Abstract
Maintaining civil infrastructure, including bridges, has been a keen technical issue in developed countries and will surely be one in developing countries in the near future. An effective maintenance strategy strongly depends on timely decisions on the health condition of the structure. Bridge health monitoring (BHM) using vibration data is widely recognized to be one of the effective technologies that aid decision-making on bridge maintenance. This research focuses on long-term BHM expecting that changes in physical properties of the bridge subject to aged-deterioration progress slowly. In the practical application of the long-term BHM, one of the difficulties is that the observed vibration data includes environmental influences such as temperature change. In order to achieve high accuracy in evaluating modal parameters of the bridge, other influencing variables have to be taken into consideration. In this study, temperature is considered as the main environmental factor by means of a regression analysis. The Mahalanobis distance (MD), a multivariate statistical distance, is adopted to emphasize potential changes in the identified modal parameters. The validity of the proposed approach is investigated utilizing vibration data measured at a real bridge in service.
Highlights
Damage in bridges has been reported in many countries due to deterioration, aging, heavy loads, etc.How to establish an economical and efficient structural soundness evaluation system has been a keen issue in the field of civil engineering for years
The Mahalanobis distance is a generalized distance, which can be considered as a single-dimensional quantity that expresses the degree of divergence of a multivariate sample with respect to the central point of the set of normally distributed multivariate samples it belongs in considering the correlations between the variables
By estimating Mahalanobis distance (MD) of a certain observation point, the similarity of the vibrational properties at that time to the intact ones can be quantitatively expressed, which is focused at for damage-detecting in this study. Another advantage of adopting MD as the indicator is that it contains the information of multiple variables, the modal parameters, which vary in a level that is not obvious enough to draw conclusion about the existence of damages, and by accumulation, minimal changes in modal parameters due to change in vibration characteristics during long-term monitoring become noticeable difference in MD, which makes it easier for decision-making
Summary
Evaluation of bridge instability caused by dynamic scour based on fractal theory Tzu-Kang Lin, Rih-Teng Wu, Kuo-Chun Chang et al. Shinae Jang, Sung-Han Sim, Hongki Jo et al. A constituent-based preprocessing approach for characterising cartilage using NIR absorbance measurements. Fast processing spectral discrimination for hyperspectral imagers based on interferometry. Journal of Physics: Conference Series 628 (2015) 012055 doi:10.1088/1742-6596/628/1/012055. Of Civil and Earth Resources Eng., Graduate School of Eng., Kyoto University, Kyoto, JAPAN. Of Civil and Earth Resources Eng., Graduate School of Eng., Undergraduate student, Dept. Of Global Engineering, Kyoto University, Kyoto, JAPAN Dept. of Civil and Earth Resources Eng., Graduate School of Eng., Undergraduate student, Dept. of Global Engineering, Kyoto University, Kyoto, JAPAN
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