Bituminous coal in the Xutuan Coal Mine of the Huaibei Mining Bureau (China) is the research object of this study. The influence of moisture content on the porosity of the bituminous coal was investigated from a microscopic perspective by using a high-solution 3D X-ray micro-analyzer. The threshold segmentation method was used to segment the scanning slices of the coal samples. The threshold values of the various media were in the following order (from large to small): minerals, water, matrices, and fractures. The scanning volume and actual volume proportions of the different media in the coal samples with different moisture contents were calculated. The accuracy of the computerized tomography (CT) scanning method in measuring the coal moisture content was verified by comparison with the results obtained using the weighing method. 3D reconstructed coal samples, with different moisture contents, were analyzed, as well as separately reconstructed fractures and water in the coal samples with different moisture contents. The heterogeneity and anisotropy of the coal mass were explained quantitatively by the CT scanning intensity. A commonly used fracture classification method indicated that the primary fracture in the coal sample was a type A fracture. The results of the analysis of water in the coal fracture indicated that the porosity of bituminous coal decreased with the increase in moisture content in conditions of atmospheric pressure and a short immersion period. However, a certain level of porosity remained evident, and the degree of fracture development of the coal samples remained unchanged. This is attributed to the minor volumetric change in the minerals in the coal samples, as the water does not completely occupy the fractures in the coal samples, and the dissolution of the minerals by water is therefore not significant. The reasons for the moisture content affecting gas adsorption, seepage, and strength of a coal body were analyzed from a microscopic perspective. In addition, the types of fractures and water in the coal samples were classified by employing statistics and analyses of volume, surface area, specific surface area, and aspect ratio of the fractures and the water in the coal samples with different moisture contents.
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