An integrated prediction model of cobalt ion concentration based on oxidation-reduction potential
An integrated prediction model of cobalt ion concentration based on oxidation-reduction potential
复制标题
基于氧化还原电位的钴离子浓度综合预测模型
DOI：
10.1016/j.hydromet.2013.09.015
复制
发表时间：
2013-11-01
期刊：
影响因子：
4.7
通讯作者：
Yang, C. H.
中科院分区：
文献类型：
--
作者：
Sun, B.;Gui, W. H.;Yang, C. H.
除钴是湿法炼锌中的一个重要步骤，在湿法炼锌过程中加入锌粉和催化剂，使钴离子逐渐脱除。除钴工艺的合理运行需要对钴离子浓度进行在线检测，这反映了除钴工艺的现状。本文的目的是建立一个能够在线预测钴离子浓度的模型。在机理研究的基础上，建立了动力学模型。应用电极反应动力学，将可在线检测的氧化还原电位引入动力学模型。动力学模型显示出令人满意的跟踪能力，但精度有限。为了克服精度上的局限性，提出了一种数据驱动的补偿方法，并将其与动力学模型相结合。测试结果表明，所提出的综合模型能够及时准确地预测出口钴离子浓度。(C)2013爱思唯尔B.V.保留所有权利。
Cobalt removal is an important step in zinc hydrometallurgy, in which by adding zinc dust and catalyzer, cobalt ion is gradually removed. Reasonable operation of cobalt removal process requires online detection of cobalt ion concentration, which indicates the current state of cobalt removal. The aim of this paper is to build a model capable of predicting cobalt ion concentration online. A kinetic model was built based on a mechanism study. ORP (oxidation-reduction potential), which can be detected online, was introduced into the kinetic model by applying the kinetics of electrode reaction. The kinetic model shows satisfying tracking ability but limited accuracy. To overcome the limitation in accuracy, a data-driven compensation method was proposed and integrated with the kinetic model. Test results show that the proposed integrated model can provide an accurate prediction of outlet cobalt ion concentration in time. (C) 2013 Elsevier B.V. All rights reserved.