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.
Static weight estimation and system design for multiple-sensor weigh-in-motion
2000
17 Seiten, 11 Quellen
Aufsatz (Zeitschrift)
Englisch
Continuous Calibration Weigh-in-Motion System Using Static Weight Data
Transportation Research Record | 2022
|Design of multiple-sensor weigh-in-motion systems
Kraftfahrwesen | 1990
|Design of multiple-sensor weigh-in-motion systems
Tema Archiv | 1990
|Design of Multiple-Sensor Weigh-in-Motion Systems
SAGE Publications | 1990
|Multiple Sensor Weigh-In-Motion: Optimal Design and Experimental Study
British Library Conference Proceedings | 1998
|