Bing Qu*, Ping Liao, Yaolong Huang
Structural Durability & Health Monitoring, Vol.16, No.4, pp. 323-341, 2022, DOI:10.32604/sdhm.2022.021446
Abstract The method of time series analysis, applied by establishing appropriate mathematical models for bridge health monitoring data and making forecasts of structural future behavior, stands out as a novel and viable research direction for bridge state assessment. However, outliers inevitably exist in the monitoring data due to various interventions, which reduce the precision of model fitting and affect the forecasting results. Therefore, the identification of outliers is crucial for the accurate interpretation of the monitoring data. In this study, a time series model combined with outlier information for bridge health monitoring is established using intervention analysis theory, and the forecasting… More >
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