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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
: ~! ^0 b# i" ~4 r' ~/ e5 i汪金良1 ,卢宏2 ,汪仁良3 ,曾青云1
: |& \# N5 M' x; D(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 ;9 _) G/ P, R3 _. L/ d, z4 g
31 贵溪冶炼厂,江西贵溪335424)
' @7 ~/ u) t" c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
$ `: J9 u0 G- |7 ^5 E' ?+ R% u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; Y" G8 H2 ?7 N0 [
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1 `/ Y4 W/ d; f* l
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- q/ b' R& K j5 w9 `0 V
控制在110 ±012 ,自热熔炼应控制在1134 以上。9 m v+ l6 [6 Y9 U1 e, _7 M" m e
关键词:神经网络;闪速熔炼;铜;因素
; t* a* a) d; W0 G$ R中图分类号: TF811 文献标识码:A 文章编号:1007 - 7545 (2008) 02 - 0002 - 04
! B- | C+ U3 DAnalysis of the Effect Factors of Copper Flash Smelting+ `9 n, E8 \4 O$ t9 Q
Based on Neural Network
6 ~/ ]( A# L' P7 ?3 W) KWAN GJ in2liang1 , LU Hong2 , WAN G Ren2liang3 , ZEN G Qing2yun1! ~, Y. s/ u4 [5 D! ]- ^& {
(11 Faculty of Material and Chemist ry Engineering , Jiangxi University of Science and Technology ,
! A! s- O* F j- l% o: g' K* IGanzhou 341000 , China ; 21 Faculty of Information Engineering , Jiangxi University of Science and Technology ,
; v; K1 w' u5 ^1 q" FGanzhou 341000 , China ; 31 Guixi Smelter , Guixi 335424 , China)5 b/ u) f' S0 h& t& ~
Abstract :The effect s of t he oxygen grade , t he oxygen volume per ton concent rate , t he flux rate and t he el2- u; f7 i" ?5 m; I3 S- p9 y
ement s content in copper concent rate on the copper flash smelting process are st udied based on the built
$ {' `1 E% Z5 Z3 |2 q9 Wneural network model1 Result s show t hat the mat te grade reduces , t he matte temperat ure increases but t he
8 p. d: e/ g, U9 rFe/ SiO2 in slag changes lit tle when t he oxygen grade increases ; the mat te grade , the mat te temperat ure4 A$ f Y) M; L1 P. L
and t he Fe/ SiO2 in slag increase all when t he oxygen volume per ton concent rate increases ; t he Fe/ SiO2 in
& ~- G8 f0 G* {0 q7 r$ m `9 @9 Islag drop s clearly when t he flux ratio increases ; t he increment of t he Cu content in concent rate makes t he: T* x5 G/ v( `6 u' X
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- Y; v" J6 Z+ b7 U# b" P8 T
posite to t he Cu content ; S/ Cu should be cont rolled f rom 018 to 112 generally , but more than 1134 for, _9 B4 [2 p- j# R H L: |" P! F# D
self2heat smelting1
9 p0 M1 k' h4 m$ ^0 iKeywords :Neural network ; Flash Smelting ; Copper ; Factors |
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发表于 2009-7-20 17:43:03
