Automated Crack Detection Method Based on Deep Learning and 3D Reconstruction for Concrete Bridges
|
|
|||||||||||
Détails bibliographiques
| Auteur(s): |
Tao Sun
(College of Civil Engineering, Hunan University, Changsha, Hunan Province, China)
Lu Deng (College of Civil Engineering, Hunan University, Changsha, Hunan Province, China; Key Laboratory for Damage Diagnosis of Engineering Structures of Hunan Province, China Hunan University, Changsha, China) Ran Cao (College of Civil Engineering, Hunan University, Changsha, Hunan Province, China; Key Laboratory for Damage Diagnosis of Engineering Structures of Hunan Province, China Hunan University, Changsha, China) Wei Wang (College of Civil Engineering, Hunan University, Changsha, Hunan Province, China; Key Laboratory for Damage Diagnosis of Engineering Structures of Hunan Province, China Hunan University, Changsha, China) |
||||
|---|---|---|---|---|---|
| Médium: | papier de conférence | ||||
| Langue(s): | anglais | ||||
| Conférence: | IABSE Congress: Bridges and Structures: Connection, Integration and Harmonisation, Nanjing, People's Republic of China, 21-23 September 2022 | ||||
| Publié dans: | IABSE Congress Nanjing 2022 | ||||
|
|||||
| Page(s): | 1506-1513 | ||||
| Nombre total de pages (du PDF): | 8 | ||||
| DOI: | 10.2749/nanjing.2022.1506 | ||||
| Abstrait: |
Automated image-based bridge crack detection, as a promising technique, can be used to overcome the limitations of human visual inspection. However, results from current image-based methods are generally localized and lack 3D geometric information, which makes it difficult for structural assessment. To solve this issue, a crack detection method that combines deep learning and 3D reconstruction is proposed in this paper. Firstly, a 2D feature-based approach is developed to extract keyframes from the video adaptively. Secondly, a segmentation network is implemented to conduct pixel-level crack segmentation. Finally, image-based 3D reconstruction and crack mapping are used to create the 3D structure model with crack semantics. A field experiment is also carried out on an in-service concrete bridge for validation and discussion of the proposed method. The 3D model created by the proposed method can significantly improve the crack inspection of concrete bridges. |
||||
| Copyright: | © 2022 International Association for Bridge and Structural Engineering (IABSE) | ||||
| License: | Cette oeuvre ne peut être utilisée sans la permission de l'auteur ou détenteur des droits. |
||||