Title
A Bridge Damage Detection Approach Using Vehicle-Bridge Interaction Analysis And Neural Network Technique
Abstract
This paper is intended to develop an economical and convenient method bridge identification approach based on Neural Network (NN) technique using dynamic bridge responses induced by the running vehicles. In the proposed approach, a NN for bridge damage identification is established using the running vehicle-induced bridge vibration data as input and the structural damage condition as output. To develop such a system, the possible damage patterns of the bridge are assumed according to theoretical and empirical considerations at first. Then, the running vehicle-induced dynamic responses of the bridge under a certain damage pattern are calculated employing a developed vehicle-bridge interaction analysis procedure. The obtained structural vibration responses are then used as training data to establish the NN system. In this paper, the basic process of the proposed approach and the evaluation of its feasibility are indicated using simple numerical bridge and vehicle models. © 2012 Taylor & Francis Group.
Publication Date
1-1-2012
Publication Title
Bridge Maintenance, Safety, Management, Resilience and Sustainability - Proceedings of the Sixth International Conference on Bridge Maintenance, Safety and Management
Number of Pages
376-383
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1201/b12352-48
Copyright Status
Unknown
Socpus ID
84863917998 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/84863917998
STARS Citation
Hattori, H.; He, X.; Catbas, F. N.; Furuta, H.; and Kawatani, M., "A Bridge Damage Detection Approach Using Vehicle-Bridge Interaction Analysis And Neural Network Technique" (2012). Scopus Export 2010-2014. 5698.
https://stars.library.ucf.edu/scopus2010/5698