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Operational modal analysis for estimating the dynamic properties of a stadium structure during a football game

机译:用于评估足球比赛期间体育场结构动力特性的操作模态分析

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During a football game, the ambient vibrations at the roof of a football stadium were recorded. A very large data set consisting of 4 hours of data, sampled at 80 Hz, is available. By a data reduction procedure, the complete data set could be analysed at once in a very short time. The data set was also split in shorter segments corresponding to certain events before, during and after the game to investigate the influence of varying operational conditions on the dynamic properties.rnAs the structural vibrations were caused by unmeasurable wind and crowd excitation, Operational Modal Analysis has to be applied to find the dynamic characteristics of the structure. The new operational PolyMAX parameter estimation method is used and compared with Stochastic Subspace Identification. Stochastic Subspace Identification requires the correlations between the responses as primary data, whereas PolyMAX operates on spectra or half spectra (i.e. the Fourier transform of the positive time lags of the correlation functions). The main advantage of PolyMAX is that it yields extremely clear stabilisation diagrams, making an automation of the parameter identification process rather straightforward. This enables a continuous monitoring of the dynamic properties of a structure.
机译:在足球比赛期间,记录了足球场屋顶的周围振动。提供了一个非常庞大的数据集,其中包含以80 Hz采样的4个小时的数据。通过数据缩减程序,可以在很短的时间内立即分析完整的数据集。数据集也被分为较短的部分,分别对应于游戏之前,期间和之后的某些事件,以研究变化的操作条件对动力特性的影响。rn由于结构振动是由不可测量的风和人群激励引起的,因此操作模态分析具有用于寻找结构的动力特性。使用了新的可操作PolyMAX参数估计方法,并将其与随机子空间识别进行了比较。随机子空间识别需要将响应之间的相关作为主要数据,而PolyMAX则对光谱或半光谱进行操作(即相关函数的正时滞的傅立叶变换)。 PolyMAX的主要优点在于,它可以产生极其清晰的稳定图,从而使参数识别过程的自动化变得相当简单。这样可以连续监视结构的动态特性。

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