基于数据驱动的铜闪速熔炼能效优化算法研究
Research on Energy Efficiency Optimization Algorithm for Copper Flash Smelting Process Based on Data-driven
Abstract
铜闪速熔炼工序具有多变量、非线性、大时滞、强耦合、生产波动大的特点,传统的基于机理模型的优化控制系统很难适应多变的运行条件,预测结果偏差较大,影响最终的控制效果。随着计算机技术的发展,复杂工业过程中积累了大量生产数据,为我们从人工智能的角度进行建模与优化控制提供了数据基础。 本论文以某大型闪速炼铜企业的闪速熔炼生产过程为研究对象。为了实现铜闪速熔炼工序中的节能减耗,本文提出了一种满足三大工艺指标(冰铜品位,冰铜温度,渣中铁硅比)约束的能效优化模型:首先,我们用最小二乘支持向量机对历史数据进行训练得到三大指标预测模型;然后,我们给出优化数学模型并以三大工艺指标为约束,用改进的粒子群优化算法对能... The characteristics of the copper flash smelting process include: multiple variable, nonlinearity, strong coupling, long delay and large fluctuations. With the development of computer technology and industrial automation, the complex industrial process has produced a large number of production data, which contains rich information for the mining of their patterns. In order to improve energy effi...