A Turboshaft Aeroengine Fault Detection Method Based on One-Class Support Vector Machine and Transfer Learning-Reference-Cited by-同舟云学术

A Turboshaft Aeroengine Fault Detection Method Based on One-Class Support Vector Machine and Transfer Learning

Published:2022-11 Issue:6 Volume:35 Page:
ISSN:0893-1321
Container-title:Journal of Aerospace Engineering
language:en
Short-container-title:J. Aerosp. Eng.

Author:

Zhu Ye¹^ORCID,Du Chenglie²,Liu Zhiqiang³^ORCID,Chen Yao-Bin⁴,Zhao Yong-Ping⁵^ORCID

Affiliation:

1. Senior Researcher, School of Computer Science, Northwestern Polytechnical Univ., Xi’an 710072, China. ORCID: .

2. Professor, School of Computer Science, Northwestern Polytechnical Univ., Xi’an 710072, China.

3. Professor, School of Computer Science, Northwestern Polytechnical Univ., Xi’an 710072, China. ORCID: .

4. Engineer, College of Energy and Power Engineering, Nanjing Univ. of Aeronautics and Astronautics, Nanjing 210016, China.

5. Professor, College of Energy and Power Engineering, Nanjing Univ. of Aeronautics and Astronautics, Nanjing 210016, China (corresponding author). ORCID: .

Publisher

American Society of Civil Engineers (ASCE)

Subject

Mechanical Engineering,Aerospace Engineering,General Materials Science,Civil and Structural Engineering

Link

https://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29AS.1943-5525.0001485

Reference31 articles.

1. Bai Y. Y. J. Li B. W. Zhang and Y. C. Zhao. 2020. “Intelligent fault diagnosis of aeroengine based on algorithm fusion.” In Proc. 2020 IEEE 4th Information Technology Networking Electronic and Automation Control Conf. 255–261. New York: IEEE.

2. Kernel k-means clustering based local support vector domain description fault detection of multimodal processes

3. Integrating structured biological data by Kernel Maximum Mean Discrepancy

4. Fault detection in operating helicopter drivetrain components based on support vector data description

5. Density weighted support vector data description

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