A deep learning-based prognostic approach for predicting turbofan engine degradation and remaining useful life

A deep learning-based prognostic approach for predicting turbofan engine degradation and remaining useful life

Abstract Predicting the Remaining Useful Life (RUL) of turbofan engines can prevent air disasters caused by component degradation. It is an important procedure in prognostics and health management (PHM). Therefore, a deep learning-based RUL prediction approach is proposed. The CMAPSS benchmark datas...

Full description

Saved in:
Bibliographic Details
Main Authors: Samiha M. Elsherif, Bassel Hafiz, M. A. Makhlouf, Osama Farouk
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Subjects:
C-MAPSS
Remaining useful life prediction
CNN
LSTM
Prognostics
Online Access:https://doi.org/10.1038/s41598-025-09155-z
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://doi.org/10.1038/s41598-025-09155-z

Similar Items