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Mode Shape Description and Model Updating of Axisymmetric Structures Using Radial Tchebichef Moment Descriptors

机译:使用径向Tchebichef矩描述仪模拟轴对称结构的形状描述和模型更新

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A novel approach for mode shape feature extraction and model updating of axisymmetric structures based on radial Tchebichef moment (RTM) descriptors is proposed in this study. The mode shape features extracted by RTM descriptors can effectively compress the full-field modal vibration data and retain the most important information. The reconstruction of mode shapes using RTM descriptors can accurately describe the mode shapes, and the simulation shows that the RTM function is superior to Zernike moment function in terms of its mathematical properties and its shape reconstruction ability. In addition, the proposed modal correlation coefficient of the RTM amplitude can overcome the main disadvantage of using the modal assurance criterion (MAC), which has difficulty in identifying double or close modes of symmetric structures. Furthermore, the model updating of axisymmetric structures based on RTM descriptors appears to be more efficient and effective than the normal model updating method directly using modal vibration data, avoids manipulating large amounts of mode shape data, and speeds up the convergence of updating parameters. The RTM descriptors used in correlation analysis and model updating are demonstrated with a cover of an aeroengine rig. The frequency deviation between the test and the FE model was reduced from 17.13% to 1.23% for the first 13 modes via the model updating process. It verified the potential to industrial application with the proposed method.
机译:本研究提出了一种基于径向TCHEBICHEF时刻(RTM)描述符的模式形状特征提取和模型更新的新方法。 RTM描述符提取的模式形状功能可以有效地压缩全场模态振动数据并保留最重要的信息。使用RTM描述符的模式形状的重建可以准确地描述模式形状,并且模拟表明RTM功能在其数学特性和其形状重建能力方面优于Zernike矩函数。此外,RTM幅度的所提出的模态相关系数可以克服使用模态保证标准(MAC)的主要缺点,这难以识别对称结构的双或关闭模式。此外,基于RTM描述符的轴对称结构的模型更新似乎比使用模态振动数据直接的正常模型更新方法更有效和有效,避免了操纵大量模式形状数据,并加速更新参数的收敛。用于相关性分析和模型更新的RTM描述符与航空发动机钻机的盖子进行了演示。通过模型更新过程,测试和FE模型之间的频率偏差从前13种模式的17.13%降低至1.23%。它验证了具有所提出的方法的工业应用。

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