高炉铁水硅质量分数的非线性检验

Determinant of nonlinear trait of silicon content in blast furnace hot metal

为检验硅质量分数w(Si)的非线性特征,以邯郸钢铁公司7号高炉在线采集的2000炉铁水的w(Si)数据作为母体样本空间,首先运用替代数据法对w(Si)时间序列做非线性定量检验;针对替代数据法容易受系统噪声和时间序列自相关程度影响的缺点,根据信息论冗余图像法进一步对w(Si)序列做非线性定性判别;通过与典型的线性自回归模型和混沌Lorenz模型的冗余图像的比较,指出w(Si)序列的非线性并非是噪声引起的平凡非线性,而是高炉冶炼内在机理决定的本质非线性,为应用非线性模型对炉温做预测和控制建立理论了依据。

With thetime series （containing 2000 data points） of silicon content in No. 7 blast furnace （BF） at Han Iron and Steel Group Co. as sample space, a quantitative surrogate data technique was used to ex- amine the nonlinear characteristic in the time series. For the shortcoming of the quantitative method that data are vulnerable to the system noise and the autocorrelation degree of timing sequence, a further qualitative nonlinear discriminant was proposed according to the images of information-theoretic functional - redundancies （linear and nonlinear forms）. The redundant image comparison between silicon constant and two typical data series （linear regression model and chaos Lorenz model） shows that the nonlinearity of silicon constant is not ordinary nonlinearity caused by noise, but the intrinsic nonlinearity decided by the blast furnace smelting inherent mechanism. The analysis provides firm rationale for the nonlinear predic- tion and control of furnace temperature.