Method for Remaining Useful Life Prediction of Turbofan Engines Combining Adam Optimization-Based Self-Attention Mechanism with Temporal Convolutional Networks

Conducting the remaining useful life (RUL) prediction for an aircraft engines is of significant importance in enhancing aircraft operation safety and formulating reasonable maintenance plans. Addressing the issue of low prediction model accuracy due to traditional neural networks’ inability to fully...

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Автори:	Hairui Wang, Dongjun Li, Ya Li, Guifu Zhu, Rongxiang Lin
Формат:	Artigo
Мова:	Inglês
Опубліковано:	MDPI AG 2024-09-01
Серія:	Applied Sciences
Предмети:	turbofan engine remaining useful life prediction self-attention mechanism temporal convolutional network
Онлайн доступ:	https://www.mdpi.com/2076-3417/14/17/7723
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