基于火焰图像与光谱特征的炼钢终点温度预测  

End Point Temperature Prediction of Converter Steelmaking Based on Characteristics of Flame Image and Spectrum

作　　者：刘帅 周木春[1] Liu Shuai;Zhou Muchun(School of Electronic and Optical Engineering,Nanjing University of Science&Technology,Nanjing 210094,Jiangsu,China)

机构地区：[1]南京理工大学电子工程与光电技术学院,江苏南京210094

出　　处：《激光与光电子学进展》2023年第4期437-440,共4页Laser & Optoelectronics Progress

基　　金：国家自然科学基金(61675098)。

摘　　要：转炉炼钢终点温度的精确控制能够提高最终出钢的质量。为了提高终点钢水温度的预测精度,使用一种修正的比色测温法计算炉口火焰温度,通过改进的竞争性自适应重加权算法提取火焰光谱特征波长,最后将图像和光谱特征融合分析,建立炼钢终点温度预测模型。模型预测结果的均方根误差为15.8556 K,预测误差在±20 K内的准确率为87.50%,±30 K内的准确率为95.00%。与单独使用图像特征或光谱特征建立的模型相比,所提模型的预测误差最小,准确率最高。所提模型能够有效地预测转炉炼钢终点温度,满足炼钢生产的现场要求。Accurately controlling the end point temperature of converter steelmaking can considerably enhance the quality of final tapping.Modified colorimetric thermometry was used to determine the temperature of the furnace mouth flame to enhance the molten steel temperature prediction accuracy at the end point;furthermore,the improved competitive adaptive reweighted algorithm was used to extract the characteristic wavelength of the flame spectrum.Finally,the image and spectral features were fused and analyzed.Subsequently,a steelmaking end point temperature prediction model was established.The root mean square error of the proposed model’prediction is 15.8556 K,the accuracy within the prediction error of±20 K is 87.50%,and the accuracy within the prediction error of±30 K is 95.00%.Compared with the model established solely using the image feature or spectral feature,the prediction error of the proposed model is the lowest,and the accuracy is the highest.This confirms that the model established in this experiment has a good end point temperature prediction and can successfully meet the field requirements of steelmaking production.

关 键 词：光谱学 转炉炼钢 比色测温 竞争性自适应重加权算法 终点预测 

分 类 号：TF713.1[冶金工程—钢铁冶金]