This paper presents a road characteristic identification method derived from wheel vibration. Firstly, analyses the friction principle between tires and road, road characteristic restrict road adhesion coefficient; Secondly, the wheel vibration model shows that wheel vibration mappings road characteristic; Thirdly, wheel vibration signal is decomposed by wavelet transform, using FFT get the high frequency spectrum vectors of wheel vibration; Finally, built and trained the RBF neural network classifier with the frequency spectrum vectors. For fine blacktop and mattess, the high frequency spectrum of wheel vibration displays obvious difference, the road type identification accuracy reaches 100%.


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    Titel :

    Road characteristic identification based on wavelet neural network


    Beteiligte:
    Lu Junhui, (Autor:in) / Zhou Rongzheng, (Autor:in) / Ding Jianjun, (Autor:in) / Wu Shijing, (Autor:in)


    Erscheinungsdatum :

    01.06.2009


    Format / Umfang :

    1686442 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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