Radar Detection-based Modeling in a Blast Furnace: a Prediction Model of Burden Surface Shape after Charging
Radar Detection-based Modeling in a Blast Furnace: a Prediction Model of Burden Surface Shape after Charging
复制标题
DOI：
10.2355/isijinternational.isijint-2018-267
复制
发表时间：
2018-11
影响因子：
1.8
通讯作者：
Jiuzhou Tian;A. Tanaka;Qingwen Hou;Xianzhong Chen
中科院分区：
文献类型：
--
作者：
Jiuzhou Tian;A. Tanaka;Qingwen Hou;Xianzhong Chen
高炉料面形状是影响炼铁生产效率的重要因素，雷达检测是一种先进的高炉料面形状监测方法。在本文中，一个基于雷达探测的模型，用于预测料面形状的开发，以协助运营商制定充电策略。所用数据分别由机械摆动雷达获得的真实的高炉工作状态的检测记录和高炉数据库系统的控制记录组成。通过对堆积密度函数的定义和分析，揭示了建模原理的物理意义。该模型结合经典的强制装药轨迹子模型和检测驱动的炉料下降计算，采用高斯半径基函数逼近炉料装药过程的堆积机理。参数辨识结果表明，该模型能较好地逼近料面半径分布。与焦炭层的结果相比，矿石层的参数范围较窄。性能比较表明，该模型具有更高的预测精度的局部细节和全局形状比经典的折线模型。
Radar detection is an advanced method for monitoring a blast furnace’s inner burden surface shape, which is an important factor that largely affects the production efficiency of the iron-making process. In this paper, a radar detection-based model for the prediction of burden surface shape was developed for assisting operators in developing a charging strategy. The data used are composed of both the detection and controlling records of a real, working-state blast furnace obtained by mechanical swing radar and a furnace database system, respectively. By defining and analyzing the stacking density function, the physical meanings of the modeling principles were revealed. Combined with the classical force charging trajectory sub-model and detection-driven burden descent calculation, the proposed model adopts Gaussian radius basis functions to approximate the stacking mechanism of the burden charging process. The parameter identification results show that the model can approximate the burden surface radius profile well. Compared with the results obtained for coke layers, the parameters’ ranges for the ore layers are narrower. Performance comparison shows that the proposed model has the advantages of higher prediction accuracy for both local details and global shape over the classical polygonal line model.