光子学报, 2014, 43 (9): 0930002, 网络出版: 2014-10-23
PLS算法在激光诱导击穿光谱分析炉渣成分中的应用
Slag Quantitative Analysis Based on PLS Model by Laser-induced Breakdown Spectroscpy
光谱学 激光诱导击穿光谱 偏最小二乘 炉渣 归一化 定量分析 实时在线 Spectroscopy LIBS PLS Slag Normalization Quantitative analysis On-line
摘要
炉渣成分的实时在线检测是目前金属冶炼企业迫切需求的一项技术.本文利用激光诱导击穿光谱技术结合偏最小二乘回归模型对炉渣中的CaO、MgO、Al2O3和Fe进行定量分析.采用背景修正和基于等离子体成像强度的谱线归一化法对光谱进行预处理, 有效提高了光谱强度的准确性和稳定性.利用25块已知成分的炉渣样品建立偏最小二乘回归定量分析模型, 并用其预测另外5块样品成分.CaO、MgO、Al2O3和Fe预测结果的平均相对误差分别为4.7%、11.5%、17.9%和12.5%.实验结果表明, 激光诱导击穿光谱结合偏最小二乘回归方法可实现炉渣成分实时在线检测.
Abstract
On-line quantitative analysis of slag, which could greatly improve product quality and reduce energy consumption, is a highly demanded technique in metallurgic industry.Laser induced breakdown spectroscopy combined partial least squares regression model was proposed to determine the content of CaO, MgO, Al2O3 and Fe in slag.Background correction and spectral normalization, which used plasma intensity as reference signal, were applied to improve spectral signal stability.5 slag samples were analyzed by using the partial least squares regression model established with 25 slag elements-known samples.The mean prediction relative error of CaO, MgO, Al2O3 and Fe was 4.7%、11.5%、17.9% and 12.5%, respectively.The experimental results indicate that laser-induced breakdown spectroscopy combined PLS is a potential tool for on-line quantitative analysis of slag.
陈兴龙, 董凤忠, 王静鸽, 倪志波, 贺文干, 付洪波, 徐骏. PLS算法在激光诱导击穿光谱分析炉渣成分中的应用[J]. 光子学报, 2014, 43(9): 0930002. CHEN Xing-long, DONG Feng-zhong, WANG Jing-ge, NI Zhi-bo, HE Wen-gan, FU Hong-bo, XU Jun. Slag Quantitative Analysis Based on PLS Model by Laser-induced Breakdown Spectroscpy[J]. ACTA PHOTONICA SINICA, 2014, 43(9): 0930002.