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Received June 10, 2015
Accepted January 6, 2016
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This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/bync/3.0) which permits
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Intelligent identification of the flow regimes of two-component particles in a fluidized bed with the optimized fuzzy c-means clustering algorithm
Key Laboratory of Energy Thermal Conversion and Control of Ministry of Education, School of Energy and Environment, Southeast University, Nanjing 210096, China 1Engineering Design & Research Institute, Southeast University, Nanjing 210096, China
zzhong@seu.edu.cn
Korean Journal of Chemical Engineering, May 2016, 33(5), 1674-1680(7)
https://doi.org/10.1007/s11814-016-0006-9
https://doi.org/10.1007/s11814-016-0006-9
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Abstract
Flow regime identification is important in the application of fluidized beds. This paper provides a method for deciding flow regime number by objective criterion. The optimized fuzzy c-means clustering algorithm was used to cluster the flow regime classification of two-component particles in a fluidized bed. The genetic algorithm was applied to optimize the initial center clusters of fuzzy c-means clustering. Hilbert-Huang transform was applied to analyze pressure fluctuation signals and extract the characteristic parameters. Three clusters were found and respectively ascribed to three flow regimes: bubbling bed, slugging bed, and turbulent bed. A multilayer neural network was used to train and test the identification system of the flow regimes. The identification accuracies of bubbling bed, slugging bed, and turbulent bed can reach 91.67%, 92.85%, and 91.30%, respectively
Keywords
References
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Coppens MO, van Ommen JR, Schouten JC, Chem. Eng. J., 96(1-3), 1 (2003)
Yang TY, Leu LP, Chem. Eng. Sci., 63, 7 (2008)
Kuhn FT, Schouten JC, Mudde RF, vandenBleek CM, Scarlett B, Meas. Sci. Technol., 7, 3 (1996)
van der Schaaf J, van Ommen JR, Takens F, Schouten JC, van den Bleek CM, Chem. Eng. Sci., 59, 8 (2004)
Briongos JV, Aragon JM, Palancar MC, Powder Technol., 162, 2 (2006)
Briongos JV, Aragon JA, Palancar MC, Chem. Eng. Sci., 62, 11 (2007)
Karimi M, Mostoufi N, Zarghami R, Sotudeh-Gharebagh R, Chem. Eng. Sci., 66, 20 (2011)
Ji HS, Ohara H, Kuramoto K, Tsutsumi A, Yoshida K, Hirama T, Chem. Eng. Sci., 55, 2 (2000)
Lin TJ, Juang RC, Chen YC, Chen CC, Chem. Eng. Sci., 56, 3 (2001)
Llop MF, Jand N, Gallucci K, Llauro FX, Chem. Eng. Sci., 71, 252 (2012)
Johnsson F, Zijerveld RC, Schouten JC, van den Bleek CM, Leckner B, Int. J. Multiph. Flow, 26, 4 (2000)
Haubein NC, Broadbelt LJ, Schlosberg RH, Ind. Eng. Chem. Res., 43(1), 18 (2004)
Bi HT, Chem. Eng. Sci., 62, 13 (2007)
Sasic S, Leckner B, Johnsson F, Prog. Energy Combust. Sci., 33, 5 (2007)
van Ommen JR, Sasic S, van der Schaaf J, Gheorghiu S, Johnsson F, Coppens MO, Int. J. Multiph. Flow, 37, 5 (2011)
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Miin CS, Sulaiman SA, Raghavan VR, Heikal MR, Naz MY, Korean J. Chem. Eng., 32, 11 (2015)
Bezdek JCDJC, IEEE Transactions on Computers, 835 (1975)
Bezdek JC, Ehrlich R, Full W, Computers Geosciences, 10, 2 (1984)
