Macerals particle characteristics analysis of tar-rich coal in northern Shaanxi based on image segmentation models via the U-Net variants and image feature extraction

To investigate the particle characteristics of tar-rich coal macerals before separation, this study focuses on the tar-rich coal in northern Shaanxi, China, as the research object. The image segmentation models of U-Net variants (Mobile-Unet, VGG-Unet, Res-Unet, and TransUNet) are combined with OpenCV feature extraction to systematically study the particle morphology, particle size, liberation characteristics, and density separation process of coal macerals. The results indicate that the morphology of vitrinite tends to an olive-like shape as the particle size decreases, whereas the morphology of inertinite is complex and changeable. Further, the particle sizes of raw coal, vitrinite, and inertinite range from 0.09 mm to 0.075 mm, and their morphology uniformity is the best in this range. The statistical difference between the grid calculation point method (GCPM) and the pixel area statistics method (PASM) is mainly due to the particle size uniformity. When the particle size is less than 0.03 mm, the error is less than 3.0 %. By narrowing the range of the liberation densities and separating them preferentially, samples within the range of the unliberated densities are returned to the regrinding process to separate and enrich the vitrinite and inertinite groups in coal, which effectively improves their purity and recovery. In summary, Res-UNet, TransUNet, and the PASM not only have considerable potential for the qualitative analysis of maceral compositions and their liberation types but also provide powerful computer-assisted measurement to achieve reasonable separation and utilization of coal macerals.