Investigation of erosive wear behaviour of tungsten carbide cobalt coated metal matrix composites using ANN
Keywords:
Erosion, SEM, WC-Co, Al2O3, AlAbstract
An artificial neural network (ANN) model was employed on erosive wear result of aluminium 7034 T6 reinforced with different weight percentage of Al2O3 and SiC with tungsten carbide cobalt (WC-Co) coated composites. WC-Co in the form of powder was pretreated before coating, to identify the inflence of pretreatment on the substrate. The WC-Co coating was deposited with high velocity oxy fuel (HVOF) sparay method. The microstructural examination was carried through scanning electron microscope (SEM) and to identify the elemental composition of coated specimens, energy dispersive X-ray analysis (EDX) was used. These material charecterisation shows that pretreated WC-Co coated Al 7034 T6 composites at 500 µm size exhibit thick closely packed, low porosity and good adhesion of membrane, while specimen at 400 µm size showed properties opposite to the 500 µm size speciemen. To predict the erosive wear behaviour of WC-Co coated Al7034 T6 composite, neural network model uses the parameters such as impact velocity, stand-off-distance, erodent temperature, impingement angle, the weight percentage of reinforcement and coating thickness. It is found that predicted values from the artificial neural network can be compared with the experimental result values.Downloads
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H. Yu, Y. Zhengy, and Z. Yao, “Cavitation erosion corrosion behaviour of manganesenickel-aluminum bronze in comparison with manganese-brass,” Journal of Materials Science and Technology Shenyang, vol. 25, pp. 758-766, 2009.
T. Yan, L. Tan, D. Xiong, X. Liu, B. Zhang, and K. Yang, “Fluoride treatment and in vitro corrosion behavior of an AZ31B magnesium alloy,” Materials Science and Engineering C, vol. 30 pp. 740–748, 2010.
Z. B. Qi, B. Liu, Z. T. Wu, F. P. Zhu, Z. C. Wang, and C. H. Wu, “A comparative study of the oxidation behavior of Cr2N and CrN coatings,” Thin Solid Films, vol. 544, pp. 515–520, 2013.
A. Dent, S. DePalo, and S. Sampath, “Examination of the Wear Properties of HVOF Sprayed Nanostructured and Conventional WC-Co Cermets with Different Binder Phase Contents,” Journal of Thermal Spray Technology, vol. 114, pp. 551-558, 2002.
C.-H. Hsu, W.-C. Huang, Y.-P. Lee, and W.- Y. Ho, “Effect of nitrogen atmosphere heat treatment on structure and wear behavior of CrAlSiN nanocomposite film,” Surface & Coatings Technology, vol. 320, pp. 230–234, 2017.
T. Sahraoui, S. Guessasma, M. A Jeridane, and M. Hadji, “HVOF sprayed WC–Co coatings: Microstructure, mechanical properties and friction moment prediction,” Materials & Design, vol. 31(3), pp. 1431-7, 2010.
J. M. Guilemany, S. Dosta, J. Nin, and J. R. Miguel, “Study of the properties of WC-Co nanostructured coatings sprayed by highvelocity Oxyfuel,” Journal of thermal spray technology, vol. 14(3), pp. 405-413, 2005.
A. M. S. Hamouda, S. Sulaiman, T. R. Vijayaram, M. Sayuti, and M. H. M. Ahmad, “Processing and characterization of particulate reinforced aluminium silicon matrix composite,” Journal of Achievements in Materials and Manufacturing Engineering, vol. 25, pp.12-16, 2007.
N. Miyazaki, “Solid particle erosion of composite materials: A critical review,” Journal of Composite Materials, vol. 50 (23), pp. 3175-3217, 2016.
M. Pasha and M. Kaleemulla, “Taguchi approach to influence of processing parameters on erosive wear behaviour of Al7034-T6 composites,” Transactions of Nonferrous Metals Society of China, vol. 27, pp. 2163−2171, 2017.
S. C. Vettivel, N. Selvakumar, and N. Leema, “Experimental and prediction of sintered Cu– W composite by using artificial neural networks,” Materials and Design, vol. 45, pp.323–335. 2013.
L. A. Dobrzański and R. Honysz, “Application of artificial neural networks in modelling of normalised structural steels mechanical properties,” Journal of Achievements in Materials and Manufacturing Engineering, vol. 32 :1, pp. 37-45, 2009.
X. Shen, X. Wang, F. Sun, and C. Ding, “Sandblasting pretreatment for deposition of diamond films on WC-Co hard metal substrates,” Diamond & Related Materials, vol. 73, pp. 7–14, 2017.
J. A. Lee, D. P. Almond, and B. Harris, “The use of neural networks for the prediction of fatigue lives of composite materials,” Composites: Part A, vol. 30:11, pp. 59–69, 1999.
Z. Jiahua, S. Yijun, F. Xin, W. Huaiyuan, and L. Xiaohua, “Prediction on tribological properties of carbon fiber and TiO2 synergistic reinforced polytetrafluoro ethylene composites with artificial neural networks,” Materials & Design, vol. 30, pp. 1042-9, 2009.
Z. Zhang and K. Friedrich, “Artificial neural networks applied to polymer composites: a review,” Composites Science and Technology, vol. 63, pp. 2029–2044, 2003.
K. L. Rutherford, P. W. Hatto, C. Davies, and I. M Hutchings, “Abrasive wear resistance of TiN/NbN multi-layers: measurement and neural network modelling,” Surface and Coatings Technology, vol. 86–87, pp. 472–9, 1996.
S. P. Jones, R. Jansen, and R. L. Fusaro, “Preliminary investigation of neural network techniques to predict tribological properties,” Tribology Transactions, vol. 40:2, pp. 312– 20, 1997.
S. A. Kalogirou, “Artificial neural networks in renewable energy systems applications: a review,” Renewable, and Sustainable Energy Reviews, vol. 5:4, pp. 373–401, 2001.
J. Musil andJ. Vlček, “Magnetron sputtering of hard nanocomposite coatings and their properties,” Surface Coating Technology, vol. 142–144, pp. 557–566, 2001.
P. Patsalas, C. Charitidis, and S. Logothetidis, “The effect of substrate temperature and biasing on the mechanical properties and structure of sputtered titanium nitride thin films,” Surface Coating Technology, vol. 125, pp. 335–340, 2000.
J. M. Guilemany, J. M. de Paco, J. Nutting, and J. R. Miguel, “Characterization of the W2C Phase Formed during the HVOF Spraying of a WC-12Co Powder,” Metallurgical, and Material Transaction A, vol. 30, pp. 1913-1921, 1999.
C. Verdon, A. Karimi, and J. L. Martin, “A Study of High Velocity Oxy- Fuel Thermally Sprayed Tungsten Carbide Based Coatings Part 1,” Microstructures, Material Science and Engineering A, vol. 246, pp. 11-24, 1998.
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