On the feasibility of simultaneous identification of a material property of a Timoshenko beam and a moving vibration source

On the feasibility of simultaneous identification of a material property of a Timoshenko beam and a moving vibration source
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铁莫申柯梁材料特性与运动振动源同时辨识的可行性

DOI:
10.1016/j.engstruct.2020.111346
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发表时间:
2021
影响因子:
5.5
通讯作者:
Jeong, Chanseok
Jeong, Chanseok
中科院分区:
工程技术2区
文献类型:
--
作者:
Guidio, Bruno;Jeong, Chanseok

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本文采用有限元法求解连续梁在移动振源作用下的波动方程,研究了利用连续梁的实测振动数据同时识别连续梁的材料特性和移动振源的可行性。数值结果表明:首先,本文提出的反演方法能够检测出连续梁模型的运动波源特性和弹性模量的空间变化,其在本工作中被设置为逐块均匀的。第二,即使当移动振动源的移动速度随时间不恒定时,基于GA的联合反演也是有效的。第三,测量数据中的噪声对反演精度的不利影响随着控制参数的数量增加而变得更加显著。通过使用所提出的方法,工程师可以利用现代传感器测量的车辆引起的桥梁上的环境振动的被动波源为基础的结构健康监测(SHM)。
This paper presents a computational study for investigating the feasibility of simultaneous identification of a material property of a Timoshenko continuous beam and a moving vibration source on the beam by using the data of measured vibrations on it. This work employs the finite element method to solve the wave equations of a Timoshenko beam subject to a moving vibrational source. It uses the Genetic Algorithm (GA) as an inversion solver to identify the values of targeted control parameters that characterize a material property of the beam and a moving vibration source on it. The numerical results show that, first, the presented inversion method can detect the characteristics of a moving wave source as well as the spatial variation of the elastic modulus of a Timoshenko-beam continuous bridge model, which is set to be piece wisely homogeneous in this work. Second, the GA-based joint inversion is effective even when the moving vibrational source’s moving velocity is not constant over time. Third, the detrimental effect of noise in measurement data on the accuracy of the inversion becomes more significant as the number of control parameters increases. By using the presented method, engineers can take advantage of vehicle-induced ambient vibrations on bridges measured by modern sensors for the sake of passive wave source-based structural health monitoring (SHM).
利用遗传算法更新直升机旋翼桨叶有限元模型
DOI: --
发表时间: 2003
期刊:
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DOI: 10.1061/(asce)em.1943-7889.0001909
发表时间: 2021
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发表时间: 2010-01-01
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通讯作者: Kallivokas, Loukas F.