I-Corps: Real-time Monitoring of Civil Structures Using Video Cameras
I-Corps: Real-time Monitoring of Civil Structures Using Video Cameras
批准号:
1833341
负责人:
Thomas Heaton
金额:
$5.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2018
资助国家:
美国
项目状态:
已结题
起止时间:
2018-04-01 至 2020-03-31
中文摘要
这个i-Corps项目的更广泛的影响/商业潜力是开发一种新的工具,用于称重过桥的卡车。与现有的卡车称重系统相比,该技术有望价格低廉、易于部署、速度快且非常难以规避。对超重卡车进行更一致的实时识别可以显著减少这些超重卡车每年造成的数百亿美元的道路损害。该系统的另一个好处是,它有望提供一种新的工具来识别桥梁变形响应的变化。这些变化将有助于诊断桥梁的结构损伤。该i-Corps项目采用光电技术,实时监测土建结构的结构变形。这项技术的目的是增强/取代现有的系统,这些系统依赖于称重站的称重传感器。这项技术使用被动摄像系统测量结构在动态载荷下的变形,该系统可以从远处监控结构。该系统使用现成的商用摄像机来监视结构上的特定目标,例如紧固件、反射器或结构特征。然后,使用专有的像素处理算法处理实时视频,以计算3个轴上的亚毫米位移和旋转。在实时观察时,这些信息以及由存档数据生成的数据产品可以用于确定结构的性能、动态加载的影响,甚至结构失效的预测。该系统还可以用来识别超重卡车,以便在道路和桥梁上执行重量限制。该系统在暴露于典型照明条件、动态或其他环境条件下时提供高带宽测量。我们已经对桥梁和一栋建筑进行了真实世界的条件测试,以验证该技术的可行性。该奖项反映了NSF的法定使命,并通过使用基金会的智力优势和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
The broader impact/commercial potential of this I-Corps project is to develop a new tool for weighing trucks as they cross bridges. Compared with existing truck weighing systems, the technology promises to be inexpensive, easy to deploy, fast and very difficult to evade. More consistent real-time identification of overweight trucks could significantly decrease the tens of billions of dollars per year of roadway damage caused by these overweight trucks. An additional benefit of the system is that it promises to provide a new tool to identify changes in the deformation response of bridges. These changes will help to diagnose structural damage to bridges. This I-Corps project employs electro-optical technology to monitor the structural deformations of civil structures in real-time. The intent of this technology is to augment/replace existing systems that rely on load cells at weigh stations. The technology measures the deformation of structures under dynamic loads with a passive camera system that can monitor the structure from a distance. The system uses off-the-shelf commercially available video cameras to monitor a specific target on a structure, such as a fastener, reflector, or structural feature. The real-time video is then processed using proprietary pixel manipulation algorithms to calculate sub-millimeter displacements and rotations in 3 axes. The information, when observed in real-time, as well as the data products generated from the archived data can be used to determine the performance of structures, the impacts of dynamic loading, and even the prediction of structural failures. The system can also be used to identify overweight trucks in order to enforce weight limits on roads and bridges. This system provides high bandwidth measurements while exposed to typical lighting condition dynamics or other ambient conditions. We have conducted real-world conditions tests on bridges and a building that validate the feasibility of the technology.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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