Based on the self-anchored suspension bridge, Fumin Bridge in Tianjin, the dynamic response of the bridge is monitored continuously and real-time under the condition of no closed traffic. The original data of structural vibration displacement are collected by GPS sensors. After the monitoring data preprocessed, filtered and noise reduction, applying the random decrement technique extended by auto-regressive moving average, this article recognized the modal parameter of the bridge. The results show that the method is very close to the results of finite element analysis, and the modal parameter of the bridge can be recognized reliably by GPS-RTK data.%以自锚式悬索桥天津市富民桥为背景,在交通不封闭的情况下对富民桥的动态响应进行连续的实时监测,通过GPS传感器采集结构振动位移原始数据.应用时间序列法(ARMA)扩展随机减量法(RDT),对预处理和滤波降噪后的监测数据进行分析,识别桥梁结构的模态参数.研究结果表明,该方法与有限元分析得出的结果非常接近,证明该法用于GPS-RTK数据识别桥梁模态参数可行可靠.
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