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Structural Damage Detection of Truss Bridge under Environmental Variability |
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PP: 259-265 |
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Author(s) |
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Ling Yu,
Junhua Zhu,
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Abstract |
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| Focused on the effects of environmental and operational variability on the structures, a novel procedure for structural linear
and nonlinear damage detection is proposed based on the time series analysis and the higher statistical moments. The higher statistical
moments of residual error of AR model, such as skewness and kurtosis, are then defined as the new damage-sensitive features to be a
complimentary. Six integrated damage-sensitive features are further defined for vibration-based damage detection in terms of arithmetic
and geometric mean of the residual errors. A series of experiments on a complicated truss bridge combined with a steel bridge plate have
been conducted in laboratory. Damage was simulated by loosening the bolts of joints, and environmental variability were introduced
by changing the shaker input level. 16 acceleration data of the bridge in each baseline and test state are measured and recorded for the
structural damage detection. Based on these time series of acceleration data, the applicability of the proposed procedure is evaluated.
Some valued conclusions are made and discussions suggested as well. |
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