Abstract: In response to the problems of untimely and inaccurate coal-rock interface recognition and lack of appropriate technical means during the construction of cross-seam drilling for gas drainage by bottom drainage roadway, a coal-rock interface recognition system based on drilling parameters (rotational speed, rotary torque, propulsion force, advance velocity, crushing work ratio) was developed. The entire system consists of a data sensing layer, a data acquisition layer and a data analysis layer. Among them, the data sensing layer and the data acquisition layer are also collectively called the drilling data acquisition system, which can collect the drilling parameters in real time. The data analysis layer performs the data learning and model training for the drilling parameters with coal or rock classification labels using the Support Vector Machine (SVM) classification algorithm, then classifies and predicts the unknown drilling parameters, and ultimately achieves the automatic recognition of coal-rock interface. The field application of Zhongtai Mining in Hebi, Henan shows that: the rotary torque, advance velocity and crushing work ratio fluctuate significantly at the coal-rock interface, and thus they can be regarded as the three characteristic parameters to distinguish the coal and rock. The SVM classification model using linear kernel functions can accurately distinguish the drilling parameters in the two types of formations. By learning from the 89 sample data in the training set, a 100% accuracy rate can be obtained in the test set, which also indicates that the characteristic parameters and the formation information are linearly separable. Generally, the promotion and application of this system can not only provide a way to obtain the basic data for coal-rock classification and identification, but also provide certain scientific basis and guidance for the identification of coal-rock interface recognition in cross-seam drilling, thereby ensuring the standardized drilling and avoiding the occurrence of unproductive zones.