This paper shows an influence of chemical composition of used electrolyte, such as amount of sulphuric acid in electrolyte, amount of aluminium cations in electrolyte and amount of oxalic acid in electrolyte, and operating parameters of process of anodic oxidation of aluminium such as the temperature of electrolyte, anodizing time, and voltage applied during anodizing process. The paper shows the influence of those parameters on the resulting thickness of aluminium oxide layer. The impact of these variables is shown by using central composite design of experiment for six factors (amount of sulphuric acid, amount of oxalic acid, amount of aluminium cations, electrolyte temperature, anodizing time, and applied voltage) and by usage of the cubic neural unit with Levenberg-Marquardt algorithm during the results evaluation. The paper also deals with current densities of 1 A · dm(-2) and 3 A · dm(-2) for creating aluminium oxide layer.

Department of Mathematics Informatics and Cybernetics Faculty of Manufacturing Technologies with a Seat in Prešov Technical University of Košice Bayerova 1 080 01 Prešov Slovakia

Department of Mechanical Engineering Institute of Technology and Businesses in České Budějovice Okružní 10 37001 České Budějovice Czech Republic

Department of Technologies and Materials Faculty of Mechanical Engineering Technical University of Košice Mäsiarska 74 042 00 Košice Slovakia

Zobrazit více v PubMed

Baumeister J., Banhart J., Weber M. Aluminium foams for transport industry. Materials & Design. 1997;18(4–6):217–220. doi: 10.1016/s0261-3069(97)00050-2. DOI

Gombár M., Kmec J., Badida M., Sobotová L., Vagaská A., Michal P. The simulation of the temperature effects on the microhardness of anodic alumina oxide layers. Metalurgija. 2014;53(1):59–62.

Badida M., Gombár M., Kmec J., Sobotová L., Vagaská A., Michal P. Štúdium vplyvu chemického zloženia elektrolytu na mikrotvrdosť vrstvy vytvorenej anodickou oxidáciou hliníka. Chemicke Listy. 2013;107:973–977.

Salmalian K., Soleimani M. Modelling of energy absorption in square cross-section aluminum energy absorbers by hybrid ANFIS networks. International Journal of Mathematical Models and Methods in Applied Sciences. 2011;5(7):1154–1161.

Michal P., Gombár M., Vagaská A., Piteľ J., Kmec J. Experimental study and modeling of the zinc coating thickness. Advanced Materials Research. 2013;712–715:382–386. doi: 10.4028/www.scientific.net/amr.712-715.382. DOI

Tsangaraki-Kaplanoglou I., Theohari S., Dimogerontakis T., et al. Effect of alloy types on the electrolytic coloring process of aluminum. Surface & Coatings Technology. 2006;200(12-13):3969–3979. doi: 10.1016/j.surfcoat.2005.02.174. DOI

Djozan D., Amir-Zehni M. Anodizing of inner surface of long and small-bore aluminum tube. Surface and Coatings Technology. 2003;173(2-3):185–191. doi: 10.1016/S0257-8972(03)00510-3. DOI

Michal P., Vagaská A., Gombár M., Kmec J., Spišák E., Badida M. Prediction of the effect of chemical composition of electrolyte on the thickness of anodic aluminium oxide layer. International Journal of Mathematicals Models and Methods in Applied Sciences. 2014;8:152–155.

Badida M., Gombar M., Sobotova L., Kmec J., Vagaská A., Michal P. The influence of sodium chloride on the resulting AAO film thickness. Advanced Materials Research. 2013;816-817:18–22. doi: 10.4028/www.scientific.net/amr.816-817.18. DOI

Gombár M., Vagaská A., Kmec J., Michal P. Microhardness of the coatings created by anodic oxidation of aluminium. Applied Mechanics and Materials. 2013;308:95–100. doi: 10.4028/www.scientific.net/amm.308.95. DOI

Tsangaraki-Kaplanoglou I., Theohari S., Dimogerontakis T., Wang Y.-M., Kuo H.-H., Kia S. Effect of alloy types on the anodizing process of aluminum. Surface & Coatings Technology. 2006;200(8):2634–2641. doi: 10.1016/j.surfcoat.2005.07.065. DOI

Patermarakis G. Development of a theory for the determination of the composition of the anodizing solution inside the pores during the growth of porous anodic Al2O3 films on aluminium by a transport phenomenon analysis. Journal of Electroanalytical Chemistry. 1998;447(1-2):25–41. doi: 10.1016/s0022-0728(97)00604-9. DOI

Aerts T., de Graeve I., Nelissen G., et al. Experimental study and modelling of anodizing of aluminium in a wall-jet electrode set-up in laminar and turbulent regime. Corrosion Science. 2009;51(7):1482–1489. doi: 10.1016/j.corsci.2008.12.001. DOI

Sahab A. R., Mehrzad Gilmalek Y. An automatic diagnostic machine for ECG arrhythmias classification based on wavelet transformation and neural networks. International Journal of Circuits, Systems and Signal Processing. 2011;5(3):255–262.

Hrehova S., Mizakova J. Using GUI of matlab and fuzzy principles for evaluating of some process quality. International Journal of Fuzzy Systems and Advanced Applications. 2014;1:7–14.

Pohl J., Jirsík V., Honzík P. Stochastic optimization algorithm with probability vector in mathematical function minimization and travelling salesman problem. WSEAS Transactions on Information Science and Applications. 2013;10(8):249–260.

Evin E., Kmec J., Fechová E. Optimizing of electric discharge texturing parameters of rolls of the rolling mill of steel sheets. Applied Mechanics and Materials. 2013;420:78–84. doi: 10.4028/www.scientific.net/amm.420.78. DOI

Vagaská A., Gombár M., Kmec J., Michal P. Statistical analysis of the factors effect on the zinc coating thickness. Applied Mechanics and Materials. 2013;378:184–189. doi: 10.4028/www.scientific.net/AMM.378.184. DOI

Rodriguez R., Bukovsky I., Homma N. Potentials of quadratic neural unit for applications. Journal of Software Science and Computational Intelligence. 2011;3(3):1–12.

Samek D., Varacha P. Time series prediction using artificial neural networks: single and multi-dimensional data. International Journal of Mathematical Models and Methods in Applied Sciences. 2013;7(1):38–46.

Pital J., Mižák J. Computational intelligence and low cost sensors in biomass combustion process. Proceedings of the 3rd IEEE Symposium on Computational Intelligence in Control and Automation (CICA '13); April 2013; Singapore. pp. 181–184. DOI

Vita V., Vitas A., Chatzarakis G. E. Design, implementation and evaluation of an optimal iterative learning control algorithm. WSEAS Transactions on Circuits and Systems. 2011;10(2):39–48.

Kaur B. P., Aggrarwal H. An optimization of a planning information system using fuzzy inference system and adaptive neuro-fuzzy inference system. WSEAS Transactions on Information Science and Applications. 2013;10(8):249–260.

Daqrouq K., Al-Qawasmi A., Daoud O., Al-Sawalmeh W. Self-organizing map weights and wavelet packet entropy for speaker verification. International Journal of Circuits, Systems and Signal Processing. 2012;6(1):12–20.

Lungu M. New non-linear adaptive command system for the aircrafts' attitude control. International Journal of Circuits, Systems and Signal Processing. 2011;5(1):19–28.