BRIGE: Continuous Structural Health Monitoring Framework for Bridge Structures

这项扩大参与工程研究启动补助金（bridge）为开发概率连续结构健康监测框架提供资金。新的框架将允许结构损伤估计为刚度损失的概率条款。该框架允许将损伤识别结果的置信度作为识别模态参数不确定性的函数进行估计，这些参数是直接从连续测量中计算出来的。这个新框架将应用于位于塔夫茨大学校园的人行桥原型（Dowling Hall人行桥）。人行桥暴露在各种环境条件下，并且足够大，可以展示复杂的结构行为，为在不同环境影响下对结构完整性进行现实评估提供了机会。作为该框架的一部分，基于使用加速度计和应变片测量的低幅环境振动响应，提取了Dowling Hall人行桥的模态参数。然后使用分离方法从确定的固有频率中去除变化的环境条件（温度和相对湿度）的影响。将识别出的连续固有频率、模态振型及其统计特征输入递归贝叶斯有限元模型更新算法进行概率损伤识别。如果成功，这项研究的结果将提高损伤检测算法的准确性和信心，从而通过为更好地分配有限的财政资源提供更有效的工程基础，从而加强对基础设施的监测和维护。此外，该原型连续监测系统为民用基础设施系统健康监测的综合研究和教学提供了一个实时的跨学科实验室。在这个项目中，来自弱势群体的学生的参与将通过K-12外展和本科研究来促进。

This Broadening Participation Research Initiation Grant in Engineering (BRIGE) provides funding for the development of a probabilistic continuous structural health monitoring framework. The novel framework will allow structural damage to be estimated as a loss of stiffness in probabilistic terms. The framework permits estimation of confidence in damage identification results as a function of uncertainty in the identified modal parameters which are directly calculated from continuous measurements. This new framework will be applied to a prototype footbridge (Dowling Hall Footbridge) located at the Tufts University campus. The footbridge is exposed to a wide range of environmental conditions and is large enough to exhibit complex structural behavior, providing an opportunity for a realistic assessment of structural integrity in the presence of varying environmental effects. As part of this framework, modal parameters of the Dowling Hall Footbridge are extracted based on the low-amplitude ambient vibration response measured using accelerometers and strain gages. Separation methods are then used to remove the effects of changing environmental conditions (temperature and relative humidity) from the identified natural frequencies. The continuous stream of identified natural frequencies, mode shapes, and their statistical characteristics are fed into a recursive Bayesian finite element model updating algorithm for probabilistic damage identification. If successful, the results of this research will improve the accuracy and confidence of damage detection algorithms, thus permitting enhanced monitoring and maintenance of infrastructure by providing a more effective engineering basis for better allocation of limited financial resources. In addition, the prototype continuous monitoring system provides a live, cross-disciplinary laboratory for integrated research and teaching in health monitoring of civil infrastructure systems. During this project, participation of students from underrepresented groups will be promoted through K-12 outreach and undergraduate research.