ABSTRACT

The cross temperature measuring device is applied to monitor the top temperature and gas flow distribution in the blast furnace (BF) during the ironmaking process. However, the temperature of the BF roof is relatively high, which causes damage to the cross temperature measuring device. Therefore, this paper proposes an efficient estimation method. First of all, the data filtering method are used to solve the problems of noise interference. Moreover, as the fact that BF cross temperature measurement is affected by interference factors, it is easy to cause information redundancy. Aiming at this, the maximum information coefficient (MIC) correlation analysis and sequence dislocation method are used to determine the input variables and its action time of the model. Finally, an estimation model based three-layer long and short-term memory network (LSTM3) is established. The experimental results show that the LSTM3 can estimate the centre temperature of cross temperature measuring device.

摘要

交叉温度测量装置用于监测炼铁过程中高炉（BF）的炉顶温度和气流分布。但高炉顶板温度较高，造成交叉测温装置损坏。因此，本文提出了一种有效的估计方法。首先，采用数据滤波方法解决噪声干扰问题。此外，由于BF交叉温度测量受干扰因素的影响，容易造成信息冗余。针对此，采用最大信息系数（MIC）相关分析和序列错位法确定模型的输入变量及其作用时间。最后，建立了基于三层长短期记忆网络（LSTM3）的估计模型。实验结果表明，LSTM3可以估计交叉测温装置的中心温度。