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A three-dimensional feature extraction-based method for coal cleat characterization using X-ray μCT and its application to a Bowen Basin coal specimen by Yulai Zhang; Matthew Tsang; Mark Knackstedt; Michael Turner; Shane Latham; Euan Macaulay; Rhys Pitchers is a Engineering article available to read on EtoBox.

What is A three-dimensional feature extraction-based method for coal cleat characterization using X-ray μCT and its application to a Bowen Basin coal specimen about?

Cleats are the dominant micro-fracture network controlling the macro-mechanical behavior of coal. Improved understanding of the spatial characteristics of cleat networks is therefore important to the coal mining industry. Discrete fracture networks (DFNs) are increasingly used in engineering analyses to spatially model fractures at various scales. The reliability of coal DFNs largely depends on the confidence in the input cleat statistics. Estimates of these parameters can be made from image-based three-dimensional (3D) characterization of coal cleats using X-ray micro-computed tomography (μCT). One key step in this process, after cleat extraction, is the separation of individual cleats, without which the cleats are a connected network and statistics for different cleat sets cannot be measured. In this paper, a feature extraction-based image processing method is introduced to identify and separate distinct cleat groups from 3D X-ray μCT images. Kernels (filters) representing explicit cleat features of coal are built and cleat separation is successfully achieved by convolutional operations on 3D coal images. The new method is applied to a coal specimen with 80 mm in diameter and 100

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Author

Yulai Zhang; Matthew Tsang; Mark Knackstedt; Michael Turner; Shane Latham; Euan Macaulay; Rhys Pitchers

Publisher

Elsevier BV

Published

2024

Language

EN

Field

Engineering (Physical Sciences)