Paper Info
Title
Sensor Data Fusion in Multi-Sensor Weigh-In-Motion Systems.
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.
Year
DOI
Venue
2020
10.3390/s20123357
SENSORS
Keywords
DocType
Volume
data fusion,weigh in motion (WIM) systems,multi-sensor WIM,accuracy of WIM systems
Journal
20
Issue
ISSN
Citations 
12
1424-8220
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
janusz gajda1125.13
Sroka, R.212.81
Piotr Burnos300.68