The method of fully mechanized top-coal caving mining has become the main method of mining thick-seam coal. The process parameters of fully mechanized caving will affect the recovery rate and gangue content of top coal. Through numerical simulation software, the top-coal recovery rate and gangue content, under different fully mechanized caving process parameters, were simulated, and the influence law of different fully mechanized caving process parameters on top-coal recovery rate and gangue content was obtained. A decision model for top-coal caving process parameters was established with a BP neural network, and the optimal top-coal caving parameters were obtained for the actual situation of a working face. On this basis, a in-lab similarity simulation test of the particle material was carried out. The results show that the top-coal recovery rate and gangue content were 86.56% and 3.45%, respectively, and the coal caving effect was good. A BP neural network was used to study the decisions optimizing fully mechanized caving process parameters, which effectively improved the decision-making efficiency thereabout and provided a basis for realizing intelligent, fully mechanized caving mining.

Coal is an important resource for China and even for the whole world. With the improvement of mechanization, automation and intelligence of coal mining equipment in China, there has been an imbalance between the speed of mining and of excavating. Adopting efficient cutting paths is beneficial to improving roadway excavation efficiency and alleviating the imbalance between mining and excavation. In this paper, taking the 12307 belt roadway of Wangjialing Coal Mine as the research background, the geomechanical parameters and distribution characteristics of the surrounding rock were observed and studied, and the test results of in-situ stress, surrounding rock structure and surrounding rock strength were obtained. Based on the test results, a numerical model was established, and the stress and displacement distribution law of the surrounding rock of the roadway under different cutting paths were analyzed, and two optimal cutting paths were proposed based on the actual situation, and industrial tests were carried out. The test results show that using the “snake” cutting path from bottom to top, the roadway section forming effect is good, and a single cycle excavation takes 34 min, which verified the effectiveness of the cutting path design. On the basis of specific engineering geological conditions, excavation equipment and technology, combined with experimental testing, numerical simulation and other methods, the roadway excavation cutting path can be optimized, and the research results can provide a reference for the design of cutting paths for coal mine excavation roadways with the same geological conditions.

The accurate perception of straightness of a scraper conveyor is important for the construction of intelligent working faces in coal mines. In this paper, we propose a precision compensation model based on rotation error angle to improve the accuracy of the fiber Bragg grating (FBG) curvature sensor of a scraper conveyor. The correctness of the model is verified by theoretical analysis, numerical simulation, and experiments. Finally, the feasibility of the model is analyzed and discussed for field application in a coal mine. When the rotation error angle is within the range of 0~90°, according to the strain of FBG obtained by numerical simulation, the radius of the curvature is inversely calculated by the compensation model. The relative error of each discrete point is within ±0.9%, and the relative error after fitting is less than 0.2%. The experiment shows that the relative error of the curvature radius after fitting according to the theoretical formula is less than ±3%, and the relative error of the curvature radius value obtained by the inverse deduction of each discrete point is less than ±6%, which verifies the correctness and applicability of the compensation model. In addition, the compensation model with the FBG curvature sensor has broad application prospects in coal mine underground conveyors, submarine pipelines and ground pipelines.

Roadway excavation is the leading project in coal mining, and the cantilever roadheader is the main equipment in roadway excavation. Autonomous cutting by cantilever roadheaders is the key to realize safe, efficient and intelligent tunneling for underground roadways. In this paper, the working device of a cantilever roadheader was simplified into a series of translation or rotation joints, and the spatial pose model and spatial pose coordinate system of the roadheader were established. Using the homogeneous transformation matrix and the robot-related theory, the space pose transformation matrix of the roadheader and the space pose equation of the cutting head of the roadheader were derived. The forward kinematics and inverse kinematics of the cutting head were solved by using the D-H parameter method and an inverse transformation method. The location coordinates of the inflection point of the cutting process path for a rectangular roadway were determined, and cutting path planning and control were carried out based on the inflection point coordinates. Finally, MATLAB software was used to simulate the limit cutting area of the cutting head and the cutting process path. The simulation results showed that the limit cutting section had a bulging waist shape, the boundary around the roadway was flat, and the roadway cutting error was controlled within 1mm, which verified the reliability and effectiveness of the autonomous cutting theory of the roadheader. It lays a mathematical model and theoretical foundation for the realization of “autonomous operation of unmanned tunneling equipment”.

A cantilever roadheader is the main tunneling equipment for underground coal mine roadways. The key to the safe, efficient and intelligent development of coal enterprises is to achieve the autonomous cutting and intelligent control of the cantilever roadheader. In order to realize the automatic cutting shaping control of a large-section coal roadway, the path planning and control method of secondary automatic cutting of a cantilever roadheader were studied. The Wangjialing 12307 belt roadway was used as the engineering background, the vertical displacement law of the roadway roof under different cutting paths was simulated with the FLAC 3D software, the reasonable cutting path was determined according to the actual situation, and the underground industrial test was carried out. The simplified model and spatial position and attitude coordinate system of the roadheader were established, the kinematics of the roadheader was analyzed, and the position and attitude expression of the cutting head center in the roadway coordinate system was obtained. The simplified model of the cutting head was established, the position expression of the pick in the roadway coordinate system was derived, the position coordinate of the inflection point and the cutting step distance were determined according to the relationship between the cutting head and the roadway boundary, and the cutting path control flow was designed. Finally, the reliability of the cutting path control method was verified with a MATLAB simulation. The research works provide a theoretical foundation for path planning and control to realize “secondary autonomous cutting of cantilever roadheader”.