IFD-MDCN: Multibranch denoising convolutional networks with improved flow direction strategy for intelligent fault diagnosis of rolling bearings under noisy conditions-Reference-Cited by-同舟云学术

IFD-MDCN: Multibranch denoising convolutional networks with improved flow direction strategy for intelligent fault diagnosis of rolling bearings under noisy conditions

Published:2023-09 Issue: Volume:237 Page:109387
ISSN:0951-8320
Container-title:Reliability Engineering & System Safety
language:en
Short-container-title:Reliability Engineering & System Safety

Author:

Li Sheng,Ji J.C.^ORCID,Xu Yadong^ORCID,Sun Xiuquan,Feng Ke,Sun Beibei,Wang Yulin,Gu Fengshou^ORCID,Zhang Ke,Ni Qing

Publisher

Elsevier BV

Subject

Industrial and Manufacturing Engineering,Safety, Risk, Reliability and Quality

Reference39 articles.

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2. Global contextual residual convolutional neural networks for motor fault diagnosis under variable-speed conditions;Xu;Reliab Eng Syst Saf,2022

3. Attention-based multiscale denoising residual convolutional neural networks for fault diagnosis of rotating machinery;Xu;Reliab Eng Syst Saf,2022

4. A novel vibration-based prognostic scheme for gear health management in surface wear progression of the intelligent manufacturing system;Feng;Wear,2023

5. A Gaussian-guided adversarial adaptation transfer network for rolling bearing fault diagnosis;Wu;Adv Eng Inf,2022

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