Attentive Bidirectional Long Short-Term Memory Model to Predict the Remaining Useful Life of Aircraft Engines

Accurate Remaining Useful Life (RUL) prediction for turbofan engines remains a challenging issue for the aviation industry due to operational condition variability, sensor noise, and the relatively complex degradation patterns of turbofans. To address this important research problem, we propose a ne...

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Bibliografische Detailangaben

Hauptverfasser:	Andreia Seixas Leal, Ravinesh C. Deo, Salvin S. Prasad, Luis Carlos De Castro Santos, Mumtaz Ali, Lilian Berton
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	IEEE 2025-01-01
Schriftenreihe:	IEEE Access
Schlagworte:	Aircraft maintenance artificial intelligence prognostics and health management remaining useful life aviation turbofan
Online-Zugang:	https://ieeexplore.ieee.org/document/11314518/
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