Optimization and simulation of adaptive mining cutting path in complex undulating coal seam

Adaptive cutting planning of shearer based on the fluctuation of coal seam is one of the key problems to realize intelligent unmanned mining in coal mine. However, the adaptability of existing shearer cutting planning scheme considering the changes of complex geological conditions is relatively weak. Aiming at the problems of incomplete consideration of coal seam distribution information characteristics, lack of appropriate shearer cutting path planning model for different undulating conditions and poor continuous planning accuracy in fully mechanized coal mining faces, an adaptive cutting path optimization model for complex undulating coal seams is proposed. Firstly, the time series prediction model of shearer drum height is established based on particle swarm optimization least squares support vector machine, which can realize accurate and advanced prediction of shearer drum height. Then, the optimization models of adaptive cutting path planning for fully mechanized working face under near horizontal condit