基于自由振动响应识别桥梁断面颤振导数的人工蜂群算法

基于桥梁节段模型风洞试验自由振动衰减时程信号，提出了桥梁断面颤振导数识别的人工蜂群算法。基于最小二乘原理，将竖弯和扭转信号的整体残差平方和作为目标函数，使用人工蜂群算法对相关参数进行寻优搜索，识别出桥梁断面的颤振导数。与其他迭代算法相比，人工蜂群算法是受生物启发产生的寻优算法，对初值没有要求，从而避免了迭代初值对识别精度的影响。为考察人工蜂群算法在桥梁断面颤振导数识别中的有效性，进行了理想平板模型仿真以及某大桥节段模型风洞试验，结果表明，桥梁断面颤振导数识别的人工蜂群算法具有较好的稳定性和可靠性。

ARTIFICIAL BEE COLONY ALGORITHM FOR FLUTTER DERIVATIVES IDENTIFICATION OF BRIDGE DECKS USING FREE VIBRATION RECORDS

Based on the coupled free vibration records of bridge deck sectional model testing,a flutter derivatives identification method based on the artificial bee colony(ABC)algorithm is proposed.The objective function is constructed as the ensemble residual quadratic sum of the vertical and torsional vibration time histories in the sense of least squares.The ABC algorithm is used to search the optimal parameters so that the value of the objective function is minimized.Compared with other iteration methods,the ABC algorithm can facilitate the identification process with no need for initial values.In order to investigate the effectiveness of the ABC algorithm in the flutter derivatives identification,an ideal thin-plate model simulation and a real bridge sectional model testing are carried out.The results show that the ABC algorithm for the flutter derivatives identification of bridge decks is robust and reliable.