Genetic Algorithm based X-Ray Diffraction Analysis for Chemical Control of Aluminium Smelters Baths

Shakhnaz Akhmedova, Igor Yakimov, Aleksandr Zaloga, Sergey Burakov, Eugene Semenkin, Petr Dubinin, Oksana Piksina, Eugene Andryushenko

Abstract

Aluminium production is based on the high-temperature electrolysis of alumina in molten fluoride salts. Part of the fluoride compounds continuously evaporates, which violates the optimal composition of the electrolyte in the electrolytic baths. It causes a technological necessity for regular adjustment of the electrolyte composition by the addition of fluorides according to results of automatic express analysis of the electrolyte. Control of the main composition characteristics is performed automatically by XRD phase analysis of crystallized electrolyte samples. The XRD method, usually used on aluminium smelters, requires periodic calibration with reference samples, whose phase composition is exactly known. The preparation of such samples is a rather complicated problem because samples include 5-6 different phases with variable microcrystalline structure. An alternative diffraction method is the Rietveld method, which does not require reference samples to be used. The method is based on the modelling of the experimental powder patterns of electrolyte samples as the sum of the phase of component powder patterns, calculated from their atomic crystal structure. The simulation includes a refinement of the profile parameters and crystal structure of phases by the nonlinear least squares method (LSM). The problem with the automation of this approach is the need to install a set of initial values of the parameters that can and should be automatically refined by LSM to exact values. To solve this problem, the article proposed an optimization method 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 shown that this approach provides the necessary accuracy and complete automation of the electrolyte composition control.

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Paper Citation


in Harvard Style

Akhmedova S., Yakimov I., Zaloga A., Burakov S., Semenkin E., Dubinin P., Piksina O. and Andryushenko E. (2015). Genetic Algorithm based X-Ray Diffraction Analysis for Chemical Control of Aluminium Smelters Baths . In Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 978-989-758-122-9, pages 32-39. DOI: 10.5220/0005561900320039


in Bibtex Style

@conference{icinco15,
author={Shakhnaz Akhmedova and Igor Yakimov and Aleksandr Zaloga and Sergey Burakov and Eugene Semenkin and Petr Dubinin and Oksana Piksina and Eugene Andryushenko},
title={Genetic Algorithm based X-Ray Diffraction Analysis for Chemical Control of Aluminium Smelters Baths},
booktitle={Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},
year={2015},
pages={32-39},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005561900320039},
isbn={978-989-758-122-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - Genetic Algorithm based X-Ray Diffraction Analysis for Chemical Control of Aluminium Smelters Baths
SN - 978-989-758-122-9
AU - Akhmedova S.
AU - Yakimov I.
AU - Zaloga A.
AU - Burakov S.
AU - Semenkin E.
AU - Dubinin P.
AU - Piksina O.
AU - Andryushenko E.
PY - 2015
SP - 32
EP - 39
DO - 10.5220/0005561900320039