Water-filled mining goaves are extremely prone to water inrush accidents in coal mines, and the transient electromagnetic method (TEM) is a good geophysical method for detecting water-rich areas. Considering that conventional TEM was mainly carried out on the ground, to increase the detection resolution, the underground TEM was used to detect the water-filled goaves in this study. Based on the whole-space model, the data-processing method of the underground TEM was studied. The whole-space geoelectric model was established based on actual coal-measure strata data, and the whole-space TEM response of the water-filled goaves was modeled using the finite-difference time-domain method. The results showed that the low-resistance areas of the apparent resistivity contours can accurately reflect the water abundance of the mining goaves. The underground TEM was used to detect the water abundance of the mining goaf in a mine environment and its detection results were consistent with the actual results.

Hidden, water-abundant areas in coal mines pose a serious threat to mine safety and production. Underground transient electromagnetic method (TEM) is one of the most effective means of detecting water-abundant areas in front of the roadway head. Traditional TEM theories and applications are interpreted mainly on the vertical component. In this study, multicomponent responses of TEM in underground roadways were modeled using the finite-difference time-domain method. Physical simulation was also used for advanced detection of TEM in the roadway. Both the numerical and physical simulation results show that the horizontal component is more sensitive to the location of water-abundant areas. The results of the joint interpretation with both horizontal and vertical components were verified in a practical coal mine application, indicating that it is feasible to use the horizontal component in interpreting TEM data. Thus, the horizontal component could serve as a new approach for coal mine TEM data processing and interpretation.

We present an original error-diffusion method which produces visually pleasant halftone images while preserving fine details and visually identifiable structures present in the original images. Our method is conceptually simple and computationally efficient. The source image is analyzed, and its local frequency content is detected. The main component of the frequency content (main frequency, orientation and contrast) serve as lookup table indices to a pre-calculated database of modifications to a standard error diffusion. The modifications comprise threshold modulation and variation of error-diffusion coefficients. The whole system is calibrated in such a way that the produced halftone images are visually close to the original images (patches of constant intensity, patches containing sinusoidal waves of different frequencies/orientations/contrasts, as well as natural images of different origins). Our system produces images of visual quality comparable to that presented in [Pang et al. 2008], but much faster. When processing typical images of linear size of several hundreds of pixels, our error-diffusion system is two to three orders of magnitude faster than [Pang et al. 2008]. Thanks to its speed combined with high visual quality, our error-diffusion algorithm can be used in many practical applications which may require digital halftoning: printing, visualization, geometry processing, various sampling techniques, etc.