Fast measurement of coking properties of coal using laser induced breakdown spectroscopy

Spectrochimica Acta Part B: Atomic Spectroscopy - Tập 191 - Trang 106406 - 2022
Zongyu Hou1,2, Zhe Wang1,2, Liang Li3, Xiang Yu4, Tianxi Li5, Huaiwei Yao5, Gangyao Yan6, Qing Ye6, Zijun Liu7, Hongqi Zheng7
1State Key Lab of Power System, Department of Energy and Power Engineering, Tsinghua-BP Clean Energy Centre, Tsinghua University, Beijing 100084, China
2Shanxi Research Institute for Clean Energy, Tsinghua University, Taiyuan 030032, China
3Beijing Research Institute of Chemical Engineering and Metallurgy, Beijing 101149, China
4China National Uranium Corporation, Beijing 100013, China
5Henan Golden Horse Energy Co., LTD, Jiyuan, 454650, China
6Guoneng Bengbu Power Generation Co., Ltd, China
7Jinneng Holding Tashan Power Generation Co., Ltd, China

Tài liệu tham khảo

Sheta, 2019, Coal analysis by laser-induced breakdown spectroscopy: a tutorial review, J. Anal. Atom. Spectrom., 34, 1047, 10.1039/C9JA00016J Yao, 2018, Development of a Rapid Coal Analyzer Using Laser-Induced Breakdown Spectroscopy (LIBS), Appl. Spectrosc., 72, 1225, 10.1177/0003702818772856 Shui, 2007, Effect of coal soluble constituents on caking property of coal, Fuel, 86, 1396, 10.1016/j.fuel.2006.11.027 Dı́ez, 2002, Coal for metallurgical coke production: predictions of coke quality and future requirements for cokemaking, Int. J. Coal Geol., 50, 389, 10.1016/S0166-5162(02)00123-4 Romero, 2014, LIBS Analysis for Coal, 511 Wang, 2015, A Rising Force for the World-Wide Development of Laser-Induced Breakdown Spectroscopy, Plasma Sci. Technol., 17, 617, 10.1088/1009-0630/17/8/01 Guo, 2021, Development in the application of laser-induced breakdown spectroscopy in recent years: A review, Front. Phys., 16, 22500, 10.1007/s11467-020-1007-z Fu, 2020, Mechanism of signal uncertainty generation for laser-induced breakdown spectroscopy, Front. Phys., 16, 22502, 10.1007/s11467-020-1006-0 Wang, 2021, Recent advances in laser-induced breakdown spectroscopy quantification: From fundamental understanding to data processing, TrAC Trends Anal. Chem., 143, 10.1016/j.trac.2021.116385 Gaft, 2008, Laser Induced Breakdown Spectroscopy machine for online ash analyses in coal, Spectrochim. Acta B: At. Spectrosc., 63, 1177, 10.1016/j.sab.2008.06.007 Feng, 2011, A PLS model based on dominant factor for coal analysis using laser-induced breakdown spectroscopy, Anal. Bioanal. Chem., 400, 3261, 10.1007/s00216-011-4865-y Hou, 2016, A hybrid quantification model and its application for coal analysis using laser induced breakdown spectroscopy, J. Anal. Atom. Spectrom., 31, 722, 10.1039/C5JA00475F Song, 2021, Industrial at-line analysis of coal properties using laser-induced breakdown spectroscopy combined with machine learning, Fuel, 306, 10.1016/j.fuel.2021.121667 Li, 2013, A partial least squares based spectrum normalization method for uncertainty reduction for laser-induced breakdown spectroscopy measurements, Spectrochim. Acta B: At. Spectrosc., 88, 180, 10.1016/j.sab.2013.07.005 He, 2013, In-situ measurement of sodium and potassium release during oxy-fuel combustion of lignite using laser-induced breakdown spectroscopy: effects of O-2 and CO2 concentration, Energy Fuel, 27, 1123, 10.1021/ef301750h Andrade, 2010, Classical univariate calibration and partial least squares for quantitative analysis of brass samples by laser-induced breakdown spectroscopy, Spectrochim. Acta B: At. Spectrosc., 65, 658, 10.1016/j.sab.2010.04.008 Krug, 2010, Comparison of univariate and multivariate calibration for the determination of micronutrients in pellets of plant materials by laser induced breakdown spectrometry, Spectrochim. Acta B: At. Spectrosc., 65, 66, 10.1016/j.sab.2009.11.007 Dyar, 2011, Strategies for Mars remote Laser-Induced Breakdown Spectroscopy analysis of sulfur in geological samples, Spectrochim. Acta B: At. Spectrosc., 66, 39, 10.1016/j.sab.2010.11.016 El Haddad, 2014, Application of a series of artificial neural networks to on-site quantitative analysis of lead into real soil samples by laser induced breakdown spectroscopy, Spectrochim. Acta B: At. Spectrosc., 97, 57, 10.1016/j.sab.2014.04.014 El Haddad, 2012, Artificial neural network for on-site quantitative analysis of soils using laser induced breakdown spectroscopy, Spectrochim. Acta B: At. Spectrosc., 79–80, 51 Burakov, 2007, Quantitative analysis of alloys and glasses by a calibration-free method using laser-induced breakdown spectroscopy, Spectrochim. Acta B: At. Spectrosc., 62, 217, 10.1016/j.sab.2007.03.021 Barreda, 2012, Fast quantitative determination of platinum in liquid samples by laser-induced breakdown spectroscopy, Anal. Bioanal. Chem., 403, 2601, 10.1007/s00216-012-6019-2 Dyar, 2012, Comparison of partial least squares and lasso regression techniques as applied to laser-induced breakdown spectroscopy of geological samples, Spectrochim. Acta B: At. Spectrosc., 70, 51, 10.1016/j.sab.2012.04.011 Weisberg, 2014, Measuring lanthanide concentrations in molten salt using laser-induced breakdown spectroscopy (LIBS), Appl. Spectrosc., 68, 937, 10.1366/13-07390 Zheng, 2014, Study of laser energy in multi-element detection of pulverized coal flow with laser-induced breakdown spectroscopy, Spectrosc. Spectr. Anal., 34, 221 Clegg, 2009, Multivariate analysis of remote laser-induced breakdown spectroscopy spectra using partial least squares, principal component analysis, and related techniques, Spectrochim. Acta B: At. Spectrosc., 64, 79, 10.1016/j.sab.2008.10.045 Anderson, 2011, The influence of multivariate analysis methods and target grain size on the accuracy of remote quantitative chemical analysis of rocks using laser induced breakdown spectroscopy, Icarus, 215, 608, 10.1016/j.icarus.2011.07.034 Martin, 2005, Analysis of preservative-treated wood by multivariate analysis of laser-induced breakdown spectroscopy spectra, Spectrochim. Acta B: At. Spectrosc., 60, 1179, 10.1016/j.sab.2005.05.022 Yaroshchyk, 2010, Quantitative measurements of loss on ignition in iron ore using laser-induced breakdown spectroscopy and partial least squares regression analysis, Appl. Spectrosc., 64, 1335, 10.1366/000370210793561600 Zhang, 2015, Quantitative and classification analysis of slag samples by laser induced breakdown spectroscopy (LIBS) coupled with support vector machine (SVM) and partial least square (PLS) methods, J. Anal. At. Spectrom., 30, 368, 10.1039/C4JA00421C Zhang, 2014, A novel approach for the quantitative analysis of multiple elements in steel based on laser-induced breakdown spectroscopy (LIBS) and random forest regression (RFR), J. Anal. At. Spectrom., 29, 2323, 10.1039/C4JA00217B Quarles, 2014, Fluorine analysis using Laser Induced Breakdown Spectroscopy (LIBS), J. Anal. At. Spectrom., 29, 1238, 10.1039/c4ja00061g Barbieri Gonzaga, 2012, A compact and low cost laser induced breakdown spectroscopic system: Application for simultaneous determination of chromium and nickel in steel using multivariate calibration, Spectrochim. Acta B: At. Spectrosc., 69, 20, 10.1016/j.sab.2012.02.007 Stipe, 2010, Laser-induced breakdown spectroscopy of steel: A comparison of univariate and multivariate calibration methods, Appl. Spectrosc., 64, 154, 10.1366/000370210790619500 Feng, 2011, A PLS model based on dominant factor for coal analysis using laser-induced breakdown spectroscopy, Anal. Bioanal. Chem., 400, 3261, 10.1007/s00216-011-4865-y Wang, 2011, A multivariate model based on dominant factor for laser-induced breakdown spectroscopy measurements, J. Anal. Atom. Spectrom., 26, 2289, 10.1039/c1ja10041f Wang, 2011, A non-linearized PLS model based on multivariate dominant factor for laser-induced breakdown spectroscopy measurements, J. Anal. Atom. Spectrom., 26, 2175, 10.1039/c1ja10113g Qin, 2016, Caking property and active components of coal based on group component separation, Int. J. Min. Sci. Technol., 26, 571, 10.1016/j.ijmst.2016.05.006 Chen, 1989, Significance and application of the caking index of coal - 10 years review, Fuel Process. Technol., 21, 99, 10.1016/0378-3820(89)90064-7 Mitra, 1978, Effect of ash on maximum thickness of plastic layer of coals, Fuel, 57, 639, 10.1016/0016-2361(78)90195-3