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铝电解过程的多维决策系统 被引量:3

Multidimensional Decision System for Aluminium Electrolytic Process
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摘要 基于能量平衡和物料平衡原理,结合工业生产实际,设计了铝电解生产过程多维决策系统;首先基于槽电阻的频域特征,对铝电解槽实施状态诊断;其次确定了温度和氟化铝为主参数的氟化铝挥发速率模型;进一步通过电解质成分的分析和计算,建立了过热度的软测量模型,根据实际测量值在线修正计算结果;文章还以温度、过热度和铝水平划分了工业铝电解槽种槽况,以槽况为基础来决策铝电解过程的设定电压、氟化铝添加量和出铝量;该系统在某厂300kA铝电解槽的控制系统中应用,运行结果表明,电流效率提高,直流电耗明显降低。 The multidimensional decision system for aluminum production was developed based on the energy balance, the material bal ance and also considering the industrial production practice. Firstly, the cell state diagnosis was implemented based on the frequency charac teristics of cell resistance; secondly the aluminum fluoride volatilization rate model was built; thirdly, the superheat soft measurement model was given by use of both the analysis and calculation of electrolyte composition which was on line correction by the actual measured value. This paper made the decision of the voltage setting, A1F3 addition and aluminum tapping amount in aluminum electrolysis process based on the cell condition. This system have been applied in a 300kA aluminum production control system, the results showed that current efficiency Increased, power consumption reduced.
出处 《计算机测量与控制》 北大核心 2013年第10期2783-2785,共3页 Computer Measurement &Control
基金 国家自然科学基金资助项目(50114007)
关键词 铝电解 故障诊断 多维决策 过热度 aluminum electrolysis fault diagnosis multidimensional decision superheat
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参考文献6

  • 1Zeng S P, Li J H. Model Predictive Control of Superheat for Pre- bake Aluminum Production Cells [A]. TMS Light Metals FC] 2008, 347-351.
  • 2Zeng S P, Lin Cui, Li J H. Diagnosis System for Alumina Reduction Based on BP Neural Network [J]. JOURNAL OF COMPUTERS, 2012, 7 (4). 929-933.
  • 3Berlezin A I. Bath superheat to control electrolysis process TMS Light Metals EC. 2007.- 545 - 550.
  • 4曾水平,李晋宏.300kA铝电解槽过热度计算与控制[A].第八届全球智能控制与自动化大会[c].2010,4755-4760.
  • 5曾水平,吴连成.铝电解过程温度的模糊模式识别[J].模式识别与人工智能,2001,14(4):466-469. 被引量:11
  • 6王坚,赵志强,曾水平,包昌,刘强.多维决策系统在300kA预焙铝电解槽温度控制中的应用[J].冶金自动化,2010,34(1):54-57. 被引量:1

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