling bearings with spalling fatigue using digital twin technology
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence
Link
https://link.springer.com/content/pdf/10.1007/s10489-023-05010-8.pdf
Reference40 articles.
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3. Feng K, Ji J, Ni Q, Li Y, Mao W, Liu L (2023) A novel vibration-based prognostic scheme for gear health management in surface wear progression of the intelligent manufacturing system. Wear 522:204697
4. Lv Y, Guo X, Zhou Q, Qian L, Liu J (2023) Predictive maintenance decision-making for variable faults with non-equivalent costs of fault severities. Adv Eng Inf 56:102011
5. Li Q, Yan C, Chen G, Wang H, Li H, Wu L (2022) Remaining useful life prediction of rolling bearings based on risk assessment and degradation state coefficient. ISA Trans 129:413–428
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