Automated Crack Detection Method Based on Deep Learning and 3D Reconstruction for Concrete Bridges
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Bibliografische Angaben
| Autor(en): |
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: | Tagungsbeitrag | ||||
| Sprache(n): | Englisch | ||||
| Tagung: | IABSE Congress: Bridges and Structures: Connection, Integration and Harmonisation, Nanjing, People's Republic of China, 21-23 September 2022 | ||||
| Veröffentlicht in: | IABSE Congress Nanjing 2022 | ||||
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| Seite(n): | 1506-1513 | ||||
| Anzahl der Seiten (im PDF): | 8 | ||||
| DOI: | 10.2749/nanjing.2022.1506 | ||||
| Abstrakt: |
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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| Stichwörter: |
Risserkennung
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| Copyright: | © 2022 International Association for Bridge and Structural Engineering (IABSE) | ||||
| Lizenz: | Die Urheberrechte (Copyright) für dieses Werk sind rechtlich geschützt. Es darf nicht ohne die Zustimmung des Autors/der Autorin oder Rechteinhabers/-in weiter benutzt werden. |
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