基于响应面法的煤矸石氯化焙烧除铁工艺参数优化  

Optimization of process parameters for iron removal by chlorination roasting of coal gangue based on response surface methodology

作　　者：张雨涵 赵雪淞[1,2] 李婷婷 王雪松 张婷 ZHANG Yuhan;ZHAO Xuesong;LI Tingting;WANG Xuesong;ZHANG Ting(School of Mining,Liaoning Technical University,123000 Fuxin,China;College of Science,Liaoning Technical University,123000 Fuxin,China;Batang Company,Huadian Jinsha River Upstream Hydropower Development Company Limited,626700 Ganzi,China;School of Materials Science and Engineering,Liaoning Technical University,123000 Fuxin,China)

机构地区：[1]辽宁工程技术大学矿业学院,辽宁阜新123000 [2]辽宁工程技术大学理学院,辽宁阜新123000 [3]华电金沙江上游水电开发有限公司巴塘分公司,四川甘孜626700 [4]辽宁工程技术大学材料科学与工程学院,辽宁阜新123000

出　　处：《煤炭转化》2024年第1期81-90,共10页Coal Conversion

基　　金：2021年度辽宁省教育厅科学研究经费项目(LJKZ0328)。

摘　　要：为解决煤矸石氯化焙烧除铁过程中氯化剂消耗量过高、焙烧时间掌握不准以及除铁率难以达到期望值的问题,以CaCl_(2)作为氯化剂对煤矸石进行氯化焙烧除铁,在焙烧温度分别为600℃,700℃,800℃,900℃,1000℃,CaCl_(2)添加量(质量分数)分别为5%,10%,15%,20%,25%,焙烧时间分别为90 min,120 min,150 min,180 min,210 min的单因素实验基础上,通过Design-Expert13.0.6软件设计和优化了煤矸石氯化焙烧除铁实验。通过方差分析、等高线分析、响应面分析证明了模型的可靠并分析了各变量之间的交互影响关系。运用响应面优化法以除铁率为指标优化了工艺参数。结果表明:焙烧温度与焙烧时间交互最为显著,CaCl_(2)添加量与焙烧时间交互最低。各影响因子按影响显著性由大到小依次为焙烧温度、CaCl_(2)添加量、焙烧时间;随着焙烧温度升高除铁率进一步提升,由于焙烧温度超过1000℃后产物会转为莫来石,因此控制焙烧温度不超过950℃,当CaCl_(2)添加量达到15%时除铁率最好,超过这一添加量会降低除铁率,焙烧时间达到180 min时除铁率基本上达到了最高值,继续延长焙烧时间对除铁率的影响不大;对响应面模型预测并优化后得到了最佳的工艺条件,即焙烧温度为915℃,CaCl_(2)添加量为15%,焙烧时间为175 min,在此条件下除铁率达到了95.23%,实验值与预测值基本一致。To address issues such as excessive chlorinating agent consumption,inaccurate roasting time and unsatisfactory iron removal ratios,CaCl_(2) was used as chlorinating agent to remove iron from coal gangue in this paper.The single-factor experiments were conducted at various conditions,involving the chlorination roasting process at 600℃,700℃,800℃,900℃and 1000℃,CaCl_(2) added amount(mass fraction)ranging from 5%,10%,15%,20%,to 25%,and roasting time ranging from 90 min,120 min,150 min,180 min,to 210 min,respectively.Design and optimization of all iron removal experiments using chlorination roasting of coal gangue were conducted with the assistance of Design-Expert 13.0.6 software.The reliability of the model was validated through analysis of variance,contour analysis and response surface analysis,and the interaction relationships among various variables were also analyzed.The process parameters were optimized using the response surface optimization method,with the iron removal ratio serving as the index.The results show that the interaction between roasting temperature and roasting time has the most pronounced effect,while the interaction between CaCl_(2) added amount and roasting time has the least significant impact.The order of significance for the influence factors from large to small is as follows:roasting temperature,CaCl_(2) added amount,roasting time.The iron removal ratio continues to increase with an increase in the roasting temperature.Given the product transforms into mullite when the roasting temperature surpasses 1000℃,it is required to keep the roasting temperature below 950℃.When the addition of CaCl_(2) reaches 15%,the best iron removal ratio is achieved.Exceeding this amount will reduce the iron removal ratio.When the roasting time reaches 180 min,the iron removal ratio approaches its peak value.Further extending the roasting time has little effect on the iron removal ratio.The process conditions,determined through the prediction and optimization of the response surface model,are as fol

关 键 词：煤矸石 氯化焙烧 除铁率 响应曲面法 高岭土 

分 类 号：TD849.5[矿业工程—煤矿开采]