化工矿物与加工2026，Vol.55Issue(3)：69-78,10.DOI:10.16283/j.cnki.hgkwyjg.2026.03.009
浮选加药智能化控制技术研究进展
Research progress on intelligent control technology of flotation dosing
程贯瑞 1黄宋魏 1和丽芳 2吴丽萍 1何济帆 1唐浩珀 1李丹阳1
作者信息
- 1. 昆明理工大学 国土资源工程学院,云南 昆明 650093
- 2. 昆明理工大学 城市学院,云南 昆明 650051
- 折叠
摘要
Abstract
Dosing is the key link to realize the separation and efficient recovery of useful minerals in flotation process.Due to the variability of ore properties and the characteristics of multivariable,nonlinear,strong disturbance and time delay in the flotation process,the traditional dosing control method has obvious deficiencies in dynamic adapt-ability and control accuracy.In recent years,with the rapid development of computer vision,neural network and other technologies and their popularization and application in the field of mineral processing,flotation dosing control has accelerated to intelligent development.This paper summarizes the research status of control system architecture and working principle based on computer vision(CV)state perception and modeling support,intelligent optimization con-trol model construction based on artificial neural network(ANN),intelligent optimization control method based on fuzzy reasoning,intelligent optimization control method based on knowledge reasoning and intelligent optimization con-trol technology of flotation dosing.Constructing a closed-loop control system that integrates multi-modal perception,intelligent reasoning and adaptive optimization capabilities,and combining emerging technologies such as digital twin and reinforcement learning to realize the whole process perception and dynamic optimization of flotation dosing process is an important direction for future research on intelligent optimization control of flotation dosing.关键词
浮选加药/智能优化控制/计算机视觉/神经网络/数字孪生/强化学习Key words
flotation reagent dosing/intelligent optimization control/computer vision/neural networks/digital twin/reinforcement learning分类
信息技术与安全科学引用本文复制引用
程贯瑞,黄宋魏,和丽芳,吴丽萍,何济帆,唐浩珀,李丹阳..浮选加药智能化控制技术研究进展[J].化工矿物与加工,2026,55(3):69-78,10.
