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Estimation of parameter matrices based on measured data

机译:基于实测数据的参数矩阵估计

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摘要

Finite element structural updating based on measured data may inherent significant errors due to uncertainties in the updated physical parameter matrices. This study presents ana lytical equations to estimate the change in the physical parameter matrices based on the measured modal data of dynamic systems and the measured displacement data of static systems. The equations for the parameter estimation are derived by minimizing cost func tions in the satisfaction of the eigenvalue equation, the mode shape orthogonality require ments for the dynamic system, and the satisfaction of the measured displacement data for the static systems. The proposed method utilizes the Moore-Penrose inverse for the inverse of the rectangular matrices without using Lagrange multipliers. Comparing the analytical results with Berman & Nagy's method and Yang & Chen's method, this study demonstrates that the derived equations take simpler forms and produce more accurate results. The proposed method can be widely utilized in predicting static or dynamic param eter matrices for the design and analysis of any structure.
机译:基于更新后的物理参数矩阵的不确定性,基于测量数据的有限元结构更新可能会固有的重大误差。这项研究提出了一个解析方程,根据测得的动态系统模态数据和测得的静态系统位移数据,估算物理参数矩阵的变化。参数估计的方程式是通过最小化特征函数方程式中的成本函数,动态系统的振型正交性要求以及静态系统的实测位移数据的满足性而得出的。所提出的方法在不使用拉格朗日乘数的情况下将Moore-Penrose逆用于矩形矩阵的逆。将分析结果与Berman&Nagy方法和Yang&Chen方法相比较,该研究表明,导出的方程采用更简单的形式并产生更准确的结果。所提出的方法可广泛用于预测静态或动态参数矩阵,以用于任何结构的设计和分析。

著录项

  • 来源
    《Applied Mathematical Modelling》 |2011年第10期|p.4816-4823|共8页
  • 作者单位

    Department of Architectural Engineering, Chung-Ang University, Republic of Korea;

    Department of Civil and Environmental Engineering, 4105 Seamans Center, The University of Iowa, Iowa City, IA 52242-1527, USA;

    Department of Architectural Engineering, Kangwon National University, Hyoja 2 Dong, Chuncheon, South Korea;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    modal data; parameter matrices; cost function; minimization; orthogonality;

    机译:模态数据参数矩阵成本函数;最小化正交性;
  • 入库时间 2022-08-18 03:00:08

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