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Published on: August 8, 2019
Sensor Data Fusion in Multi-Sensor Weigh-In-Motion Systems
Janusz Gajda1, Ryszard Sroka1, Piotr Burnos1
1Department of Measurement and Electronics, AGH University of Science and Technology, Al. A. Mickiewicza 30, 30-059 Cracow, Poland.
Abstract:
In this paper, we present the results of a comparison of two estimators of the gross vehicle weight (GVW) and the static load of individual axles of vehicles. The estimators were used to process measurement data derived from Multi-Sensor Weigh-In-Motion systems (MS-WIM). The term estimator is understood as an algorithm according to which the dynamic axle load measurement results are processed in order to determine the static load. The result obtained is called static load estimate. As a measure of measurement uncertainty, we adopted the standard deviation of the static load estimate. The mean value and the maximum likelihood estimators were compared. Studies were conducted using simulation methods based on synthetic data and experimental data obtained from a WIM system equipped with 16 lines of polymer axle load sensors. We have shown a substantially lower uncertainty of estimates determined using the maximum likelihood estimator. The results obtained have considerable practical significance, particularly during long-term usage of multi-sensor WIM systems.
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