Bridge Damage Severity Quantification Using Multipoint Acceleration Measurement and Artificial Neural Networks
Joint Authors
Chun, Pang-jo
Yamashita, Hiroaki
Furukawa, Seiji
Source
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-09-30
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
The deterioration of bridges as a result of ageing is a serious problem in many countries.
To prevent the failure of these deficient bridges, early damage detection which helps us to evaluate the safety of bridges is important.
Therefore, the present research proposed a method to quantify damage severity by use of multipoint acceleration measurement and artificial neural networks.
In addition to developing the method, we developed a cheap and easy-to-make measurement device which can be made by bridge owners at low cost and without the need for advance technical skills since the method is mainly intended to apply to small to midsized bridges.
In addition, the paper gives an example application of the method to a weathering steel bridge in Japan.
It can be shown from the analysis results that the method is accurate in its damage identification and mechanical behavior prediction ability.
American Psychological Association (APA)
Chun, Pang-jo& Yamashita, Hiroaki& Furukawa, Seiji. 2015. Bridge Damage Severity Quantification Using Multipoint Acceleration Measurement and Artificial Neural Networks. Shock and Vibration،Vol. 2015, no. 2015, pp.1-11.
https://search.emarefa.net/detail/BIM-1078337
Modern Language Association (MLA)
Chun, Pang-jo…[et al.]. Bridge Damage Severity Quantification Using Multipoint Acceleration Measurement and Artificial Neural Networks. Shock and Vibration No. 2015 (2015), pp.1-11.
https://search.emarefa.net/detail/BIM-1078337
American Medical Association (AMA)
Chun, Pang-jo& Yamashita, Hiroaki& Furukawa, Seiji. Bridge Damage Severity Quantification Using Multipoint Acceleration Measurement and Artificial Neural Networks. Shock and Vibration. 2015. Vol. 2015, no. 2015, pp.1-11.
https://search.emarefa.net/detail/BIM-1078337
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1078337