Automatic cross-sectional roughness profiling
Surface roughness of rock joints has major influence on the shear strength of rock joints and is also one of the most important factors for estimating the mechanical behavior of rock masses. Hence, an accurate determination on surface roughness of rock joints is necessary. In this report, measuremen...
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Format: | Final Year Project |
Language: | English |
Published: |
2013
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Online Access: | http://hdl.handle.net/10356/53820 |
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Institution: | Nanyang Technological University |
Language: | English |
Summary: | Surface roughness of rock joints has major influence on the shear strength of rock joints and is also one of the most important factors for estimating the mechanical behavior of rock masses. Hence, an accurate determination on surface roughness of rock joints is necessary. In this report, measurement of rock surface method using high resolution digital photogrammetry and surface roughness analysis using various profile roughness parameters are investigated. There are three basic steps to analyze the roughness of the rock joints: (1) Camera calibration for accuracy assessment (2) 3D photogrammetric point cloud extraction (3) Compilation of profile parameters for surface roughness analysis. Eight parameters including six two-dimensional parameters and two three-dimensional parameters have been proposed to characterize the roughness of the surfaces into Joint Roughness Coefficients. Correlation between tensile strain rate and Joint Roughness Coefficient were formed. Results showed that the Joint Roughness Coefficient decreased with the tensile strain rate (ὲ). RMS first derivative of the profile (Z2) was found to have the strongest correlation to the tensile strain rate. The equation below is the correlation of Joint Roughness Coefficient based on RMS first derivative of the profile (Z2) with tensile strain rate:
JRC=-1.3ἐ +27.8
In conclusion, Close Range Photogrammetry is suitable for measurement of joint roughness. However, further study needs to be done on the 3D parameters to improve the roughness analysis results. |
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