Fiber Optic Method for Bridge Health Assessment Based on Long-Gauge Sensors

基于长规格传感器的桥梁健康评估光纤方法

• 批准号: 1362723
• 负责人: Branko Glisic
• 金额: $ 20万
• 依托单位: Princeton University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-07-01 至 2017-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1362723&HistoricalAwards=false
• 关键词: Fiber; Optic; Method; Bridge; Health

For civil infrastructure there is a need for structural health monitoring to provide an optimized maintenance, lifetime extension, and improved safety. Structural health monitoring can provide accurate and in-time information concerning condition and residual life of civil infrastructure. It consists of instrumentation of the structure with sensors and transformation of the collected data into meaningful and actionable information for the owner or manager of the structure, so decision makers can undertake informed and economical maintenance and repair actions. This project focuses on the typical bridge beam systems that represent 60 percent of all US bridges. The objective of this project is to pursue research in creating and validating a universal health assessment system for typical beam bridges based on static and dynamic measured strains using long-gauge fiber optic sensors. This research will provide means to avoid disruptive closures and catastrophic failures, while also ensuring on-going reliable health assessment. The success of the project stands to have profound societal impact by addressing public safety and minimizing economic disruption. The neutral axis and the deformed shape are universal beam parameters that reflect bridge health and performance condition. Real-time determination of these parameters has potential to enable a robust bridge health monitoring assessment method. Fundamental questions associated with determination of these parameters addressed in this project are related to: 1) variability of these parameters and uncertainty in their determination under damaged and undamaged conditions, and 2) transformation of the collected data into meaningful and actionable information to the bridge owner or manager. The objective of the project is to create a reliable method for performance and health assessment of beams in bridges based on determination of the position of the neutral axis and on deformed shape. State-of-the-art long-gauge fiber optic strain sensors have inherent advantage to acquire data relevant to the global structural scale. Algorithms will be created based on general probabilistic approaches, Bayesian structural identification, and performance prediction models taking in to account variability and uncertainties in collected data. Experimental validation will be performed both through laboratory tests and controlled tests on two bridges in-use. The method will be applicable to existing and new beam bridges and will not be material dependent.

对于民用基础设施，需要进行结构性健康监测，以提供优化的维护，终生扩展和改善的安全性。结构性健康监测可以提供有关民用基础设施的状况和剩余寿命的准确及时信息。它由传感器的仪器组成，并将收集的数据转换为结构的所有者或经理，因此决策者可以采取知情，经济的维护和维修操作。该项目着重于典型的桥梁系统，该系统占美国桥梁的60％。 该项目的目的是通过使用长距离光纤传感器基于静态和动态测量的菌株来创建和验证典型的梁桥的通用健康评估系统。这项研究将提供避免破坏性封闭和灾难性失败的手段，同时确保正在进行的可靠健康评估。该项目的成功通过解决公共安全和最大程度地减少经济破坏来产生深远的社会影响。中性轴和变形的形状是反映桥梁健康和性能状况的通用光束参数。这些参数的实时确定有可能实现强大的桥梁健康监测评估方法。与确定本项目中有关的这些参数相关的基本问题与以下方面有关：1）这些参数的可变性和在受损和未损坏的条件下确定的不确定性的可变性，以及2）将收集的数据转换为有意义且可行的信息，或经理。该项目的目的是基于确定中性轴的位置和变形形状，为桥梁中的梁的性能和健康评估创建可靠的方法。最先进的长距离光纤应变传感器具有获取与全球结构尺度相关的数据的固有优势。将基于一般概率方法，贝叶斯结构识别以及绩效预测模型来创建算法，以考虑收集的数据中的可变性和不确定性。实验验证将通过实验室测试和对两座桥梁的控制测试进行。该方法将适用于现有和新的梁桥，并且不依赖于物质。