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

作　　者：陈兴龙[1,2] 董凤忠[2,3] 王静鸽[2] 倪志波[2] 贺文干 付洪波[2] 徐骏 

机构地区：[1]合肥工业大学仪器科学与光电工程学院,合肥230009 [2]中国科学院安徽光学精密机械研究所,合肥230031 [3]中国科学技术大学环境科学与光电技术学院,合肥230026 [4]上海卫星装备研究所,上海200240

出　　处：《光子学报》2014年第9期120-124,共5页Acta Photonica Sinica

基　　金：国家自然科学基金(No.11075184)资助

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.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, A12 03 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 ootential tool for on-line quantitative analysis of slag.

关 键 词：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 

分 类 号：O657.3[理学—分析化学] O433.1[理学—化学]