基于遗传算法与随机减量技术的气动阻尼识别方法研究

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摘要随机减量技术(random decrement technique，RDT)因其计算快、成本低的优点，在工程结构模态参数识别中应用广泛。针对RDT在信号截断幅值与样本时长的选取比较主观带来的误差问题，采用遗传算法(genetic algorithm, GA)对其进行改进，提出改进的随机减量技术GA-RDT，并将其应用于某超高层建筑气弹模型的气动阻尼识别。首先，对RDT方法得到的自由衰减曲线进行拟合并定义误差，分析截断幅值A和样本时长T对误差（优化目标）的影响，采用遗传算法寻找A和T的最优解；其次，基于气弹模型风洞试验所得的顶点加速度时程，结合GA-RDT方法和Hilbert-Huang变换（Hilbert-Huang transform，HHT）方法进行气动阻尼识别；最后，以自然激励技术(natural excitation technique, NExT)识别所得的气动阻尼比为基准，对比分析GA-RDT方法相对于传统RDT方法的精度优势。结果表明，与NExT方法所得的气动阻尼比相比，GA-RDT方法识别得到的不同风速时X向、Y向与扭转向的气动阻尼比的平均误差均小于0.14%，其识别精度显著高于传统RDT方法，从而验证了基于GA-RDT的气动阻尼识别方法的可行性。

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	唐龙飞1
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	郑朝荣1
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关键词 ：超高层建筑, 气动阻尼识别, 遗传算法, 改进的随机减量技术, 自然激励技术

Abstract：The random decrement technique (RDT) has been widely utilized in the modal parameter identification of engineering structures, due to its advantage of rapid computation and low cost. Aiming at the shortcomings of subjective selection of truncation amplitude and sample duration in the RDT, which brings large error in the modal parameter identification, the genetic algorithm is adopted to revise the RDT and the improved RDT (GA-RDT) method is proposed, and then the GA-RDT method is applied in the aerodynamic damping ratio identification of an aeroelastic model of a supertall building. Firstly, the free decay curve obtained by the RDT is fitted and then the error is defined. The effect of the cut-off amplitude and sample duration on the optimization target is analyzed and the genetic algorithm is utilized to search the optimal solution of these two parameters. Secondly, based on the tip acceleration time history acquired by the aeroelastic model wind tunnel test, the aerodynamic damping ratio is identified by combining the GA-RDT and Hilbert-Huang transformation method. Finally, the aerodynamic damping ratio identified by the natural excitation technique (NExT) is regarded as the benchmark, and the identification accuracy based on the GA-RDT method and traditional RDT method are discussed. The results show that, when compared with the aerodynamic damping ratio identified by the NExT method, the corresponding results identified by the GA-RDT method under different wind speeds have an average error of less than 0.14% in the X, Y and torsional directions respectively, and the identification accuracy is much better than those identified by the traditional RDT method. Therefore, the feasibility of the aerodynamic damping identification method based on the GA-RDT method is verified.

Key words： supertall building aerodynamic damping identification genetic algorithm improved random decrement technique natural excitation technique

收稿日期: 2021-11-08 出版日期: 2023-03-28

引用本文:

唐龙飞1,2，郑朝荣1,3. 基于遗传算法与随机减量技术的气动阻尼识别方法研究[J]. 振动与冲击, 2023, 42(6): 16-23.
TANG Longfei1,2，ZHENG Chaorong1,3. Identification method of aerodynamic damping based on the genetic algorithm and random decrement technique. JOURNAL OF VIBRATION AND SHOCK, 2023, 42(6): 16-23.

链接本文:

http://jvs.sjtu.edu.cn/CN/ 或 http://jvs.sjtu.edu.cn/CN/Y2023/V42/I6/16

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