Remaining useful life estimation of bearing via temporal convolutional networks enhanced by a gated convolutional unit-Reference-Cited by-同舟云学术

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Remaining useful life estimation of bearing via temporal convolutional networks enhanced by a gated convolutional unit

Published:2024-07 Issue: Volume:133 Page:108308
ISSN:0952-1976
Container-title:Engineering Applications of Artificial Intelligence
language:en
Short-container-title:Engineering Applications of Artificial Intelligence

Author:

Qin Yujie^ORCID,Gan Fanfan,Xia Baizhan^ORCID,Mi Dong,Zhang Lizhang

Funder

Hunan University

Publisher

Elsevier BV

Reference53 articles.

1. Optimized random forest model for remaining useful life prediction of experimental bearings;Alfarizi;IEEE Trans. Ind. Inf.,2023

2. A two-phase-based deep neural network for simultaneous health monitoring and prediction of rolling bearings;Bai;Reliab. Eng. Syst. Saf.,2023

3. Probabilistic state of health and remaining useful life prediction for Li-ion batteries;Bracale;IEEE Trans. Ind. Appl.,2023

4. Remaining useful life estimation of aircraft engines using a modified similarity and supporting vector machine (SVM) approach;Chen;Energies,2017

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