摘要
精矿品位是反映浮选过程的一项重要经济技术指标,而在浮选过程中精矿品位一直难以得到快速精确的测量,从而影响着浮选过程的优化与控制。综述了近年来国内外对于浮选过程精矿品位软测量技术的研究现状,着重介绍了基于回归分析、神经网络和支持向量机等软测量建模方法,并对软测量技术在精矿品位预测中的应用前景进行了展望。
The concentrate grade is an important economical index reflecting the performance of flotation process, while the concentrate grade is hard to realtime measure exactly and rapidly, which affects the optimization and control of the flotation process. The paper summarized the soft sensing technology for estimation of concentrate grade in process of flotation over recent years at home and abroad; and stressed the modeling method for soft sensing technology based on regression analysis, neural network and support vector machine. It also prospected the application of soft sensing technology to estimation of concentrate grade.
出处
《矿山机械》
北大核心
2013年第8期8-12,共5页
Mining & Processing Equipment
基金
中央高校基本科研业务费专项资金资助项目(2012LWB22)
关键词
精矿品位
软测量
浮选过程
回归分析
神经网络
支持向量机
： concentrate grade
soft sensing
flotation process
regression analysis
neural network
supportvector machinemachine
