Rock Mass Surface Roughness Characterization Using Image Analysis Technique
The joint roughness coefficient (JRC) is very important to determine the shear strength of the rock, for example, as one of the inputs for the Barton-Bandis model. Conventionally, the Barton comb profilometer is widely used in the field but some issues related to accessibility, labor-intensive, a...
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| Format: | Monograph |
| Language: | English |
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Universiti Sains Malaysia
2021
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| Online Access: | http://eprints.usm.my/57295/1/Rock%20Mass%20Surface%20Roughness%20Characterization%20Using%20Image%20Analysis%20Technique.pdf |
| _version_ | 1825907663786999808 |
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| author | Adnan, Raja Asyraf Azizan Raja |
| author_facet | Adnan, Raja Asyraf Azizan Raja |
| author_sort | Adnan, Raja Asyraf Azizan Raja |
| collection | USM |
| description | The joint roughness coefficient (JRC) is very important to determine the shear
strength of the rock, for example, as one of the inputs for the Barton-Bandis model.
Conventionally, the Barton comb profilometer is widely used in the field but some issues
related to accessibility, labor-intensive, and time-consuming. To tackle these problems,
this study aims to evaluate the photogrammetry technique in producing reliable JRC
measurements. To achieve this, a set of JRC replica of the rock mass is produced to
determine the JRC readings. In addition, a drone is used to take photos of the JRC model
with high quality as Unmanned Aerial Vehicle (UAV) photogrammetry method. The
reliability of such measures depends on some parameters such as the number of images,
image quality, and the number of point clouds. The digitalization of the JRC model will
take place to create a 3D model using photogrammetry. The JRC measurement results
are compared with the manual Barton comb profilometer method. Then, an actual rock
mass is used to verify the photogrammetry technique. As result, the JRC of the 3D model
can be produced by using the image analysis technique. The ultra-high quality has the
most accurate measurement as actual length with zero percent error compared to actual
measurement using Barton comb. As for low, medium, and high quality, the error was
15.54%, 9.46%, 2.7% respectively to the actual. However, the medium quality is the
most efficient way since it can produce the reliable JRC measurement within a short
period and can practically use for fieldwork. |
| first_indexed | 2024-03-06T16:07:33Z |
| format | Monograph |
| id | usm.eprints-57295 |
| institution | Universiti Sains Malaysia |
| language | English |
| last_indexed | 2024-03-06T16:07:33Z |
| publishDate | 2021 |
| publisher | Universiti Sains Malaysia |
| record_format | dspace |
| spelling | usm.eprints-572952023-03-14T03:06:39Z http://eprints.usm.my/57295/ Rock Mass Surface Roughness Characterization Using Image Analysis Technique Adnan, Raja Asyraf Azizan Raja T Technology TA Engineering (General). Civil engineering (General) The joint roughness coefficient (JRC) is very important to determine the shear strength of the rock, for example, as one of the inputs for the Barton-Bandis model. Conventionally, the Barton comb profilometer is widely used in the field but some issues related to accessibility, labor-intensive, and time-consuming. To tackle these problems, this study aims to evaluate the photogrammetry technique in producing reliable JRC measurements. To achieve this, a set of JRC replica of the rock mass is produced to determine the JRC readings. In addition, a drone is used to take photos of the JRC model with high quality as Unmanned Aerial Vehicle (UAV) photogrammetry method. The reliability of such measures depends on some parameters such as the number of images, image quality, and the number of point clouds. The digitalization of the JRC model will take place to create a 3D model using photogrammetry. The JRC measurement results are compared with the manual Barton comb profilometer method. Then, an actual rock mass is used to verify the photogrammetry technique. As result, the JRC of the 3D model can be produced by using the image analysis technique. The ultra-high quality has the most accurate measurement as actual length with zero percent error compared to actual measurement using Barton comb. As for low, medium, and high quality, the error was 15.54%, 9.46%, 2.7% respectively to the actual. However, the medium quality is the most efficient way since it can produce the reliable JRC measurement within a short period and can practically use for fieldwork. Universiti Sains Malaysia 2021-10-01 Monograph NonPeerReviewed application/pdf en http://eprints.usm.my/57295/1/Rock%20Mass%20Surface%20Roughness%20Characterization%20Using%20Image%20Analysis%20Technique.pdf Adnan, Raja Asyraf Azizan Raja (2021) Rock Mass Surface Roughness Characterization Using Image Analysis Technique. Project Report. Universiti Sains Malaysia, Pusat Pengajian Kejuruteraan Awam. (Submitted) |
| spellingShingle | T Technology TA Engineering (General). Civil engineering (General) Adnan, Raja Asyraf Azizan Raja Rock Mass Surface Roughness Characterization Using Image Analysis Technique |
| title | Rock Mass Surface Roughness Characterization Using Image Analysis Technique |
| title_full | Rock Mass Surface Roughness Characterization Using Image Analysis Technique |
| title_fullStr | Rock Mass Surface Roughness Characterization Using Image Analysis Technique |
| title_full_unstemmed | Rock Mass Surface Roughness Characterization Using Image Analysis Technique |
| title_short | Rock Mass Surface Roughness Characterization Using Image Analysis Technique |
| title_sort | rock mass surface roughness characterization using image analysis technique |
| topic | T Technology TA Engineering (General). Civil engineering (General) |
| url | http://eprints.usm.my/57295/1/Rock%20Mass%20Surface%20Roughness%20Characterization%20Using%20Image%20Analysis%20Technique.pdf |
| work_keys_str_mv | AT adnanrajaasyrafazizanraja rockmasssurfaceroughnesscharacterizationusingimageanalysistechnique |