Abstract: It is very difficult to automatically identify the current process during the intelligent construction of coal mine drill rigs. In response to this, an operation process identification method was proposed, which includes hierarchical modeling of drill rig operation and probability inference of process execution. Firstly, the coupling process among the components of different granularity during the operation of drill rig is described and modeled based on the hierarchical analysis method, which reveals the interactive characteristics between equipment, function and system during the execution of each process. Secondly, Bayesian probabilistic reasoning method is introduced based on the above research to establish a process execution probability inference model, and the causal relationship between the attribute of the components of different granularity and the process status during the operation of drill rig is analyzed. Then, the collected sensing data is processed and provided as real-time evidence for the process identification model, thereby obtaining the execution probability of each drilling process by inference. Finally, the number of current executed process was inferred by the process identification method proposed herein, taking the hydraulic pressure value, the rotational speed and the movement speed of the drilling head during the operation process of ZDY23000LDK drill rig as the input. The experimental results show that the identification accuracy of the make-up process, drilling process and pull-out process reaches 85.3%, 81.2% and 87.1%, respectively, proving that the proposed identification method is feasible and practical. The above research provides a hierarchical decoupling method for the operation processes of drill rig and an analysis method for the interaction process between components of different granularity of drill rigs, providing technical support for the research on intelligent control methods of drill rigs and the development of advanced intelligent geological equipment.