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SCALING MODE SHAPES OBTAINED FROM OPERATING DATA

机译:从操作数据中获得的缩放模式形状

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A set of scaled mode shapes is a complete representation ofrnthe linear dynamic properties of a structure. They can bernused for a variety of different analyses, including structuralrnmodifications, forced response simulations, excitation forcerncalculations from measured responses, and FRF synthesisrnfor comparison with experimental data.rnWhen mode shapes are obtained exp erimentally from operatingrndata, they are not properly scaled to preserve the massrn& elastic properties of the structure. By operating data, wernmean that only structural responses were measured. Excitationrnforces were not measured.rnIn this paper, we review the traditional methods for scalingrnexperimental mode shapes using FRFs, and also introducerntwo new methods that don't require FRF measurement. Thernnew methods combine a search algorithm with the SDMrn(Structural Dynamics Modification or eigenvalue modification)rnalgorithm to perform a series of structural modificationsrnuntil proper scaling of the mode shapes is achieved.rnDetails of the methods and examples of their use are included.
机译:一组缩放模式形状是结构线性动力学特性的完整表示。它们可用于各种不同的分析,包括结构修改,强制响应模拟,由测得响应得到的激励力计算以及与实验数据进行比较的FRF综合。当从操作数据中通过实验获得模态时,它们没有适当缩放以保持质量。结构的弹性特性。通过运行数据,wernmean只能测量结构响应。没有测量激励力。在本文中,我们回顾了使用FRF缩放实验模式形状的传统方法,并介绍了两种不需要FRF测量的新方法。这些新方法将搜索算法与SDMrn(结构动力学修改或特征值修改)算法结合起来进行一系列结构修改,直到实现模式形状的适当缩放为止。方法的详细信息及其使用示例包括在内。

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