Research on Health Monitoring of Urban Rail Transit Bridges
In order to ensure the accuracy of monitoring the operation status of bridges,bridge health monitoring systems usually use sensors with high sampling frequency to collect bridge data in real time,and long-term exposure of sensors to harsh environments will lead to data drift and loss of monitoring data.In view of the massive data of the bridge health monitoring system,the monitoring data of a continuous beam bridge in Wuhan urban rail transit was processed by using the Shoreler criterion-smoothing prior filtering method,and analyzed in combination with rel-evant specifications.The results show that the proposed method can well eliminate outliers and low-frequency noise,separate the temperature effect of the deflection data,and evaluate the health status of the bridge.
Bridge health monitoringData preprocessingSmoothing prior filteringAssess
万方数据
维普
