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Robust parametric updating of uncertain finite element models from experimental modal analysis

机译:实验模态分析中不确定有限元模型的鲁棒参数更新

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In this paper, a methodology is presented to perform the robust updating of complex uncertain dynamical systems with respect to modal experimental data in the context of structural dynamics. Since both model uncertainties and data uncertainties must be considered in the computational model, then the uncertain computational model is constructed by using the nonparametric probabilistic approach. We present an extension to the probabilistic case of the input error methodology for modal analysis adapted to the deterministic updating problem. It is shown that such an extension to the robust updating context induces some conceptual difficulties and is not straightforward. The robust updating formulation leads us to solve a mono-objective optimization problem in presence of inequality probabilistic constraints. A numerical application is presented in order to show the efficiency of the proposed method.
机译:在本文中,提出了一种方法,以在结构动态的背景下对模态实验数据进行复杂不确定动态系统的鲁棒更新。由于模型不确定性和数据不确定性必须在计算模型中考虑,因此通过使用非参数概率方法构建不确定的计算模型。我们向模态分析呈现输入误差方法的概率情况的扩展,适用于确定性更新问题。结果表明,鲁棒更新上下文的这种扩展会引起一些概念困难并且不简单。稳健的更新制定使我们在存在不等式概率约束时解决单对象优化问题。提出了数值应用,以显示所提出的方法的效率。

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