不同处理工艺钢渣的X射线衍射和X射线荧光光谱分析及其活性指数预测模型

以不同处理工艺钢渣，即转炉热泼渣、转炉滚筒渣、铸余渣、铁水脱硫渣、电炉热泼渣和电炉滚筒渣作为研究对象。利用X射线衍射仪和X射线荧光光谱分析仪研究钢渣的化学成分与物相组成。利用BP神经网络模型建立钢渣活性指数预测模型，研究化学成分、物相组成与活性的关系。结果表明： 钢渣的处理工艺不同，其化学成分与物相组成存在明显差异；钢渣活性指数预测模型具有良好的符合性，即相对误差为2.42%和-2.54%，能充分反映输入层与输出层之间的映射关系。

X-Ray Diffraction (XRD) and X-Ray Fluorescence (XRF) Analysis of Steel Slags in Different Treatment Process and Active Index Prediction Model

Steel slags in different treatment processes (such as layer pouring slag from converter, rotating furnace slag from converter, casting slag, desulfurized slag, layer pouring slag from electric furnace and rotating furnace slag from electric furnace) were set as the research objects. Research on steel slag’s chemical composition and phase composition was carried out by X-Ray diffraction (XRD) and X-Ray fluorescence (XRF). The relationship of chemical composition, phase composition and activity was fitted by steel slag activity index prediction model with back-propagation neural network. The results showed that steel slag treatment process is different, its chemical composition and phase composition are obviously different. Steel slag activity index prediction model is of good compliance, and the relative errors are 2.42% and -2.54%, which can fully reflect the mapping relationship between input layer and output layer.