Dual-drive RUL Prediction of Gear Transmission Systems based on Dynamic Model and Unsupervised Domain Adaption under Zero Sample-Reference-Cited by-同舟云学术

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Dual-drive RUL Prediction of Gear Transmission Systems based on Dynamic Model and Unsupervised Domain Adaption under Zero Sample

Published:2024-08 Issue: Volume: Page:110442
ISSN:0951-8320
Container-title:Reliability Engineering & System Safety
language:en
Short-container-title:Reliability Engineering & System Safety

Author:

Han Yaoyao,Ding Xiaoxi,Gu Fengshou,Chen Xiaohui,Xu Minmin

Funder

National Key Clinical Specialty Discipline Construction Program of China

Support Program for Longyuan Youth and Fundamental Research Funds for the Universities of Gansu Province

Publisher

Elsevier BV

Reference52 articles.

1. Deep learning-based remaining useful life estimation of bearings using multi-scale feature extraction;Li;Reliab Eng Syst Safe,2019

2. Deep transfer learning based on Bi-LSTM and attention for remaining useful life prediction of rolling bearing;Dong;Reliab Eng Syst Safe,2023

3. Vibration characteristics and condition monitoring of internal radial clearance within a ball bearing in a gear-shaft-bearing system;Xu;Mech Syst Signal Pr,2022

4. Conditionsensenet: A deep interpolatory convnet for bearing intelligent diagnosis under variational working conditions;Wang;IEEE T Ind Inform,2021

5. Vibration feature extraction using signal processing techniques for structural health monitoring: a review;Zhang;Mech Syst Sig Process,2022

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