A denoising semi-supervised deep learning model for remaining useful life prediction of turbofan engine degradation
Y Wang, Y Wang - Applied Intelligence, 2023 - Springer
Remaining useful life (RUL) prediction is significant for reliability analysis and the reduction
of maintenance costs for turbofan engine systems. However, most of the existing methods …
of maintenance costs for turbofan engine systems. However, most of the existing methods …
[HTML][HTML] Remaining useful life predictions for turbofan engine degradation using semi-supervised deep architecture
In recent years, research has proposed several deep learning (DL) approaches to providing
reliable remaining useful life (RUL) predictions in Prognostics and Health Management …
reliable remaining useful life (RUL) predictions in Prognostics and Health Management …
A lightweight transformer and depthwise separable convolution model for remaining useful life prediction of turbofan engines
R Li, H Zhan, J Yu, R Wang, K Han - Measurement Science and …, 2023 - iopscience.iop.org
The degradation of turbofan engines under complex operating conditions makes it difficult to
predict their remaining useful life (RUL), which affects aircraft maintenance efficiency and …
predict their remaining useful life (RUL), which affects aircraft maintenance efficiency and …
A deep learning model for remaining useful life prediction of aircraft turbofan engine on C-MAPSS dataset
In the era of industry 4.0, safety, efficiency and reliability of industrial machinery is an
elementary concern in trade sectors. The accurate remaining useful life (RUL) prediction of …
elementary concern in trade sectors. The accurate remaining useful life (RUL) prediction of …
Remaining useful life prediction of turbofan engines using CNN-LSTM-SAM approach
J Li, Y Jia, M Niu, W Zhu, F Meng - IEEE Sensors Journal, 2023 - ieeexplore.ieee.org
Accurate remaining useful life (RUL) prediction of turbofan engines can effectively avoid
serious air disaster due to engine failure by mining its component degradation …
serious air disaster due to engine failure by mining its component degradation …
A remaining useful life prognosis of turbofan engine using temporal and spatial feature fusion
C Peng, Y Chen, Q Chen, Z Tang, L Li, W Gui - Sensors, 2021 - mdpi.com
The prognosis of the remaining useful life (RUL) of turbofan engine provides an important
basis for predictive maintenance and remanufacturing, and plays a major role in reducing …
basis for predictive maintenance and remanufacturing, and plays a major role in reducing …
Data-driven deep learning-based attention mechanism for remaining useful life prediction: Case study application to turbofan engine analysis
Accurately predicting the remaining useful life (RUL) of the turbofan engine is of great
significance for improving the reliability and safety of the engine system. Due to the high …
significance for improving the reliability and safety of the engine system. Due to the high …
Channel attention & temporal attention based temporal convolutional network: A dual attention framework for remaining useful life prediction of the aircraft engines
The health of the aircraft engines is of great concern. And it is a key task to predict the
remaining useful life (RUL) of the aircraft engines accurately. However, there are still …
remaining useful life (RUL) of the aircraft engines accurately. However, there are still …
Time-varying Gaussian Encoder based Adaptive Sensor-Weighted Method for Turbofan Engine Remaining Useful Life Prediction
Remaining useful life (RUL) prediction, as an essential aspect of condition-based
maintenance (CBM), has attracted substantial interest in industrial measurement. Recently …
maintenance (CBM), has attracted substantial interest in industrial measurement. Recently …
A contrastive learning framework enhanced by unlabeled samples for remaining useful life prediction
Deep learning (DL)-based methods for remaining useful life (RUL) prediction have received
increasing research attention due to excellent feature extraction abilities. Most DL methods …
increasing research attention due to excellent feature extraction abilities. Most DL methods …
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