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首页> 外文期刊>Journal of aerospace engineering >Vibration-Based Structural Damage Identification under Varying Temperature Effects
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Vibration-Based Structural Damage Identification under Varying Temperature Effects

机译：温度影响下基于振动的结构损伤识别

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摘要

Vibration-based methods are promising for damage identification; however, their capabilities for damage identification under temperature variations are usually limited. In the paper, a vibration-based nondestructive global damage identification method based on a genetic algorithm (GA) is proposed to identify structural damage location and severity under the influence of temperature variation and noise. The proposed method is verified by a number of damage scenarios of a three-span continuous beam and a two-span steel grid and shows good robustness under random noise levels. First, considering that the material properties of a structure and boundary conditions of a system are generally temperature-dependent, the relation between temperature and elastic and geometric stiffness matrices is introduced, and damage parameters along with temperature are defined as variables of the numeric model. Second, a GA is introduced where a new objective function with different weight coefficients, combined with frequencies and mode shape, is proposed and developed. Third, damage identification of a three-span continuous beam and a two-span steel grid under temperature variation is carried out numerically, considering changes of material properties and boundary conditions, and damage existence, location, and severity are accurately identified. Finally, it is shown that the proposed method is very robust even when the data are polluted with artificial noise. (c) 2018 American Society of Civil Engineers.
机译：基于振动的方法有望用于损伤识别。但是，它们在温度变化下识别损坏的能力通常受到限制。提出了一种基于遗传算法的基于振动的无损全局损伤识别方法，以识别温度变化和噪声影响下的结构损伤位置和严重程度。该方法通过三跨连续梁和两跨钢格板的多种破坏场景得到验证，并且在随机噪声水平下显示出良好的鲁棒性。首先，考虑到结构的材料特性和系统的边界条件通常与温度有关，介绍了温度与弹性和几何刚度矩阵之间的关系，并将损伤参数与温度一起定义为数值模型的变量。其次，引入遗传算法，提出并开发了具有不同权重系数的新目标函数，并结合了频率和振型。第三，考虑材料特性和边界条件的变化，对温度变化下的三跨连续梁和两跨钢格板进行了损伤识别，并通过数值模拟确定了损伤的存在，位置和严重性。最后，证明了该方法即使在数据被人为噪声污染的情况下也非常健壮。 （c）2018年美国土木工程师学会。

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