Iterative optimal sensor placement for adaptive structural identification using mobile sensors: Numerical application to a footbridge
Iterative optimal sensor placement for adaptive structural identification using mobile sensors: Numerical application to a footbridge
复制标题
使用移动传感器进行自适应结构识别的迭代最佳传感器放置：人行桥的数值应用
DOI：
10.1016/j.ymssp.2023.110556
复制
发表时间：
2023
影响因子：
8.4
通讯作者：
Rife, Jason
中科院分区：
文献类型：
--
作者：
Bagirgan, Burak;Mehrjoo, Azin;Moaveni, Babak;Papadimitriou, Costas;Khan, Usman;Rife, Jason
提出了一种利用少量移动的传感器进行结构系统结构识别和模型修正的迭代最优传感器布置（OSP）框架。模型更新是通过贝叶斯推理方法，通过渐近近似的计算效率来解决。以迭代的方式，OSP执行，以最小化信息熵估计模型的更新参数。每次OSP迭代的目的是找到移动的传感器的下一个位置，其中更新参数的先验概率分布被假定为从上一次迭代获得的后验概率分布。重复该过程，直到更新参数的不确定性下降到预定阈值以下。在每次迭代中，采用前向顺序传感器布局算法求解OSP问题。该算法提供了一个接近最优的解决方案，是更有效的相比，穷举搜索。这个建议的框架被应用到一个数值的案例研究，即道林厅人行天桥位于塔夫茨大学校园。本研究中所使用的修正参数为桥面不同节段的附加质量。使用附加质量的目的是在桥梁的特定部分上创建真实的伪损坏。所提出的迭代系统辨识方法适用于估计更新参数，考虑不同数量的可用传感器。这项研究表明，迭代OSP方法使用少量的移动的传感器放置迭代提供更好的模型更新结果相比，使用一个最佳的静态传感器配置的情况下，涉及大量的传感器。
This paper proposes an iterative optimal sensor placement (OSP) framework for structural identification and model updating of structural systems using a small number of mobile sensors. The model updating is performed through a Bayesian inference approach which is solved through asymptotic approximation for computational efficiency. In an iterative manner, the OSP is performed to minimize the information entropy in estimating the updating parameters of the model. Each OSP iteration is performed to find the next location of mobile sensors, where the prior probability distribution of updating parameters is assumed as the posterior probability distribution obtained from the previous iteration. This process is repeated until the uncertainties of updating parameters fall below a predetermined threshold. A forward sequential sensor placement algorithm is used to solve the OSP problem at each iteration. This algorithm provides a nearly-optimal solution and is much more efficient compared to an exhaustive search. This proposed framework is applied to a numerical case study, namely the Dowling Hall Footbridge located at Tufts University campus. Updating parameters used in this study are the added mass at different segments of the bridge deck. The purpose of using added mass is to create a realistic pseudo damage on a specific portion of the bridge. The proposed iterative system identification approach is applied for estimation of updating parameters considering different number of available sensors. This study shows that the iterative OSP approach using a small number of mobile sensors placed iteratively provides better model updating results compared to the case of using an optimal static sensor configuration involving larger number of sensors.