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An improved perturbation method for stochastic finite element model updating

机译:随机有限元模型更新的一种改进的摄动方法

摘要

In this paper, an improved perturbation method is developed for the statistical identification of structural parameters by using the measured modal parameters with randomness. On the basis of the first-order perturbation method and sensitivity-based finite element (FE) model updating, two recursive systems of equations are derived for estimating the first two moments of random structural parameters from the statistics of the measured modal parameters. Regularization technique is introduced to alleviate the ill-conditioning in solving the equations. The numerical studies of stochastic FE model updating of a truss bridge are presented to verify the improved perturbation method under three different types of uncertainties, namely natural randomness, measurement noise, and the combination of the two. The results obtained using the perturbation method are in good agreement with, although less accurate than, those obtained using the Monte Carlo simulation (MCS) method. It is also revealed that neglecting the correlation of the measured modal parameters may result in an unreliable estimation of the covariance matrix of updating parameters. The statistically updated FE model enables structural design and analysis, damage detection, condition assessment, and evaluation in the framework of probability and statistics.
机译:本文提出了一种改进的摄动方法,通过使用随机测量的模态参数对结构参数进行统计识别。基于一阶摄动法和基于灵敏度的有限元(FE)模型更新,导出了两个递归方程组,用于根据所测模态参数的统计量估计随机结构参数的前两个矩。引入正则化技术来缓解求解方程时的不适感。给出了桁架桥随机有限元模型更新的数值研究,以验证在三种不同类型的不确定性(即自然随机性,测量噪声以及两者的组合)下的改进的摄动方法。使用扰动方法获得的结果与使用蒙特卡洛模拟(MCS)方法获得的结果相比,尽管准确性较差,但与它们具有很好的一致性。还揭示出,忽略所测量的模态参数的相关性可能导致更新参数的协方差矩阵的不可靠估计。经过统计更新的有限元模型可以在概率和统计的框架内进行结构设计和分析,损伤检测,状况评估和评估。

著录项

  • 作者

    Hua XG; Ni YQ; Chen ZQ; Ko JM;

  • 作者单位
  • 年度 2008
  • 总页数
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类

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