An Ensemble Domain Adaptation Network With High-Quality Pseudo Labels for Rolling Bearing Fault Diagnosis-Reference-Cited by-同舟云学术

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An Ensemble Domain Adaptation Network With High-Quality Pseudo Labels for Rolling Bearing Fault Diagnosis

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:

Xie Ming¹^ORCID,Liu Jianxin¹^ORCID,Li Yifan²^ORCID,Feng Ke³^ORCID,Ni Qing⁴^ORCID

Affiliation:

1. State Key Laboratory of Rail Transit Vehicle System, Southwest Jiaotong University, Chengdu, China

2. School of Mechanical Engineering, Southwest Jiaotong University, Chengdu, China

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

4. School of Mechanical and Mechatronic Engineering, University of Technology Sydney, Sydney, NSW, Australia

Funder

National Natural Science Foundation of China

Key Research and Development Program of Sichuan Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/19/10367905/10494242.pdf?arnumber=10494242

Reference46 articles.

1. Knowledge Transfer for Rotary Machine Fault Diagnosis

2. Remaining useful life prediction across machines using multi-source adversarial online knowledge distillation

3. Transfer learning using computational intelligence: A survey

4. Edge Computing on IoT for Machine Signal Processing and Fault Diagnosis: A Review

5. A Transfer Ensemble Learning Method for Evaluating Power Transformer Health Conditions with Limited Measurement Data

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Semi-supervised source-free domain adaptation method via diffusive label propagation for rotating machinery fault diagnosis;Reliability Engineering & System Safety;2024-12

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