Determination of RQD by digital image analysis

2018
Sarıçam, İ. Turgut
Digital image processing and analysis methods allow us to automate routine tasks. Rock Quality Designation (RQD) is a rock quality index used in rock mechanics and geotechnical designs of slopes and underground excavations. Manual logging of hundreds of meters of rock core samples with a tape measure is a very laboursome and tedious process. In this research study, a method is introduced for the segmentation of cores and the determination of RQD from digital images of rows of core samples in core boxes in order to compute RQD in an automatic way by finding and locating natural fractures in cores and measuring intact core lengths. First, three digital true color images of a core box, with the same camera position but different light source positions, are taken using a high resolution camera. After the detection of the core box with color thresholding, the sections of the box are detected by using Hough transform and boundary tracing algorithms. Then, the cores are extracted from each section using color thresholding. After cleaning the shadows created by different light sources using various techniques, the segmentation part is finished by combining similar regions with each other. Later, non-cylindrical parts of the cores are detected by looking at the changes caused by two different light sources. After completion of the fracture detection in the drill core, RQD is calculated by measuring the valid centerline lengths of each core. All coding routines are developed in MATLAB 2017a. Two different core boxes with 4 and 5 rows storing HQ and NQ diameter cores having various joint/bedding plane angles are photographed several times with different core placements. It is shown that the method is capable of separating even tightly fit joint surface cores. Moreover, it can successfully detect non-cylindrical parts of the cores, and avoid small or irregularly shaped ones which should not be included in RQD calculation.

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Citation Formats
İ. T. Sarıçam, “Determination of RQD by digital image analysis,” M.S. - Master of Science, Middle East Technical University, 2018.