Damage Detection and Monitoring of a Concrete Structure Using 3D Laser Scanning
Surface damage detection, geometry measurement and monitoring are important for assessing the condition and risk of concrete structures. Therefore, to effectively assess the damage to a concrete structure, a 3D laser scanner accurately estimates the damage within a short timeframe and with less cost...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-06-01
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| Series: | Engineering Proceedings |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2673-4591/36/1/1 |
| _version_ | 1797241254231146496 |
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| author | Manik Das Adhikari Tae-Hwan Kim Sang-Guk Yum Joon-Yeong Kim |
| author_facet | Manik Das Adhikari Tae-Hwan Kim Sang-Guk Yum Joon-Yeong Kim |
| author_sort | Manik Das Adhikari |
| collection | DOAJ |
| description | Surface damage detection, geometry measurement and monitoring are important for assessing the condition and risk of concrete structures. Therefore, to effectively assess the damage to a concrete structure, a 3D laser scanner accurately estimates the damage within a short timeframe and with less cost than the traditional inspection approaches. This study presents a framework for automated surface damage detection and structural health monitoring of a concrete structure using a X7 laser scanner (Trimble, Westminster, CO, USA). The methodology includes the use of 3D laser scanning technology to capture the 3D geometry of the concrete structure, followed by a detailed analysis of the data to identify any areas of damage or crack. The isodata and object-based image analysis (OBIA) techniques were applied to a 2D image generated from 3D cloud points. Overall accuracy (>89.6) and kappa statistics (>0.83) of both classification techniques exhibit good agreement between the classified and reference image. The OBIA technique was shown to be more effective in detecting minor cracks (<5 mm) and damage on a concrete structure. It was observed that the proposed approach is effective at identifying and monitoring the structural health of a concrete structure. The ability to continuously monitor the structure in this manner allows for early detection of damage and can aid in the maintenance and repair of the structure. Furthermore, this approach can robustly perform structural health monitoring and damage estimation. |
| first_indexed | 2024-04-24T18:20:24Z |
| format | Article |
| id | doaj.art-8db388b01029460492bb7d016f518bb4 |
| institution | Directory Open Access Journal |
| issn | 2673-4591 |
| language | English |
| last_indexed | 2024-04-24T18:20:24Z |
| publishDate | 2023-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Engineering Proceedings |
| spelling | doaj.art-8db388b01029460492bb7d016f518bb42024-03-27T13:36:25ZengMDPI AGEngineering Proceedings2673-45912023-06-01361110.3390/engproc2023036001Damage Detection and Monitoring of a Concrete Structure Using 3D Laser ScanningManik Das Adhikari0Tae-Hwan Kim1Sang-Guk Yum2Joon-Yeong Kim3Department of Civil Engineering, Gangneung-Wonju National University, Gangneung 25457, Republic of KoreaDepartment of Security Service, Yongin University, Yongin 17092, Republic of KoreaDepartment of Civil Engineering, Gangneung-Wonju National University, Gangneung 25457, Republic of KoreaDepartment of R&D Lab, SQ Engineering Co. Ltd., Sonpa-gu, Seoul 05818, Republic of KoreaSurface damage detection, geometry measurement and monitoring are important for assessing the condition and risk of concrete structures. Therefore, to effectively assess the damage to a concrete structure, a 3D laser scanner accurately estimates the damage within a short timeframe and with less cost than the traditional inspection approaches. This study presents a framework for automated surface damage detection and structural health monitoring of a concrete structure using a X7 laser scanner (Trimble, Westminster, CO, USA). The methodology includes the use of 3D laser scanning technology to capture the 3D geometry of the concrete structure, followed by a detailed analysis of the data to identify any areas of damage or crack. The isodata and object-based image analysis (OBIA) techniques were applied to a 2D image generated from 3D cloud points. Overall accuracy (>89.6) and kappa statistics (>0.83) of both classification techniques exhibit good agreement between the classified and reference image. The OBIA technique was shown to be more effective in detecting minor cracks (<5 mm) and damage on a concrete structure. It was observed that the proposed approach is effective at identifying and monitoring the structural health of a concrete structure. The ability to continuously monitor the structure in this manner allows for early detection of damage and can aid in the maintenance and repair of the structure. Furthermore, this approach can robustly perform structural health monitoring and damage estimation.https://www.mdpi.com/2673-4591/36/1/1laser scanningpoint cloudssurface damage detectionimage classificationmonitoringdamage quantification |
| spellingShingle | Manik Das Adhikari Tae-Hwan Kim Sang-Guk Yum Joon-Yeong Kim Damage Detection and Monitoring of a Concrete Structure Using 3D Laser Scanning Engineering Proceedings laser scanning point clouds surface damage detection image classification monitoring damage quantification |
| title | Damage Detection and Monitoring of a Concrete Structure Using 3D Laser Scanning |
| title_full | Damage Detection and Monitoring of a Concrete Structure Using 3D Laser Scanning |
| title_fullStr | Damage Detection and Monitoring of a Concrete Structure Using 3D Laser Scanning |
| title_full_unstemmed | Damage Detection and Monitoring of a Concrete Structure Using 3D Laser Scanning |
| title_short | Damage Detection and Monitoring of a Concrete Structure Using 3D Laser Scanning |
| title_sort | damage detection and monitoring of a concrete structure using 3d laser scanning |
| topic | laser scanning point clouds surface damage detection image classification monitoring damage quantification |
| url | https://www.mdpi.com/2673-4591/36/1/1 |
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