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Vehicle-Assisted Techniques for Health Monitoring of Bridges
Bridges are designed to withstand different types of loads, including dead, live, environmental, and occasional loads during their service period. Moving vehicles are the main source of the applied live load on bridges. The applied load to highway bridges depends on several traffic parameters such a...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7349906/ https://www.ncbi.nlm.nih.gov/pubmed/32575359 http://dx.doi.org/10.3390/s20123460 |
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author | Shokravi, Hoofar Shokravi, Hooman Bakhary, Norhisham Heidarrezaei, Mahshid Rahimian Koloor, Seyed Saeid Petrů, Michal |
author_facet | Shokravi, Hoofar Shokravi, Hooman Bakhary, Norhisham Heidarrezaei, Mahshid Rahimian Koloor, Seyed Saeid Petrů, Michal |
author_sort | Shokravi, Hoofar |
collection | PubMed |
description | Bridges are designed to withstand different types of loads, including dead, live, environmental, and occasional loads during their service period. Moving vehicles are the main source of the applied live load on bridges. The applied load to highway bridges depends on several traffic parameters such as weight of vehicles, axle load, configuration of axles, position of vehicles on the bridge, number of vehicles, direction, and vehicle’s speed. The estimation of traffic loadings on bridges are generally notional and, consequently, can be excessively conservative. Hence, accurate prediction of the in-service performance of a bridge structure is very desirable and great savings can be achieved through the accurate assessment of the applied traffic load in existing bridges. In this paper, a review is conducted on conventional vehicle-based health monitoring methods used for bridges. Vision-based, weigh in motion (WIM), bridge weigh in motion (BWIM), drive-by and vehicle bridge interaction (VBI)-based models are the methods that are generally used in the structural health monitoring (SHM) of bridges. The performance of vehicle-assisted methods is studied and suggestions for future work in this area are addressed, including alleviating the downsides of each approach to disentangle the complexities, and adopting intelligent and autonomous vehicle-assisted methods for health monitoring of bridges. |
format | Online Article Text |
id | pubmed-7349906 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-73499062020-07-15 Vehicle-Assisted Techniques for Health Monitoring of Bridges Shokravi, Hoofar Shokravi, Hooman Bakhary, Norhisham Heidarrezaei, Mahshid Rahimian Koloor, Seyed Saeid Petrů, Michal Sensors (Basel) Review Bridges are designed to withstand different types of loads, including dead, live, environmental, and occasional loads during their service period. Moving vehicles are the main source of the applied live load on bridges. The applied load to highway bridges depends on several traffic parameters such as weight of vehicles, axle load, configuration of axles, position of vehicles on the bridge, number of vehicles, direction, and vehicle’s speed. The estimation of traffic loadings on bridges are generally notional and, consequently, can be excessively conservative. Hence, accurate prediction of the in-service performance of a bridge structure is very desirable and great savings can be achieved through the accurate assessment of the applied traffic load in existing bridges. In this paper, a review is conducted on conventional vehicle-based health monitoring methods used for bridges. Vision-based, weigh in motion (WIM), bridge weigh in motion (BWIM), drive-by and vehicle bridge interaction (VBI)-based models are the methods that are generally used in the structural health monitoring (SHM) of bridges. The performance of vehicle-assisted methods is studied and suggestions for future work in this area are addressed, including alleviating the downsides of each approach to disentangle the complexities, and adopting intelligent and autonomous vehicle-assisted methods for health monitoring of bridges. MDPI 2020-06-19 /pmc/articles/PMC7349906/ /pubmed/32575359 http://dx.doi.org/10.3390/s20123460 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Shokravi, Hoofar Shokravi, Hooman Bakhary, Norhisham Heidarrezaei, Mahshid Rahimian Koloor, Seyed Saeid Petrů, Michal Vehicle-Assisted Techniques for Health Monitoring of Bridges |
title | Vehicle-Assisted Techniques for Health Monitoring of Bridges |
title_full | Vehicle-Assisted Techniques for Health Monitoring of Bridges |
title_fullStr | Vehicle-Assisted Techniques for Health Monitoring of Bridges |
title_full_unstemmed | Vehicle-Assisted Techniques for Health Monitoring of Bridges |
title_short | Vehicle-Assisted Techniques for Health Monitoring of Bridges |
title_sort | vehicle-assisted techniques for health monitoring of bridges |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7349906/ https://www.ncbi.nlm.nih.gov/pubmed/32575359 http://dx.doi.org/10.3390/s20123460 |
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