Vibration-based damage detection methods are used in structural applications to identify the global dynamic response of the system. The purpose of the work presented is to exhibit a vibration-based damage detection algorithm that calculates a damage indicator, based on limited frequency bands of the transmissibility function that have high coherence, as a metric for changes in the dynamic integrity of the structure. The methodology was tested using numerical simulation, laboratory experimentation, and field testing with success in detecting, comparatively locating, and relatively quantifying different damages while also parametrically investigating variables which have been identified as issues within similar existing methods. Throughout both the numerical and laboratory analyses, the results were used to successfully detect damage as a result of crack growth or formation of new cracks. 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 to 60 mm) 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 by limiting the features of transmissibility to frequency ranges of high coherence, the effect of these parameters, as compared to the effect of damage, become less significant and can be neglected for some instances. 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.
Identifer | oai:union.ndltd.org:uiowa.edu/oai:ir.uiowa.edu:etd-6342 |
Date | 01 December 2015 |
Creators | Schallhorn, Charles Joseph |
Contributors | Rahmatalla, Salam |
Publisher | University of Iowa |
Source Sets | University of Iowa |
Language | English |
Detected Language | English |
Type | dissertation |
Format | application/pdf |
Source | Theses and Dissertations |
Rights | Copyright 2015 Charles Schallhorn |
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