DocumentCode
3706873
Title
Genetic algorithm based X-ray diffraction analysis for chemical control of aluminium smelters baths
Author
Shakhnaz Akhmedova;Igor Yakimov;Aleksandr Zaloga;Sergey Burakov;Eugene Semenkin;Petr Dubinin;Oksana Piksina;Eugene Andryushenko
Author_Institution
Siberian State Aerospace University, Krasnoyarsk, Russia
Volume
1
fYear
2015
fDate
7/1/2015 12:00:00 AM
Firstpage
32
Lastpage
39
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.
Keywords
"Genetic algorithms","Crystals","X-ray diffraction","X-ray scattering","Diffraction","Aluminum","Powders"
Publisher
ieee
Conference_Titel
Informatics in Control, Automation and Robotics (ICINCO), 2015 12th International Conference on
Type
conf
Filename
7350441
Link To Document