Cross‐machine intelligent fault diagnosis of gearbox based on deep learning and parameter transfer-Reference-Cited by-同舟云学术

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Cross‐machine intelligent fault diagnosis of gearbox based on deep learning and parameter transfer

Published:2021-12-11 Issue:3 Volume:29 Page:
ISSN:1545-2255
Container-title:Structural Control and Health Monitoring
language:en
Short-container-title:Structural Contr & Hlth

Author:

Han Te¹^ORCID,Zhou Taotao²,Xiang Yongyong³^ORCID,Jiang Dongxiang⁴

Affiliation:

1. Department of Industrial Engineering Tsinghua University Beijing China

2. Center for Risk and Reliability University of Maryland College Park Maryland USA

3. College of Mechanical Engineering Zhejiang University of Technology Hangzhou China

4. State Key Lab of Power System, Department of Energy and Power Engineering Tsinghua University Beijing China

Funder

China Postdoctoral Science Foundation

Publisher

Wiley

Subject

Mechanics of Materials,Building and Construction,Civil and Structural Engineering

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/stc.2898

Reference54 articles.

1. Rolling bearing fault diagnosis under fluctuant conditions based on compressed sensing

2. Identification of mechanical compound-fault based on the improved parameter-adaptive variational mode decomposition

3. A review of stochastic resonance in rotating machine fault detection

4. Particle filtering‐based adaptive training of neural networks for real‐time structural damage diagnosis and prognosis

5. The Entropy Algorithm and Its Variants in the Fault Diagnosis of Rotating Machinery: A Review

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