Integrating Misidentification and OOD Detection for Reliable Fault Diagnosis of High-Speed Train Bogie-Reference-Cited by-同舟云学术

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Integrating Misidentification and OOD Detection for Reliable Fault Diagnosis of High-Speed Train Bogie

Published:2024-09 Issue:9 Volume:25 Page:11935-11945
ISSN:1524-9050
Container-title:IEEE Transactions on Intelligent Transportation Systems
language:
Short-container-title:IEEE Trans. Intell. Transport. Syst.

Author:

Feng Yong¹^ORCID,Chen Jinglong¹^ORCID,Xie Zongliang¹^ORCID,Xie Jingsong²^ORCID,Pan Tongyang²^ORCID,Li Chao³,Zhao Qing⁴^ORCID

Affiliation:

1. State Key Laboratory for Manufacturing and Systems Engineering, Xi’an Jiaotong University, Xi’an, China

2. School of Traffic and Transportation Engineering, Central South University, Changsha, China

3. Dongfeng Liuzhou Motor Company Ltd., Liuzhou, China

4. Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada

Funder

National Natural Science Foundation of China

Guangxi Science and Technology Major Project

Key Research and Development Projects of Shaanxi Province

Fundamental Research Funds for Central Universities

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6979/10659279/10480918.pdf?arnumber=10480918

Reference48 articles.

1. Fully Decomposed Singular Value and Fixed Dictionary Extreme Learning Machine for Bogie Fault Diagnosis

2. High-speed Train Bogie Faults Diagnosis Using Singular Spectrum Analysis

3. Density-Based Affinity Propagation Tensor Clustering for Intelligent Fault Diagnosis of Train Bogie Bearing

4. Applications of machine learning to machine fault diagnosis: A review and roadmap

5. Artificial intelligence for fault diagnosis of rotating machinery: A review

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