Remaining useful life prediction framework for crack propagation with a case study of railway heavy duty coupler condition monitoring
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DOI: 10.1016/j.ress.2022.108915
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References listed on IDEAS
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Cited by:
- Keshun, You & Guangqi, Qiu & Yingkui, Gu, 2024. "Optimizing prior distribution parameters for probabilistic prediction of remaining useful life using deep learning," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
- Xie, Mingjiang & Wang, Yifei & Zhao, Jianli & Pei, Xianjun & Zhang, Tairui, 2024. "Prediction of pipeline fatigue crack propagation under rockfall impact based on multilayer perceptron," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
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Keywords
Crack propagation; Remaining useful life; Delay time; Hypothetical distribution; SVR with Kalman filtering; Railway heavy duty coupler;All these keywords.
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