TCRSCANet: Harnessing Temporal Convolutions and Recurrent Skip Component for Enhanced RUL Estimation in Mechanical Systems

TCRSCANet: Harnessing Temporal Convolutions and Recurrent Skip Component for Enhanced RUL Estimation in Mechanical Systems

Abstract Estimating the remaining useful life (RUL) of critical industrial assets is of crucial importance for optimizing maintenance strategies, enabling proactive planning of repair tasks, enhanced reliability, and reduced downtime in prognostic health management (PHM). Deep learning-based data-dr...

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Bibliographic Details
Main Authors: Abdul Wahid, John G. Breslin, Muhammad Ali Intizar
Format: Article
Language:English
Published: Springer Nature 2024-01-01
Series:Human-Centric Intelligent Systems
Subjects:
Industry 4.0
Smart manufacturing
Recurrent skip component (RSC)
Attention layer (AL)
Remaining useful life (RUL)
Temporal convolution with recurrent-skip-component and attention mechanism network (TCRSCANet)
Online Access:https://doi.org/10.1007/s44230-023-00060-0

Internet

https://doi.org/10.1007/s44230-023-00060-0

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