Data-Driven Deep Learning-Based Attention Mechanism for Remaining Useful Life Prediction: Case Study Application to Turbofan Engine Analysis

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 dimension and complex features of sensor data in RUL prediction, this paper proposes four data-driven prognostic models...

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Bibliographic Details
Main Authors: Amgad Muneer, Shakirah Mohd Taib, Sheraz Naseer, Rao Faizan Ali, Izzatdin Abdul Aziz
Format: Article
Language:English
Published: MDPI AG 2021-10-01
Series:Electronics
Subjects:
turbofan engine degradation
data-driven prognostic
deep neural network (DNN)
prognostics and health management (PHM)
remaining useful life (RUL)
uncertainty
Online Access:https://www.mdpi.com/2079-9292/10/20/2453

Internet

https://www.mdpi.com/2079-9292/10/20/2453

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