基于主导因子的Laser诱导击穿光谱多元测量模型
A Novel Multivariate Model Based on Dominant Factor for Laser-induced Breakdown Spectroscopy Measurements
摘要：
本文提出了一种将偏最小二乘法与基于物理原理的主导因子相结合的新方法。以元素的特征谱线强度为主导因子，采用偏最小二乘法（PLS）进一步提高模型的精度。描述了特征谱线强度偏离理想状态的演化过程，并根据对偏离的理解，对非线性自吸收和元素间干涉效应进行了建模，以提高主导因子模型的精度。新的多变量模型结合了传统单变量模型和PLS模型的优点，并通过一个主导因子来携带主要的定量信息，部分避免了PLS应用中过度使用光谱中的无关噪声。主导因素使得组合模型在宽的浓度范围内更稳健，并且PLS应用提高了具有校准样品集内的基质的样品的模型准确度。结果表明，当使用传统的全光谱信息PLS方法时，基于最终主导因子的PLS模型的RMSEP从5.25%下降到2.33%。此外，随着对激光诱导等离子体物理的理解的发展，有可能很容易地提高主导因素模型以及所提出的新的多变量模型的准确性。
英文摘要：
This paper presents a new approach of applying partial least squares method combined with a physical principle based dominant factor. The characteristic line intensity of the specific element was taken to build up the dominant factor to reflect the major elemental concentration and partial least squares (PLS) approach was then applied to further improve the model accuracy. The deviation evolution of characteristic line intensity from the ideal condition was depicted and according to the deviation understanding, efforts were taken to model the non-linear self-absorption and inter-element interference effects to improve the accuracy of dominant factor model. With a dominant factor to carry the main quantitative information, the novel multivariate model combines advantages of both the conventional univariate and PLS models and partially avoids the overuse of the unrelated noise in the spectrum for PLS application. The dominant factor makes the combination model more robust over a wide concentration range and PLS application improves the model accuracy for samples with matrices within the calibration sample set. Results show that RMSEP of the final dominant factor based PLS model decreased to 2.33% from 5.25% when using the conventional PLS approach with full spectral information. Furthermore, with the development in understanding the physics of the laser-induced plasma, there is potential to easily improve the accuracy of the dominant factor model as well as the proposed novel multivariate model.
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