In order to accurately identify the types of wheel faults in urban rail trains, a method based on improved ensemble empirical mode decomposition (EEMD) and Hilbert transform is proposed. The improved EEMD decomposition of the acquired vibration signal obtains several intrinsic mode functions (IMFs), and the Hilbert transform is performed on the IMF component containing the main information components, and judged the type of failure of the train wheels according to the fault characteristic frequency of the Hilbert spectrum. The experimental results show that the method can be used to identify the fault types of urban rail train wheels effectively and accurately.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Urban Rail Train Wheel Fault Diagnosis Based on Improved EEMD


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Qin, Yong (Herausgeber:in) / Jia, Limin (Herausgeber:in) / Liu, Baoming (Herausgeber:in) / Liu, Zhigang (Herausgeber:in) / Diao, Lijun (Herausgeber:in) / An, Min (Herausgeber:in) / Fu, Ning (Autor:in) / Qian, Kaijie (Autor:in) / Xing, Zongyi (Autor:in)

    Kongress:

    International Conference on Electrical and Information Technologies for Rail Transportation ; 2019 ; Qingdao, China October 25, 2019 - October 27, 2019



    Erscheinungsdatum :

    04.04.2020


    Format / Umfang :

    11 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Urban Rail Train Wheel Fault Diagnosis Based on Improved EEMD

    Fu, Ning / Qian, Kaijie / Xing, Zongyi | British Library Conference Proceedings | 2020


    Urban Rail Train Wheel Fault Diagnosis Based on Improved EEMD

    Fu, Ning / Qian, Kaijie / Xing, Zongyi | TIBKAT | 2020


    Train wheel size prediction based on EEMD-LSTM model

    Chen, Chunjun / Li, Yongjie | British Library Conference Proceedings | 2022


    A Fault Diagnosis Method of Gear Based on SVD and Improved EEMD

    Song, Mengmeng / Xiao, Shungen | Springer Verlag | 2017


    Short-Term Passenger Flow Prediction for Urban Rail Based on Improved EEMD-Ensemble Learning

    Qiao, Yaoqin / Zhou, Huijuan / Zhang, Xiayu et al. | Springer Verlag | 2024