A Structural Surface Crack Detection Method Based on 3D Reconstruction

ZHANG Haoyu; DING Yong; LI Denghua

doi:10.13204/j.gyjzG22102611

Volume 54 Issue 5

May 2024

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ZHANG Haoyu, DING Yong, LI Denghua. A Structural Surface Crack Detection Method Based on 3D Reconstruction[J]. INDUSTRIAL CONSTRUCTION, 2024, 54(5): 60-67. doi: 10.13204/j.gyjzG22102611

Citation:

ZHANG Haoyu, DING Yong, LI Denghua. A Structural Surface Crack Detection Method Based on 3D Reconstruction[J]. INDUSTRIAL CONSTRUCTION, 2024, 54(5): 60-67. doi: 10.13204/j.gyjzG22102611

ZHANG Haoyu, DING Yong, LI Denghua. A Structural Surface Crack Detection Method Based on 3D Reconstruction[J]. INDUSTRIAL CONSTRUCTION, 2024, 54(5): 60-67. doi: 10.13204/j.gyjzG22102611

Citation:

ZHANG Haoyu, DING Yong, LI Denghua. A Structural Surface Crack Detection Method Based on 3D Reconstruction[J]. INDUSTRIAL CONSTRUCTION, 2024, 54(5): 60-67. doi: 10.13204/j.gyjzG22102611

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A Structural Surface Crack Detection Method Based on 3D Reconstruction

doi: 10.13204/j.gyjzG22102611

ZHANG Haoyu¹,
DING Yong^{1
,
,},
LI Denghua^2,3

1. Nanjing University of Science and Technology, Nanjing 210094, China;
2. Nanjing Research Institute of Water Resources, Nanjing 210029, China;
3. Key Laboratory of Reservoir Dam Safety, Ministry of Water Resources, Nanjing 210029, China

Received Date: 2022-10-26
Available Online: 2024-06-22

Abstract

Abstract

In view of the lack of integrated expression of crack region parameters in traditional digital image processing-based crack monitoring methods, the paper proposed a structural surface crack detection method based on three-dimensional reconstruction. This method not only improves the accuracy of crack edge recognition but also realizes the integration of crack regions and parameter calculation. The location of cracks can be determined by mapping two-dimensional cracks onto three-dimensional models. The main work includes: planning the photographic path, collecting image data, and constructing an image dataset targeting building cracks according to the facade height and structural characteristics of the building; establishing a three-dimensional model of the exterior facade area with cracks using Structure from Motion SfM reconstruction technology, and obtaining object distance information without the need for ranging equipment based on the distance from the camera center to the crack fitting plane; identifying and segmenting structural surface cracks using cascaded neural networks; calculating crack parameters using the pixel resolution obtained from the real-world 3D model. The experimental results demonstrated that the proposed method could accurately identify cracks in building facades while simultaneously calculating crack widths and lengths, ultimately achieving crack integration and localization. The relative error of crack width is less than 1.5%, indicating good practical value.
- concrete crack detection,
- deep learning,
- 3D realistic model,
- pixel resolution

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References(17)

References

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