摘要
随着矿产资源日益稀缺与环保要求日趋严格,传统矿物检测方法已无法满足现代矿业需求。因此,研究聚焦于矿石成分分析、分类与检测、粒度检测三大核心技术,系统综述了光电成像技术、人工智能及多技术联用方法在矿物检测领域的应用现状,评估其优势与局限性,并展望未来发展趋势。研究内容涵盖了矿石成分分析技术的革新、几种主要的矿石分类与检测技术的发展及矿石粒度检测技术从传统方法到深度学习技术的优化。结果表明,现代技术显著提升了检测精度与效率,但仍存在环境适应性不足等问题。未来研究应聚焦多技术协同应用、轻量化模型构建及小样本学习策略,以推动智能矿山建设与资源合理开发。
With the increasing scarcity of mineral resources and the growing stringency of environmental requirements,traditional mineral detection methods can no longer meet the demands of modern mining.Therefore,this study focuses on three core technologies ore composition analysis,classification and detection,and particle size detection systematically reviewing the application status of optoelectronic imaging technology,artificial intelligence,and multi-technology integration methods in the field of mineral detection.It evaluates their advantages and limitations and explores future development trends.The research covers innovations in ore composition analysis techniques,the development of several major ore classification and detection technologies,and the optimization of ore particle size detection from traditional methods to deep learning technologies.The results demonstrate that modern technologies significantly improve detection accuracy and efficiency,though problems such as insufficient environmental adaptability remain.Future research should prioritize the synergistic application of multiple technologies,the construction of lightweight models,and few-shot learning strategies to advance the construction of smart mines and the rational exploitation of resources.
作者
龙益丹
Long Yidan(Chongqing Normal University,Chongqing,401331)
出处
《当代化工研究》
2025年第12期20-22,共3页
Modern Chemical Research
关键词
矿物检测
矿石成分分析
矿石分类分析
矿石粒度分析
mineral detection
analysis of ore composition
ore classification and analysis
analysis of ore particle size
