Novel Transfer Learning Based on Support Vector Data Description for Aeroengine Fault Detection-Reference-Cited by-同舟云学术

Novel Transfer Learning Based on Support Vector Data Description for Aeroengine Fault Detection

Published:2024-05 Issue:3 Volume:37 Page:
ISSN:0893-1321
Container-title:Journal of Aerospace Engineering
language:en
Short-container-title:J. Aerosp. Eng.

Author:

Zhao Yong-Ping¹^ORCID,Peng Pei²,Chen Yao-Bin³,Jin Hui-Jie²

Affiliation:

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

2. Ph.D. Student, College of Energy and Power Engineering, Nanjing Univ. of Aeronautics and Astronautics, Nanjing 210016, China.

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

Publisher

American Society of Civil Engineers (ASCE)

Link

https://ascelibrary.org/doi/pdf/10.1061/JAEEEZ.ASENG-4712

Reference32 articles.

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

2. Cui J. Y. Tian X. Cui J. Wang L. Jiang and M. Yu. 2020. “A method for fault diagnosis of aviation engine gas system.” In Proc. 39th Chinese Control Conf. 4244–4248. Beijing: Systems Engineering Society of China. https://doi.org/10.23919/CCC50068.2020.9189544.

3. DeCastro J. A. J. S. Litt and D. K. Frederick. 2008. “A modular aero-propulsion system simulation of a large commercial aircraft engine.” In Proc. 44th AIAA/ASME/SAE/ASEE Joint Propulsion Conf. and Exhibit 2008–4579. Reston VA: American Institute of Aeronautics and Astronautics.

4. Aero-engine fault diagnosis based on one-class classification of SVM;Fan Y. P.;Gas Turbine Exp. Res.,2006

5. Domain-adversarial training of neural networks;Ganin Y.;J. Mach. Learn. Res.,2016