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发表于 2009-7-21 15:24:58
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来自： 中国河南郑州
有色金属(冶炼部分) 2008 年2 期
6 p8 n5 r/ B! S汪金良1 ,卢宏2 ,汪仁良3 ,曾青云1; O N2 O3 T- y2 I, n/ S+ Q
(11 江西理工大学材料与化学工程学院,赣州341000 ;21 江西理工大学信息工程学院,赣州341000 ;
3 E8 X5 p* l9 }4 ^31 贵溪冶炼厂,江西贵溪335424)
2 g* z1 E, o; a# z' V5 A摘要:基于已建立的神经网络模型,研究了富化率、吨矿氧量、熔剂率以及铜精矿主要成分对铜闪速熔炼" m# Q' P2 j* J
过程的影响。结果表明:富化率的增大会使铜锍品位降低、铜锍温度升高,而对渣含Fe/ SiO2 影响不大;
. X) i1 g/ }, Y/ E& y W6 ^$ p吨矿氧量的增加会使铜锍品位、铜锍温度及渣含Fe/ SiO2 都升高;熔剂率的增加会使渣含Fe/ SiO2 明显# p2 M [! P/ x2 P3 W! x
下降;精矿中Cu 含量的增大会使铜锍品位升高,铜锍温度稍微降低;而Fe 的影响与Cu 相反;S/ Cu 一般
; |+ T8 J" O t/ }" `控制在110 ±012 ,自热熔炼应控制在1134 以上。3 W6 j- B& b; @$ Z
关键词:神经网络;闪速熔炼;铜;因素' w9 N: h. x+ X. a/ ~5 j
中图分类号: TF811 文献标识码:A 文章编号:1007 - 7545 (2008) 02 - 0002 - 04
) @1 f& Z4 ?2 i( N5 } HAnalysis of the Effect Factors of Copper Flash Smelting3 B ~2 c- D& @, d7 A3 n( l- t
Based on Neural Network
; }/ R7 J+ M& g) jWAN GJ in2liang1 , LU Hong2 , WAN G Ren2liang3 , ZEN G Qing2yun1
9 H+ ^3 P0 @ \7 W1 E, ]( m* _(11 Faculty of Material and Chemist ry Engineering , Jiangxi University of Science and Technology ,
1 f4 ^! o1 U% O6 N. L* r& q v! NGanzhou 341000 , China ; 21 Faculty of Information Engineering , Jiangxi University of Science and Technology ,, {4 Z- X p5 B
Ganzhou 341000 , China ; 31 Guixi Smelter , Guixi 335424 , China)
: P5 b$ x+ I1 T0 R/ gAbstract :The effect s of t he oxygen grade , t he oxygen volume per ton concent rate , t he flux rate and t he el2
, G+ T3 R5 f9 Oement s content in copper concent rate on the copper flash smelting process are st udied based on the built+ ?- l8 r2 l0 K4 g1 O. P
neural network model1 Result s show t hat the mat te grade reduces , t he matte temperat ure increases but t he
, @1 y, S4 \4 T7 R. r" }8 l/ f! tFe/ SiO2 in slag changes lit tle when t he oxygen grade increases ; the mat te grade , the mat te temperat ure
; y/ b( B9 ?2 |+ S+ G! c# |7 A( Xand t he Fe/ SiO2 in slag increase all when t he oxygen volume per ton concent rate increases ; t he Fe/ SiO2 in
8 H! Z" t1 B( u" eslag drop s clearly when t he flux ratio increases ; t he increment of t he Cu content in concent rate makes t he
V- W. {4 |2 @3 s& Cmat te grade increase but t he mat te temperature drop lit tle ; t he effect of the Fe content in concent rate is op25 S- y0 x- B! z6 I' c; w
posite to t he Cu content ; S/ Cu should be cont rolled f rom 018 to 112 generally , but more than 1134 for
' O' O6 K" L7 O4 Kself2heat smelting1. m! P; j" n% |" T! L+ b
Keywords :Neural network ; Flash Smelting ; Copper ; Factors |
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发表于 2009-7-20 17:43:03
