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Structural Condition Assessment in a Prestressed Concrete Bridge Based on Analysis of Environmental Effects on Long-term Strain Monitoring Data



Authors' group has been working on a SHM project in an existing concrete bridge located in an area of heavy snowfall in Japan for these three years. In this paper, the application of seasonal ARIMA model estimation to the statistical structural condition assessment was firstly shown by applying it to the acquired long-term strain data. In the results, the plot of estimated seasonal AR and MA coefficients showed a distribution with a linear regression that indicate the patterns of strain time-series. However, the plots from the strain data acquired in the snowy season showed different regressions. It was then considered that the patterns of time-series structural responses were changed due to the existence of accumulated snow. To verify the influence of snow accumulation, the temperature distribution of the target bridge were continuously measured through a year. The acquired data showed that there were complex temperature distributions through a year not only within the cross-section but also in the longitudinal direction. Especially in the temperature difference between top and bottom of the girder cross-sections, the seasonal trends that was considered to be related to the existence of snow accumulation could be observed. It was considered that the snow accumulation affected the detail temperature distribution of the bridge, and its difference caused the different regression in the seasonal AR-MA plots. This consideration could also indicate that there was a possibility of using the seasonal ARIMA model coefficients plot for capturing the structural response changes also due to the significant structural condition changes.

doi: 10.12783/SHM2015/102

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