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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
7 s3 \. g6 T& j2 u- v: k汪金良1 ,卢宏2 ,汪仁良3 ,曾青云14 O1 W3 w* k5 H# r
(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 J$ @/ p, i& M1 m* `: G. @31 贵溪冶炼厂,江西贵溪335424)$ e0 V0 {0 H% l' ^
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
# V' i1 t5 T5 E' j. ?0 q! h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;2 v3 x1 L$ {- R" S
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
$ g8 _: D7 \5 @+ o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9 |! s5 H( Y3 }
控制在110 ±012 ,自热熔炼应控制在1134 以上。
- S* s/ Q6 Y7 H3 x关键词:神经网络;闪速熔炼;铜;因素9 \, d' t- R" E4 W3 S
中图分类号: TF811 文献标识码:A 文章编号:1007 - 7545 (2008) 02 - 0002 - 046 ?, S0 {$ v) f- ? z6 c
Analysis of the Effect Factors of Copper Flash Smelting
+ m! i& g3 [ ?Based on Neural Network1 c& c# K& i2 w" S" @2 X: ^
WAN GJ in2liang1 , LU Hong2 , WAN G Ren2liang3 , ZEN G Qing2yun1. i/ ]+ k4 P5 O
(11 Faculty of Material and Chemist ry Engineering , Jiangxi University of Science and Technology ,
2 [+ p6 O1 T T* c- T/ u6 x0 {7 |. ^Ganzhou 341000 , China ; 21 Faculty of Information Engineering , Jiangxi University of Science and Technology ,
/ O9 I4 Q. v" y3 E- nGanzhou 341000 , China ; 31 Guixi Smelter , Guixi 335424 , China)
& Z; g5 y$ Z$ S' FAbstract :The effect s of t he oxygen grade , t he oxygen volume per ton concent rate , t he flux rate and t he el2
: X3 I0 ^5 h! v7 g% Xement s content in copper concent rate on the copper flash smelting process are st udied based on the built6 @: q5 {$ C- O* s
neural network model1 Result s show t hat the mat te grade reduces , t he matte temperat ure increases but t he* L O h7 R% R* o* H9 Y
Fe/ SiO2 in slag changes lit tle when t he oxygen grade increases ; the mat te grade , the mat te temperat ure
3 n8 l2 h1 Z: f' k9 c1 Mand t he Fe/ SiO2 in slag increase all when t he oxygen volume per ton concent rate increases ; t he Fe/ SiO2 in5 h1 x0 P: c, L+ L) \& Z
slag drop s clearly when t he flux ratio increases ; t he increment of t he Cu content in concent rate makes t he+ L3 ]& Y& L }% j( h2 u5 k3 K2 U
mat te grade increase but t he mat te temperature drop lit tle ; t he effect of the Fe content in concent rate is op2( L2 Z4 w% V, A$ q Y- ^' p* s3 C/ p
posite to t he Cu content ; S/ Cu should be cont rolled f rom 018 to 112 generally , but more than 1134 for. n% ]2 y4 }# O" y1 n% V
self2heat smelting1 l' S% f3 A; D" o8 y* i/ R
Keywords :Neural network ; Flash Smelting ; Copper ; Factors |
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发表于 2009-7-20 17:43:03
