Improving the Drive-by Bridge Inspection Performance by Vehicle Parameter Optimization
Yifu Landownload PDF
Abstract. Recently, there has been an increasing emphasis in the Indirect bridge health monitoring method employing passing vehicles, which is regarded as one of the most effective approaches in bridge damage screening. However, few researches have been conducted on the Drive-by bridge inspection method using vehicle displacement profile as damage indicator due to the challenges in displacement measurement and result accuracy. This paper proposes an optimization approach of designing the optimum vehicle parameters to improve the performance of vehicle displacement-based Drive-by bridge damage inspection. A generalized Vehicle-Bridge Interaction (VBI) system is built in MATLAB, where the bridge is modelled as a simply supported beam with 10 elements and the passing vehicle is represented as a simplified quarter car. Employing the Monte Carlo methods, the optimum parameters are determined by numerous simulations processed under diverse damage scenarios. Results show that by employing the optimal vehicle parameters, the bridge damages can be detected effectively and accurately for general damage scenarios based on the vehicle displacement profile. The proposed optimization method can contribute to the wide application of vehicle displacement-based Drive-by bridge damage inspection, providing merits in simplicity and visualization.
Drive-by Bridge Inspection, Vehicle Bridge Interaction, Vertical Vehicle Displacement, Vehicle Configuration, Parameter Optimization
Published online 2/20/2021, 8 pages
Copyright © 2021 by the author(s)
Published under license by Materials Research Forum LLC., Millersville PA, USA
Citation: Yifu Lan, Improving the Drive-by Bridge Inspection Performance by Vehicle Parameter Optimization, Materials Research Proceedings, Vol. 18, pp 195-202, 2021
The article was published as article 23 of the book Structural Health Monitoring
Content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.
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