Quantitative Analysis of Aluminum Alloy Based on Laser-Induced Breakdown Spectroscopy and Radial Basis Function Neural Network

Lijian Pan; Weifang Chen; Rongfang Cui; Miaomiao Li

doi:10.3788/LOP57.193002

Laser & Optoelectronics Progress, Volume. 57, Issue 19, 193002(2020)

Quantitative Analysis of Aluminum Alloy Based on Laser-Induced Breakdown Spectroscopy and Radial Basis Function Neural Network

Lijian Pan, Weifang Chen^*, Rongfang Cui, and Miaomiao Li

Author Affiliations

College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu 210001, China

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Abstract Get PDF(in Chinese)

Figures & Tables(9)

Fig. 1. Structure of neural network

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Fig. 2. Schematic of LIBS experimental system

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Fig. 3. LIBS spectrum of aluminum alloy

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Fig. 4. Univariate linear calibration curves of five main nonaluminum elements. (a) Mg; (b) Si; (c) Fe; (d) Mn; (e) Cu

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Fig. 5. Effect of v_spread on the performance of RBF model

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Fig. 6. Prediction of five main nonaluminum elements by RBF neural networks. (a) Mg; (b) Si; (c) Fe; (d) Mn; (e) Cu

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Table 1. Content of main non-Al elements in different standard samples of aluminum alloy

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Table 1. Content of main non-Al elements in different standard samples of aluminum alloy

Standardsample	Mass fraction /%
Standardsample	Si	Fe	Cu	Mn	Mg
3003	0.135	0.384	0.1580	1.0700	0.013
5052	0.120	0.150	0.0030	0.0060	2.560
5083	0.044	0.086	0.0009	0.6170	4.220
5962	0.587	0.392	0.0830	0.4170	3.410
5963	0.279	0.650	0.1170	0.2150	4.720
6061	0.640	0.546	0.2900	0.0940	1.000
6063a	0.390	0.135	0.0025	0.0036	0.825
6063b	0.419	0.187	0.0710	0.0550	0.540

Table 2. Spectral lines for analysis
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Table 2. Spectral lines for analysis
Element Analytical spectral line /nm
Al 281.61, 305.01, 308.21, 358.64, 396.17
Mn 257.55, 259.37, 263.21, 279.48
Mg 277.99, 279.06, 280.25, 285.21
Fe 234.33, 238.18, 302.05
Si 288.15, 390.55
Cu 324.73, 327.41

Table 3. Quantitative analysis results calculated by different models for standard samples of aluminum alloy
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Table 3. Quantitative analysis results calculated by different models for standard samples of aluminum alloy
Element RMSE /% R²
Linearcalibration RBF Linearcalibration RBF
Si 8.10 0.18 0.741 0.959
Fe 7.49 0.33 0.781 0.968
Cu 7.74 0.13 0.764 0.972
Mn 7.97 0.36 0.973 0.995
Mg 5.52 0.55 0.986 0.994

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Lijian Pan, Weifang Chen, Rongfang Cui, Miaomiao Li. Quantitative Analysis of Aluminum Alloy Based on Laser-Induced Breakdown Spectroscopy and Radial Basis Function Neural Network[J]. Laser & Optoelectronics Progress, 2020, 57(19): 193002

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Paper Information

Category: Spectroscopy

Received: Jan. 2, 2020

Accepted: Feb. 24, 2020

Published Online: Sep. 23, 2020

The Author Email: Chen Weifang (meewfchen@nuaa.edu.cn)

DOI:10.3788/LOP57.193002

Topics

laser devices and laser physics

Lasers and Laser Optics

Laser physics

laser manufacturing

Instrumentation, Measurement and Metrology

Table 1. Content of main non-Al elements in different standard samples of aluminum alloy

Table 1. Content of main non-Al elements in different standard samples of aluminum alloy

Table 2. Spectral lines for analysis

Table 2. Spectral lines for analysis

Table 3. Quantitative analysis results calculated by different models for standard samples of aluminum alloy

Table 3. Quantitative analysis results calculated by different models for standard samples of aluminum alloy