A New Cross-Domain Bearing Fault Diagnosis Framework Based on Transferable Features and Manifold Embedded Discriminative Distribution Adaption Under Class Imbalance-Reference-Cited by-同舟云学术

A New Cross-Domain Bearing Fault Diagnosis Framework Based on Transferable Features and Manifold Embedded Discriminative Distribution Adaption Under Class Imbalance

Published:2023-04-01 Issue:7 Volume:23 Page:7525-7545
ISSN:1530-437X
Container-title:IEEE Sensors Journal
language:
Short-container-title:IEEE Sensors J.

Author:

Yu Xiao¹^ORCID,Yin Hongshen¹,Sun Li²,Dong Fei¹^ORCID,Yu Kun¹^ORCID,Feng Ke³^ORCID,Zhang Yongchao³^ORCID,Yu Wanli⁴^ORCID

Affiliation:

1. IOT Perception Mine Research Center and the School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, China

2. School of Electrical Engineering, China University of Mining and Technology, Xuzhou, China

3. School of Engineering, The University of British Columbia, Kelowna, BC, Canada

4. Institute of Electrodynamics and Microelectronics, University of Bremen, Bremen, Germany

Funder

National Natural Science Foundation of China

Jiangsu Postdoctoral Research Support Program

Natural Science Foundation of Jiangsu

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/7361/10089784/10057216.pdf?arnumber=10057216

Reference55 articles.

1. Transfer learning based on improved stacked autoencoder for bearing fault diagnosis

2. A new deep auto-encoder method with fusing discriminant information for bearing fault diagnosis

3. Bearing fault diagnosis using transfer learning and optimized deep belief network

4. Bearing fault diagnosis based on VMD fuzzy entropy and improved deep belief networks;jin;J Vib Eng Technol,2022

5. A Post-Processing Method for Time-Reassigned Multisynchrosqueezing Transform and Its Application in Processing the Strong Frequency-Varying Signal

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