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Investigation on a curvature‐based damage detection method using displacement under moving vehicle
Author(s) -
Sun Zhen,
Nagayama Tomonori,
Nishio Mayuko,
Fujino Yozo
Publication year - 2018
Publication title -
structural control and health monitoring
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.587
H-Index - 62
eISSN - 1545-2263
pISSN - 1545-2255
DOI - 10.1002/stc.2044
Subject(s) - curvature , structural engineering , parametric statistics , finite element method , displacement (psychology) , bridge (graph theory) , engineering , reliability (semiconductor) , computer science , mathematics , geometry , psychology , medicine , psychotherapist , power (physics) , statistics , physics , quantum mechanics
Summary Detection of potential damages is of much significance for aging bridges, which has attracted extensive attention in recent years. In this paper, a damage detection method is proposed utilizing dynamic displacement of a bridge under a moving vehicle. First, the theoretical basis of this method is elaborated. The idea is to use the static component of displacement measurements under a moving vehicle, and to use the calculated curvature change to identify damage in bridges. In order to obtain the static component, a technique is proposed for curvature calculation. Second, the proposed method is verified with two examples. In the first example, a finite element model of a single span bridge under a moving vehicle is used to show reliability of the method. Both vehicle–bridge interaction and road surface roughness are considered in the analysis. Parametric study on damage intensity, data acquisition location, vehicle passing path, and damping ratio provides guidance for application in real bridges. In the second example, a field test on a prestressed concrete viaduct is conducted to calibrate its finite element model. Artificial damage, that is, concrete crack and tendon rupture, was created, and the proposed method is used to identify the damage. Analysis results show capability of the method. Finally, conclusions are drawn, and suggestions are given for application of the proposed method on damage detection of real bridges.