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Finite Element Model Updating Techniques of Complex Assemblies with Linear and Nonlinear Components

机译:线性和非线性组件复合组件的有限元模型更新技术

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In this work, finite element model updating techniques are presented for identifying the linear and nonlinear parts of dynamic systems using vibration measurements of their components. The measurements are taken to be either response time histories or frequency response functions of linear and nonlinear components of the system. The model updating techniques were coupled with robust and accurate finite element analysis software in order to produce computational effective results. The developed framework is applied to a geometrically complex and lightweight experimental bicycle frame with nonlinear suspension fork components. The identification of modal characteristics of the frame (linear part) is based on an experimental investigation of its dynamic response. The modal characteristics are then used to update the finite element model. The nonlinear suspension components are identified using the experimentally obtained response spectra for each of the components tested separately. Single and multi-objective structural identification methods with appropriate substructuring methods, are used for estimating the parameters (material properties, shell thickness properties and nonlinear properties) of the finite element model, based on minimizing the deviations between the experimental and analytical dynamic characteristics. Finally, the numerical result of the complete system assembly was compared to experimental results of the equivalent physical structure of the bike.
机译:在这项工作中,提出了有限元模型更新技术,用于使用组件的振动测量来识别动态系统的线性和非线性部分。测量被认为是系统的线性和非线性组件的响应时间历史或频率响应函数。模型更新技术与鲁棒和准确的有限元分析软件耦合,以产生计算有效的结果。开发的框架应用于几何复合体和轻质实验自行车架,具有非线性悬浮叉组件。框架(线性部件)的识别基于其动态响应的实验研究。然后使用模态特性来更新有限元模型。使用实验获得的响应光谱鉴定非线性悬浮液组分,用于分别测试的每个组分。具有适当的子结构方法的单个和多目标结构识别方法,用于估计有限元模型的参数(材料特性,壳体厚度和非线性性质),基于最小化实验和分析动态特性之间的偏差。最后,将完整的系统组件的数值结果与自行车的等同物理结构的实验结果进行了比较。

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