Transformer is an important equipment in the traction power supply system. Once it fails, it will affect the normal operation of the train and even threaten the personal safety of passengers. Therefore, it is very necessary to diagnose the fault of the transformer of the traction power supply system. At present, power companies have made a lot of achievements in power equipment fault diagnosis, but there are still real-time and accuracy problems. The Internet of Things (IoT) uses cloud computing, parallel computing, and synchronous computing to realize data fusion processing, decision-making, and control, and can perform real-time monitoring and intelligent processing of the transformer status of the traction power supply system. In order to diagnose faults on railway transformers in a timely and accurate manner, this paper combines the real-time information obtained by the IoT with the fault diagnosis of transformers, screens the faulty equipment, and then uses the status information as the characteristic quantity to realize the fault diagnosis of the transformer.


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    Titel :

    Transformer Fault Diagnosis Algorithm for Traction Power Supply System Based on IoT


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Jia, Limin (Herausgeber:in) / Qin, Yong (Herausgeber:in) / Liang, Jianying (Herausgeber:in) / Liu, Zhigang (Herausgeber:in) / Diao, Lijun (Herausgeber:in) / An, Min (Herausgeber:in) / Wu, Zhensheng (Autor:in) / Zhang, Zhongli (Autor:in) / He, Jie (Autor:in) / Yue, Bin (Autor:in)

    Kongress:

    International Conference on Electrical and Information Technologies for Rail Transportation ; 2021 October 21, 2021 - October 23, 2021



    Erscheinungsdatum :

    2022-02-22


    Format / Umfang :

    8 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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