Research on modeling and application of digital twin system for mine auxiliary transportation

The focus of this paper is to achieve the remote collaborative linkage and visual monitoring of the mine auxiliary transportation system. Aiming at the problems of high modeling difficulty, low accuracy and poor data correlation of the auxiliary transportation system, a modeling method of the mine auxiliary transportation system based on digital twin is proposed. The architecture of the mine auxiliary transportation system is built based on the five-dimensional model of digital twin, and research is conducted around four key technologies: geometric modeling, logical modeling, data hierarchical mapping, and data information fusion and matching. The multi-source data fusion modeling method is adopted, and the laser point cloud is combined with oblique photogrammetry to design a hybrid filtering algorithm to simplify the laser point cloud. An auxiliary transportation virtual model oriented to real physical behaviors is constructed after fusion and registration, and the accuracy of the model is verified. The extended stochastic advanced decision petri net model is designed to describe the interaction logic of the auxiliary transportation system. The hierarchical mapping system of the entire process of mine auxiliary transportation is constructed with the “Robot–Material–Environment” elements as the core, and the OPC UA architecture is adopted for data modeling and matching. Finally, through the actual auxiliary transportation system of a coal mine in Guizhou as an application case, a digital twin prototype system for auxiliary transportation is developed and a layered mapping software and hardware test environment is built to verify the proposed model and system. The results show that the average deviation of the local accuracy of the roadway model generated after processing the multi-source point cloud data with the hybrid filtering algorithm is 0.02 m. The auxiliary transportation twin system under hierarchical mapping visually and accurately presents the status and process of physical layer equipment, and the virtual–real linkage delay is 1 s. The reliability of the proposed method was verified through cases, effectively improving the working efficiency and safety performance of auxiliary transportation throughout the mine. The research results provide a new approach for the intelligent construction of the mine auxiliary transportation system.