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Identification of mechanical systems with local nonlinearities through discrete-time Volterra series and Kautz functions

机译:通过离散时间Volterra级数和Kautz函数识别具有局部非线性的机械系统

摘要

Mathematical modeling of mechanical structures is an important research area in structural dynamics. One of the goals of this area is to obtain a model that accurately predicts the dynamics of the system. However, the nonlinear eff ects caused by large displacements and boundary conditions like gap, backlash or joint are not as well understood as the linear counterpart. This paper identifies a non-parametric discrete-time Volterra model of a benchmark nonlinear structure consisting of a cantilever beam connected to a thin beam at its free end. Time-domain data experimentally measured are used to identify the Volterra kernels, which are expanded with orthogonal Kautz functions to facilitate the identification process. The nonlinear parameters are then estimated through a model updating process involving optimization of the residue between the numerical and experimental kernels. The advantages and drawbacks of the Volterra series for modeling the behavior of nonlinear structures are finally indicated with suggestions to overcome the disadvantages found during the tests.
机译:机械结构的数学建模是结构动力学的重要研究领域。该领域的目标之一是获得一个能够准确预测系统动态的模型。但是,由大位移和边界条件(例如间隙,齿隙或接缝)引起的非线性效应并不像线性对应那样好理解。本文确定了基准非线性结构的非参数离散时间Volterra模型,该模型由悬臂梁连接到其自由端的细梁组成。实验测量的时域数据用于识别Volterra内核,并通过正交Kautz函数对其进行扩展以促进识别过程。然后,通过模型更新过程来估计非线性参数,该过程包括优化数值和实验内核之间的残差。最后指出了Volterra系列用于建模非线性结构行为的优缺点,并提出了克服测试中发现的缺点的建议。

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