Measurement of Rock Joint Surfaces by Using Smartphone Structure from Motion (SfM) Photogrammetry
The measurement of rock joint surfaces is essential for the estimation of the shear strength of the rock discontinuities in rock engineering. Commonly used techniques for the acquisition of the morphology of the surfaces, such as profilometers and laser scanners, either have low accuracy or high cos...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-01-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/21/3/922 |
| _version_ | 1797405811372195840 |
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| author | Pengju An Kun Fang Qiangqiang Jiang Haihua Zhang Yi Zhang |
| author_facet | Pengju An Kun Fang Qiangqiang Jiang Haihua Zhang Yi Zhang |
| author_sort | Pengju An |
| collection | DOAJ |
| description | The measurement of rock joint surfaces is essential for the estimation of the shear strength of the rock discontinuities in rock engineering. Commonly used techniques for the acquisition of the morphology of the surfaces, such as profilometers and laser scanners, either have low accuracy or high cost. Therefore, a high-speed, low-cost, and high-accuracy method for obtaining the topography of the joint surfaces is necessary. In this paper, a smartphone structure from motion (SfM) photogrammetric solution for measuring rock joint surfaces is presented and evaluated. Image datasets of two rock joint specimens were taken under two different modes by using an iPhone 6s, a Pixel 2, and a T329t and subsequently processed through SfM-based software to obtain 3D models. The technique for measuring rock joint surfaces was evaluated using the root mean square error (RMSE) of the cloud-to-cloud distance and the mean error of the joint roughness coefficient (JRC). The results show that the RMSEs by using the iPhone 6s and Pixel 2 are both less than 0.08 mm. The mean errors of the JRC are −7.54 and −5.27% with point intervals of 0.25 and 1.0 mm, respectively. The smartphone SfM photogrammetric method has comparable accuracy to a 3D laser scanner approach for reconstructing laboratory-sized rock joint surfaces, and it has the potential to become a popular method for measuring rock joint surfaces. |
| first_indexed | 2024-03-09T03:15:34Z |
| format | Article |
| id | doaj.art-0e41f37b1bd24ddab2b45e57441256af |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T03:15:34Z |
| publishDate | 2021-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-0e41f37b1bd24ddab2b45e57441256af2023-12-03T15:18:58ZengMDPI AGSensors1424-82202021-01-0121392210.3390/s21030922Measurement of Rock Joint Surfaces by Using Smartphone Structure from Motion (SfM) PhotogrammetryPengju An0Kun Fang1Qiangqiang Jiang2Haihua Zhang3Yi Zhang4Faculty of Engineering, China University of Geosciences, Wuhan 430074, ChinaFaculty of Engineering, China University of Geosciences, Wuhan 430074, ChinaWuhan Design and Research Institute Co., Ltd., China Coal Technology & Engineering Group Corp, Wuhan 430064, ChinaTechnical Research & Development Institute, Kumagai Gumi Co., Ltd., Ibaraki 3002651, JapanDepartment of Civil Engineering, Tsinghua University, Beijing 100084, ChinaThe measurement of rock joint surfaces is essential for the estimation of the shear strength of the rock discontinuities in rock engineering. Commonly used techniques for the acquisition of the morphology of the surfaces, such as profilometers and laser scanners, either have low accuracy or high cost. Therefore, a high-speed, low-cost, and high-accuracy method for obtaining the topography of the joint surfaces is necessary. In this paper, a smartphone structure from motion (SfM) photogrammetric solution for measuring rock joint surfaces is presented and evaluated. Image datasets of two rock joint specimens were taken under two different modes by using an iPhone 6s, a Pixel 2, and a T329t and subsequently processed through SfM-based software to obtain 3D models. The technique for measuring rock joint surfaces was evaluated using the root mean square error (RMSE) of the cloud-to-cloud distance and the mean error of the joint roughness coefficient (JRC). The results show that the RMSEs by using the iPhone 6s and Pixel 2 are both less than 0.08 mm. The mean errors of the JRC are −7.54 and −5.27% with point intervals of 0.25 and 1.0 mm, respectively. The smartphone SfM photogrammetric method has comparable accuracy to a 3D laser scanner approach for reconstructing laboratory-sized rock joint surfaces, and it has the potential to become a popular method for measuring rock joint surfaces.https://www.mdpi.com/1424-8220/21/3/922rock jointstructure from motion (SfM)photogrammetrysmartphone |
| spellingShingle | Pengju An Kun Fang Qiangqiang Jiang Haihua Zhang Yi Zhang Measurement of Rock Joint Surfaces by Using Smartphone Structure from Motion (SfM) Photogrammetry Sensors rock joint structure from motion (SfM) photogrammetry smartphone |
| title | Measurement of Rock Joint Surfaces by Using Smartphone Structure from Motion (SfM) Photogrammetry |
| title_full | Measurement of Rock Joint Surfaces by Using Smartphone Structure from Motion (SfM) Photogrammetry |
| title_fullStr | Measurement of Rock Joint Surfaces by Using Smartphone Structure from Motion (SfM) Photogrammetry |
| title_full_unstemmed | Measurement of Rock Joint Surfaces by Using Smartphone Structure from Motion (SfM) Photogrammetry |
| title_short | Measurement of Rock Joint Surfaces by Using Smartphone Structure from Motion (SfM) Photogrammetry |
| title_sort | measurement of rock joint surfaces by using smartphone structure from motion sfm photogrammetry |
| topic | rock joint structure from motion (SfM) photogrammetry smartphone |
| url | https://www.mdpi.com/1424-8220/21/3/922 |
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