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多元回归综合优化碳化硅超细粉球团变温干燥工艺

  • 李军 许树栋 张红超 王露 李朋
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  • 中国矿业大学(北京)化学与环境工程学院,北京 100083

收稿日期: 2017-01-13

  修回日期: 2017-03-06

  网络出版日期: 2017-06-14

Multi-variable Regression Analysis Applied to Process Optimization of Variable Temperature Drying on SiC Ultra-fine Powder Pellets#br#  

  • Jun LI Shudong XU Hongchao ZHANG Lu WANG Peng LI
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  • School of Chemical and Environmental Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China

Received date: 2017-01-13

  Revised date: 2017-03-06

  Online published: 2017-06-14

摘要

采用先高温后低温的变温干燥工艺降低碳化硅超细粉球团的干燥成本,以干燥时间和单位能耗为指标,以变温干燥的前期温度、前期风速、转换干基含水率、后期风速和后期温度为主要影响因素进行了L16(45)正交实验,研究了变温干燥工艺,并结合多元回归,根据多指标权重进行线性加权和优化. 结果表明,最佳优化变温干燥工艺参数为前温期度200℃、前期风速0.83 m/s、转换干基含水率5%、后期风速1.78 m/s、后期温度140,该条件下干燥时间为203 min,单位能耗为65 MJ/kg.

本文引用格式

李军 许树栋 张红超 王露 李朋 . 多元回归综合优化碳化硅超细粉球团变温干燥工艺[J]. 过程工程学报, 2017 , 17(3) : 600 -604 . DOI: 10.12034/j.issn.1009-606X.217114

Abstract

To reduce drying cost of the SiC ultra-fine powder pellets, variable temperature drying technology which had higher temperature at first and lower temperature afterwards was put forward. The temperature and wind velocity in the early and later period, together with conversion moisture content, were the main influencing factors during this process. These factors were studied by the L16(45) orthogonal experiment which using drying time and unit energy consumption as drying indexes. Multi-variable regression model combined with the weight value of each indexes were also used to fit the design conditions. The optimal parameters of variable temperature drying process were as follow: the temperature in the early period was 200℃, the wind velocity in the initial stage was 0.83 m/s, the transforming dry basis moisture content was 5%, the wind speed in the later period was 1.78 m/s, and the temperature in the later period was 140℃. Under these conditions, the drying time was 203 min and unit energy consumption was 65 MJ/kg.

参考文献

[1] 焦梦瑶.中国碳化硅行业国际竞争力状况研究[D].开封:河南大学,2013:1-10.
JIAO M Y. The Study on International Competitiveness Status of Chinese Silicon Carbide Industry[D]. Kaifeng: Henan University, 2013:1-10.
[2] 杨怀春,马进国,姜国才等.碳化硅对转炉炼钢脱氧合金化的影响分析[J].新疆钢铁,2014,2:43-45.
YANG H C;MA J G;JIANG G C;Xinjiang Bayi Iron&Steel Stock[J]. 2014,2:43-45.
[3] 万福祥,何刚,程维和等.碳化硅在电炉熔炼上的应用[J].金属加工,2010,5:63-64.
WANG F X,HE G,CHENG W H. The Application of SiC on Electric Furnace Smelting[J], MW Metal Forming,2010,5:63-64.
[4] 江思佳,刘启觉.稻谷变温干燥工艺研究[J].粮食与饲料工业,2009,2:10-12.
JIANG S J, LIU Q J. Variable Temperature Drying of Rice[J]. Cereal & Feed Industry,2009,2:10-12.
[5] 王庆惠,李忠新,杨劲松等.圣女果分段式变温变湿热风干燥特性[J].农业工程学报,2014,3:271-276.
WANG Q H,LI Z X,YANG J S.Dried characteristics of cherry tomatoes using temperature and humidity by stages changed hot-air drying method[J]. Transactions of the Chinese Society of Agricultural Engineering, 2014,3:271-276.
[6] 吴中华,李文丽,赵丽娟等.枸杞分段式变温热风干燥特性及干燥品质[J].农业工程学报,2015,11:287-292.
WU Z H,Li W L,ZHAO L J. Drying characteristics and product quality of Lycium barbarum under stages-varying temperatures drying process[J]. Transactions of the Chinese Society of Agricultural Engineering, 2015, 11: 287-292.
[7] 郭晓龙,肉孜?阿木提.小白杏变温干燥的试验研究[J].农产品工程,2015,4:52-53.
GUO X L, ROUZI?AMUTI. Experimental Study on Temperature Variable Drying of Little White Apricot. Agrifood engineering, 2015,4:52-53.
[8] 张玮,龚金红,张学农等.多元回归综合优化去甲基斑蝥素壳聚糖纳米粒的制备工艺[J].中国药学杂志,2008,43(15):1162-1166.
ZHANG W,GONG J H,ZHANG X N.Multi-Variable Regression Analysis Applied to Synchronously Optimize Preparation of Nanoparticles[J]. Chinese Pharmaceutical Journal, 2008, 43(15): 1162-1166.
[9] 李卫江,郭晓汾,张毅等.基于Matlab优化算法的物流中心选址[J].长安大学学报(自然科学版),2006,3:76-79.
LI W J, GUO X F, ZHANG Y. Logistics Center Location Based on Matlab Optimization Algorithm[J]. Journal of Chang’an University(Natural Science Edition),2006,3:76-79.
[10] 吴银亮,陈林,郭礼波.基于非线性Fmincon法的抗滑桩优化设计[J].铁道建筑,2011,5:81-84.
WU Y L, CHEN L, GUO L B. Optimum Design on Anti-slide Pile Based on Fmincon nonlinear method[J]. Railway Engineering, 2011,5:81-84.
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