An Adaptive Activation Transfer Learning Approach for Fault Diagnosis-Reference-Cited by-同舟云学术

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An Adaptive Activation Transfer Learning Approach for Fault Diagnosis

Published:2023-10 Issue:5 Volume:28 Page:2645-2656
ISSN:1083-4435
Container-title:IEEE/ASME Transactions on Mechatronics
language:
Short-container-title:IEEE/ASME Trans. Mechatron.

Author:

Chen Yongyi¹^ORCID,Zhang Dan¹^ORCID,Zhu Kunpeng²^ORCID,Yan Ruqiang³^ORCID

Affiliation:

1. Department of Automation, Zhejiang University of Technology, Hangzhou, China

2. Institute of Advanced Manufacturing Technology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Changzhou, China

3. School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, China

Funder

Natural Science Foundation of Zhejiang Province

National Natural Science Foundation of China

Major Project of Science and Technology Innovation in Ningbo City

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/3516/10287648/10056250.pdf?arnumber=10056250

Reference32 articles.

1. Domain Adversarial Transfer Network for Cross-Domain Fault Diagnosis of Rotary Machinery

2. Retraining Strategy-Based Domain Adaption Network for Intelligent Fault Diagnosis

3. Deep Transfer Network With Adaptive Joint Distribution Adaptation: A New Process Fault Diagnosis Model

4. Intelligent Fault Diagnosis With Deep Adversarial Domain Adaptation

5. A novel transfer learning method for bearing fault diagnosis under different working conditions

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