A multi-stage semi-supervised learning approach for intelligent fault diagnosis of rolling bearing using data augmentation and metric learning-Reference-Cited by-同舟云学术

A multi-stage semi-supervised learning approach for intelligent fault diagnosis of rolling bearing using data augmentation and metric learning

Published:2021-01 Issue: Volume:146 Page:107043
ISSN:0888-3270
Container-title:Mechanical Systems and Signal Processing
language:en
Short-container-title:Mechanical Systems and Signal Processing

Author:

Yu Kun,Lin Tian Ran^ORCID,Ma Hui^ORCID,Li Xiang^ORCID,Li Xu

Publisher

Elsevier BV

Subject

Computer Science Applications,Mechanical Engineering,Aerospace Engineering,Civil and Structural Engineering,Signal Processing,Control and Systems Engineering

Reference56 articles.

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2. An intelligent fault diagnosis approach based on transfer learning from laboratory bearings to locomotive bearings;Yang;Mech. Syst. Signal Process.,2019

3. Model-based uneven loading condition monitoring of full ceramic ball bearings in starved lubrication;Shi;Mech. Syst. Signal Process.,2020

4. Calculation of mesh stiffness of spur gears considering complex foundation types and crack propagation path;Chen;Mech. Syst. Sig. Process.,2019

5. Time-varying mesh stiffness calculation of cracked spur gears;Ma;Eng. Fail. Anal.,2014

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