The process of urbanization in China is accelerating continuously, which has greatly promoted the development of urban rail transit. Subway has gradually become the main way for people to travel in the city. Therefore, it has important economic value and social significance to ensure the normal operation of subway vehicles. The maintenance of pantograph carbon contact strip (PCCS) is one of the important contents of subway operation and maintenance.

    The subway vehicle has no power supply, it gets power through the contact between the PCCS and the rigid catenary. However, with the influence of various external factors such as wear, impact and operating environment change, the performance and health of PCCS will degrade inevitably. This paper selected the data of H type of PCCS for further study, and used three similarity models such as hash similarity, pairwise similarity and residual similarity in MATLAB predictive maintenance toolbox to predict the RUL of PCCS, furthermore, the predicted results were compared and the relative error were controlled in about 10%. Finally, the prediction results of the similarity model are compared with those of the linear regression model to verify the validity of the similarity model.


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    Titel :

    RUL Prediction of Railway PCCS Based on Data-Driven Method


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Qin, Yong (Herausgeber:in) / Jia, Limin (Herausgeber:in) / Liang, Jianying (Herausgeber:in) / Liu, Zhigang (Herausgeber:in) / Diao, Lijun (Herausgeber:in) / An, Min (Herausgeber:in) / Zhao, Tianke (Autor:in)

    Kongress:

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



    Erscheinungsdatum :

    23.02.2022


    Format / Umfang :

    13 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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