神经网络遗传算法在氯碱生产过程中的应用  

Application of neural network genetic algorithm in chlor-alkali production

作　　者：马浩天 杨友良 马翠红 王禄 MA Haotian;YANG Youliang;MA Cuihong;WANG Lu(College of Electrical Engirleering,North China University of Science and Technology,Tangshan 063200,China)

机构地区：[1]华北理工大学电气工程学院,河北唐山063200

出　　处：《氯碱工业》2019年第2期18-21,共4页Chlor-Alkali Industry

摘　　要：对氯碱产业而言,氯碱电解槽的电解一直是其主要能耗。笔者用BP基于神经网络遗传算法的方法对氯碱电解槽的电解效率进行优化,并在某厂3万t/a烧碱离子膜车间的电解效率进行试验。优化之前,该电解槽电流效率为92.75%;利用神经网络遗传算法优化后,电流效率达到93.36%,带来的经济效益可达200万元/a。In chlor -alkali industry,energy is mainly consumed in the electrolysis of chlor -alkali electrolyzers.The authors use BP neural network genetic algorithm to optimize the electrolysis efficiency of chlor -alkali electrolyzcrs and conduct experiments in a 30 000 t/a ion-exchange membrane caustic soda plant.Before optimization,the current efficiency of the electrolyzers was 92.75%.After optimization by using neural network genetic algorithm,the current efficiency reaches 93.36%,creating 2 million yuan of economic benefit per year.

关 键 词：氯碱 神经网络建模 遗传算法 电解 

分 类 号：TQ114.262[化学工程—无机化工]