Point cloud-based automatic finite element modeling utilizing UAV

Pengyu Li; Shijie Zhou; Binbin Li; Yasutaka Narazaki

doi:10.1117/12.3025537

28 February 2024 Point cloud-based automatic finite element modeling utilizing UAV

Pengyu Li, Shijie Zhou, Binbin Li, Yasutaka Narazaki

Proceedings Volume 13071, International Conference on Mechatronic Engineering and Artificial Intelligence (MEAI 2023); 130713M (2024) https://doi.org/10.1117/12.3025537
Event: International Conference on Mechatronic Engineering and Artificial Intelligence (MEAI 2023), 2023, Shenyang, China

Abstract

Historical arch bridges in China have experienced a gradual deterioration in structural integrity due to prolonged use and increasing traffic loads. Ensuring the safety of the arch bridge as well as the pedestrian demands precise health assessment of these bridges, which normally requires finite element (FE) modeling and updating. To facilitate the FE modeling with limited information, a point cloud-based automatic FE modeling strategy is explored in this study. The unmanned aerial vehicle is first employed to do an on-site survey via images and videos to provide the geometric data of the historical arch bridge. They are then transformed into point cloud data to reconstruct a 3D solid model of the bridge. The FE mesh is finally implemented with element properties assigned to obtain the targeted FE model. An ambient vibration test is also conducted to extract the structural modal parameters, for further verification of the constructed FE model and possibly FE model updating. The proposed strategy is based on commonly available software, and thus easy to implement. It offers a rapid means of building the FE model, laying the groundwork for the condition assessment of the historical arch bridges.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Pengyu Li, Shijie Zhou, Binbin Li, and Yasutaka Narazaki "Point cloud-based automatic finite element modeling utilizing UAV", Proc. SPIE 13071, International Conference on Mechatronic Engineering and Artificial Intelligence (MEAI 2023), 130713M (28 February 2024); https://doi.org/10.1117/12.3025537

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