[KSCI] Korea Science Citation Index Service

http://dx.doi.org/10.12989/sss.2014.13.5.849

Indirect structural health monitoring of a simplified laboratory-scale bridge model

Cerda, Fernando (Universidad de Concepcion)
Chen, Siheng (Department of Electrical and Computer Engineering, Carnegie Mellon University)
Bielak, Jacobo (Department of Civil and Environmental Engineering, Carnegie Mellon University)
Garrett, James H. (Department of Civil and Environmental Engineering, Carnegie Mellon University)
Rizzo, Piervincenzo (Department of Civil and Environmental Engineering, University of Pittsburgh)
Kovacevic, Jelena (Department of Electrical and Computer Engineering, Carnegie Mellon University)

Publication Information

Smart Structures and Systems / v.13, no.5, 2014 , pp. 849-868 More about this Journal

Abstract

An indirect approach is explored for structural health bridge monitoring allowing for wide, yet cost-effective, bridge stock coverage. The detection capability of the approach is tested in a laboratory setting for three different reversible proxy types of damage scenarios: changes in the support conditions (rotational restraint), additional damping, and an added mass at the midspan. A set of frequency features is used in conjunction with a support vector machine classifier on data measured from a passing vehicle at the wheel and suspension levels, and directly from the bridge structure for comparison. For each type of damage, four levels of severity were explored. The results show that for each damage type, the classification accuracy based on data measured from the passing vehicle is, on average, as good as or better than the classification accuracy based on data measured from the bridge. Classification accuracy showed a steady trend for low (1-1.75 m/s) and high vehicle speeds (2-2.75 m/s), with a decrease of about 7% for the latter. These results show promise towards a highly mobile structural health bridge monitoring system for wide and cost-effective bridge stock coverage.

Keywords

indirect SHM; laboratory experiment; damage detection; classification;

Citations & Related Records

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