矿石品位在线检测技术发展研究

Development of Online Detection Technologies for Ore Grade

矿石品位是衡量矿产经济价值的核心指标,相应在线检测能力事关矿山企业经济效益、环境影响和生产智能化水平。本文论述了矿石品位在线检测技术的应用价值及分类情况,从放射性检测、光学检测、电磁检测、机器视觉检测等技术方向出发,梳理了矿石品位在线检测技术研究与应用进展;辨识了相关技术发展面临的挑战,涵盖技术研究层面的精度瓶颈与干扰因素、信号解析与优化难题、模型构建与数据依赖关系,实际应用层面的辐射安全与成本效益考量、适应多样矿石特性的技术突破、恶劣环境下稳定运行与即时反馈。进一步阐述了矿石品位在线检测技术未来发展方向,包括多模态融合与智能感知技术前沿探索、智能感知与数据处理算法迭代升级、微型化/远程化/智能化设备研发、实时动态监测网络系统构建与优化等关键技术攻关突破内容,深度学习促进微观与宏观特征融合分析、量子计算与生物启发算法、智能传感器网络与物联网技术等新兴技术前瞻探索内容。建议在技术创新与设备升级、标准制定与规范建设、“产学研用”合作机制深化、人才培养与队伍建设、国际合作与资源共享等方面积极行动,以矿石品位在线检测技术提升促进矿产资源开发利用的智能化、高效化发展。

The ore grade is a core indicator for measuring the economic value of minerals,and its online detection capability is related to the economic benefits,environmental impact,and production intelligence level of a mining enterprise.This study discusses the application value and classification of online detection technologies for ore grade and summarizes the research and application progress of these technologies in terms of the following technical directions:radioactive,optical,electromagnetic,and machine-vision detection.Challenges faced by the development of related technologies are identified at the technical research and practical application levels.Challenges at the technical research level include(1)accuracy bottlenecks and interference factors,(2)difficulties in signal analysis and optimization,and(3)model construction and data dependency.Challenges at the practical application level include(1)radiation safety and cost-effectiveness,(2)technological breakthroughs adapted to diverse ore characteristics,and(3)stable operation and real-time feedback in harsh environments.The study further elaborates on the future development directions of online detection technologies for ore grade.Future efforts should focus on breakthroughs in exploring the forefront of multimodal fusion and intelligent perception technologies,iterating and upgrading intelligent perception and data processing algorithms,developing miniaturized/remote/intelligent equipment,and constructing and optimizing real-time dynamic monitoring network systems.Moreover,emerging technologies,such as deep learning for promoting the fusion analysis of micro and macro features,quantum computing and bioinspired algorithms,as well as intelligent sensor networks and the Internet of Things technology,are summarized.Furthermore,active actions are recommended in the following aspects:(1)technological innovation and equipment upgrading,(2)standards formulation and standardization construction,(3)deepening of the industry-education-research-application cooperation mechanism,(4)talent cultivation and team building,and(5)international cooperation and resource sharing,thereby promoting the intelligent and efficient development and utilization of mineral resources.