Vision-Based Detection of Bridge Damage Captured by Unmanned Aerial Vehicles (1.18)
| 项目名称： | Vision-Based Detection of Bridge Damage Captured by Unmanned Aerial Vehicles (1.18) |
| 摘要： | Bridge inspection is a vital component of any bridge management strategy of a state DOT. A visual inspection is the predominant approach used in a routine inspection. With visual inspection, only basic tools are used. However, according to research, there can be significant variation in the condition ratings assigned to a structure simply based on visual inspection. The use of unmanned aerial vehicles (UAVs) has recently been explored for the use of bridge inspections. UAVs equipped with high resolution or infrared cameras can be used to scan a bridge taking hundreds of images and essentially building a navigable 3D model of the bridge. Additionally, recent advances in machine learning may be employed to automatically identify different types of bridge damage. This research project will evaluate the effectiveness of using more autonomous methods for the collection and analysis of bridge deck images for the purpose of identifying the type and extent of damage in concrete decks. |
| 状态： | Active |
| 资金： | 351597 |
| 资助组织： | Transportation Infrastructure Durability Center；Office of the Assistant Secretary for Research and Technology；University of Rhode Island, Kingston；Rhode Island Department of Transportation |
| 管理组织： | Transportation Infrastructure Durability Center<==>University of Rhode Island, Kingston |
| 项目负责人： | Dunn, Denise E |
| 执行机构： | Transportation Infrastructure Durability Center<==>University of Rhode Island, Kingston |
| 主要研究人员： | Gindy Ph.D. , Mayrai；Hendawi, Abdeltawab；Licht, Stephen；Stegagno, Paolo |
| 开始时间： | 20220901 |
| 预计完成日期： | 20240630 |
| 主题领域： | Bridges and other structures；Data and Information Technology；Highways；Maintenance and Preservation |
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