Abstract: The key of improve the degree of coal mining automation and unmanned mining is to improve the coal and rock identification ability of shearer. On the basis of memory cutting,this study proposed a coal and rock identification method using grey prediction theory based on the force of idler shaft in shearer’ s ranging arm. The idler shaft stress was monitored in real-time when the shearer cut different cutting media,and the intelligent prediction system of shear- er’s cutting route was established according to the idler shaft stress,the cutting route was corrected in real-time. As a result,the tracking and adapt ability of the shearer was improved. The method was tested on the experiment platform in Zhangjiakou coal mine machinery factory. The result shows that the average stress of shearer with rock cutting is larger than coal cutting by 19. 45% . Thus,shearer is able to distinguish the interface between coal and rock.