Partial least squares regression calculation for quantitative analysis of metals submerged in water measured using laser-induced breakdown spectroscopy

Takahashi Tomoko; Thornton Blair; Sato Takumi; Ohki Toshihiko; Ohki Koichi; Sakka Tetsuo

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Partial least squares regression calculation for quantitative analysis of metals submerged in water measured using laser-induced breakdown spectroscopy

机译：使用激光诱导的击穿光谱测量水浸没在水中金属的定量分析的局部最小二乘性分析

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Effects of different parameters regarding partial least squares (PLS) regression analysis are investigated for quantitative analysis of water-submerged brass samples. The concentrations of Cu and Zn in various brass alloys were quantified using PLS, and the performance after different signal processing steps (normalization, smoothing, and background subtraction) and database segmentation by excitation temperature is compared. In addition, the effects of averaging numbers on the results are examined. From the results, normalization was found to be the most effective among three established signal processing methods. The effects of both peak and background fluctuations seen in the signals are reduced by normalization. It was found that temperature segmentation of the database in an appropriate range, which should be high enough for reliable peak detection, can further improve the accuracy of PLS calculations. The proposed method is applicable in real time, and can potentially be used for automated fast and accurate measurements of solids at oceanic pressures. (C) 2018 Optical Society of America

机译：研究了关于局部最小二乘（PLS）回归分析的不同参数的影响，用于水淹黄铜样品的定量分析。使用PLS量化各种黄铜合金中Cu和Zn的浓度，比较了不同信号处理步骤（归一化，平滑和背景减法）和通过激励温度的数据库分段的性能。此外，检查了平均数量对结果的影响。从结果中，发现标准化是三种建立的信号处理方法中最有效的。通过标准化降低了信号中看到的峰值和背景波动的影响。结果发现，在适当的范围内，数据库的温度分割，应该足够高以获得可靠的峰值检测，可以进一步提高PLS计算的准确性。所提出的方法是实时适用的，并且可能用于在海洋压力下用于自动化和准确测量固体。（c）2018年光学学会

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《Applied optics》 |2018年第20期|共12页
作者
Takahashi Tomoko; Thornton Blair; Sato Takumi; Ohki Toshihiko; Ohki Koichi; Sakka Tetsuo;
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Univ Tokyo Inst Ind Sci Meguro Ku 4-6-1 Komaba Tokyo 1538505 Japan;

Univ Tokyo Inst Ind Sci Meguro Ku 4-6-1 Komaba Tokyo 1538505 Japan;

Natl Maritime Res Inst 6-38-1 Shinkawa Mitaka Tokyo 1810004 Japan;

OK Lab Co Ltd 8-7-3 Shimorenjyaku Mitaka Tokyo 1810013 Japan;

OK Lab Co Ltd 8-7-3 Shimorenjyaku Mitaka Tokyo 1810013 Japan;

Kyoto Univ Dept Energy &

Hydrocarbon Chem Nishikyo Ku Kyoto 6158510 Japan;

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Partial least squares regression calculation for quantitative analysis of metals submerged in water measured using laser-induced breakdown spectroscopy

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