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首页> 外文期刊>Journal of aerospace engineering >Bayesian Nonparametric Modeling of Structural Health Indicators under Severe Typhoons and Its Application to Modeling Modal Frequency
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Bayesian Nonparametric Modeling of Structural Health Indicators under Severe Typhoons and Its Application to Modeling Modal Frequency

机译：严重台风下结构健康指标的贝叶斯非参数建模及其应用于模型频率的应用

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摘要

Structural health indicators, such as modal frequencies, have been commonly utilized to interpret the health condition of monitored structures. This study modeled the relationship between structural health indicators and ambient conditions under severe typhoons. For this purpose, a two-stage Bayesian probabilistic procedure was established. In the first stage, the Bayesian spectral density approach (BSDA) is applied to identify the structural health indicators, namely the modal frequencies in this study, using the measured structural response. In the second stage, the Bayesian nonparametric general regression (BNGR) is introduced to model the relationship between the identified structural health indicators and some selected typhoon-induced ambient conditions. By using Bayesian model selection in conjunction with general regression, BNGR is able to select the most appropriate set of influencing/input variables for the prediction of the structural health indicators without prescribing any functional form. Full-scale measurements of a 22-story reinforced concrete (RC) building were used to demonstrate the efficacy of the procedure. The measurements consisted of over 280 h of structural response and the corresponding ambient conditions captured under the five most severe tropical cyclones that affected the region from 2011 to 2013. This study provides a promising framework for reliable interpretation of the variation of structural health indicators. Although the modal frequencies were considered in this study, the proposed two-stage procedure is applicable for other structural health indicators. (c) 2019 American Society of Civil Engineers.
机译：诸如模态频率的结构健康指标，通常用于解释监测结构的健康状况。本研究模拟了严重台风下结构健康指标与环境条件的关系。为此目的，建立了一个两级贝叶斯概率程序。在第一阶段，使用测量的结构响应，应用贝叶斯光谱密度方法（BSDA）识别结构健康指标，即该研究中的模态频率。在第二阶段，引入贝叶斯非参数一般回归（BNGR）以模拟所识别的结构健康指标与一些选定的台风诱导的环境条件之间的关系。通过使用Gayesian模型选择与一般回归结合，BNGR能够选择最合适的影响/输入变量集，以便在不规定任何功能形式的情况下预测结构健康指标。 22层钢筋混凝土（RC）建筑的全尺寸测量用于证明程序的疗效。测量由超过280小时的结构反应和相应的环境条件捕获，从2011年到2013年影响该地区的五个受到影响区域的五个最严重的热带气旋。该研究提供了可靠地解释结构健康指标的变异的有希望的框架。虽然在本研究中考虑了模态频率，但提出的两级程序适用于其他结构健康指标。 （c）2019年美国土木工程学会。

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