In this paper, The method of parameter estimation for railway vehicle is discussed. To support condition-based maintenance based on diagnosing the fault of vehicle, We build a CRH2 high-speed railway vehicle lateral state space model and use Rao-Blackwellised Particle Filter(RBPF)-based method for parameter estimation. However, the standard RBPF-based method does not adapt to non-Gaussian noise when verified using the real track irregularity as the input of model instead of Gaussian noise. An improved RBPF estimation method is introduced which can estimate parameters with real track irregularity


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Parameter estimation of high-speed railway vehicle using improved Rao-Blackwellised Particle Filter


    Beteiligte:
    Xu, Bowen (Autor:in) / Zhang, Zhongshun (Autor:in) / Geng, Shaoyang (Autor:in) / Ma, Lei (Autor:in)


    Erscheinungsdatum :

    2014-10-01


    Format / Umfang :

    1390251 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    6.0501 Rao-Blackwellised Particle Filtering for Fault Diagnosis

    Institute of Electrical and Electronics Engineers | British Library Conference Proceedings | 2002





    A Study of the Rao-Blackwellised Particle Filter for Efficient and Accurate Vision-Based SLAM

    Sim, R. / Elinas, P. / Little, J. J. | British Library Online Contents | 2007