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

林阳, 封周权, 华旭刚, 陈政清

林阳, 封周权, 华旭刚, 陈政清. 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[J]. 工程力学, 2020, 37(2): 192-200. DOI: 10.6052/j.issn.1000-4750.2019.03.0143
引用本文: 林阳, 封周权, 华旭刚, 陈政清. 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[J]. 工程力学, 2020, 37(2): 192-200. DOI: 10.6052/j.issn.1000-4750.2019.03.0143
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LIN Yang, FENG Zhou-quan, HUA Xu-gang, CHEN Zheng-qing. ARTIFICIAL BEE COLONY ALGORITHM FOR FLUTTER DERIVATIVES IDENTIFICATION OF BRIDGE DECKS USING FREE VIBRATION RECORDS[J]. Engineering Mechanics, 2020, 37(2): 192-200. DOI: 10.6052/j.issn.1000-4750.2019.03.0143
Citation: LIN Yang, FENG Zhou-quan, HUA Xu-gang, CHEN Zheng-qing. ARTIFICIAL BEE COLONY ALGORITHM FOR FLUTTER DERIVATIVES IDENTIFICATION OF BRIDGE DECKS USING FREE VIBRATION RECORDS[J]. Engineering Mechanics, 2020, 37(2): 192-200. DOI: 10.6052/j.issn.1000-4750.2019.03.0143
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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

  • 湖南大学风工程与桥梁工程湖南省重点实验室, 湖南, 长沙 410082

基金项目: 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）
详细信息
    作者简介:

    林阳(1996-),男,河南人,硕士生,主要从事桥梁风工程研究(E-mail:linyang@hnu.edu.cn);华旭刚(1978-),男,浙江人,教授,博士,博导,主要从事风工程研究(E-mail:cexghua@hnu.edu.cn);陈政清(1947-),男,湖南人,教授,博士,博导,主要从事工程力学研究(E-mail:zqchen@hnu.edu.cn).

    通讯作者:

    封周权(1982-),男,湖南人,助理教授,博士,硕导,主要从事风工程及结构监测与控制研究(E-mail:zqfeng@hnu.edu.cn).

  • 中图分类号: U441.3

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

  • Key Laboratory for Wind and Bridge Engineering of Hunan Province, Hunan University, Changsha, Hunan 410082, China

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    摘要
  • 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。
    Abstract: 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.
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    • 参考文献(24)
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出版历程
  • 收稿日期:  2019-03-26
  • 修回日期:  2019-07-03
  • 刊出日期:  2020-05-26

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