Case Analysis of Applications for Deep Learning Technology in the Mining Industry

Abstract

Applications for deep learning technology in the mining industry were investigated to utilize deep learning technology in the domestic mining field. Deep learning is specialized in abstracting high-dimensional nonlinear problems, such as geological problems. The author investigated the applications of deep learning technology for mining cycle that is divided into investigation, exploration, development, mine operation, and disaster analysis. In the survey and exploration phase, a number of studies have been proposed to carry out mineral potential mapping by integrating geochemical and geophysical explorations, geological maps, fault lines, and topographic information. In the mine development and management phase, studies on autonomous situation detection, automatic calculation, and equipment control were carried out using mine status data measured by sensors or cameras. The hazard analysis phase was mainly used for status awareness and hazard prediction. In order for deep learning technology to be effectively utilized in the domestic mining field, relevant domestic research is required.