Development of key technologies for intelligent recognition and sorting of ore and rock based on machine vision
基于机器视觉的矿岩智能识别与分选关键技术开发

摘要

矿岩智能分选是矿物加工领域的重要环节，传统方法存在效率低、精度差等问题。本文开发了基于机器视觉的矿岩智能识别与分选系统，通过构建高性能图像采集系统和深度学习算法，实现了矿岩的高精度识别。系统集成自动化控制技术，完成矿岩的自动分选。实验表明，该系统分选精度提高30%以上，效率提升50%，显著降低了成本，为矿物加工行业的智能化发展提供了有力支持。

Abstract

Intelligent sorting of ore and rock is a crucial process in the field of mineral processing. Traditional methods suffer from low efficiency and poor accuracy. This paper presents the development of an intelligent recognition and sorting system for ore and rock based on machine vision. By constructing a high-performance image acquisition system and employing deep learning algorithms, the system achieves high-precision recognition of ore and rock. Integrated with automated control technology, the system completes the automatic sorting of ore and rock. Experiments show that the system increases sorting accuracy by more than 30% and improves efficiency by 50%, significantly reducing costs. This provides strong support for the intelligent development of the mineral processing industry.