Laser Journal, Volume. 45, Issue 6, 88(2024)
The effect of spectral preprocessing wavelet transform basis functions selection on the classification accuracy of aluminum alloys combining FIBS and machine learning
[2] [2] Huang Y, Gou M J, Jiang K, et al. Recent quantitative research of near infrared spectroscopy in traditional Chinese medicine analysis[J]. Applied Spectroscopy Reviews, 2019, 54:63-82.
[3] [3] Bec K B, Grabska J, Kirchler C G, et al. NIR spectra simulation of thymol for better understanding of the spectra forming factors, phase and concentration effects and PLS regression features[J]. Journal of Molecular Liquids, 2018, 268: 895-913.
[4] [4] Chen J B, Sun S Q, Ma F, et al. Vibrational microspectroscopic identification of powdered traditional medicines: Chemical micromorphology of Poria observed by infrared and Raman microspectroscopy[J]. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 2014, 128: 629-637.
[5] [5] Fan Q M, Chen C Y, Huang Z Q, et al. Discrimination of Rhizoma Gastrodiae (Tianma) using 3D synchronous fluorescence spectroscopy coupled with principal component analysis[J]. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 2015, 136:1621-1625.
[6] [6] Cai L Z, Wang Z Z, Li C, et al. Development of an in situ diagnostic system for mapping the deposition distribution on plasma facing components of the HL-2M tokamak[J]. Review of Scientific Instruments, 2019, 90:053503.
[8] [8] Quarles C D, Gonzalez J J, East L J, et al. Fluorine analysis using laser induced breakdown spectroscopy[J]. Journal of Analytical Atomic Spectrometry, 2014, 29(7): 1238-1242.
[9] [9] Rifai K, Laflamme M, Constantin M. Analysis of gold in rock samples using laser-induced breakdown spectroscopy: matrix and heterogeneity effects[J]. Spectrochimica Acta Part B: Atomic Spectroscopy, 2017, 134:33-41.
[10] [10] Anzano J, Casanova M E, Bermúdez M S, et al. Rapid characterization of plasticsusing laser- induced plasma spectroscopy[J]. Polymer Testing, 2006, 25(5): 623-627.
[11] [11] Li X G, Lu X T, Zhang Y, et al. Effect of the target positions on the rapid indentification of aluminum alloy by using filament-induced breakdown spectroscopy combined with machine learning[J]. Chin. Phys. B, 2022, 32(5): 054212.
[12] [12] Dillam J D R, Simon V D E, Wouter S, et al. Real-time classification of aluminum metal scrap with laser-induced breakdown spectroscopy using deep and other machine learning approaches[J]. Spectrochimica Acta Part B: Atomic Spectroscopy, 2022, 196:106519.
[13] [13] Dai Y J, Zhao S Y, Song C, et al. Indentification of aluminum alloy by laser-induced breakdown spectroscopy combined with machine algorithm[J]. Microwave and Optical Technology Lettter, 2021, 1-6.
[14] [14] Yu Y, Guo L B, Hao Z Q, et al. Accuracy improvement on polymer indentification using laser - induced breakdown spectroscopy with adjusting spectral weightings[J]. Optics Express, 2014, 22(4): 3895-3901.
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YU Hailong, GAO Yujin, XIE Yunshuang, YANG Shuo, TANG Yuxuan, GAO Xun, LIN Jingquan. The effect of spectral preprocessing wavelet transform basis functions selection on the classification accuracy of aluminum alloys combining FIBS and machine learning[J]. Laser Journal, 2024, 45(6): 88
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Received: Oct. 28, 2023
Accepted: Nov. 26, 2024
Published Online: Nov. 26, 2024
The Author Email: Xun GAO (gaoxun@cust.edu.cn)