Volume 26 Issue 1
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CHEN Yue-jian, LI Yi-fan, LING Liang, LIU Jian-xin, JIN Si-qin, ZHOU Kai. Research review on dynamics and fault diagnosis of railway vehicle gearboxes[J]. Journal of Traffic and Transportation Engineering, 2026, 26(1): 176-199. doi: 10.19818/j.cnki.1671-1637.2026.058
Citation: CHEN Yue-jian, LI Yi-fan, LING Liang, LIU Jian-xin, JIN Si-qin, ZHOU Kai. Research review on dynamics and fault diagnosis of railway vehicle gearboxes[J]. Journal of Traffic and Transportation Engineering, 2026, 26(1): 176-199. doi: 10.19818/j.cnki.1671-1637.2026.058
shu

Research review on dynamics and fault diagnosis of railway vehicle gearboxes

doi: 10.19818/j.cnki.1671-1637.2026.058
  • 1.

    Department of Mechanical Engineering, University of Manitoba, Winnipeg R3T 5V6, Manitoba, Canada

  • 2.

    State Key Laboratory of Rail Transit Vehicle System, Southwest Jiaotong University, Chengdu 610031, Sichuan, China

  • 3.

    School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, Sichuan, China

  • 4.

    CRRC Qishuyan Institute Co., Ltd., Changzhou 213011, Jiangsu, China

  • 5.

    College of Transportation, Tongji University, Shanghai 201804, China

Funds:

Joint Fund of National Natural Science Foundation of China U2268210

Youth Fund of National Natural Science Foundation of China 52405125

National Key R&D Program of China 2022YFB3402900

CRRC Major Project 2024CKA327

Open Research Project of Technology and Equipment of Rail Transit Operation and Maintenance Key Laboratory of Sichuan Province 2024YW003

More Information
  • Corresponding author: LI Yi-fan, professor, PhD, E-mail: liyifan@swjtu.edu.cn
  • Received Date: 2025-03-02
  • Accepted Date: 2025-09-26
  • Rev Recd Date: 2025-09-01
  • Publish Date: 2026-01-28
    Abstract
  • The research progress on dynamic modeling and response characteristics analysis of railway vehicle gearboxes was reviewed from two aspects: the dynamic research under internal and external excitation, and the dynamic research under fault conditions. The advantages and disadvantages of different models were summarized in terms of the research object, consideration factors, and coupling complexity. The influence of different fault types on the dynamic characteristics of gearboxes was concluded. The application of signal processing methods and artificial intelligence technologies in the fault diagnosis of railway vehicle gearbox was systematically elaborated. The characteristics and shortcomings of the existing methods were also discussed. The results show that the dynamic modeling and characteristic research of railway vehicle gearboxes should fully consider the unique working environment and structural characteristics of gearboxes, focus on developing high-precision rigid-flexible coupling multi-body dynamic models, and strengthen the modeling and experimental verification of multi-physics field coupling, thus providing more reliable theoretical support for fault feature extraction and health status assessment. In addition, the research on the fault evolution mechanism of typical fault modes should be enhanced. The methods including hybrid modeling and digital twin should be combined to conduct composite fault scenario simulation and full-life simulation analysis, offering a theoretical basis for the fault prediction and health management of railway vehicle gearboxes. Finally, more advanced fault diagnosis technologies should be developed with actual train data to verify the effectiveness of the diagnostic methods, so as to meet the high precision and real-time requirements of railway vehicle fault diagnosis, and promote the theoretical and practical progress of health management and operation decision-making throughout the entire life cycle of railway vehicle gearboxes.

     

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