Title

Computer Vision And Sensor Fusion For Structural Health Monitoring Framework With Emphasis On Unit Influence Line Analysis

Abstract

Civil Infrastructure Systems performance change over their during their life due to different reasons such as damage, unexpected loadings, severe environmental conditions not anticipated during design, and even aging due to normal continued use. These loadings contribute to structural deterioration and damage. Condition assessment is one of the most challenging activities performed by civil engineers to objectively evaluate if structures are safe for the public use. In order to evaluate the condition of existing bridges effectively, engineers need to take into account several factors while trying to come with a correct judgment. In this paper, the variation of unit influence line (UIL), is employed as an index for predicting bridge behavior under known loading conditions. The UCF-4-Span Bridge is used to explore the integration of imaging devices and traditional sensing technology, with emphasis on the analysis of UIL as index for evaluating and tracking behavioral variations in bridges. Video images and computer vision techniques are used to detect, classify and track different vehicles (input) crawling over the bridge while sensors measure the associated responses (output). UIL are extracted and compared for diagnostic, evaluation, and condition assessment. © 2009 Society for Experimental Mechanics Inc.

Publication Date

12-1-2009

Publication Title

Conference Proceedings of the Society for Experimental Mechanics Series

Number of Pages

-

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

Socpus ID

84861559398 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84861559398

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