Nonlinear Structures & Systems, Volume 1 - Proceedings of the 40th IMAC, A Conference and Exposition on Structural Dynamics 2022
Nonlinear Structures & Systems, Volume 1 - Proceedings of the 40th IMAC, A Conference and Exposition on Structural Dynamics 2022
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非线性结构
DOI：
10.1007/978-3-031-04086-3_9
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发表时间：
2023
期刊：
影响因子：
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通讯作者：
Lee K
中科院分区：
文献类型：
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作者：
Lee K
自激振动存在于许多工程应用中，例如机翼颤振、钻柱粘滑振动和车轮摆振。这些自激振动通常是不需要的，因为它们会对系统造成严重损坏。为了避免此类现象，系统的精确数学模型至关重要。自激系统通常被建模为具有 Hopf 分岔的动力系统。与线性系统相比，从数据中识别这种非线性动力系统更具挑战性。在本研究中，我们提出了两种不同的使用实验分岔分析数据的自激系统数学模型识别方法。第一种方法考虑经验数学模型，其系数被确定以适合测量的分岔图。第二种方法考虑基本的 Hopf 范式模型，并学习数据驱动的坐标变换，将范式状态空间映射到物理坐标。所开发的方法应用于在二自由度颤振装置上收集的分叉数据，这两种方法显示出有希望的结果。讨论了这些方法的优点和缺点。
Self-excited vibrations can be found in many engineering applications such as flutter of aerofoils, stick-slip vibrations in drill strings, and wheel shimmy. These self-excited vibrations are generally unwanted since they can cause serious damage to the system. To avoid such phenomena, an accurate mathematical model of the system is crucial. Self-excited systems are typically modelled as dynamical systems with Hopf bifurcations. The identification of such non-linear dynamical system from data is much more challenging compared to linear systems.In this research, we propose two different mathematical model identification methods for self-excited systems that use experimental bifurcation analysis data. The first method considers an empirical mathematical model whose coefficients are identified to fit the measured bifurcation diagram. The second approach considers a fundamental Hopf normal form model and learns a data-driven coordinate transformation mapping the normal form state-space to physical coordinates. The approaches developed are applied to bifurcation data collected on a two degree-of-freedom flutter rig and the two methods show promising results. The advantages and disadvantages of the methods are discussed.