Genetic algorithm for automated X-ray diffraction full-profile analysis of electrolyte composition on aluminium smelters

Описание

Тип публикации: статья из журнала (материалы конференций, опубликованные в журналах)

Конференция: 12th International Conference on Informatics in Control, Automation and Robotics, ICINCO 2015; Colmar, France; Colmar, France

Год издания: 2016

Идентификатор DOI: 10.1007/978-3-319-31898-1_5

Ключевые слова: Aluminium electrolyte, Aluminium industry, Bath ratio, Chemical control, Cryolite ratio, Genetic algorithms, Rietveld method, X-ray diffraction analysis, Algorithms, Alumina, Aluminum, Automation, Carrier concentration, Chemical analysis, Crystal atomic structure, Crystal structure, Fluorine compounds, Information science, Least squares approximations, Optimization, Robotics, Structure (composition), X ray diffraction analysis, Chemical controls, Composition characteristics, Electrolyte compositions, Microcrystalline structures, Nonlinear least squares methods, Electrolytes

Аннотация: Aluminium is produced by means of the electrolysis of alumina in molten fluoride salts. A certain proportion of the fluoride compounds continuously evaporates, and this negatively impacts on the optimal composition of the electrolyte in the electrolytic baths. It means that a regular adjustment of the electrolyte composition is reqПоказать полностьюuired by the addition of fluorides based on the results of the automatic express analysis of the electrolyte. TheXRDphase analysis of crystallized electrolyte samples automatically performs the control of the main composition characteristics. This method, most frequently implemented in conjunction with aluminium smelters, necessitates periodic calibrationwith reference samples, whose phase composition is known exactly. The preparation of such samples is relatively complex since samples include 5-6 different phases with variable microcrystalline structure. One further diffraction method is the Rietveld method, which can be implemented without the use of reference samples. The method is based on the modelling of the experimental powder patterns of crystalline samples as the sumof the powder patterns of comprised phases, calculated from their atomic crystal structure. Included in the simulation is a refinement of the profile parameters and crystal structure of phases using the nonlinear least squares method. The difficulty associated with the automation of this approach is that a set of initial values for the parameters must be inputted that must be automatically refined by LSM to exact values. In order to resolve this problem, an optimization method was put forward by the article based on an evolutionary choice of initial values of profile and structural parameters using a genetic algorithm. The criterion of the evolution is the minimization of the profile R-factor, which represents the weighted discrepancy between the experimental and model powder patterns of the electrolyte sample. It is established that this approach achieves the required level of accuracy and complete automation of the electrolyte composition control. © Springer International Publishing Switzerland 2016.

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Издание

Журнал: (21 July 2015 through 23 July 2015

Выпуск журнала: Vol. 383

Номера страниц: 79-93

Авторы

  • Akhmedova Sh.A. (Siberian State Aerospace University)
  • Burakov S.V. (Siberian State Aerospace University)
  • Semenkin E.S. (Siberian State Aerospace University)
  • Zaloga A.N. (Siberian Federal University)
  • Yakimov I.S. (Siberian Federal University)
  • Dubinin P.S. (Siberian Federal University)
  • Piksina O.E. (Siberian Federal University)
  • Andryushchenko E.S. (Siberian Federal University)

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