Enhanced Bridge Weigh-in-Motion System Using Hybrid Strain–Acceleration Sensor Data
Publication: Journal of Bridge Engineering
Volume 27, Issue 9
Abstract
In this study, a novel acceleration-based vehicle identification method is employed within a hybrid bridge weigh-in-motion (BWIM) system in which the traditional strain-based BWIM system is augmented with an array of accelerometers. The implementation of such a system is discussed through a full-scale case study arterial highway bridge in the province of New Brunswick, Canada. The accuracy of the proposed vehicle identification method was studied in detail using an extensive set of field study data. To achieve this, a systematic evaluation of existing methods for velocity estimation and axle identification was conducted, evaluating the effects of vehicle direction, lane position, vehicle velocity, and vehicle configuration. The methods were compared based on the sensor signal characteristics, the velocity estimation techniques, axles detection methods, and the effects on gross vehicle weight (GVW) calculation. From this study, it was found that the proposed hybrid system resulted in more accurate velocity estimation, axle identification, and ultimately better GVW estimation.
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Acknowledgments
The authors would like to thank the Natural Sciences and Engineering Research Council of Canada (NSERC) and the New Brunswick Department of Transportation and Infrastructure (NBDTI) for supporting this research.
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Published In
Journal of Bridge Engineering
Volume 27 • Issue 9 • September 2022
Copyright
© 2022 American Society of Civil Engineers.
History
Received: Dec 28, 2021
Accepted: May 11, 2022
Published online: Jul 7, 2022
Published in print: Sep 1, 2022
Discussion open until: Dec 7, 2022
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