Big Bang-Big Crunch optimization for parameter estimation in structural systems

Big Bang-Big Crunch optimization for parameter estimation in structural systems
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用于结构系统参数估计的 Big Bang-Big Crunch 优化

DOI:
10.1016/j.ymssp.2010.03.012
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发表时间:
2010-11
影响因子:
8.4
通讯作者:
Zhou, Jin
Zhou, Jin
中科院分区:
工程技术1区
文献类型:
--
作者:
Tang, Hesheng;Xue, Songtao;Xie, Liyu;Zhou, Jin

文献摘要

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提出了一种新的基于大爆炸-大破裂(BB-BC)优化方法的结构系统参数估计方法,将参数估计问题描述为高维多峰优化问题。BB-BC方法的灵感来自于宇宙演化理论之一。BB-BC的潜力在于其固有的数值简单性、快速收敛速度和易于实现。仿真结果表明,在输出数据有限、信号受噪声污染、质量、阻尼或刚度未知的情况下,该方法对结构系统参数的辨识具有较好的效果。结果表明,BB-BC法比现有的方法有较好的结果。此外,该方法在计算上更简单。
A new approach to parameter estimation of structural systems using the recently developed Big Bang-Big Crunch (BB-BC) optimization is proposed, in which the parameter estimation is formulated as a multi-modal optimization problem with high dimension. The BB-BC method is inspired by one of the theories of the evolution of universe. The potentialities of BB-BC are its inherent numerical simplicity, high convergence speed, and easy implementation. The performances of the proposed method are investigated with simulation results for identifying the parameters of structural systems under conditions including limited output data, noise-polluted signals, and no priori knowledge of mass, damping, or stiffness. It is observed that BB-BC gives comparatively better results than existing methods. Moreover the method is computationally simpler.
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