Rapid detection and recognition of phosphors using laser-induced breakdown spectroscopy and principal component analysis method—back propagation neural network algorithm
Rapid detection and quality monitoring of phosphor materials have always been a difficult problem in phosphor materials market. In this work, an independently proposed method based on principal component analysis method—error back propagation neural network algorithm—laser induced breakdown spectros...
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| Published in | Laser physics Vol. 34; no. 5; pp. 55701 - 55709 |
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| Main Authors | , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
IOP Publishing
01.05.2024
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1054-660X 1555-6611 |
| DOI | 10.1088/1555-6611/ad3429 |
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| Abstract | Rapid detection and quality monitoring of phosphor materials have always been a difficult problem in phosphor materials market. In this work, an independently proposed method based on principal component analysis method—error back propagation neural network algorithm—laser induced breakdown spectroscopy (PCA-BPNN-LIBS) was used for the detection and recognition of phosphors. Firstly, spectroscopic study was carried out on phosphor material samples, and the composition of phosphor elements was analyzed according to the full emission spectrum. Spectral data with different element characteristics detected by LIBS were used as training data sets for further identification. Then PCA method and BPNN algorithm were applied to identify 4 types phosphor samples (P11, P20, P43, P46). A very clear distinction graph was obtained, and the classification accuracy of 99.93% was verified. Allresults show that the proposed PCA-BPNN-LIBS method is an effective method for rapid analysis and recognition of phosphors. |
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| AbstractList | Rapid detection and quality monitoring of phosphor materials have always been a difficult problem in phosphor materials market. In this work, an independently proposed method based on principal component analysis method—error back propagation neural network algorithm—laser induced breakdown spectroscopy (PCA-BPNN-LIBS) was used for the detection and recognition of phosphors. Firstly, spectroscopic study was carried out on phosphor material samples, and the composition of phosphor elements was analyzed according to the full emission spectrum. Spectral data with different element characteristics detected by LIBS were used as training data sets for further identification. Then PCA method and BPNN algorithm were applied to identify 4 types phosphor samples (P11, P20, P43, P46). A very clear distinction graph was obtained, and the classification accuracy of 99.93% was verified. Allresults show that the proposed PCA-BPNN-LIBS method is an effective method for rapid analysis and recognition of phosphors. |
| Author | Yao, Hongbing Sun, Zhongmou Shen, Lingbin Tian, Dongpeng Ge, Yifan Liu, Yuzhu Tian, Liping |
| Author_xml | – sequence: 1 givenname: Lingbin surname: Shen fullname: Shen, Lingbin organization: College of Science, Hohai University , Nanjing 213022, People’s Republic of China – sequence: 2 givenname: Liping surname: Tian fullname: Tian, Liping organization: Jiangsu International Joint Laboratory on Meteorological Photonics and Optoelectronic Detection, Nanjing University of Information Science and Technology , Nanjing 210044, People’s Republic of China – sequence: 3 givenname: Hongbing surname: Yao fullname: Yao, Hongbing organization: College of Science, Hohai University , Nanjing 213022, People’s Republic of China – sequence: 4 givenname: Dongpeng surname: Tian fullname: Tian, Dongpeng organization: Jiangsu International Joint Laboratory on Meteorological Photonics and Optoelectronic Detection, Nanjing University of Information Science and Technology , Nanjing 210044, People’s Republic of China – sequence: 5 givenname: Yifan surname: Ge fullname: Ge, Yifan organization: Jiangsu International Joint Laboratory on Meteorological Photonics and Optoelectronic Detection, Nanjing University of Information Science and Technology , Nanjing 210044, People’s Republic of China – sequence: 6 givenname: Zhongmou surname: Sun fullname: Sun, Zhongmou organization: Jiangsu International Joint Laboratory on Meteorological Photonics and Optoelectronic Detection, Nanjing University of Information Science and Technology , Nanjing 210044, People’s Republic of China – sequence: 7 givenname: Yuzhu surname: Liu fullname: Liu, Yuzhu organization: Jiangsu International Joint Laboratory on Meteorological Photonics and Optoelectronic Detection, Nanjing University of Information Science and Technology , Nanjing 210044, People’s Republic of China |
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| Title | Rapid detection and recognition of phosphors using laser-induced breakdown spectroscopy and principal component analysis method—back propagation neural network algorithm |
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