Intelligent unmanned mining is a key process in coal mine production, which has direct impact on the production safety, coal output, economic benefits and social benefits of coal mine enterprises. With the rapid development and popularization of 5G+ intelligent mines and coal mine intelligent equipment in China, the intelligentization of intelligent unmanned mining has become an important research topic. Especially with the promulgation of some Chinese policies and regulations, intelligent unmanned mining technology has become one of the key technologies of coal mine production. To understand the connotation, status quo and development trends of intelligent unmanned mining, this paper takes the relationship between key technologies and engineering application of intelligent unmanned mining in China as the perspective. It is proposed that the intelligent unmanned mining technology is in the whole process of working face mining. A research structure of unmanned follow-up operation and safe patrol is changing to the mode of intelligent adaptive mining, followed by the basic concepts and characteristics of intelligent unmanned mining. Relevant researches that maybe beneficial to the proposed research content are reviewed in four layers, which include basic theory, key technology, mining mode, and overall design system theory and technology. Finally, the current intelligent unmanned mining mode and future trends in this field in China are summarized.

Coal seam impact risk assessment is the premise of coal mine safety, which can reduce the occurrence of underground impact pressure accidents and directly affect the safety, coal production, economic and social benefits of coal mining enterprises. In order to evaluate the impact risk of coal seams more reasonably and comprehensively, and consider the weights of different influencing factors on the impact risk of coal seams, the neural network model is proposed to evaluate the impact risk of coal seams. Mining depth, impact tendency, geological structure and mining technology are selected as the influencing factors of coal seam impact risk. Each influencing factor contains different evaluation indices, a total of 18. The 18 evaluation indices and the impact risk level are normalized and quantified. The BP neural network model for evaluating coal seam impact risk level is established, and the impact risk of 2-1 coal seams in a mine in Inner Mongolia is comprehensively evaluated and analyzed in this study. The results show that the BP neural network model can represent coal seam impact risk level well. The application of the BP neural network model to evaluate coal seam impact risk level has the characteristics of high precision, fast calculation speed and less artificial calculation, which provides an efficient and convenient method for the evaluation of coal seam impact risk.

Aiming at the calculation problem of bearing pressure of typical overlying strata structure, in this paper, mechanical calculation, field monitoring and other methods are used to study the influence range of abutment pressure. Recently, many major rock burst accidents in working surface show that with the increase of mining depth and the change of overlying strata structure, the abutment pressure distribution has become one of the problems of safe mining. The influence range, distribution of high stress area and peak position of working surface support pressure need to be solved urgently; and through theoretical analysis, this paper reveals (whole rock single-layer structure, whole rock layered structure, whole rock single-layer structure—without arch in soil layer, whole rock layered structure—without arch in soil layer, whole rock single-layer structure—with soil arching, whole rock layered structure—with soil arching) the stress transfer mode, transfer size, and arching conditions of overlying strata in different areas. The mechanical system of abutment pressure calculation for typical overburden structure is established, which provides theoretical basis for mine optimization design scheme, mining sequence, and limited personnel distance.