摘要
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。
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.
作者
林阳
封周权
华旭刚
陈政清
LIN Yang;FENG Zhou-quan;HUA Xu-gang;CHEN Zheng-qing(Key Laboratory for Wind and Bridge Engineering of Hunan Province,Hunan University,Changsha,Hunan 410082,China)
出处
《工程力学》
EI
CSCD
北大核心
2020年第2期192-200,共9页
Engineering Mechanics
基金
国家自然科学基金项目(51708203)
湖南省高校创新平台开放基金项目(17K022)
中央高校基本科研业务费项目(531118010047)
关键词
桥梁工程
颤振导数
人工蜂群算法
参数识别
优化方法
bridge engineering
flutter derivatives
artificial bee colony algorithm
parameter identification
optimization method