Automated Crack Detection Method Based on Deep Learning and 3D Reconstruction for Concrete Bridges
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Bibliographic Details
| Author(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) |
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| Medium: | conference paper | ||||
| Language(s): | English | ||||
| Conference: | IABSE Congress: Bridges and Structures: Connection, Integration and Harmonisation, Nanjing, People's Republic of China, 21-23 September 2022 | ||||
| Published in: | IABSE Congress Nanjing 2022 | ||||
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| Page(s): | 1506-1513 | ||||
| Total no. of pages: | 8 | ||||
| DOI: | 10.2749/nanjing.2022.1506 | ||||
| Abstract: |
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. |
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| Keywords: |
crack detection deep learning 3D reconstruction bridge crack inspection
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| Copyright: | © 2022 International Association for Bridge and Structural Engineering (IABSE) | ||||
| License: | This creative work is copyrighted material and may not be used without explicit approval by the author and/or copyright owner. |
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