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Identifying VIV vibration modes by use of the Empirical Orthogonal Functions technique

机译:通过使用经验正交功能技术识别VIV振动模式

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The Empirical Orthogonal Functions (EOF) technique has widely being used by oceanographers and meteorologists, while the Singular Value Decomposition (SVD) being a related technique is frequently used in the statistics community. Another related technique called Principal Component Analysis (PCA) is observed being used for instance in pattern recognition. The predominant applications of these techniques are data compression of multivariate data sets which also facilitates subsequent statistical analysis of such data sets. Within Ocean Engineering the EOF technique is not yet widely in use, although there are several areas where multivariate data sets occur and where the EOF technique could represent a supplementary analysis technique. Examples are oceanographic data, in particular current data. Furthermore data sets of model- or full-scale data of loads-and responses of slender bodies, such as pipelines and risers are relevant examples. One attractive property of the EOF technique is that it does not require any a priori information on the physical system by which the data is generated. In the present paper a description of the EOF technique is given. Thereafter an example on use of the EOF technique is presented. The example is analysis of response data from a model test of a pipeline in a long free span exposed to current. The model test program was carried out in order to identify the occurrence of multi-mode vibrations and vibration mode amplitudes In the present example the EOF technique demonstrates the capability of identifying predominant vibration modes of inline as well as cross-flow vibrations. Vibration mode shapes together with mode amplitudes and frequencies are also estimated. Although the present example is not sufficient for concluding on the applicability of the EOF technique on a general basis, the results of the present example demonstrate some of the potential of the technique.
机译:经验正交功能(EOF)技术广泛被海洋记录器和气象学家使用,而统计界经常使用奇异值分解(SVD)。观察到另一个称为主成分分析(PCA)的相关技术,例如在模式识别中。这些技术的主要应用是多变量数据集的数据压缩,其还促进了这种数据集的后续统计分析。在海洋工程中,EOF技术在使用中尚未广泛,尽管存在多变量数据集的几个区域,并且EOF技术可以代表补充分析技术。例子是海洋学数据,特别是当前数据。此外,数据集或负载的全尺度数据和细长体的响应,例如管道和立管的响应是相关的例子。 EOF技术的一个有吸引力的属性是它不需要在生成数据系统上的任何先验信息。在本文中,给出了EOF技术的描述。此后,提出了关于EOF技术的使用示例。该示例是在暴露于电流的长自由跨度中的管道模型测试的响应数据分析。为了识别模型测试程序,以识别多模振动的发生和本示例中的振动模式幅度,EOF技术证明了识别型在线的主要振动模式以及交叉流量振动的能力。振动模式也估计与模式幅度和频率一起。尽管本示例不足以在一般基础上对EOF技术的适用性结论,但是本示例的结果证明了该技术的一些潜力。

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