A quantitative analysis method assisted by image features in laser-induced breakdown spectroscopy

2019 ◽  
Vol 1082 ◽  
pp. 30-36 ◽  
Author(s):  
Jiujiang Yan ◽  
Zhongqi Hao ◽  
Ran Zhou ◽  
Yun Tang ◽  
Ping Yang ◽  
...  
Author(s):  
Fu Chang ◽  
Jianhong Yang ◽  
Huili Lu ◽  
Haixia Li

The quantitative analysis accuracy of laser-induced breakdown spectroscopy (LIBS) will decrease if the temperatures of testing samples are different from the temperature under which the calibration model is established. For...


2015 ◽  
Vol 30 (7) ◽  
pp. 1541-1551 ◽  
Author(s):  
Jianhong Yang ◽  
Cancan Yi ◽  
Jinwu Xu ◽  
Xianghong Ma

Data fluctuation in multiple measurements of Laser Induced Breakdown Spectroscopy (LIBS) greatly affects the accuracy of quantitative analysis. Our proposed method achieved better prediction accuracy and modeling robustness.


2013 ◽  
Vol 313-314 ◽  
pp. 579-582
Author(s):  
You Liang Yang ◽  
Jun Xiang Li ◽  
Fan Wei Meng ◽  
Cui Hong Ma

This paper introduced the principle about the technology of Laser-induced Breakdown Spectroscopy (LIBS) of quantitative analysis. It was reviewed about the quantitative analysis of LIBS reduced method of matrix. The reason of cause matrix effect was not clear, but the matrix effect on the LIBS quantitative analysis of the impact can not be ignored. The LIBS quantitative analysis method was divided into two categories: one was based on the calibration curve with the mathematical matrix correction method; the other was combined with neural network reduction method of matrix. This paper was introduced for the two categories of methods, and gives an example to explain.


2017 ◽  
Vol 32 (11) ◽  
pp. 2164-2172 ◽  
Author(s):  
Cancan Yi ◽  
Yong Lv ◽  
Han Xiao ◽  
Shan Tu

In this paper, a novel and quantitative LIBS analysis method based on a sparse low-rank matrix approximation via convex optimization is proposed.


2017 ◽  
Vol 72 (1) ◽  
pp. 129-140 ◽  
Author(s):  
Jianhong Yang ◽  
Xiaomeng Li ◽  
Jinwu Xu ◽  
Xianghong Ma

The quantitative analysis accuracy of calibration-free laser-induced breakdown spectroscopy (CF-LIBS) is severely affected by the self-absorption effect and estimation of plasma temperature. Herein, a CF-LIBS quantitative analysis method based on the auto-selection of internal reference line and the optimized estimation of plasma temperature is proposed. The internal reference line of each species is automatically selected from analytical lines by a programmable procedure through easily accessible parameters. Furthermore, the self-absorption effect of the internal reference line is considered during the correction procedure. To improve the analysis accuracy of CF-LIBS, the particle swarm optimization (PSO) algorithm is introduced to estimate the plasma temperature based on the calculation results from the Boltzmann plot. Thereafter, the species concentrations of a sample can be calculated according to the classical CF-LIBS method. A total of 15 certified alloy steel standard samples of known compositions and elemental weight percentages were used in the experiment. Using the proposed method, the average relative errors of Cr, Ni, and Fe calculated concentrations were 4.40%, 6.81%, and 2.29%, respectively. The quantitative results demonstrated an improvement compared with the classical CF-LIBS method and the promising potential of in situ and real-time application.


Author(s):  
Raquel C Machado ◽  
Diego Victor Babos ◽  
Daniel Fernandes Andrade ◽  
Edenir Rodrigues Pereira-Filho

Quantitative analysis requires several efforts to obtain an adequate calibration method to overcome matrix effects employing direct solid analysis by laser-induced breakdown spectroscopy (LIBS). To this end, in this study,...


Author(s):  
Fu Chang ◽  
Jianhong Yang ◽  
Huili Lu ◽  
Haixia Li

It is significant to improve the repeatability of quantitative analysis of laser-induced breakdown spectroscopy (LIBS) in one-shot measurement where the skill of averaging is not valid because multiple measurements are...


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