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首页> 外文期刊>ISIJ international >Optimization of Partial-least-square Regression for Determination of Manganese in Low-alloy Steel by Single-shot Laser-induced Breakdown Spectroscopy
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Optimization of Partial-least-square Regression for Determination of Manganese in Low-alloy Steel by Single-shot Laser-induced Breakdown Spectroscopy

机译：单次激光诱导击穿光谱法测定偏最小二乘回归法测定低合金钢中锰

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摘要

Laser-induced breakdown spectroscopy (LIBS) is employed for ultra-high-speed determination of the manganese content in various steel specimens. LIBS is widely known as a method for elemental analysis with a rapid response. It has several advantages such that it can work under ambient pressure, and that specimens can be tested without any pre-treatment such as acid digestion, cleaning, or polishing of surface of the specimens. We applied a laboratory-build LIBS system for the determination of Mn in a series of low-alloy steel certified reference materials by a multivariate analysis using partial-least-square regression. Considering enough intensities of Mn emission lines and spectral interferences from emission lines of the iron matrix in these alloys, two wavelength ranges for the spectrograph could be employed. By minimizing the predicted residual sum of squares and the root mean square error of prediction, the analytical result of the Mn concentrations could be obtained with reasonable accuracy and precision.
机译：激光诱导击穿光谱法（LIBS）用于超高速测定各种钢样品中的锰含量。 LIBS是众所周知的一种具有快速响应的元素分析方法。它具有几个优点，使其可以在环境压力下工作，并且可以在不进行任何预处理（例如酸消解，清洁或抛光样品表面）的情况下测试样品。我们应用了实验室建立的LIBS系统，通过偏最小二乘回归进行多元分析，从而测定了一系列低合金钢认证参考材料中的Mn。考虑到这些合金中锰发射线的强度足够大以及铁基体发射线的光谱干扰，可以使用两个波长范围的光谱仪。通过最小化预测的残差平方和和预测的均方根误差，可以以合理的准确度和精确度获得锰浓度的分析结果。

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