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Modal identifiability of a cable-stayed bridge using proper orthogonal decomposition

机译:使用适当正交分解的斜拉桥的模态可识别性

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摘要

The recent research on proper orthogonal decomposition (POD) has revealed the linkage between proper orthogonal modes and linear normal modes. This paper presents an investigation into the modal identifiability of an instrumented cable-stayed bridge using an adapted POD technique with a band-pass filtering scheme. The band-pass POD method is applied to the datasets available for this benchmark study, aiming to identify the vibration modes of the bridge and find out the so-called deficient modes which are unidentifiable under normal excitation conditions. It turns out that the second mode of the bridge cannot be stably identified under weak wind conditions and is therefore regarded as a deficient mode. To judge if the deficient mode is due to its low contribution to the structural response under weak wind conditions, modal coordinates are derived for different modes by the band-pass POD technique and an energy participation factor is defined to evaluate the energy participation of each vibration mode under different wind excitation conditions. From the non-blind datasets, it is found that the vibration modes can be reliably identified only when the energy participation factor exceeds a certain threshold value. With the identified threshold value, modal identifiability in use of the blind datasets from the same structure is examined.
机译:对适当正交分解(POD)的最新研究揭示了适当正交模式与线性法线模式之间的联系。本文介绍了一种采用带通滤波方案的自适应POD技术对仪器化斜拉桥的模态可识别性的研究。带通POD方法应用于可用于该基准研究的数据集,旨在识别桥梁的振动模式并找出在正常激发条件下无法识别的所谓的缺陷模式。事实证明,在弱风条件下无法稳定地确定桥梁的第二模式,因此被认为是一种缺陷模式。为了判断缺陷模式是否是由于其在弱风条件下对结构响应的贡献较小而导致的,通过带通POD技术推导了不同模式的模态坐标,并定义了能量参与因子以评估每种振动的能量参与在不同的风力激励条件下运行。从非盲数据集中发现,只有当能量参与因子超过某个阈值时,才能可靠地识别振动模式。通过确定的阈值,检查了来自相同结构的盲数据集在使用中的模态可识别性。

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