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The role of modal parameters uncertainty estimation in automated modal identification, modal tracking and data normalization

机译:模态参数不确定性估计在自动模态标识中的作用,模态跟踪和数据归一化

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During the last decade, many vibration-based structural health monitoring systems have been successfully implemented in different structures such as bridges, towers, stadia and wind turbines, with the aim of studying the structure dynamics and its evolution over time, eventually detecting the occurrence of novel structural behaviour that may indicate the presence of damage.Such vibration-based monitoring systems generally rely on the identification of modal properties, which are then used as monitoring features. Therefore, from operational modal analysis to the tracking of those features and finally to data normalization, many processing steps occur that depend on the accuracy of the identified modal properties. Thus, the estimation of the uncertainties associated with the identified modal properties increases the robustness of this process.In this context, data obtained from the continuous dynamic monitoring of a concrete arch dam has been used to evaluate the gains of quantifying the uncertainties of modal properties, evaluating in particular the effect of taking these uncertainties into consideration when performing automated operational modal analysis, modal tracking and data normalization. Nevertheless, it is observed that the most significant gains of considering estimates uncertainties occur when these quantities are used for removing outliers during modal tracking.
机译:在过去的十年中,许多基于振动的结构健康监测系统已经成功地在不同的结构中实现,例如桥梁,塔,斯塔迪亚和风力涡轮机,目的是研究结构动态及其随着时间的推移,最终检测到发生的情况新颖的结构行为,可以指示存在损伤的存在。基于振动的监测系统通常依赖于模态属性的识别,然后用作监视特征。因此,从操作模态分析到跟踪这些特征并最终到数据归一化,发生了许多处理步骤,这取决于所识别的模态属性的准确性。因此,与所识别的模态特性相关的不确定性的估计增加了该过程的鲁棒性。在此上下文中,从混凝土拱坝的连续动态监测获得的数据已被用于评估量化模态属性的不确定性的增益,特别评估在执行自动操作模态分析,模态跟踪和数据标准化时考虑以下这些不确定性的效果。然而,观察到,考虑估计这些数量在模态跟踪期间消除异常值时,会发生最显着的收益。

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