A New Analytical Method for Reduction Process of Iron Ore Based on the Power Spectrum
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A series of direct smelting reduction experiment has been implemented with different iron ore bases by thermogravimetric analyzers. The derivative thermogravimetric data have been obtained from these experiments. The data are then decomposed by the technology of empirical mode decomposition to receive its embedded characteristics of the power spectrum. Secondly, based on the obtained power spectrum, the energy transferring behavior for reduction process of iron oxide is analyzed and is compared with other methods (i.e., analytical reagent). Finally, the desired spectral characteristics of the power spectrum for the reduction process of Huimin iron ore can be determined. The result would play a significant role in strengthening the smelting process of Huimin iron ore.
KeywordsDerivative thermogravimetric (DTG) Empirical mode decomposition (EMD) Power spectrum Energy transfer
- Donskoi E, Liu F, McElwain DLS (1998) Two-dimensional modelling of nonisothermal reduction of an iron ore-coal composite pellet. In: Noye BJ, Teubner M, Gill A (eds) Computational techniques and applications: CTAC97. World Scientific Publishing Co, Adelaide, pp 193–200Google Scholar
- Granett BR, Guzzo L, Coupon J, Arnouts S, Hudelot P, Ilbert O, Mccracken HJ, Mellier Y, Adami C, Bel J, Bolzonella M, Bottini D, Cappi A, Cucciati O, De La Torre S, Franzetti P, Fritz A, Garilli B, Iovino A, Krywult J, Le Brun V, Le Fevre O, Maccagni D, Malek K, Marulli F, Meneux B, Paioro L, Polletta M, Pollo A, Scodeggio M, Schlagenhaufer H, Tasca L, Tojeiro R, Vergani D, Zanichelli A (2011) The power spectrum from the angular distribution of galaxies in the CFHTLS-Wide fields at redshift ~ 0.7. Mon Not R Astron Soc 421:251–261. https://doi.org/10.1111/j.1365-2966.2011.20297.x CrossRefGoogle Scholar
- Huang NE, Shen Z, Long SR, Wu MC, Shih HH, Zheng Q, Yen NC, Tung CC, Liu HH (1998) The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis. Proc R Soc A Math Phys Eng Sci 454:903–995. https://doi.org/10.1098/rspa.1998.0193 MathSciNetCrossRefzbMATHGoogle Scholar
- Martinez-Gonzalez E (2008) Cosmic microwave background anisotropies: the power spectrum and beyond. In: Martinez V, Saar E, Gonzales E, Pons-Borderia M (eds) Data analysis in cosmology, vol 665. Lecture notes in physics. Springer, Berlin, pp 79–120. https://doi.org/10.1007/978-3-540-44767-2_4 CrossRefGoogle Scholar