Multi-Head Attention Network with Adaptive Feature Selection for RUL Predictions of Gradually Degrading Equipment

Multi-Head Attention Network with Adaptive Feature Selection for RUL Predictions of Gradually Degrading Equipment

A multi-head-attention-network-based method is proposed for effective information extraction from multidimensional data to accurately predict the remaining useful life (RUL) of gradually degrading equipment. The multidimensional features of the desired equipment were evaluated using a comprehensive...

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Bibliographic Details
Main Authors: Lei Nie, Shiyi Xu, Lvfan Zhang
Format: Article
Language:English
Published: MDPI AG 2023-04-01
Series:Actuators
Subjects:
adaptive feature selection
multi-head attention
temporal convolutional network
bidirectional long short-term memory
remaining useful life
Online Access:https://www.mdpi.com/2076-0825/12/4/158

Internet

https://www.mdpi.com/2076-0825/12/4/158

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