A noval RUL prediction method for rolling bearing: TcLstmNet-CBAM

A noval RUL prediction method for rolling bearing: TcLstmNet-CBAM

Abstract Rolling bearings are pivotal components within rotating mechanical systems, and accurately predicting their remaining service life holds significant practical importance. This paper addresses issues prevalent in common deep learning methods for predicting remaining useful life (RUL), notabl...

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Bibliographic Details
Main Authors: Qiang Liu, Zhengwei Dai, Hongxi Lai, Minghao Chen, Huiyuan Huang, Jiahui Fu, Mingxin Hou, Xiaoming Xu, Guangbin Wang, Jin Yan
Format: Article
Language:English
Published: Nature Portfolio 2025-04-01
Series:Scientific Reports
Subjects:
Remaining useful life
Rolling bearings
Feature extraction
Parallel network
CBAM
TCN
Online Access:https://doi.org/10.1038/s41598-025-98845-9
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https://doi.org/10.1038/s41598-025-98845-9

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