Remaining Useful Life Prediction for Aero-Engine Based on Hybrid CNN-GRU Model
Author:
Affiliation:
1. Research Institute of Aero-Engine, Beihang University,Beijing,China
2. Logistics School, Beijing Wuzi University,Beijing,China
Funder
National Postdoctoral Program for Innovative Talents
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9986510/9986514/09987018.pdf?arnumber=9987018
Reference13 articles.
1. Remaining useful life prediction via a variational autoencoder and a time‐window‐based sequence neural network
2. Damage propagation modeling for aircraft engine run-to-failure simulation
3. Remaining useful life prediction of aeroengine based on fusion neural network;li;Journal of Propulsion Technology,2021
4. Residual life prediction of aeroengine based on 1D-CNN and Bi-LSTM;che;Journal of Mechanical Engineering,2021
5. Remaining useful life estimation in prognostics using deep convolution neural networks
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