Journal article
Crack detection and health monitoring of highway steel-girder bridges
STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL, Vol.14(3), pp.281-299
2015
DOI: 10.1177/1475921714568404
Abstract
A vibration-based damage-detection methodology is presented in this work to monitor the health condition of a highway steel-girder bridge in Iowa. The contribution of the proposed methodology is to combine the transmissibility function, coherence function, and probabilistic schemes to construct a percent-violation that gives critical information about the health condition of the bridge. The percent-violation creates two alarm severities, watch and warning, depending on how many times the percent-violation successively crosses an objective threshold created from the healthy data. Field results using stochastic operational traffic loading have indicated the capability of the proposed methodology in evaluating the changes in the health condition of a section of the bridge and in consistently detecting cracks of various sizes (30-60mm) on a sacrificial specimen integrated with the bridge abutment and a floor beam. Fluctuations in environmental and loading conditions have been known to create some uncertainties in most damage-detection processes; however, this work demonstrated that using an objective threshold, these uncertainties will be contained. Additionally, based on the sacrificial specimen's results, once damage is initiated or propagated on the structure, the effect of these parameters becomes less relevant. The results of additional field testing using controlled impact forces on the sacrificial specimen have reinforced the findings from the operational loading in detecting damage.
Details
- Title: Subtitle
- Crack detection and health monitoring of highway steel-girder bridges
- Creators
- C Schallhorn - University of IowaS Rahmatalla - University of Iowa
- Resource Type
- Journal article
- Publication Details
- STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL, Vol.14(3), pp.281-299
- DOI
- 10.1177/1475921714568404
- ISSN
- 1741-3168
- Language
- English
- Date published
- 2015
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Civil and Environmental Engineering; Injury Prevention Research Center
- Record Identifier
- 9984239294402771
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