利用粒子群优化算法实现阻尼比和频率的精确识别

胡 峰;吴 波;胡友民;史铁林

振动与冲击 ›› 2009, Vol. 28 ›› Issue (7) : 8-11,2.

PDF(285 KB)
PDF(285 KB)
振动与冲击 ›› 2009, Vol. 28 ›› Issue (7) : 8-11,2.
论文

利用粒子群优化算法实现阻尼比和频率的精确识别

  • 胡 峰,吴 波,胡友民,史铁林
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Exact Evaluation of Damping and Frequency Based on Partical Swarm Optimization Algorithm

  • Hu Feng,Wu Bo,Hu You-min,Shi Tie-lin
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摘要

摘要:本文提出了一种利用粒子群优化算法辨识阻尼比和频率的方法。该方法将系统频率、阻尼比、幅值和相位的辨识问题转化为非线性优化问题,引入粒子群优化算法寻找全局最优解。基于粒子群优化的阻尼比和频率辨识方法不需要测量激励信号,原理简单,实现容易。仿真和实验结果表明:基于粒子群优化算法的阻尼比和频率辨识方法不受邻近模态耦合的影响。在无噪声条件下具有较高的辨识精度,随着信噪比的逐步降低,辨识精度开始逐步下降。用低通滤波器滤除高阶模态后,得到的脉冲响应信号对频率、阻尼比、幅值的辨识精度影响很小,对相位的辨识精度影响很大。


Abstract

This paper proposes a novel approach for structure modal parameter identification. The approach changes the identification problem to an optimal one. The global optimal solutions for the required parameters, including frequency, damping ratio, amplitude and phase of the structure can be obtained by taking the advantage of the Partical Swarm Optimization. The results of numerical simulation studies showed that the accuracy of this method is comparatively higher, and the adjacent modal coupling has no effect on its accuracy. The FIR lowpass has effect on the phase’s identification.

关键词

粒子群优化 / 阻尼识别 / 频率识别 / 低通滤波器

Key words

Partical Swarm Optimization / damping recognition / frequency recognition / lowpass

引用本文

导出引用
胡 峰;吴 波;胡友民;史铁林. 利用粒子群优化算法实现阻尼比和频率的精确识别[J]. 振动与冲击, 2009, 28(7): 8-11,2
Hu Feng;Wu Bo;Hu You-min;Shi Tie-lin. Exact Evaluation of Damping and Frequency Based on Partical Swarm Optimization Algorithm[J]. Journal of Vibration and Shock, 2009, 28(7): 8-11,2

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