BRIGE: Continuous Structural Health Monitoring Framework for Bridge Structures

这扩大参与研究启动补助金工程（BRIGE）提供资金的概率连续结构健康监测框架的发展。新的框架将允许结构损伤估计为刚度损失的概率。该框架允许损伤识别结果的置信度估计作为直接从连续测量计算的所识别的模态参数的不确定性的函数。这个新的框架将被应用到位于塔夫茨大学校园的原型人行天桥（道林大厅人行天桥）。人行桥暴露于各种环境条件下，并且足够大，可以表现出复杂的结构行为，从而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，道林霍尔人行桥的模态参数提取的基础上使用加速度计和应变计测量的低幅环境振动响应。然后使用分离方法从识别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。识别的固有频率，振型，和他们的统计特性的连续流被送入一个递归贝叶斯有限元模型更新算法的概率损伤识别。如果成功，这项研究的结果将提高损坏探测算法的准确性和可信度，从而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，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。在该项目期间，将通过K-12外联和本科生研究促进代表性不足群体的学生的参与。

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.