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首页> 外文期刊>International journal of steel structures >Model Updating and Crack Detection for Elastically Restrained Tapered Cantilever-Type Beam Using Natural Frequencies
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Model Updating and Crack Detection for Elastically Restrained Tapered Cantilever-Type Beam Using Natural Frequencies

机译：弹性约束锥形悬臂梁的固有频率模型更新与裂纹检测

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摘要

The current paper presents a method to update the baseline model and detect cracks in tapered cantilever pipe-type beams which are restrained by a translational and rotational spring with a tip mass at the free end using natural frequencies. Modal parameters of intact beam are obtained by applying boundary conditions to a general solution for tapered beam. The equivalent bending stiffness is used to calculate natural frequencies of cracked beams. An experimental study is carried out. The translational and rotational spring constants are updated to establish a baseline model using a neural network. Then, several numerical analyses of the cracked beams are carried out to extract the natural frequencies, and those are used in constructing the training patterns of a neural network. The committee of neural networks are employed to identify the cracks. The crack identifications are carried out for the 3 damage cases, and it is found that the estimated crack locations and sizes agree reasonably well with the exact values.
机译：当前的论文提出了一种更新基线模型并检测锥形悬臂管型梁中的裂纹的方法，该方法受到平移和旋转弹簧的约束，该弹簧在自由端具有固有频率的末端质量。完整光束的模态参数是通过将边界条件应用于锥形光束的一般解而获得的。等效弯曲刚度用于计算裂纹梁的固有频率。进行了实验研究。使用神经网络更新平移和旋转弹簧常数以建立基线模型。然后，对裂化梁进行了几次数值分析，以提取固有频率，并将其用于构建神经网络的训练模式。神经网络委员会被用来识别裂缝。对3种损坏情况进行了裂纹识别，发现估计的裂纹位置和大小与精确值相当吻合。

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