摘要
针对磨矿分级过程的关键工艺指标磨矿粒度难以用常规控制方法进行有效控制的难题,将智能设定方法与常规控制相结合,提出了基于案例推理的磨矿分级系统智能设定控制方法.以粒度指标的区间控制为目标,依据边界条件和运行工况等信息,由智能设定模型自动更新各基础控制回路的设定值,避免了人工设定的主观性及随意性,各控制回路跟踪更新的设定值,从而将粒度控制在目标范围内.该方法已成功应用于某赤铁矿选厂的磨矿分级过程,应用效果表明提出的方法是有效的.
Particle size is a key technical index in ore grinding-classification process, which is difficult to control effectively with conventional loop control strategies. An intelligent control setting approach based on CBR for the grinding-classification system is proposed by combining intelligent method with conventional loop control. Aiming at the interval control of the particle size index and according to the information on boundary conditions and current operating conditions, a model is .set intelligently to update automatically all the basic loop setpoints, thus avoiding the subjectivity and randomicity arising from arbitrary process control setting. Then, the outputs from control loops can track down the updated setpoints relevantly to control the particle size within the target zone. The approach proposed has successfully been applied to the grinding- classification process of a hematite ore processing plant, and its effectiveness is proved evidently.
出处
《东北大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2007年第5期613-616,共4页
Journal of Northeastern University(Natural Science)
基金
国家重点基础研究发展计划项目(2002CB312201)
国家自然科学基金重点资助项目(60534010)
国家创新研究群体科学基金资助项目(60521003)
长江学者和创新团队发展计划项目(IRT0421)
关键词
智能设定控制
案例推理
磨矿分级系统
磨矿粒度
区间控制
intelligent control setting
case-based reasoning （ CBR）
grinding-classification system
particle size
interval control
