NOUFERROUS METALLURGICAL EQUIPMENT

This paper aiming at the working conditions of large ore blocks and easy jamming in the automatic loading process of unmanned rail transportation, constructs an ore block size recognition system based on the application design of machine vision library OpenCV and YOLO training model. The system can realize the functions of ore block size calculation, ore block size quantity and time distribution statistics, real-time alarm and query of super large blocks, etc., realize the detection and management of ore block size in the chute, ensure the safety of ore discharge equipment under the working conditions of unmanned rail transportation, and reduce the labor intensity of manual monitoring, providing reference for the implementation of unmanned mine system and digital transformation.