Comparison of Depth Camera and Terrestrial Laser Scanner in Monitoring Structural Deflections
Modeling a structure in the virtual world using three-dimensional (3D) information enhances our understanding, while also aiding in the visualization, of how a structure reacts to any disturbance. Generally, 3D point clouds are used for determining structural behavioral changes. Light detection and...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-12-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/21/1/201 |
| _version_ | 1797543100697018368 |
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| author | Michael Bekele Maru Donghwan Lee Kassahun Demissie Tola Seunghee Park |
| author_facet | Michael Bekele Maru Donghwan Lee Kassahun Demissie Tola Seunghee Park |
| author_sort | Michael Bekele Maru |
| collection | DOAJ |
| description | Modeling a structure in the virtual world using three-dimensional (3D) information enhances our understanding, while also aiding in the visualization, of how a structure reacts to any disturbance. Generally, 3D point clouds are used for determining structural behavioral changes. Light detection and ranging (LiDAR) is one of the crucial ways by which a 3D point cloud dataset can be generated. Additionally, 3D cameras are commonly used to develop a point cloud containing many points on the external surface of an object around it. The main objective of this study was to compare the performance of optical sensors, namely a depth camera (DC) and terrestrial laser scanner (TLS) in estimating structural deflection. We also utilized bilateral filtering techniques, which are commonly used in image processing, on the point cloud data for enhancing their accuracy and increasing the application prospects of these sensors in structure health monitoring. The results from these sensors were validated by comparing them with the outputs from a linear variable differential transformer sensor, which was mounted on the beam during an indoor experiment. The results showed that the datasets obtained from both the sensors were acceptable for nominal deflections of 3 mm and above because the error range was less than <inline-formula><math display="inline"><semantics><mrow><mo>±</mo><mn>10</mn><mo>%</mo></mrow></semantics></math></inline-formula>. However, the result obtained from the TLS were better than those obtained from the DC. |
| first_indexed | 2024-03-10T13:39:55Z |
| format | Article |
| id | doaj.art-a306351e76204603b7ee061339d9a3aa |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T13:39:55Z |
| publishDate | 2020-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-a306351e76204603b7ee061339d9a3aa2023-11-21T03:09:39ZengMDPI AGSensors1424-82202020-12-0121120110.3390/s21010201Comparison of Depth Camera and Terrestrial Laser Scanner in Monitoring Structural DeflectionsMichael Bekele Maru0Donghwan Lee1Kassahun Demissie Tola2Seunghee Park3Department of the Civil, Architectural and Environmental System Engineering, Sungkyunkwan University, Suwon 16419, KoreaDepartment of Convergence Engineering for Future City, Sungkyunkwan University, Suwon 16419, KoreaDepartment of the Civil, Architectural and Environmental System Engineering, Sungkyunkwan University, Suwon 16419, KoreaSchool of Civil, Architectural Engineering and Landscape Architecture, Sungkyunkwan University, Suwon 16419, KoreaModeling a structure in the virtual world using three-dimensional (3D) information enhances our understanding, while also aiding in the visualization, of how a structure reacts to any disturbance. Generally, 3D point clouds are used for determining structural behavioral changes. Light detection and ranging (LiDAR) is one of the crucial ways by which a 3D point cloud dataset can be generated. Additionally, 3D cameras are commonly used to develop a point cloud containing many points on the external surface of an object around it. The main objective of this study was to compare the performance of optical sensors, namely a depth camera (DC) and terrestrial laser scanner (TLS) in estimating structural deflection. We also utilized bilateral filtering techniques, which are commonly used in image processing, on the point cloud data for enhancing their accuracy and increasing the application prospects of these sensors in structure health monitoring. The results from these sensors were validated by comparing them with the outputs from a linear variable differential transformer sensor, which was mounted on the beam during an indoor experiment. The results showed that the datasets obtained from both the sensors were acceptable for nominal deflections of 3 mm and above because the error range was less than <inline-formula><math display="inline"><semantics><mrow><mo>±</mo><mn>10</mn><mo>%</mo></mrow></semantics></math></inline-formula>. However, the result obtained from the TLS were better than those obtained from the DC.https://www.mdpi.com/1424-8220/21/1/201terrestrial laser scanning (TLS)depth camera (DC)hausdorff distancebilateral filteringpoint clouddeflection |
| spellingShingle | Michael Bekele Maru Donghwan Lee Kassahun Demissie Tola Seunghee Park Comparison of Depth Camera and Terrestrial Laser Scanner in Monitoring Structural Deflections Sensors terrestrial laser scanning (TLS) depth camera (DC) hausdorff distance bilateral filtering point cloud deflection |
| title | Comparison of Depth Camera and Terrestrial Laser Scanner in Monitoring Structural Deflections |
| title_full | Comparison of Depth Camera and Terrestrial Laser Scanner in Monitoring Structural Deflections |
| title_fullStr | Comparison of Depth Camera and Terrestrial Laser Scanner in Monitoring Structural Deflections |
| title_full_unstemmed | Comparison of Depth Camera and Terrestrial Laser Scanner in Monitoring Structural Deflections |
| title_short | Comparison of Depth Camera and Terrestrial Laser Scanner in Monitoring Structural Deflections |
| title_sort | comparison of depth camera and terrestrial laser scanner in monitoring structural deflections |
| topic | terrestrial laser scanning (TLS) depth camera (DC) hausdorff distance bilateral filtering point cloud deflection |
| url | https://www.mdpi.com/1424-8220/21/1/201 |
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