基于粒子群算法的金矿湿法冶金浸出率优化  

Optimization based on particle swarm algorithm for leaching rate of gold hydrometallurgy process

作　　者：袁青云[1] 王福利[1,2] 何大阔[1,2] 吴畅[3] 

机构地区：[1]东北大学信息科学与工程学院,辽宁沈阳110819 [2]东北大学流程工业综合自动化国家重点实验室,辽宁沈阳110819 [3]东北财经大学,辽宁大连116025

出　　处：《化工学报》2015年第7期2595-2600,共6页CIESC Journal

基　　金：国家自然科学基金项目(61374146;61374147);国家高技术研究发展计划项目(2011AA060204);国家重点基础研究发展计划项目(2009CB320601);上海市委科研计划项目(13dz1201700)~~

摘　　要：各浸出率的合理分配对组织金矿湿法冶金浸出过程生产具有重要作用,当前各浸出率通常由精炼厂氰化车间工程师凭人工经验给出,导致对浸出过程生产的指导具有很大的模糊性与随意性,不能保证调整后的总浸出率最大。为优化确定金矿湿法冶金各浸出率,建立以总浸出率最大为目标的优化模型,并将二阶振荡粒子群算法用于模型的求解。最后通过实验研究验证了模型和算法的有效性。Rational allocation of leaching rates is significant for the organization of leaching process production. Generally, each leaching rate is given by engineers with the help of their experiences, which makes the supervision of leaching process production with a large extent of fuzziness and randomness, and it does not guarantee that the adjusted total leaching rate is the maximum. In order to determine the optimal leaching rate of gold hydrometallurgy process, an optimization model is established with maximizing the total leaching rate of hydrometallurgy process as the goal. And the second-order oscillating particle swarm algorithm is applied to solve the model. Finally, an experimental research demonstrates the effectiveness of the established model and algorithm.

关 键 词：金矿湿法冶金 氰化浸出 浸出率 优化模型 粒子群算法 

分 类 号：TP9[自动化与计算机技术]