Scholarlink

<p>Bearings enable flexible movement of various components in the bogie section while ensuring sufficient support and stability, thereby guaranteeing safe and smooth operation of the train. Consequently, it becomes imperative to conduct fault detection on the bearings within the bogie. To date, researchers have conducted a large number of studies on train bogie bearing fault detection methods, and this paper will provide a systematic overview of these representative works. These researched fault diagnosis methods are firstly categorized into three groups, including physical-based, data-driven, and hybrid models. Data-driven bearing fault diagnosis methods based on vibration signal analysis, traditional machine learning, and deep learning are highlighted, and each type of fault diagnosis method is summarized and analyzed. Further trends and challenges in this research area are also discussed.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Fault Diagnosis of Bogie Bearings in High-Speed Train: A Review

  • 期刊论文

  • 发表日期：

    2025年7月23日

查看全文
  • Hong-Li Yang,
  • Ai-Min Sun,
  • Qing-Feng Song,
  • Zi-Hao Xia,
  • Hang-Dong Hou,
  • Fang Dong,
  • Li-Yong Ma

摘要

Bearings enable flexible movement of various components in the bogie section while ensuring sufficient support and stability, thereby guaranteeing safe and smooth operation of the train. Consequently, it becomes imperative to conduct fault detection on the bearings within the bogie. To date, researchers have conducted a large number of studies on train bogie bearing fault detection methods, and this paper will provide a systematic overview of these representative works. These researched fault diagnosis methods are firstly categorized into three groups, including physical-based, data-driven, and hybrid models. Data-driven bearing fault diagnosis methods based on vibration signal analysis, traditional machine learning, and deep learning are highlighted, and each type of fault diagnosis method is summarized and analyzed. Further trends and challenges in this research area are also discussed.