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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
4 b" z8 P3 a$ R3 A3 r' K汪金良1 ,卢宏2 ,汪仁良3 ,曾青云1
* y; D$ t; F) w# s I(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 ;4 H: u& N- l) s! @4 N7 K% P# y
31 贵溪冶炼厂,江西贵溪335424)
& G" _+ \8 o/ b+ V. Q' S: P: J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2 s$ l- W. _8 u" L# d+ [4 s" c
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;4 a* o/ B3 F# i
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
; B9 g' ^8 i h3 h0 M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
: C& M5 b" n1 Q$ {4 i控制在110 ±012 ,自热熔炼应控制在1134 以上。
$ F* L- }- |. `" `6 Y( A关键词:神经网络;闪速熔炼;铜;因素+ {$ e. H5 t0 @. ?
中图分类号: TF811 文献标识码:A 文章编号:1007 - 7545 (2008) 02 - 0002 - 04
: J7 i9 @* r/ S2 h* `Analysis of the Effect Factors of Copper Flash Smelting
8 \% N) R8 }7 h! X+ C6 v+ nBased on Neural Network1 E' h0 {" U9 ~' s1 |; u
WAN GJ in2liang1 , LU Hong2 , WAN G Ren2liang3 , ZEN G Qing2yun13 I: K" G8 n; w
(11 Faculty of Material and Chemist ry Engineering , Jiangxi University of Science and Technology ," w; J* c! M: s- V3 z- c
Ganzhou 341000 , China ; 21 Faculty of Information Engineering , Jiangxi University of Science and Technology ,
" t' P9 r* ~, `7 ^- z5 UGanzhou 341000 , China ; 31 Guixi Smelter , Guixi 335424 , China)
0 B* w7 L l( ^0 _$ O2 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
$ l6 J7 M% ~8 Y3 J1 r S, Xement s content in copper concent rate on the copper flash smelting process are st udied based on the built
( i; I) V7 b) x3 L7 J/ D2 G0 wneural network model1 Result s show t hat the mat te grade reduces , t he matte temperat ure increases but t he! _7 V S9 A/ D$ V) S( {
Fe/ SiO2 in slag changes lit tle when t he oxygen grade increases ; the mat te grade , the mat te temperat ure
9 R8 B8 F0 K# T: C/ V* ~6 `! Wand t he Fe/ SiO2 in slag increase all when t he oxygen volume per ton concent rate increases ; t he Fe/ SiO2 in
5 R5 h! R' |- L% C1 @1 z! M6 y. T" Cslag drop s clearly when t he flux ratio increases ; t he increment of t he Cu content in concent rate makes t he- P4 p! O2 V; d) Y: Q, h- T
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! Z- T |2 V0 {1 t9 {0 V
posite to t he Cu content ; S/ Cu should be cont rolled f rom 018 to 112 generally , but more than 1134 for
( i* _2 h7 i x, o/ @( r# `( I! Iself2heat smelting1
' J. O/ f5 @; W! N, W' t! E; _Keywords :Neural network ; Flash Smelting ; Copper ; Factors |
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发表于 2009-7-20 17:43:03
