Abstract: Time histories often vary too much to determine root cause of signal shift. Frequency information and extracted modal properties can correlate to structural health through quantitative change metrics. Herein, fifty-one modal-based damage indices are considered in a total of three directions. These metrics are combined via vector resultants and Genetic Algorithm to visualize final relative stiffness results by location of data capture using a color code. This work presents inspection and data mining on an obsolete three-span truss highway bridge from 1953 or 1941 (disputed). Tri-axial deck data was captured in a grid for all three spans, and the new damage detection methodology is applied to Spans 1 and 2 with Span 3 as control. Comparative analysis among the three spans quantified joint effects, and end damages due to both scour and spalling were identifiable. Furthermore, unbiased analyses provided similar results to those biased by visual inspection. A more pointed visual inspection is thus permitted post-analysis.
Keywords: Modal Analysis, Data Mining, Genetic Algorithm, Bridge Inspection, Damage Detection.
Title: Damage Index Combination via Genetic Algorithm: A Highway Bridge Case Study
Author: Elizabeth K. Ervin, Chuangshuo Zeng
International Journal of Civil and Structural Engineering Research
ISSN 2348-7607 (Online)
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