Bridge monitoring through a hybrid approach leveraging a modal updating technique and an artificial intelligence (AI) method
| 项目名称： | Bridge monitoring through a hybrid approach leveraging a modal updating technique and an artificial intelligence (AI) method |
| 摘要： | An early damage identification process in bridge structures may offer an opportunity to slowdown progressive failure and thus prevent catastrophic collapses. With a structural health monitoring system which allows real-time measurement of structural responses, this may be possible if proper techniques are employed to identify early damage in bridge structures. In doing so, the proposed project will integrate two methods (i.e., a model updating technique and an artificial intelligence (AI) prediction) that can compensate for each other’s the weakness that otherwise imposed difficulty in precise real-time application of health monitoring systems. This project will leverage a mode-updating technique with high-fidelity experimental data to obtain an accurate digital model that represents an actual bridge model. The drawback of the model updating technique (i.e., high computational time) will be overcome by applying an artificial intelligence algorithm such as artificial neural networks that are known to be computationally efficient while perusing high accuracy. The proposed approach will then result in a fast and accurate method (i.e., a model-based data-driven method) for early damage identification of bridge structures. |
| 状态： | Active |
| 资金： | $26,650.00 |
| 资助组织： | Department of Transportation |
| 项目负责人： | Brinkerhoff, Cort |
| 执行机构： | University of Hawaii, Manoa |
| 开始时间： | 20210816 |
| 预计完成日期： | 20220815 |
| 主题领域： | Administration and Management；Bridges and other structures；Construction；Data and Information Technology；Design；Environment；Maintenance and Preservation；Operations and Traffic Management；Research；Safety and Human Factors；Security and Emergencies |
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