Fault Diagnosis of Gearbox Based on Cross-Domain Transfer Learning With Fine-Tuning Mechanism Using Unbalanced Samples-Reference-Cited by-同舟云学术

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Fault Diagnosis of Gearbox Based on Cross-Domain Transfer Learning With Fine-Tuning Mechanism Using Unbalanced Samples

Published:2024 Issue: Volume:73 Page:1-10
ISSN:0018-9456
Container-title:IEEE Transactions on Instrumentation and Measurement
language:
Short-container-title:IEEE Trans. Instrum. Meas.

Author:

Sun Qiang¹^ORCID,Zhang Yaping¹^ORCID,Chu Liying¹^ORCID,Tang Yanning¹^ORCID,Xu Liangyuan¹^ORCID,Li Qing¹^ORCID

Affiliation:

1. Department of Mechanical Engineering, Anhui Agricultural University, Hefei, China

Funder

National Natural Science Foundation of China

Foundation of High-Level Talents

Anhui Engineering Laboratory of Human-Robot Integration System Equipment

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/19/10367905/10559898.pdf?arnumber=10559898

Reference24 articles.

1. Effects of tooth root cracks on vibration and dynamic transmission error responses of asymmetric gears: A comparative study

2. Multivariate intrinsic wave-characteristic decomposition and its application in gear fault diagnosis

3. Mechanism analysis for GDTE-based fault diagnosis of planetary gears

4. RUL Estimation for Rolling Bearings Using Augmented Quaternion-Based Least Mean P-Power With Correntropy Induced Metric Under Framework of Sparsity

5. A New Fractional-Order Augmented Quaternion-Valued Approach for Degradation Prognostics of Bearings Using Generalized Hamilton-Real Calculus

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