LIMITED MONITORING DATA BASED UPDATING METHOD FOR FUNDAMENTAL PERIOD OF THE BUILDING GROUP MODEL
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摘要:
通常情况下区域建筑群中仅有数量十分有限的建筑布设结构监测台阵，为充分利用有限监测建筑的监测数据提升建筑群震害模拟的精度，该研究提出了基于贝叶斯参数学习算法的建筑群模型参数更新方法通用流程，该通用流程通过采用有限监测建筑的监测数据更新建筑模型参数经验公式，以实现建筑群中所有建筑的模型参数更新。该研究选择建筑群震害分析模型的关键模型参数，即基本周期，在上述方法通用流程下推导了建筑群模型基本周期更新方法，通过建立虚拟建筑群对该方法进行了参数分析，并采用建筑群实测数据对该方法进行了进一步验证。结果表明：该方法能有效提升建筑群模型基本周期的计算精度；满足最低要求的监测建筑数量占比与经验公式参数初始均值误差、经验公式参数初始变异系数取值以及经验公式误差标准差取值密切相关，建议监测建筑数量占比取值最少为4%。该文研究为基于有限监测建筑监测数据的建筑群模型标定和更新提供了可行方法。
Abstract:Usually, only a very limited number of buildings in a region are equipped with structural monitoring arrays. In order to improve the accuracy of earthquake damage simulation for building groups with limited monitoring data, a framework for updating the model parameters of the building groups based on Bayesian parameter learning algorithm was established. In this framework, the model parameters of all buildings are updated through updating the empirical calculation formula of the model parameters based on the limited monitoring data. In this study, the fundamental period that best represents the dynamic characteristics of the structure was selected, and the updating algorithm for the fundamental period of the building groups was derived under the above framework. A parameter analysis of the updating method for the fundamental period was conducted by using a virtual building group. And the proposed method was further validated by using measured data from real building groups. The results show that this method can effectively improve the accuracy of the estimated fundamental period of the building groups; The proportion of monitoring buildings that meet the minimum requirements is closely related to error of the initial average value of empirical formula parameters, the initial coefficient of variation of empirical formula parameters, and the standard deviation of empirical formula errors. It is recommended that the proportion of monitoring buildings be set at a minimum of 4%. This study provides a feasible method for calibrating and updating building group models based on the data of limited number of monitored buildings.
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图 2 基于贝叶斯的建筑群模型参数更新方法通用流程
Figure 2. Framework of Bayesian-based updating method for building group model
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图 3 不同基本周期更新后误差对应的监测建筑数量占比
Figure 3. Error of the updated fundamental period under different proportions of the monitored buildings
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图 4 公式参数初始变异系数的不同取值对应的参数a的更新历程
Figure 4. Iteration history of parameter a under different values of initial variation coefficient of the empirical formula parameters
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图 5 公式参数初始变异系数的不同取值对应的参数b的更新历程
Figure 5. Iteration history of parameter b under different values of initial variation coefficient of the empirical formula parameters
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图 6 公式误差标准差的不同取值对应的参数a的更新历程
Figure 6. Iteration history of parameter a under different values of standard deviation of the error of the empirical formula
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图 7 公式误差标准差的不同取值对应的参数b的更新历程
Figure 7. Iteration history of parameter b under different values of standard deviation of the error of the empirical formula
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图 8 经验公式参数初始均值取值与真实值相差20%时的监测建筑数量最低占比
Figure 8. Minimum proportion of monitored buildings under the cases that the error between the initial value and the real value of the parameters of the empirical formula is 20%
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图 9 经验公式参数初始均值取值与真实值相差40%时的监测建筑最低占比
Figure 9. Minimum proportion of monitored buildings under the cases that the error between the initial value and the real value of the parameters of the empirical formula is 40%
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图 10 经验公式参数初始均值取值与真实值相差60%时的监测建筑最低占比
Figure 10. Minimum proportion of monitored buildings under the cases that the error between the initial value and the real value of the parameters of the empirical formula is 60%
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图 11 对应不同更新次数的基本周期相对误差平均值
Figure 11. The average value of relative errors of the fundamental period corresponding to different number of updating times
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图 12 对应不同基本周期相对误差的建筑数量占比
Figure 12. Proportion of buildings corresponding to different relative errors of fundamental periods
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图 13 对应不同基本周期相对误差的建筑数量累计占比
Figure 13. Cumulative proportion of buildings corresponding to different relative errors of fundamental periods
表 1 不同高度建筑数量占比
Table 1 Proportion of buildings with different heights
高度/m 30~40 40~50 50~60 60~70 >70 数量占比/(%) 73 15 9 2 1 
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表 2 不同层数建筑数量占比
Table 2 Proportion of buildings with different number of stories
层数/层 10~11 12~13 14~15 16~17 18~19 >20 数量占比/(%) 57 21 9 6 5 2
下载: 导出CSV
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