In this paper, fisher discriminant analysis (FDA) is used for fault isolation and diagnosis in rail vehicle suspension systems. The suspension systems are equipped with acceleration sensors in the corners of the car body and the two bogies. The faults considered are the lateral damper faults and the lateral spring faults in suspension systems. FDA provides an optimal projection space on the basis of the training data including the fault data and normal data to classify the test data. A vehicle model is built by SIMPACK/MATLAB software with real parameters to obtain the simulation data and the effectiveness of the proposed method is demonstrated by simulation.


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    Titel :

    Fault Diagnosis for Rail Vehicle Suspension Systems Based on Fisher Discriminant Analysis


    Beteiligte:
    Wei, Xiukun (Autor:in) / Wu, Sheng (Autor:in) / Ding, Jianlong (Autor:in) / Jia, Limin (Autor:in) / Sun, Qu (Autor:in) / Yuan, Minzhen (Autor:in)


    Erscheinungsdatum :

    2014


    Format / Umfang :

    11 Seiten





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch




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    On fault isolation for rail vehicle suspension systems

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