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为研究环境温度对珠江黄埔大桥频率监测的影响,首先要对大桥模态频率进行连续识别。珠江黄埔大桥上架设的监测系统为强震动台阵,相较于其他健康监测系统测点较少,因此,应基于强震动台阵系统的特点,选取合适的方法对大桥频率进行识别。本文通过对比分析平均正则化功率谱法(ANPSD)、频域分解法(FDD)和协方差驱动的随机子空间法(Cov-SSI)的识别结果,择优应用于珠江黄埔大桥的频率自动识别中。采用珠江黄埔大桥强震动台阵记录的2013年4月至11月加速度响应数据进行频率识别,识别结果可用于观测和研究大桥频率在环境影响下的波动情况。
In order to study the influence of ambient temperature on the frequency monitoring of Huangpu Bridge in Zhujiang River, the modal frequencies of the bridge should be continuously identified. The monitoring system installed on the Zhujiang Huangpu Bridge is a strong vibration array, which has fewer measurement points than other health monitoring systems. Therefore, the appropriate method should be adopted to identify the frequency of the bridge based on the characteristics of the strong vibration array system. By comparing and analyzing the recognition results of ANSPD, FDD and covariance-driven stochastic subspace method (Cov-SSI), this paper is applied to the automatic identification of Zhujiang Huangpu Bridge . The frequency response of acceleration data was recorded from April 2013 to November 2013 recorded by strong seismic array of Zhujiang Huangpu Bridge. The identification results can be used to observe and study the fluctuation of bridge frequency under the environmental impact.