Researching | Quantitative Analysis of Mn in Molten Steel with Multi-Factor Calibration Input Using Laser-Induced Breakdown Spectroscopy

Journals >Laser & Optoelectronics Progress >Volume 56 >Issue 22 >Page 223003 > Article

Laser & Optoelectronics Progress
Vol. 56, Issue 22, 223003 (2019)

Quantitative Analysis of Mn in Molten Steel with Multi-Factor Calibration Input Using Laser-Induced Breakdown Spectroscopy

Youliang Yang, Lu Wang^*, and Cuihong Ma

Author Affiliations

College of Electrical Engineering, North China University of Science and Technology, Tangshan, Hebei 063210, China

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DOI: 10.3788/LOP56.223003 Cite this Article Set citation alerts

Youliang Yang, Lu Wang, Cuihong Ma. Quantitative Analysis of Mn in Molten Steel with Multi-Factor Calibration Input Using Laser-Induced Breakdown Spectroscopy[J]. Laser & Optoelectronics Progress, 2019, 56(22): 223003 Copy Citation Text

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References

[1] Cheri M S, Tavassoli S H. Quantitative analysis of toxic metals lead and cadmium in water jet by laser-induced breakdown spectroscopy[J]. Applied Optics, 50, 1227-1233(2011). http://www.ncbi.nlm.nih.gov/pubmed/21460994

[2] Li M, Zhu X Y, Xu Y et al. Quantitative determination of Cu in lake water by laser induced breakdown spectroscopy[J]. Laser & Optoelectronics Progress, 50, 013001(2013).

[3] Lin Y Z, Yao M Y, Chen T B et al. Detection of Cu and Cr in the soil of navel orange plantation in Gannan by LIBS[J]. Laser & Optoelectronics Progress, 50, 053002(2013).

[4] Feng W L, Wang F J, Zeng W Q et al. CCD spectrum measurement system for laser induced breakdown spectroscopy[J]. Laser & Optoelectronics Progress, 50, 013002(2013).

[5] Chen X L, Fu H B, Wang J G et al. A multivariate nonlinear model for quantitative analysis in laser-induced breakdown spectroscopy[J]. Spectroscopy and Spectral Analysis, 34, 3100-3103(2014).

[6] Sun L X, Yu H B, Cong Z B et al. Quantitative analysis of Mn and Si of steels by laser-induced breakdown spectroscopy combined with neural networks[J]. Acta Optica Sinica, 30, 2757-2765(2010).

[7] Xu H M, Wang H Y, Liang J et al. Support vector machine regression algorithm and its application[J]. Journal of Beijing Institute of Petro-Chemical Technology, 18, 62-66(2010).

[8] Yang Y L, Wang P, Ma C H. Quantitative analysis of Mn element in liquid steel by LIBS based on particle swarm optimized support vector machine[J]. Laser & Optoelectronics Progress, 52, 073004(2015).

[9] Chen G, Zhou J. Research on parameters and forecasting interval of support vector regression model to small sample[J]. Acta Metrologica Sinica, 29, 92-96(2008).

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[11] Li J X, Yang Y L, Meng F W et al. Matrix correction method used for liquid steel online quantitative analysis by LIBS[J]. Laser & Optoelectronics Progress, 50, 031406(2013).

[12] Li C, Yao G X, Yang X Y et al. Key experimental parameter optimization for laser induced break down spectroscopy of liquid matrix[J]. Laser & Optoelectronics Progress, 56, 073002(2019).

[13] Xiu J S, Liu S M, Wang K K et al. Analytical investigation of Cu(In, Ga)Se2 thin films using laser induced break down spectroscopy technology[J]. Chinese Journal of Lasers, 45, 1211002(2018).

[14] Hu L, Zhao N J, Liu W Q et al. Quantitative analysis of Pb in water based on multivariate calibration with LIBS[J]. Acta Optica Sinica, 35, 0630001(2015).

[15] Jia Y, Zhao N J, Liu W Q et al. Continuous online detection method of heavy metals in water based on LIBS technology[J]. Chinese Journal of Lasers, 45, 0611001(2018).

[16] Bekefi G. Radiation processes in plasmas[M]. New York: Wiley and Sons(1966).

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Youliang Yang, Lu Wang, Cuihong Ma. Quantitative Analysis of Mn in Molten Steel with Multi-Factor Calibration Input Using Laser-Induced Breakdown Spectroscopy[J]. Laser & Optoelectronics Progress, 2019, 56(22): 223003

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