浮选药剂智能优化设定控制方法的研究  

Research on flotation reagent intelligent optimal setting control method

作　　者：耿增显[1] 柴天佑[1,2] 岳恒[1,2] 

机构地区：[1]东北大学流程工业综合自动化教育部重点实验室,沈阳110004 [2]东北大学自动化研究中心,沈阳110004

出　　处：《仪器仪表学报》2008年第12期2486-2491,共6页Chinese Journal of Scientific Instrument

基　　金：国家自然科学基金重点项目(60534010);国家863计划(2006AA04Z179);教育部科学技术研究重大项目(308007);高等学校学科创新引智计划(B08015)资助项目

摘　　要：针对浮选过程精矿品位和尾矿品位与浮选药剂之间具有强非线性、不确定性,难以用精确数学模型来描述,常规控制方法难以给出药剂量优化设定值的难题,将建模与控制相结合,提出了浮选药剂智能优化设定控制方法。该方法将基于案例推理的单位药剂预设定模型、基于规则推理的反馈补偿模型有机集成,在工况发生变化时,能够自动调整浮选药剂量设定值,实现浮选药剂的优化控制。该方法已在某选矿厂浮选过程中成功应用,稳定了精矿品位和尾矿品位,降低了浮选药剂消耗,取得了显著的应用效果。The concentrate grade and the tailing grade have strong nonlinearity and uncertainty with flotation reagent feeding in their dynamic behaviors, which can hardly be described using accurate mathematical model. The optimal setting of flotation reagent feeding is difficult to be determined with conventional control method. So, a flotation reagent intelligent optimal setting control method is proposed innovatively, which comprises of a pre-setting model based on CBR （case based reasoning）, a feedback compensator based on RBR （rule based reasoning）. The control system automatically updates flotation reagent setting feeding when the boundary condition changes so as to realize the intelligent optimal control of the flotation reagent. Successful industrial application shows that the concentrate grade and the tailing grade have been stabilized, the consumption of the flotation reagent has been decreased. Significant application effect has been achieved.

关 键 词：精矿品位 尾矿品位 浮选药剂 案例推理 规则推理 优化设定 

分 类 号：TP29[自动化与计算机技术—检测技术与自动化装置]