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《工程(英文)》 >> 2021年 第7卷 第9期 doi: 10.1016/j.eng.2020.11.012

基于子带瞬时能量谱的铝电解槽电压槽况敏感频域分段方法

a School of Automation, Central South University, Changsha 410083, China
b Key Laboratory of Intelligent Computing & Information Processing, Ministry of Education, Xiangtan University, Xiangtan 411105, China c School of Metallurgy and Environment, Central South University, Changsha 410083, China

收稿日期: 2020-07-12 修回日期: 2020-10-16 录用日期: 2020-11-23 发布日期: 2021-07-28

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摘要

槽电压是广泛使用且可在线测量的铝电解槽信号,多种电解槽槽况分析和控制用参数由槽电压计算得到。槽电压频域分段是设计获取这些参数的数字滤波器通带的依据。在对槽电压定性分析的基础上,本文提出子带瞬时能量谱(sub-band Instantaneous energy spectrum, SIEP),并用其对多种槽况下槽电压的频域特性进行定量表示,最终给出了槽电压槽况敏感频域分段方法。该频域分段方法将槽电压有效频段划分为低频信号区[0, 0.001] Hz和低频噪声区[0.001, 0.050] Hz;将低频噪声区再细分为[0.001, 0.010] Hz的铝液异常波动频段和[0.01, 0.05] Hz 的次低频噪声频段。与基于经验模态分解的瞬时能量谱比较,SIEP能更精细地表示槽电压有效频段内任意频段的能量随时间变化规律。该槽电压频域分段方法对槽况更敏感,可更细致地获取在线槽况信息,为工业电解槽槽况监测和控制决策提供更可靠、准确的在线依据。

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参考文献

[ 1 ] Blatch GI, Taylor MP, Fyfe M, inventors; Comalco Aluminum Ltd., assignee. Process for controlling aluminum smelting cells. United States Patent US 5089093. 1992 Feb 18.

[ 2 ] Simakov DA, Gusev AO, Bakin KB, inventors; United Company RUSAL Engineering and Technology LLC., assignee. Method for controlling an alumina feed to electrolytic cells for producing aluminum. United States Patent US 10472725. 2019 Nov 12.

[ 3 ] Schneller MC. In situ alumina feed control. JOM 2009;61(11):26–9. 链接1

[ 4 ] Schneller M, inventor. Aluminum production process control. United States Patent US 8052859. 2011 Nov 8.

[ 5 ] Zhou K, Lin Z, Yu D, Cao B, Wang ZQ, Guo S. Cell resistance slope combined with LVQ neural network for prediction of anode effect. In: Proceedings of 2015 Sixth International Conference on Intelligent Control and Information Processing (ICICIP); 2015 Nov 26–28; Wuhan, China; 2016. New York City: IEEE; 2016. p. 47–51. 链接1

[ 6 ] Meghlaoui A, inventor; Dubai Aluminium Company Ltd., assignee. Intelligent process control using predictive and pattern recognition techniques. United States Patent US 6609119. 2003 Aug 19.

[ 7 ] Thonstad J, Utigard TA, Vogt H. On the anode effect in aluminum electrolysis. In: Bearne G, Dupuis M, Tarcy G, editors. Essential readings in light metals. Cham: Springer; 2016. p. 131–8. 链接1

[ 8 ] Haurpin WE. Polarization in an aluminum reduction cell. J Electrochem Soc 1956;103(3):174–8. 链接1

[ 9 ] Bearne GP. The development of aluminum reduction cell process control. JOM 1999;51(5):16–22. 链接1

[10] Banta L, Dai C, Biedler P. Noise classification in the aluminum reduction process. In: Bearne G, Dupuis M, Tarcy G, editors. Essential readings in light metals. Cham: Springer; 2016. p. 812–6. 链接1

[11] Ding L, Zeng SP, Zeng Z. Spectral analysis of cell resistance signals in 350 kA aluminum reduction cells. Tech Autom Appl 2005;24(12):68–77. Chinese. 链接1

[12] Xiao J, Li J, Yang JH, Zou Z, Ye SL. Effect of line current fluctuation on process control of aluminium electrolysis. Mining Metall Eng 1999;19(3):44–6. Chinese. 链接1

[13] Bonny P, Gerphagnon JL, Laboure G, Keinborg M, Homsi P, Langon B, inventors; Pechiney, assignee. Process and apparatus for accurately controlling the rate of introduction and the content of alumina in an igneous electrolysis tank in the production of aluminium. United States Patent US 4431491. 1984 Feb 14.

[14] Zeng Z, Gui W, Chen X, Xie Y, Wu R. A mechanism knowledge-driven method for identifying the pseudo dissolution hysteresis coefficient in the industrial aluminium electrolysis process. Control Eng Pract 2020;102:104533. 链接1

[15] Homsi P, Peyneau JM, Reverdy M. Overview of process control in reduction cells and potlines. In: Bearne G, Dupuis M, Tarcy G, editors. Essential readings in light metals. Cham: Springer; 2016. p. 739–46. 链接1

[16] Verdenik A. Analysis and visualization of aluminum reduction cell noise based on wavelet transform. In: Williams E, editor. Light metals 2016. Cham: Springer International Publishing; 2016. p. 403–8. 链接1

[17] Li J, Liu Y, Huang Y, Wang H. Studies on the modelling of control signal filtering and noise analysis for the aluminium electrolytic process. J Cent South Inst Min Metall 1993;24(3):318–25. Chinese. 链接1

[18] Dupuis M. Cell voltage noise removal and cell voltage (or resistance) slope calculation. IFAC Proc 2007;40(11):490–2. 链接1

[19] Li M, Cui Y, Yang J, Hao D. An adaptive multi-domain fusion feature extraction with method HHT and CSSD. Acta Electron Sin 2013;41(12):2479–86. Chinese. 链接1

[20] Huang NE, Shen Z, Long SR. A new view of nonlinear water waves: the Hilbert spectrum. Annu Rev Fluid Mech 1999;31(1):417–57. 链接1

[21] Mallat S. A wavelet tour of signal processing. 3rd ed. San Diego: Academic Press; 2008. p. 11–4. 链接1

[22] Cohen L. Time–frequency distributions—a review. Proc IEEE 1989;77 (7):941–81. 链接1

[23] Qian S, Chen D. Joint time–frequency analysis. IEEE Signal Process Mag 1999;16(2):52–67. 链接1

[24] Hess-Nielsen N, Wickerhauser NMV. Wavelets and time–frequency analysis. Proc IEEE 1996;84(4):523–40. 链接1

[25] Bolós VJ, Benítez R. The wavelet scalogram in the study of time series. In: Casas E, Martínez V, editors. Advances in differential equations and applications. Cham: Springer International Publishing; 2014. p. 147–54. 链接1

[26] Tomasson GG, Melville WK. Geostrophic adjustment in a channel: nonlinear and dispersive effects. J Fluid Mech 1992;241:23–57. 链接1

[27] Urata N. Wave mode coupling and instability in the internal wave in aluminum reduction cells. In: Bearne G, Dupuis M, Tarcy G, editors. Essential readings in light metals. Cham: Springer; 2016. p. 373–8. 链接1

[28] Chiampi M, Repetto M, Chechurin V, Kalimov A, Leboucher L. Magnetic modeling and magneto–hydro–dynamic simulation of an aluminum production electrolytic cell. Compel Int J Comp Math Electr Electron Eng 1999;18(3):528–38. 链接1

[29] Xu Y, Li J, Zhang H, Lai Y. MHD calculation for aluminium electrolysis based on nonlinear shallow water model. Chin J Nonferrous Met 2011;21(1):191–7. Chinese. 链接1

[30] Wang Z, Feng N, Peng J, Wang Y, Qi X. Study of surface oscillation of liquid aluminum in 168 kA aluminum reduction cells with a new type of cathode design. In: Johnson JA, editor. Light metals 2010. Seattle: The Minerals, Metals & Materials Society; 2010. p. 485–8. 链接1

[31] Wang Y, Tie J, Tu G, Sun, Zhao R, Zhang Z. Effect of gas bubble on cell voltage oscillations based on equivalent circuit simulation in aluminum electrolysis cell. Trans Nonferrous Met Soc China 2015;25(1):335–44. 链接1

[32] Shen X. The mechanism of voltage fluctuation in aluminum reduction cell and its precautions. Light Met 2008;9:31–5. Chinese. 链接1

[33] Haupin WE. A scanning reference electrode for voltage contours in aluminum smelting cells. JOM 1971;23(10):46–9. 链接1

[34] Zhao ZB. [High temperature experimental study and numerical simulation of bubble dynamics in aluminum electrolytic process] [dissertation]. Shenyang: Northeastern University School of Metallurgy; 2016. Chinese. 链接1

[35] Li J, Tu G, Qi X, Mao J, Lu D, Feng N. Real-time monitoring and analysis on fluctuation state of liquid aluminum in 300 kA and 400 kA aluminum reduction cell. Light Met 2012;2:30–9. Chinese. 链接1

[36] Yang Z. [Causes and treatment measures of voltage pendulum in 300 kA aluminum electrolytic cell]. Technol Enterp 2012;20:289–91. Chinese. 链接1

[37] Mao S, Wang B, Tang Y, Qian F. Opportunities and challenges of artificial intelligence for green manufacturing in the process industry. Engineering 2019;5(6):995–1002. 链接1

[38] Chen H, Jiang B, Lu N. An improved incipient fault detection method based on Kullback–Leibler divergence. ISA Trans 2018;79:127–36. 链接1

[39] Gui W, Chen X, Yang C, Xie Y. Knowledge automation and its industrial application. Sci Sin Inform 2016;46(8):1016–34. Chinese. 链接1

[40] Cai T. Industrial process control systems: research status and development direction. Sci Sin Inform 2016;46(8):1003–15. Chinese. 链接1

[41] Chen H, Jiang B, Ding SX, Lu N, Chen W. Probability-relevant incipient fault detection and diagnosis methodology with applications to electric drive systems. IEEE Trans Control Syst Technol 2019;27(6):2766–73. 链接1

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