对比分析多种化学计量学方法在激光诱导击穿光谱土壤元素定量分析中的应用  

Comparative Analysis of Multiple Chemometrics Methods in Application of Laser-Induced Breakdown Spectroscopy for Quantitative Analysis of Soil Elements

作　　者：应璐娜 周卫东[1] Ying Luna;Zhou Weidong(Institute of Information Optics,Zhejiang Normal University,Jinhua,Zhejiang 321004,China)

机构地区：[1]浙江师范大学信息光学研究所,浙江金华321004

出　　处：《光学学报》2018年第12期184-190,共7页Acta Optica Sinica

基　　金：浙江省自然科学基金(Y1100286);教育部科技计划重点项目(2080656);浙江省高校重大科技攻关项目(ZD2009006);国家人事部留学人员科技活动项目择优资助项目

摘　　要：为提高激光诱导击穿光谱技术对土壤元素检测的精度,建立了相关向量机土壤元素定量分析模型,并将该模型与已有的支持向量机模型和最小二乘支持向量机模型进行对比分析。以土壤元素Ni的4条特征谱线作为分析线,对其进行全谱归一化处理后,利用训练样品集建立相关向量机、支持向量机和最小二乘支持向量机模型。测试样品集的测试结果表明:在模型预测精度方面,支持向量机模型比另两种模型方法差;在稳定性方面,最小二乘支持向量机模型比另两种模型差。在实际应用中,相关向量机模型在稳定性及预测精度上的优势使其比另两个模型更适合用于激光诱导击穿光谱技术的定量分析中。In order to improve the detection accuracy of soil elements by laser induced breakdown spectroscopy (LIBS), we establish a quantitative analysis model for soil elements of relevance vector machine (RVM). And it is compared with support vector machine (SVM) model and least squares support vector machine (LSSVM) model. The four characteristic lines of Ni element are taken as the analysis lines, after full spectral normalization, RVM, SVM and LSSVM models are established with the training sample set. According to the test results of testing sample sets, we can know that the SVM is inferior to the others model in terms of model prediction accuracy. However, in terms of model stability, LSSVM model is poorer than the others models. Therefore, in the practical applications, the advantages of RVM in model stability and prediction accuracy indicate that it is more suitable for quantitative analysis of laser-induced breakdown spectroscopy.

关 键 词：激光光学 激光诱导击穿光谱技术 定量分析 相关向量机 土壤 预测精度 稳定性 

分 类 号：O433.4[机械工程—光学工程]