A Bidirectional Long Short-Term Memory Autoencoder Transformer for Remaining Useful Life Estimation

Estimating the remaining useful life (RUL) of aircraft engines holds a pivotal role in enhancing safety, optimizing operations, and promoting sustainability, thus being a crucial component of modern aviation management. Precise RUL predictions offer valuable insights into an engine’s condition, enab...

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Vydané v:	Mathematics (Basel) Ročník 11; číslo 24; s. 4972
Hlavní autori:	Fan, Zhengyang, Li, Wanru, Chang, Kuo-Chu
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Basel MDPI AG 01.12.2023
Predmet:	Adaptation Aircraft Aircraft engines Analysis Artificial intelligence autoencoder bidirectional LSTM Coders Computational linguistics Deep learning Electric transformers Engines Estimation Feature extraction Language processing Measuring instruments Methods Natural language interfaces Neural networks Preventive maintenance remaining useful life prediction self-supervised learning Sensors Support vector machines Time series Training Transformer turbofan engine Useful life
ISSN:	2227-7390, 2227-7390
On-line prístup:	Získať plný text
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