| | --- |
| | license: mit |
| | language: |
| | - en |
| | pretty_name: Crack3D-Defect |
| | size_categories: |
| | - 1B<n<10B |
| | --- |
| | # Crack3D-Defect |
| |
|
| | `Crack3D-Defect` is a multimodal 3D point cloud dataset designed for anomaly detection in infrastructure components such as masonry arches and tunnel rings. It includes synthetic data generated from FEM simulations and real scans of infrastructure collected at multiple time steps. |
| |
|
| | The code can be found at my [GitHub repo](https://github.com/Jingyixiong/3D-Multi-FPFHI). |
| |
|
| | --- |
| |
|
| | ## π Dataset Structure |
| |
|
| | ```bash |
| | infra_3DALv1/ |
| | β |
| | βββ syn_arch_src/ |
| | β βββ memory_bank/ |
| | β β βββ min_cw0/ # Undeformed synthetic arches |
| | β β βββ min_cw0.4/ # X-displacement with 4mm minimum crack width |
| | β βββ disp_x/ |
| | β β βββ diff_cw/ # 4mm, 8mm crack width |
| | β β βββ diff_disps/ # Displacements: 8cm, 12cm, 16cm, 40cm |
| | β βββ disp_z/ # z-axis displacement |
| | β βββ disp_xz/ # x + z displacement |
| | β βββ rot_x/ # x-axis rotation |
| | β |
| | βββ real_arch_src/ |
| | β βββ memory_bank/ # London Bridge Station scans (2013/03/05) |
| | β βββ Narch_131123/ # Arch 1 after cracking (2013/11/23) |
| | β βββ Sarch_131123/ # Arch 2 after cracking (2013/11/23) |
| | β |
| | βββ tunnel/ |
| | βββ memory_bank/ # Initial tunnel scan at loading step 0 |
| | βββ 0-76-2.txt |
| | βββ 0-89-2.txt |
| | βββ 0-96-2.txt |
| | βββ 0-103-2.txt # Tunnel scans under increasing load |
| | ``` |
| |
|
| | --- |
| |
|
| | ## πΉ File Formats |
| |
|
| | | Folder | Format | Description | |
| | |-------------------|--------|-------------| |
| | | `syn_arch_src/` | `.csv` | Columns: `categoryID` (0β3), `[X, Y, Z]`, `[X_noise, Y_noise, Z_noise]`, `intensity` | |
| | | `real_arch_src/` | `.asc` | Columns: `[x, y, z, r, g, b, intensity]` | |
| | | `tunnel/` | `.txt` | Columns: `[x, y, z, intensity]` | |
| |
|
| | --- |
| |
|
| | ## π Labels |
| |
|
| | - `categoryID` for synthetic data (`syn_arch_src/`): |
| | - `0`: No crack |
| | - `1`: Intrados crack |
| | - `2`: Extrados crack |
| | - `3`: Inner crack |
| |
|
| | --- |
| |
|
| | ## π Citation |
| |
|
| | If you use this dataset, please cite the associated PhD thesis and publications. |
| | ```bibtex |
| | @article{jing2024anomaly, |
| | title={Anomaly detection of cracks in synthetic masonry arch bridge point clouds using fast point feature histograms and PatchCore}, |
| | author={Jing, Yixiong and Zhong, Jia-Xing and Sheil, Brian and Acikgoz, Sinan}, |
| | journal={Automation in Construction}, |
| | volume={168}, |
| | pages={105766}, |
| | year={2024}, |
| | publisher={Elsevier} |
| | } |
| | |
| | @article{jing20253d, |
| | title={3D multimodal feature for infrastructure anomaly detection}, |
| | author={Jing, Yixiong and Lin, Wei and Sheil, Brian and Acikgoz, Sinan}, |
| | journal={Automation in Construction}, |
| | volume={178}, |
| | pages={106388}, |
| | year={2025}, |
| | publisher={Elsevier} |
| | } |
| | |
| | @phdthesis{jing2025development, |
| | title={Development of synthetic point cloud data and deep learning algorithms for automatic segmentation and defect detection in masonry bridges}, |
| | author={Jing, Yixiong}, |
| | year={2025}, |
| | school={University of Oxford} |
| | } |
| | ``` |
| | --- |
| |
|
| | ## License |
| |
|
| | Our work is subjected to MIT License. |