A probabilistic estimation method for multiple-sensor weigh-in-motion (MS-WIM) based on the maximum likelihood (ML) estimator is presented. The theoretical analysis is based on two generic vehicle models: a 'quarter-car' model, the tyre force spectrum of which can be idealized as a single sine wave, and a 'walking beam' model corresponding to the sum of two sine waves. The range and distribution of the model parameters (as derived from previous knowledge of vehicle dynamics) ate taken into account and used as prior information ('priors') in the implementation of the method. The technique is able to determine the static axle load of high-speed vehicles with considerably better accuracy than previous theoretical analyses. A detailed investigation of simulation results is given, the advantages of the method are discussed and its ability to estimate the static loads accurately is demonstrated. Finally, the probable success rate of the algorithm is calculated and a new design procedure for multiple-sensor weigh-in-motion is introduced.


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    Title :

    Static weight estimation and system design for multiple-sensor weigh-in-motion


    Contributors:


    Publication date :

    2000


    Size :

    17 Seiten, 11 Quellen




    Type of media :

    Article (Journal)


    Type of material :

    Print


    Language :

    English




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