Calibration curve and support vector regression methods applied for quantification of cement raw meal using laser-induced breakdown spectroscopy | |
Jia, Junwei2,3; Fu, Hongbo2; Hou, Zongyu1; Wang, Huadong2,3; Ni, Zhibo2; Dong, Fengzhong2,3 | |
刊名 | PLASMA SCIENCE & TECHNOLOGY
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2019-03-01 | |
期号 | 3页码:8 |
关键词 | cement raw meal calibration curves SVR LIBS |
ISSN号 | 1009-0630 |
DOI | 10.1088/2058-6272/aae3e1 |
英文摘要 | Laser-induced breakdown spectroscopy (LIBS) is a qualitative and quantitative analytical technique with great potential in the cement industrial analysis. Calibration curve (CC) and support vector regression (SVR) methods coupled with LIBS technology were applied for the quantification of three types of cement raw meal samples to compare their analytical concentration range and the ability to reduce matrix effects, respectively. To reduce the effects of fluctuations of the pulse-to-pulse, the unstable ablation and improve the reproducibility, all of the analysis line intensities were normalized on a per-detector basis. The prediction results of the elements of interest in the three types of samples, Ca, Si, Fe, Al, Mg, Na, K and Ti, were compared with the results of the wet chemical analysis. The average relative error (ARE), relative standard deviation (RSD) and root mean squared error of prediction (RMSEP) were employed to investigate and evaluate the prediction accuracy and stability of the two prediction methods. The maximum average ARE of the CC and SVR methods is 34.62% instead of 6.13%, RSD is 40.89% instead of 7.60% and RMSEP is 1.34% instead of 0.43%. The results show that SVR method can accurately analyze samples within a wider concentration range and reduce the matrix effects, and LIBS coupled with it for a rapid, stable and accurate quantification of different types of cement raw meal samples is promising. |
资助项目 | National Natural Science Foundation of China[41775128] ; External Cooperation Program of Chinese Academy of Sciences[GJHZ1726] ; National Natural Science Foundation of China[61505223] ; China State Key Lab. of Power System[SKLD18KM11] ; Knowledge Innovation Program of the Chinese Academy of Sciences[Y03RC21124] ; China State Key Lab. of Power System[SKLD18M12] |
WOS关键词 | QUANTITATIVE-ANALYSIS ; FLUORESCENCE ; QUALITY ; LIBS |
WOS研究方向 | Physics |
语种 | 英语 |
出版者 | IOP PUBLISHING LTD |
WOS记录号 | WOS:000451072800003 |
内容类型 | 期刊论文 |
源URL | [http://ir.hfcas.ac.cn:8080/handle/334002/40380] ![]() |
专题 | 合肥物质科学研究院_中科院安徽光学精密机械研究所 |
通讯作者 | Dong, Fengzhong |
作者单位 | 1.Tsinghua Univ, Dept Thermal Engn, State Key Lab Power Syst, Tsinghua BP Clean Energy Ctr, Beijing 100084, Peoples R China 2.Chinese Acad Sci, Anhui Inst Opt & Fine Mech, Anhui Prov Key Lab Photon Devices & Mat, Hefei 230031, Anhui, Peoples R China 3.Univ Sci & Technol China, Hefei 230022, Anhui, Peoples R China |
推荐引用方式 GB/T 7714 | Jia, Junwei,Fu, Hongbo,Hou, Zongyu,et al. Calibration curve and support vector regression methods applied for quantification of cement raw meal using laser-induced breakdown spectroscopy[J]. PLASMA SCIENCE & TECHNOLOGY,2019(3):8. |
APA | Jia, Junwei,Fu, Hongbo,Hou, Zongyu,Wang, Huadong,Ni, Zhibo,&Dong, Fengzhong.(2019).Calibration curve and support vector regression methods applied for quantification of cement raw meal using laser-induced breakdown spectroscopy.PLASMA SCIENCE & TECHNOLOGY(3),8. |
MLA | Jia, Junwei,et al."Calibration curve and support vector regression methods applied for quantification of cement raw meal using laser-induced breakdown spectroscopy".PLASMA SCIENCE & TECHNOLOGY .3(2019):8. |
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