Remaining Useful Life Prognosis for Turbofan Engine Using Explainable Deep Neural Networks with Dimensionality Reduction

Remaining Useful Life Prognosis for Turbofan Engine Using Explainable Deep Neural Networks with Dimensionality Reduction

This study prognoses the remaining useful life of a turbofan engine using a deep learning model, which is essential for the health management of an engine. The proposed deep learning model affords a significantly improved accuracy by organizing networks with a one-dimensional convolutional neural ne...

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Bibliographic Details
Main Authors: Chang Woo Hong, Changmin Lee, Kwangsuk Lee, Min-Seung Ko, Dae Eun Kim, Kyeon Hur
Format: Article
Language:English
Published: MDPI AG 2020-11-01
Series:Sensors
Subjects:
deep neural network
dimensionality reduction
explainable artificial intelligence
feature selection
prognostics and health monitoring
turbofan engine
Online Access:https://www.mdpi.com/1424-8220/20/22/6626

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https://www.mdpi.com/1424-8220/20/22/6626

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