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Traffic Sensing Methodology Combining Influence Line Theory and Computer Vision Techniques for Girder Bridges
Joint Authors
Sun, Limin
Lozano-Galant, Jose Antonio
Jian, Xudong
Xia, Ye
Source
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-15, 15 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-05-27
Country of Publication
Egypt
No. of Pages
15
Main Subjects
Abstract EN
Collecting the information of traffic load, especially heavy trucks, is crucial for bridge statistical analysis, safety evaluation, and maintenance strategies.
This paper presents a traffic sensing methodology that combines a deep learning based computer vision technique with the influence line theory.
Theoretical background and derivations are introduced from both aspects of structural analysis and computer vision techniques.
In addition, to evaluate the effectiveness and accuracy of the proposed traffic sensing method through field tests, a systematic analysis is performed on a continuous box-girder bridge.
The obtained results show that the proposed method can automatically identify the vehicle load and speed with promising efficiency and accuracy and most importantly cost-effectiveness.
All these features make the proposed methodology a desirable bridge weigh-in-motion system, especially for bridges already equipped with structural health monitoring system.
American Psychological Association (APA)
Jian, Xudong& Xia, Ye& Lozano-Galant, Jose Antonio& Sun, Limin. 2019. Traffic Sensing Methodology Combining Influence Line Theory and Computer Vision Techniques for Girder Bridges. Journal of Sensors،Vol. 2019, no. 2019, pp.1-15.
https://search.emarefa.net/detail/BIM-1187417
Modern Language Association (MLA)
Jian, Xudong…[et al.]. Traffic Sensing Methodology Combining Influence Line Theory and Computer Vision Techniques for Girder Bridges. Journal of Sensors No. 2019 (2019), pp.1-15.
https://search.emarefa.net/detail/BIM-1187417
American Medical Association (AMA)
Jian, Xudong& Xia, Ye& Lozano-Galant, Jose Antonio& Sun, Limin. Traffic Sensing Methodology Combining Influence Line Theory and Computer Vision Techniques for Girder Bridges. Journal of Sensors. 2019. Vol. 2019, no. 2019, pp.1-15.
https://search.emarefa.net/detail/BIM-1187417
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1187417