| Autor: |
Wanchun Hu, Ge Xin, Jiayi Wu, Guoping An, Yilei Li, Ke Feng, Jerome Antoni |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
|
| Zdroj: |
High-Speed Railway, Vol 1, Iss 4, Pp 219-223 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2949-8678 |
| DOI: |
10.1016/j.hspr.2023.11.001 |
| Popis: |
Due to the advantages of comfort and safety, high-speed trains are gradually becoming the mainstream public transport in China. Since the operating speed and mileage of high-speed trains have achieved rapid growth, it is more and more urgent to ensure their reliability and safety. As an important component in the bogies of high-speed trains, the health state of the bearing directly affects the operational safety of the trains. It is therefore necessary to diagnoze the faults of bearings in the bogies of high-speed trains as early as possible. In this paper, the bearing fault diagnostic methods for high-speed trains have been systematically summarized with their challenges and perspectives. First, it briefly introduces the structure of bearings in the bogies as well as the fault characteristic frequencies. Then, a brief review of the research on vibration-based signal processing methods and machine learning methods has been provided. Finally, the challenges and future developments of vibration-based bearing fault diagnostic methods for high-speed trains have been analyzed. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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