BK21 Special Seminar Series  - Spring 2023중 세번째 세미나가 아래와 같이 개최됩니다.

BK21 사업의 참여교수님, 신진연구인력, 참여대학원생, 학사과정 학생들의 많은 참여 부탁드립니다.

각 연구실의 BK과제 담당자께서는 참여학생들이 참석할 수 있도록 안내 꼭 부탁드립니다.

세미나는 영어로 진행됩니다.

- 일시 : 2023년 6월 1일 (목) 오후 4시30분 

- 연사 : 윤형철 교수님(충북대학교) 

- 장소 : 오프라인: 110동 1007호, 온라인(ZOOM) ID:  436 397 4287 

- 주제 : Vision-based Structural Health Monitoring for Pedestrian Suspension Bridges 

- 초록  

 : Recently, numbers of long span pedestrian suspension bridges have been constructed worldwide. While recent tragedies regarding pedestrian suspension bridges have shown how these bridges can wreak havoc on the society, the current practice for maintenance for the pedestrian suspension bridges are not being done efficiently. Therefore, a structural health monitoring system that could help ensure the safety of pedestrian suspension bridges are needed. System identification is one of the popular applications for structural health monitoring method, which estimates the dynamic system. Most of the system identification methods for bridges are currently adapting output-only system identification method, which assumes the dynamic load to be a white noise due to the difficulty of measuring the dynamic load. In the case of pedestrian suspension bridges, the pedestrian load is within specific frequency range, resulting in large errors when using the output-only system identification method. Therefore, this study aims to develop a system identification method for pedestrian suspension bridges considering both input and output of the dynamic system. This study estimates the location and the magnitude of the pedestrian load, as well as the dynamic response of the pedestrian bridges by utilizing artificial intelligence and computer vision techniques. A simulation-based validation test and on-site validation tests was conducted to verify the performance of the proposed system. The proposed method is expected to improve the accuracy and the efficiency of the current inspection and monitoring systems for pedestrian suspension bridges.

​