Refine your search
Collections
Co-Authors
Journals
Year
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Li, Q.
- Detection of Breakwater Failure Modes From Photogrammetric Derived Point Clouds – A Case Study for Bunbury Port, Western Australia
Abstract Views :116 |
PDF Views:0
Authors
P. Helmholz
1,
L. Boyle
1,
B.E. Tily-Laurie
1,
D. May
1,
G. Singh
2,
J. Hogben
3,
Y. Ren
2,
Q. Li
4,
D. Belton
1,
S. Khaksar
4,
S.J. Snyman
3
Affiliations
1 Spatial Sciences, School for Earth and Planetary Sciences, Curtin University, Australia 5,7Innovation Central Perth, Curtin University, Australia., AU
2 Innovation Central Perth, Curtin University, Australia., AU
3 Southern Ports Authority, Australia., AU
4 Curtin Cisco Centre for Networks, School of Electrical Engineering, Computing, and Mathematical Sciences, Curtin University, Australia., AU
1 Spatial Sciences, School for Earth and Planetary Sciences, Curtin University, Australia 5,7Innovation Central Perth, Curtin University, Australia., AU
2 Innovation Central Perth, Curtin University, Australia., AU
3 Southern Ports Authority, Australia., AU
4 Curtin Cisco Centre for Networks, School of Electrical Engineering, Computing, and Mathematical Sciences, Curtin University, Australia., AU
Source
ICTACT Journal on Soft Computing, Vol 13, No 3 (2023), Pagination: 2948-2959Abstract
The concept of a digital twin is increasingly applied to a wide range of physical assets as it offers spatial contextualisation, temporal contextualisation, simulation, and optimisation. For the Southern Ports Authority (SPA) of Western Australia one important asset class is breakwater walls. SPA has implemented a spatial contextualisation for their breakwater facilities using a Geographic Information System (GIS) including the breakwater wall condition. This proof-of-concept study aims to validate that timely mapping of breakwater conditions using Unmanned Aerial Vehicles (UAV) and the information derived from the images captured by UAVs is possible. Three failure modes have been investigated using single and multiple epoch data. The failure modes are slope defects, breach or loss of crest elevation and armour movement or loss of armour interlocking. The highest potential for an automatic assessment was concluded for the Breach or loss of crest elevation failure mode. Armour movement or loss is likely to be detected as well, as long as the point spacing of the point clouds in different epochs is comparable. Further investigations are required for the loss of armour interlocking as well as for multi-epoch slope defect assessment. Hence, while it is a proof-of-concept study only, it is the first step to develop a more automated assessment of breakwater walls. Consequently, this data can then be used for simulation and optimisation and the integration of the data in business processes, i.e., the maintenance cycle for the breakwater walls.Keywords
Failure Modes, Uav, Point Cloud, Point-to-Point Comparison, Point-To-Model Comparison.
References
- A. Al-Rawabdeh and A. Habib, “Automated Feature-Based Down-Sampling Approaches for Fine Registration of Irregular Point Clouds”, Remote Sensing, Vol. 12, No. 7, pp. 1224-1234, 2020.
- P.J. Besl and N.D. McKay, “A Method for Registration of 3-D Shapes”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 14, No. 2, pp. 239-256, 1992.
- Cloud Compare Version 2.6.1 User Manual, Available at http://www.cloudcompare.org/doc/qCC/CloudCompare%2 0v2.6.1%20-%20User%20manual.pdf, Accessed at 2022.
- T. Euno and Y. Kobayashi, “Bridge Maintenance, Safety, Management, Life-Cycle Sustainability and Innovations: Breakwater Inspection System using Airbourne LiDAR”, Taylor and Francis Group. 2021.
- G. Govare, R. Viquez and H. Alfaro, “Use of Drone Technology and Photogrammetry for Beach Morphodynamics and Breakwater Monitoring”, Coastlab, Vol. 16, No. 6, pp. 1-8, 2016.
- C. Gomez and H. Purdie, “UAV- Based Photogrammetry and Geocomputing for Hazards and Disaster Risk Monitoring - A Review”, Geoenvironmental Disasters, Vol. 3, pp. 1-12, 2016.
- D. Gonçalves and U. Andriolo, “On the 3D Reconstruction of Coastal Structures by Unmanned Aerial Systems with Onboard Global Navigation Satellite System and Real-Time Kinematics and Terrestrial Laser Scanning”, Remote Sensing, Vol. 14, No. 6, pp. 1-15, 2022.
- H. Gonzalez Jorge, B. Conde and P. Arias, “UAV Photogrammetry Application to the Monitoring of Rubble Mound Breakwaters”, American Society of Civil Engineers, Vol. 30, No. 1, pp. 1-8, 2014.
- E. Grilli and F. Remondino, “A Review of Point Clouds Segmentation and Classification Algorithms”, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. 2, No. 3, pp. 339-344, 2017.
- P. Helmholz and A. Woods, “The Influence of the Point Cloud Comparison Methods on the Verification of Point Clouds using the Batavia Reconstruction as a Case Study”, Archaeopress Publishing Limited, 2020.
- R. Lemos, R. Capitao, C. Fortes and T. Martins, “A Methodology for the Evaluation of Evolution and Risk of Breakwaters”, Journal of Integrated Coastal Zone Management, Vol. 20, No. 2, pp. 103-119, 2020.
- Bunbury Port Development - Long Term Monitoring and Management Plan, Available at https://www.southernports.com.au/sites/default/files/2021- 09/Bunbury%20Port%20Development%20- %20Long%20Term%20Monitoring%20And%20Managem ent%20Plan%20%28LTMMP%29.pdf, Accessed at 2021.
- Open 3D, Available at http://www.open3d.org/docs/release/tutorial/pipelines/icp_r egistration.html, Accessed at 2023.
- PCL Version 1.11.1, Available at https://pcl.readthedocs.io/projects/tutorials/en/latest/statisti cal_outlier.html, Accessed at 2023.
- Pix4D, Version 5.0.45, Available at https://www.pix4d.com/, Accessed at 2022.
- T. Rabbani and G. Vosselman, “Segmentation of Point Clouds using Smoothness Constraint”, Proceedings of International Symposium on Recent Trends in Computer Science, pp. 248-252, 2006.
- S. Rusinkiewicz and M. Levoy, “Efficient Variants of the ICP Algorithm”, Proceedings of International Conference on 3-D Digital Imaging and Modeling, pp. 145-152, 2001.
- R.B. Rusu, “Semantic 3D Object Maps for Everyday Manipulation in Human Living Environments”, KI - Künstliche Intelligenz, Vol. 24, No. 4, pp. 91-93, 2010.
- Site Scan, “Site Scan for ArcGIS by ESRI”, Available at https://www.esri.com/en-us/arcgis/products/site-scan-forarcgis/overview, Accessed at 2022.
- P.J. Sousa and E. Franco, “Structural Monitoring of a Breakwater using UAVs and Photogrammetry”, Procedia Structural Integrity, Vol. 37, pp. 167-172, 2022.
- A. Tremeau and N. Borel, “A Region Growing and Merging Algorithm to Color Segmentation”, Pattern Recognition, Vol. 30, No. 7, pp. 1191-1203, 1997.
- United States Army Corps of Engineers, Available at https://www.publications.usace.army.mil/usacepublications/engineer-manuals/, Accessed at 2022.
- T. Ueno and Y. Kobayashi, “Breakwater Inspection System using Airborne LiDAR”, Taylor and Francis Group, 2021.
- H. Woo and K. Lee, “A New Segmentation Method for Point Cloud Data”, International Journal of Machine Tools and Manufacture, Vol. 42, No. 2, pp. 167-178, 2002.
- Q. Zhan, Y. Liang and Y. Xiao, “Color-Based Segmentation of Point Clouds”, Proceedings of International Workshop on Laser Scanning, Vol. 38, pp. 1-9, 2009.
- Y. Zhang and S. Chen, “UAV Low Altitude Photogrammetry for Powerline Inspection”, ISPRS International Journal of Geo-Information, Vol. 6, No. 1, pp. 1-16, 2017.