Literature DB >> 33374991

A Review of Intelligent Fault Diagnosis for High-Speed Trains: Qualitative Approaches.

Chao Cheng1,2,3, Jiuhe Wang1, Hongtian Chen4, Zhiwen Chen5, Hao Luo6, Pu Xie2.   

Abstract

For ensuring the safety and reliability of high-speed trains, fault diagnosis (FD) technique plays an important role. Benefiting from the rapid developments of artificial intelligence, intelligent FD (IFD) strategies have obtained much attention in the field of academics and applications, where the qualitative approach is an important branch. Therefore, this survey will present a comprehensive review of these qualitative approaches from both theoretical and practical aspects. The primary task of this paper is to review the current development of these qualitative IFD techniques and then to present some of the latest results. Another major focus of our research is to introduce the background of high-speed trains, like the composition of the core subsystems, system structure, etc., based on which it becomes convenient for researchers to extract the diagnostic knowledge of high-speed trains, where the purpose is to understand how to use these types of knowledge. By reasonable utilization of the knowledge, it is hopeful to address various challenges caused by the coupling among subsystems of high-speed trains. Furthermore, future research trends for qualitative IFD approaches are also presented.

Entities:  

Keywords:  artificial intelligence; high-speed trains; intelligent fault diagnosis (IFD) technique; qualitative approaches

Year:  2020        PMID: 33374991     DOI: 10.3390/e23010001

Source DB:  PubMed          Journal:  Entropy (Basel)        ISSN: 1099-4300            Impact factor:   2.524


  4 in total

1.  Algorithms and Methods for the Fault-Tolerant Design of an Automated Guided Vehicle.

Authors:  Ralf Stetter
Journal:  Sensors (Basel)       Date:  2022-06-20       Impact factor: 3.847

2.  Subway Gearbox Fault Diagnosis Algorithm Based on Adaptive Spline Impact Suppression.

Authors:  Zhongshuo Hu; Jianwei Yang; Dechen Yao; Jinhai Wang; Yongliang Bai
Journal:  Entropy (Basel)       Date:  2021-05-25       Impact factor: 2.524

3.  Performance Degradation Estimation of High-Speed Train Bogie Based on 1D-ConvLSTM Time-Distributed Convolutional Neural Network.

Authors:  Junxiao Ren; Weidong Jin; Liang Li; Yunpu Wu; Zhang Sun
Journal:  Comput Intell Neurosci       Date:  2022-02-26

4.  Gearbox Failure Diagnosis Using a Multisensor Data-Fusion Machine-Learning-Based Approach.

Authors:  Houssem Habbouche; Tarak Benkedjouh; Yassine Amirat; Mohamed Benbouzid
Journal:  Entropy (Basel)       Date:  2021-05-31       Impact factor: 2.524

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.