基于布谷鸟搜索算法的动载荷识别
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TU311

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国家自然科学基金资助项目(11672098)。


Dynamic load identification based on the cuckoo search algorithm
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    摘要:

    工程结构经常受到动荷载的作用,对结构产生不利的影响。为了准确有效地获取结构承载状态,提出了基于Newmark-β法的布谷鸟搜索算法识别动载荷。该算法将时间离散成若干个时间步,采用Newmark-β法对离散后系统的运动方程求解,得到动载荷作用下的结构响应;然后将动载荷响应作为优化变量,以计算响应和测量响应之间的差异为目标函数,利用布谷鸟搜索算法最小化目标函数,实现动载荷的反演。为了验证算法的准确性和有效性,以受动态载荷作用的简支桥梁为例进行反演,分别讨论了鸟巢数量、测点位置、测点数量以及测量噪声对反演结果的影响。数值算例表明,该方法可准确有效地反演动载荷。

    Abstract:

    Engineering structures are often subjected to dynamic loads, which have negative influence on the structures. In order to accurately and effectively detect the load states of structures, a cuckoo search (CS) algorithm based on the Newmark-β method is developed to identify dynamic loads. Firstly, the time is discretized into several time steps, and the discretization equation of motion is obtained. The motion equation of the discrete motion system is solved and the response of the structure under dynamic load is calculated by the Newmark-β method. Secondly, the dynamic response is selected as the optimization variable. The objective function of the dynamic load identification problem is defined as the difference between the calculated response and the measured response of the dynamic load. The dynamic load is determined through minimization of the objective function with the CS algorithm. Finally, a simply supported beam bridge subjected to dynamic load is taken as an example to verify the accuracy and effectiveness of the algorithm. The effects of the nest number, the locations of measurement points, the number of measurement points and the measurement noise on the inversed results are discussed in numerical examples. The results show that the CS algorithm can be an accurate and effective inverse system method for dynamic load identification.

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高文静,周焕林,陶然.基于布谷鸟搜索算法的动载荷识别[J].重庆大学学报,2020,43(6):30-39.

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  • 收稿日期:2020-01-04
  • 在线发布日期: 2020-06-06
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