The mining of underground coal resources often results in extensive damage to the ground surface, particularly in China, which has a large amount of coal resources. However, the laws of surface damage caused by the mining of deep and shallow underground coal resources are relatively different. This study analyzes the difference in surface damage induced by deep and shallow mining and its mechanism by field measurement and similar material simulation experiments. Surface damage is mainly manifested in the form of cracks, which can be categorized as permanent and dynamic cracks. Permanent cracks occur above the mining boundary of shallow and deep coal mines. Dynamic cracks (including dynamic stretching cracks and stepped cracks) only appear above the goaf in shallow mining. This disparity is due to the fact that strata movement in deep mining occurs in a “three zones” mode, with the failure height of strata increasing with the mining degree in an “S” shape. However, rock strata movement in shallow mining follows a “two zones” mode, with the failure height of rock strata increasing exponentially with the mining degree. Thus, the rock strata are prone to slide and become unstable in the form of benched rock beams, producing dynamic cracks, such as stepped cracks on the surface. This research improves the existing mining subsidence theory and provides technical support for relevant mines to take targeted treatment measures.

According to traditional concepts, the movement of overlying strata and surface damage caused by coal mining in horizontal coal seams are symmetrical in terms of spatial distribution. However, in a lot of engineering practices, this symmetry has not been discovered. We often use the symmetry function to establish the profile prediction function of the surface damage, which results in a large difference between the prediction result and the actual situation. To solve this problem, this paper takes subsidence velocity as an example. Firstly, the spatial distribution functions of subsidence velocity on both sides were deduced theoretically. Through comparison, it is found that the change rate of the spatial distribution curve of the coal pillar side subsidence velocity is smoother than that of the goaf side and the subsidence velocity curves are skewed to the left. Secondly, based on the idea of lossless propagation of harmonic waves and idealizing the propagation environment, the spatial propagation relationship of surface subsidence velocity in the time domain is established. Then, the Box–Cox transform function is introduced to improve the normal distribution probability density function, and a new dynamic subsidence prediction model based on the Box–Cox transformation is obtained, which is suitable for the full mining stage. The model is tested by practical cases, the prediction accuracy is better than 7%, and the prediction results can meet the needs of engineering prediction accuracy (10%). The results of this research can enrich the existing subsidence prediction theory and provide theoretical and technical support for the prediction of dynamic surface damage caused by similar mining.

Most coal resources are deposited in the form of inclined coal seams, and surface subsidence basin morphology induced by the mining of inclined coal seams is frequently skewed. The probability integral method with symmetrical distribution characteristics is widely used at present in surface subsidence prediction in coal mining in China. However, this method performs poorly when the inclined coal seam mining subsidence is predicted, and prediction accuracy decreases considerably with an increase in coal seam inclination. To solve this problem, this study first establishes three coordinate systems: a working surface rectangular coordinate system, a working face body-following coordinate system, and a surface rectangular coordinate system. Then, a random medium theory is applied to realize the superposition integral operation of the subsidence influence of unit mining in the working faces body-following coordinate system. Subsequently, the subsidence effect of a certain point on the surface is converted into the surface rectangular coordinate system. Finally, the inclined coal seam mining subsidence prediction model is constructed under the surface rectangular coordinate system. Results show that the surface subsidence caused by the mining of the inclined coal seam units conforms to the Weibull polar distribution law, and the effectiveness of the prediction model is verified through examples. The relative mean squared error of the prediction is less than 10%. The results of the study can provide theoretical and technical support for the subsidence prediction of similar mining areas.