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Hybrid sensitivity matrix for damage identification in axially functionally graded beams

机译：用于轴向功能梯度梁损伤识别的混合灵敏度矩阵

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摘要

A sensitivity-based finite element model updating approach is presented to identify the local damages in axially functionally graded (AFC) beams. The local damage is simulated by a reduction in the elemental Young's modulus of the beam. In the forward analysis, free vibration analysis is conducted to obtain the natural frequency of the beam. Then forced vibration responses of the beam under external force are obtained from Newmark direct integration. In the inverse analysis, an objective function is established and a sensitivity-based finite element model updating approach is used to identify the local damages in the beam. Two numerical examples are investigated to illustrate the correctness and efficiency of the proposed method. Damage identification results from measured natural frequencies and the dynamic responses from different excitation forces are compared. The effects of measurement noise on the identification results are investigated. Studies in this paper indicate that the proposed method is efficient and robust for identifying damages in the axially functionally graded beams. Good identified results can be obtained from the short time histories of a few number of measurement points and the first several natural frequencies.
机译：提出了一种基于灵敏度的有限元模型更新方法，以识别轴向功能梯度（AFC）梁中的局部损伤。通过减小梁的元素杨氏模量来模拟局部损伤。在前向分析中，进行自由振动分析以获得梁的固有频率。然后从Newmark直接积分获得梁在外力作用下的强迫振动响应。在反分析中，建立了目标函数，并使用基于灵敏度的有限元模型更新方法来识别梁中的局部损伤。研究了两个数值例子，以说明所提方法的正确性和有效性。根据测得的固有频率进行损伤识别，并比较不同激励力的动态响应。研究了测量噪声对识别结果的影响。本文的研究表明，所提出的方法对于识别轴向功能梯度梁中的损伤是有效且稳健的。从几个测量点的短时间历史记录和前几个固有频率可以获得良好的识别结果。

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  • 来源
    《Applied Mathematical Modelling》 |2017年第1期|604-617|共14页
  • 作者

    Z.R. Lu; X.X. Lin; Y.M. Chen; M. Huang;

  • 作者单位

    Research Center of Intelligent Transportation System, Sun Yat-sen University, Guangzhou, Guangdong Province 510006, PR China;

    Research Center of Intelligent Transportation System, Sun Yat-sen University, Guangzhou, Guangdong Province 510006, PR China;

    Research Center of Intelligent Transportation System, Sun Yat-sen University, Guangzhou, Guangdong Province 510006, PR China;

    Research Center of Intelligent Transportation System, Sun Yat-sen University, Guangzhou, Guangdong Province 510006, PR China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Damage identification; Axially functionally graded beam; Hybrid sensitivity matrix; Model updating;

    机译：损坏识别;轴向功能梯度梁;混合灵敏度矩阵;模型更新;

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