Multiple Liner Regression for Improving the Accuracy of Laser-Induced Breakdown Spectroscopy Assisted With Laser-Induced Fluorescence (LIBS-LIF)

Jie WU; Chuang-kai LI; Wen-jun CHEN; Yan-xin HUANG; Nan ZHAO; Jia-ming LI; Huan YANG; Xiang-you LI; Qi-tao LÜ; Qing-mao ZHANG

doi:10.3964/j.issn.1000-0593(2022)03-0795-07

Spectroscopy and Spectral Analysis, Volume. 42, Issue 3, 795(2022)

Multiple Liner Regression for Improving the Accuracy of Laser-Induced Breakdown Spectroscopy Assisted With Laser-Induced Fluorescence (LIBS-LIF)

Jie WU^1、1;, Chuang-kai LI^1、1;, Wen-jun CHEN^1、1;, Yan-xin HUANG^1、1;, Nan ZHAO^1、1;, Jia-ming LI^{1、1; 2; *;}, Huan YANG^3、3;, Xiang-you LI^4、4;, Qi-tao LÜ^{3、3; 5;}, and Qing-mao ZHANG^{1、1; 2; 5;}

Author Affiliations

¹1. Guangdong Provinical Key Laboratory of Nanophotonic Functional Materials and Devices, School of Information and Optoelectronic Science and Engineering, South China Normal University, Guangzhou 510006, China

³3. Sino-German College of Intelligent Manufacturing, Shenzhen Technology University, Shenzhen 518118, China

⁴4. Wuhan National Laboratory for Optoelectronics (WNLO), Huazhong University of Science and Technology, Wuhan 430074, China

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Figures & Tables(9)

Fig. 1. Schematic diagram of LIBS-LIF experimental setup

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Fig. 2. Results of Cr concentrations (a) and Ni concentrations (b) predicted by simple linear regression

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Fig. 3. LIBS spectral intensities of Ni containing samples (a) and Cr containing samples (b)

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Fig. 4. Results of Ni concentrations (a) and Cr concentrations (b) predicted by multiple linear regression

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Fig. 5. The fitting coefficients of Ni(a) and Cr(b) with different dimensions

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Fig. 6. ARE of Ni(a) and Cr(b) with different dimensions

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Fig. 7. RESECV of Ni (a) and Cr (b) with different dimensions

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Table 1. Concentrations of Cr and Ni in micro alloyed steel samples(Wt%)

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Table 1. Concentrations of Cr and Ni in micro alloyed steel samples(Wt%)

No.	镍	铬	No.	镍	铬
1	0.409	0.164	12	0.200 6	0.051
2	0.086	0.322	13	0.154	0.024
3	0.218	0.092	14	0.021	0.001 5
4	0.408	0.409	15	0.002	0.8
5	0.133	0.601	16	0.183	0.511
6	0.03	0.062	17	0.194	0.08
7	0.175	0.036	18	0.046	0.03
8	0.142	0.066	19	0.032	0.117
9	0.041	0.007 2	20	0.502	0.171
10	0.174	0.222	21	0.094	0.387
11	0.513	0.498	22	0.026	0.157

Table 2. Regression coefficients of multiple linear regression

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Table 2. Regression coefficients of multiple linear regression

Ni			Cr
波长	Ni拟合系数×10^-6	对应元素	波长	Cr拟合系数×10^-6	对应元素
301.26	31.14	Ni	428.99	7.48	Cr
305.15	19.98	Ni	425.07	6.49	Fe
305.83	18.42	Ni	427.50	6.34	Cr
310.25	14.27	Ni	432.63	6.00	Fe
303.85	10.35	Ni	425.46	4.83	Cr
305.50	7.88	Ni	430.81	3.38	Fe
300.34	5.40	Ni	420.21	2.91	Fe
306.74	2.55	Fe	428.37	2.62	Fe
			427.17	1.52	Fe
			426.06	1.47	Fe

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Jie WU, Chuang-kai LI, Wen-jun CHEN, Yan-xin HUANG, Nan ZHAO, Jia-ming LI, Huan YANG, Xiang-you LI, Qi-tao LÜ, Qing-mao ZHANG. Multiple Liner Regression for Improving the Accuracy of Laser-Induced Breakdown Spectroscopy Assisted With Laser-Induced Fluorescence (LIBS-LIF)[J]. Spectroscopy and Spectral Analysis, 2022, 42(3): 795

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Paper Information

Category: Orginal Article

Received: Mar. 5, 2021

Accepted: Jun. 13, 2021

Published Online: Apr. 19, 2022

The Author Email:

DOI:10.3964/j.issn.1000-0593(2022)03-0795-07

Topics

laser devices and laser physics

Lasers and Laser Optics

Laser physics

laser manufacturing

Instrumentation, Measurement and Metrology