期刊文献+

基于遗传算法的预焙铝电解槽操作参数优化研究

A study of Optimization of Processing Parameters of Prebaked Cell for Aluminum-Reduction Based on Genetic Algorithm
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摘要 对预焙槽炼铝生产而言,电流效率很大程度上取决于操作参数的合理配置,取得稳定的高电流效率可以降低电能消耗;以铝电解槽电流效率最大为优化目标,选取影响电流效率的6类重要操作参数:槽电压、电解质温度、铝水平、电解质水平、分子比、氟化铝料量为优化变量,建立了铝电解槽操作参数的优化模型;采用遗传算法,获得了最优参数解,并在我国某厂200kA预焙铝电解槽上进行实验,指导生产;实验结果表明,电流效率由平均92.5%提升至93.5%。 Abstract: As far as the yield in prebaked cell for aluminum--reduction, steady and high current efficiency largely depends on rational configuration of processing parameters. In this study, the current efficiency of the aluminum reduction cell was regarded as optimization ob- jective . Six important processing parameters, which influence the current efficiency highly, were optimization variables, including cell volt- age, electrolysis temperature, molecular ratio, electrolyte height, aluminum level and the dosing of aluminum fluoride. The optimization model of operation parameters was developed. The optimal parameters were obtained by the genetic algorilhm. After the model of parameter optimization was used in a 200 kA prebaked cell for aluminum--reduction in China, the current efficiency rose from 92. 5 % to 93..5
出处 《计算机测量与控制》 CSCD 北大核心 2012年第7期1849-1850,1885,共3页 Computer Measurement &Control
基金 中央高校基本科研业务费与湖南省科技计划重点(2011GK2017)
关键词 预焙铝电解槽 电流效率 遗传算法 参数优化 prebaked ceil for aluminum-- reduction current efficiency genetic algorithm parameter optimization
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