With the continuous improvement of the running speed of high-speed trains, its safety and reliability have received extensive attention from all over the world. How to understand the operating state of the train in real time and make reasonable countermeasures to avoid safety risks and save maintenance costs has already turn into a huge problem which needs to be dealt with. Based on PHM technology, this paper takes the traction motor bearing of high-speed train as an example, processes all kinds of data generated during the train operation by means of signal processing and data analysis, extracts its characteristics, and realizes the monitoring of train operation status. At the same time, based on XGboost algorithm, effective fault diagnosis and condition monitoring of high-speed trains are realized.


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    Titel :

    High-speed Train Fault Diagnosis and Condition Monitoring Based on PHM Technology


    Beteiligte:
    Yu, Jie (Autor:in) / Xiao, Song (Autor:in) / Guo, Yujun (Autor:in) / Gao, Guoqiang (Autor:in) / Wu, Guangning (Autor:in) / Zhang, Xueqin (Autor:in)


    Erscheinungsdatum :

    01.04.2023


    Format / Umfang :

    763834 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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