[PDF][PDF] Attention and long short-term memory network for remaining useful lifetime predictions of turbofan engine degradation
ABSTRACT Machine Prognostics and Health Management (PHM) is often concerned with
the prediction of the Remaining Useful Lifetime (RUL) of assets. Accurate real-time RUL …
the prediction of the Remaining Useful Lifetime (RUL) of assets. Accurate real-time RUL …
A dual-LSTM framework combining change point detection and remaining useful life prediction
Abstract Remaining Useful Life (RUL) prediction is a key task of Condition-based
Maintenance (CBM). The massive data collected from multiple sensors enables monitoring …
Maintenance (CBM). The massive data collected from multiple sensors enables monitoring …
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 …
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 …
[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 …
Joint learning of degradation assessment and RUL prediction for aeroengines via dual-task deep LSTM networks
H Miao, B Li, C Sun, J Liu - IEEE Transactions on Industrial …, 2019 - ieeexplore.ieee.org
Health assessment and prognostics are two key tasks within the prognostics and health
management frame of equipment. However, existing works are performing these two tasks …
management frame of equipment. However, existing works are performing these two tasks …
Deep learning for improved system remaining life prediction
Prognosis of manufacturing system performance degradation is essential to operation safety
and efficiency, and provides the basis for predictive maintenance scheduling. Complex …
and efficiency, and provides the basis for predictive maintenance scheduling. Complex …
MHT: A multiscale hourglass-transformer for remaining useful life prediction of aircraft engine
J Guo, S Lei, B Du - Engineering Applications of Artificial Intelligence, 2024 - Elsevier
Remaining useful life (RUL) prediction of aircraft engines is significant in the health
monitoring, operation, and maintenance of aircraft. Capturing more comprehensive device …
monitoring, operation, and maintenance of aircraft. Capturing more comprehensive device …
Multi-scale memory-enhanced method for predicting the remaining useful life of aircraft engines
W Chen, C Liu, Q Chen, P Wu - Neural Computing and Applications, 2023 - Springer
To guarantee the safe operation of machinery and reduce its maintenance costs, estimating
its remaining useful life (RUL) is a crucial task. Hence, in this study, a multi-scale memory …
its remaining useful life (RUL) is a crucial task. Hence, in this study, a multi-scale memory …
Self-attention transformer-based architecture for remaining useful life estimation of complex machines
Meaningful feature extraction from multivariate time-series data is still challenging since it
takes into account the correlation between pairs of sensors as well as the temporal …
takes into account the correlation between pairs of sensors as well as the temporal …
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