基于RDT和WT方法识别超高层建筑的模态参数

Identifying modal parameters of super tall buildings based on RDT and WT methods

超高层建筑风致振动相关的动态参数尤其是阻尼比数据资料的缺乏会增加设计阶段动态参数准确选取的难度。因而,现役超高层建筑动态响应的实测与参数识别对这些动态数据资料的补充和设计准确性的校验是十分必要的。将基于强风作用下超高层建筑——上海金茂大厦动态响应的现场实测,使用Morlet小波变换并且结合随机减量技术(RDT)识别上海金茂大厦的固有频率和阻尼比。数值结果表明,上海金茂大厦固有频率的识别非常精确,但发现阻尼比的识别随着阶数的升高其标准差有增大的趋势。

The strong wind-induced responses of Shanghai Jin Mao mansion from field measurements were analyzed by the wavelet transformation (WT) with a kernel function, the Morlet wavelet, combined with the random decrement technique (RDT). Its natural frequencies and corresponding damping ratios were identified. The numerical result shows that the identification of structural natural freguencies is considerably accurate, while with the increase of order, the standard deviation of damping ratios is growing up.