Remaining Useful Life Prediction of Rail Based on Improved Pulse Separable Convolution Enhanced Transformer Encoder

Author:

Wang Zhongmei,Li Min,He Jing,Liu Jianhua,Jia Lin

Publisher

Scientific Research Publishing, Inc.

Reference29 articles.

1. Shang, P.P., Liu, X.B. and Ma, S. (2022) Study on Rail Service Life of Shuohuang Heavy Haul Railway. Railway Engineering, 62, 68-71+85.

2. Ni, J.N., Zhang, W., Liu, N.X., et al. (2022) Demand Forecast and Development Countermeasures of Heavy Haul Railway Transportation in the “14th Five Year” Plan. Railway Freight Transport, 40, 7-11+19.

3. Digital Twin-Driven Remaining Useful Life Prediction for Gear Performance Degradation: A Review

4. Generator Parameter Calibration by Adaptive Approximate Bayesian Computation With Sequential Monte Carlo Sampler

5. Data-Driven Deep Learning-Based Attention Mechanism for Remaining Useful Life Prediction: Case Study Application to Turbofan Engine Analysis

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