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Extraction of the mode shapes of a segmented ship model with a hydroelastic response

机译:具有水弹性响应的分段船舶模型的振型提取

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The mode shapes of a segmented hull model towed in a model basin were predicted using both the Proper Orthogonal Decomposition (POD) and cross random decrement technique. The proper orthogonal decomposition, which is also known as Karhunen-Loeve decomposition, is an emerging technology as a useful signal processing technique in structural dynamics. The technique is based on the fact that the eigenvectors of a spatial coherence matrix become the mode shapes of the system under free and randomly excited forced vibration conditions. Taking advantage of the simplicity of POD, efforts have been made to reveal the mode shapes of vibrating flexible hull under random wave excitation. First, the segmented hull model of a 400 K ore carrier with 3 flexible connections was towed in a model basin under different sea states and the time histories of the vertical bending moment at three different locations were measured. The measured response time histories were processed using the proper orthogonal decomposition, eventually to obtain both the first and second vertical vibration modes of the flexible hull. A comparison of the obtained mode shapes with those obtained using the cross random decrement technique showed excellent correspondence between the two results.
机译:使用适当的正交分解(POD)和交叉随机减量技术预测了在模型盆地中拖曳的分段船体模型的模式形状。适当的正交分解,也称为Karhunen-Loeve分解,是一种新兴的技术,在结构动力学中是一种有用的信号处理技术。该技术基于以下事实:在自由和随机激发的强迫振动条件下,空间相干矩阵的特征向量成为系统的模态。利用POD的简单性,已做出努力来揭示在随机波激励下振动柔性船体的模式形状。首先,将具有3个挠性接头的400 K矿石运输船的分段船体模型拖到不同海况下的模型盆地中,并测量三个不同位置的垂直弯矩的时间历史。使用适当的正交分解处理测量的响应时间历史,最终获得柔性船体的第一和第二垂直振动模式。所获得的模态形状与使用交叉随机减量技术获得的模态形状的比较显示,两个结果之间具有极好的对应性。

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