Optimization of Separating Iron and Zinc from BF Gas Sludge by BBD Method
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摘要:
针对高炉瓦斯泥中重要有价元素铁锌分离回收利用难问题，以优化高炉瓦斯泥加热自还原热工参数、实现铁锌良好分离为目的，开展了高炉瓦斯泥球团加热自还原的单因素实验以及响应曲面中的BBD(Box-Behnken Design)法设计的因素优化实验。铁锌还原分离效果以铁、锌的金属化率作为评价指标。结果发现：各热工参数对铁、锌氧化物还原分离影响程度为加热时间>温度>造球压力；铁锌还原分离优化的热工参数为1299.95℃、加热时间为47.05 min、造球压力为8 MPa。热工参数优化条件下的BBD法实验得到：球团还原过程中铁的金属化率达94.67%、锌的金属化率达96.08%，铁主要以金属铁形式留存于球团中，锌以气态单质锌进入烟尘，在烟尘中氧化成为ZnO，铁锌实现了良好的分离。
Abstract:In order to optimize the thermal parameters of BF gas sludge and realize the good separation of iron and zinc from the sludge, the single factor experiment of heating self reduction of the sludge pellet and that of factor optimization design by BBD (Box-Behnken Design) method in response surface were carried aiming at the problem difficult to separate and recover iron and zinc from the sludge. The metallization rate of iron and that of zinc are used as the evaluation index for the separation of iron and zinc. The results show that the influence of thermal parameters on the reduction and separation of iron and zinc oxides are time > temperature > pelleting pressure; the optimized conditions are1299.95℃, 47.05 min and 8 MPa of pelleting pressure. It is obtained by the optimization test of thermal parameters designed by BBD method that the metallization of iron and zinc reach to 94.67% and 96.08%, respectively, and iron is mainly retained in pellets in the form of metallic iron and Zinc enters into the dust as a gaseous element zinc and then oxidized to ZnO dust. Good separation of iron and zinc is achieved.
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Key words:
- BF gas sludge /
- Pellet /
- Self-reduction /
- Response surface methodology
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表 1 高炉瓦斯泥成分/%
Table 1. Composition of BF gas sludge
TFe FeO SiO2 Al2O3 CaO MgO C MFe V2O5 ZnO MnO TiO2 27.6 34.38 10.18 4.26 5.60 4.43 20.00 0.83 0. 23 3.1 0.28 5.40 
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表 2 单因素实验方案
Table 2. Single factor test program
T/℃ t/min 造球压力/MPa T/℃ t/min 造球压力/MPa T/℃ t/min 造球压力/MPa T/℃ t/min 造球压力/MPa 1300 65 8 1100 45 8 1200 45 8 1200 40 6 1300 55 8 1100 40 8 1200 40 8 1200 40 7 1300 45 8 1100 35 8 1200 35 8 1200 40 8 1300 35 8 1100 30 8 1200 30 8 1200 40 9 1300 25 8 1100 25 8 1200 25 8 1200 40 10 1300 20 8 1100 20 8 1200 20 8 - - -
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表 3 响应面法实验因数水平与编码值
Table 3. Actual and code values of variables
水平 温度 时间 造球压力 因子/% 代码 因子/min 代码 因子/MPa 代码 T A t B M C 1 1350 1 65 1 10 1 0 1225 0 37.5 0 8 0 −1 1100 −1 15 −1 6 −1 注: 
、
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表 4 响应面法实验方案及结果
Table 4. Matrix and results of RSM test
A B C Y1/% Y2/% A B C Y1/% Y2/% A B C Y1/% Y2/% −1 0 1 85.3 68.2 0 1 1 95.8 91.8 0 −1 1 85.2 40.5 0 0 0 93.6 70.44 0 0 0 92.8 72.4 0 0 0 91.3 78.4 1 −1 0 92.3 81.16 1 1 0 95.3 96.08 −1 −1 0 70.3 35.2 1 0 −1 95.3 90.96 0 1 −1 94.7 87.5 −1 0 −1 86.5 68.8 0 0 0 91.5 78.6 −1 1 0 94 89.2 0 0 0 90.1 72.4 0 −1 −1 84.8 36.4 1 0 1 92 90.48 - - - - -
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表 5 Y1的方差分析
Table 5. ANOVA on Y1
来源 平方和 df 均方根 F 值 P值 显著性 模型 607.7059 5 121.5412 50.04232 < 0.0001 ** A 188.18 1 188.18 77.47961 < 0.0001 ** B 278.48 1 278.48 114.659 < 0.0001 ** AB 107.1225 1 107.1225 44.1057 < 0.0001 * A2 18.90105 1 18.90105 7.782157 0.0176 * B2 13.16494 1 13.16494 5.42042 0.0400 * 余量 26.71645 11 2.428768 * 不适合 19.26445 7 2.752064 1.477222 0.3708 不显著 纯错误 7.452 4 1.863 合计 634.4224 16 注：P≤0.0001，为非常显著，用**表示；P≤0.05，为显著，用*表示；P>0.05，为不显著
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表 6 Y2的方差分析
Table 6. ANOVA on Y2
来源 平方和 df 均方根 F值 P值 显著性 模型 5718.685 5 1143.737 47.54295 < 0.0001 ** A 1182.925 1 1182.925 49.17191 < 0.0001 ** B 3668.818 1 3668.818 152.5057 < 0.0001 ** AB 381.8116 1 381.8116 15.87117 0.0021 * A2 276.876 1 276.876 11.5092 0.0060 * B2 235.1061 1 235.1061 9.772907 0.0096 * 余量 264.6261 11 24.05692 * 不适合 207.3161 7 29.61658 2.067111 0.2518 不显著 纯错误 57.31008 4 14.32752 合计 5983.311 16 注：P≤0.0001，为非常显著，用**表示；P≤0.05，为显著，用*表示；P>0.05，为不显著
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