Multi-Head Self-Attention-Based Fully Convolutional Network for RUL Prediction of Turbofan Engines

Remaining useful life (RUL) prediction is widely applied in prognostic and health management (PHM) of turbofan engines. Although some of the existing deep learning-based models for RUL prediction of turbofan engines have achieved satisfactory results, there are still some challenges. For example, th...

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Bibliografische gegevens
Hoofdauteurs:	Zhaofeng Liu, Xiaoqing Zheng, Anke Xue, Ming Ge, Aipeng Jiang
Formaat:	Artigo
Taal:	Inglês
Gepubliceerd in:	MDPI AG 2024-07-01
Reeks:	Algorithms
Onderwerpen:	remaining useful life turbofan engine deep learning deep neural network
Online toegang:	https://www.mdpi.com/1999-4893/17/8/321
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Multi-Head Self-Attention-Based Fully Convolutional Network for RUL Prediction of Turbofan Engines

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