Abstract
In this study, the surface of AZ91D magnesium alloy was coated with ZrO2–wt.-% 22 MgO by the plasma spray method. The coatings were made at two different current levels (600 and 500 A) and three different spraying distances (120, 130 and 140 mm). The surface roughness was measured by a profilometer and hardness was measured via a microhardness test. Coated cross-sections were examined under an optical microscope (OM) and scanning electron microscope (SEM). The phases formed on the coating surfaces were detected by x-ray diffractometer (XRD). A dry sliding wear test was performed at 5, 7.5 and 10 N normal loads. Mg2Zr5O12, ZrO2, MgO, and Zr formed on the coating layers. Surface roughness and porosity percentages were enhanced by increasing the spray distance and decreasing current. The maximum microhardness value was reached at 1152 (HV0.1), and significant improvements were observed in the wear resistance of the coatings compared with that of the AZ91D. An extreme learning machine (ELM) algorithm, which is one of the machine learning algorithms, was applied to the wear loss data obtained. The success rate for the model designed using the ELM algorithm, was calculated as 0.9287 (R-squared).
References
1 Z. Bi , D. W.Mueller: Friction predication on pin-to-plate interface of PTFE material and steel, Friction (2018), pp. 1–1410.1007/s40544-018-0224-8Search in Google Scholar
2 H. Wang , G.Ma, B.Xu, Q.Yong, P.He: Design and application of friction pair surface modification coating for remanufacturing, Friction5 (2017), No. 3, pp. 351–36010.1007/s40544-017-0185-3Search in Google Scholar
3 Z. Chen , I.Etsion: Model for the static friction coefficient in a full stick elastic-plastic coated spherical contact, Friction (2018), pp. 1–1210.1007/s40544-018-0251-5Search in Google Scholar
4 D. Nam , D.Lim, S.-D.Kim, D.Seo, S. E.Shim, S.-H.Baeck: The fabrication of a conversion film on AZ31 containing carbonate product and evaluation of its corrosion resistance, Journal of Alloys and Compounds737 (2018), pp. 597–60210.1016/j.jallcom.2017.12.061Search in Google Scholar
5 D. Chen , R.Wang, Z.Huang, Y.Wu, Y.Zhang, G.Wu, D.Li, C.Guo, G.Jiang, S.Yu: Evolution processes of the corrosion behavior and structural characteristics of plasma electrolytic oxidation coatings on AZ31 magnesium alloy, Applied surface science434 (2018), pp. 326–33510.1016/j.apsusc.2017.09.232Search in Google Scholar
6 M Nouri , D.Li: Maximizing the benefit of aluminizing to AZ31 alloy by surface nanocrystallization for elevated resistance to wear and corrosive wear, Tribology International111 (2017), pp. 211–21910.1016/j.triboint.2017.03.009Search in Google Scholar
7 D. Thirumalaikumarasamy , K. S.Kamalamoorthy, V. B.Visvalingam: Effect of experimental parameters on the micro hardness of plasma sprayed alumina coatings on AZ31B magnesium alloy, Journal of Magnesium and Alloys3 (2015), No. 3, pp. 237–24610.1016/j.jma.2015.06.002Search in Google Scholar
8 T. Kubatík , Z.Pala, K.Neufuss, M.Vilémová, R.Mušálek, J.Stoulil, P.Slepička, T.Chráska: Metallurgical bond between magnesium AZ91 alloy and aluminium plasma sprayed coatings, Surface and Coatings Technology282 (2015), pp. 163–17010.1016/j.surfcoat.2015.10.032Search in Google Scholar
9 İ. Çelik : Structure and surface properties of Al2O3–TiO2 ceramic coated AZ31 magnesium alloy, Ceramics International42 (2016), No. 12, pp. 13659–1366310.1016/j.ceramint.2016.05.162Search in Google Scholar
10 D. Thirumalaikumarasamy , V.Balasubramanian, S. S.Sabari: Prediction and optimization of process variables to maximize the Young's modulus of plasma sprayed alumina coatings on AZ31B magnesium alloy, Journal of Magnesium and Alloys5 (2017), No. 1, pp. 133–14510.1016/j.jma.2017.02.002Search in Google Scholar
11 D. Thirumalaikumarasamy , K.Shanmugam, V.Balasubramanian: Corrosion performance of atmospheric plasma sprayed alumina coatings on AZ31B magnesium alloy under immersion environment, Journal of Asian Ceramic Societies2 (2014), No. 4, pp. 403–41510.1016/j.jascer.2014.08.006Search in Google Scholar
12 E. Śnieżek , J.Szczerba, P.Stoch, R.Prorok, I.Jastrzębska, W.Bodnar, E.Burkel: Structural properties of MgO–ZrO2 ceramics obtained by conventional sintering, arc melting and field assisted sintering technique, Materials and Design99 (2016), pp. 412–42010.1016/j.matdes.2016.03.106Search in Google Scholar
13 Y. Ozbek , V.Ucar, A.Demirkiran: Tribological properties of MgZrO3 coatings deposited by plasma spraying, Metallic Materials46 (2008), No. 1, pp. 27–32Search in Google Scholar
14 Y. Gao , M.Jie, Y.Liu: Mechanical properties of Al2O3 ceramic coatings prepared by plasma spraying on magnesium alloy, Surface and Coatings Technology315 (2017), pp. 214–21910.1016/j.surfcoat.2017.02.026Search in Google Scholar
15 T. Kubatík , F.Lukáč, J.Stoulil, P.Ctibor, F.Průša, K.Stehlíková: Preparation and properties of plasma sprayed NiAl10 and NiAl40 coatings on AZ91 substrate, Surface and Coatings Technology319 (2017), pp. 145–15410.1016/j.surfcoat.2017.03.064Search in Google Scholar
16 Y. Ge , W.Wang, X.Wang, Z.Cui, B.Xu: Study on laser surface remelting of plasma-sprayed Al–Si/1 wt% nano-Si3N4 coating on AZ31B magnesium alloy, Applied surface science273 (2013), pp. 122–12710.1016/j.apsusc.2013.01.204Search in Google Scholar
17 J. Xu , B.Zou, S.Zhao, Y.Hui, W.Huang, X.Zhou, Y.Wang, X.Cai, X.Cao: Fabrication and properties of ZrC–ZrB2/Ni cermet coatings on a magnesium alloy by atmospheric plasma spraying of SHS powders, Ceramics International40 (2014), No. 10, pp. 15537–1554410.1016/j.ceramint.2014.07.029Search in Google Scholar
18 B. Zou , S.Tao, W.Huang, Z. S.Khan, X.Fan, L.Gu, Y.Wang, J.Xu, X.Cai, H.Ma: Synthesis and characterization of in situ TiC–TiB2 composite coatings by reactive plasma spraying on a magnesium alloy, Applied Surface Science264 (2013), pp. 879–88510.1016/j.apsusc.2012.10.177Search in Google Scholar
19 C. Li , Y.Wang, S.Wang, L.Guo: Laser surface remelting of plasma-sprayed nanostructured Al2O3–13 wt% TiO2 coatings on magnesium alloy, Journal of Alloys and Compounds503 (2010), No. 1, pp. 127–13210.1016/j.jallcom.2010.04.215Search in Google Scholar
20 A. Abdel-Samad , A.El-Bahloul, E.Lugscheider, S.Rassoul: A comparative study on thermally sprayed alumina based ceramic coatings, Journal of materials science35 (2000), No. 12, pp. 3127–313010.1023/A:1004824104162Search in Google Scholar
21 H. Chen , Y.Zhang, C.Ding: Tribological properties of nanostructured zirconia coatings deposited by plasma spraying, Wear253 (2002), No. 7–8, pp. 885–89310.1016/S0043-1648(02)00221-1Search in Google Scholar
22 J. Li , H.Liao, X.Wang, B.Normand, V.Ji, C.Ding, C.Coddet: Improvement in wear resistance of plasma sprayed yttria stabilized zirconia coating using nanostructured powder, Tribology International37 (2004), No. 1, pp. 77–8410.1016/S0301-679X(03)00138-5Search in Google Scholar
23 P. Senthil Kumar , K.Manisekar, R.Narayanasamy: Experimental and prediction of abrasive wear behavior of sintered Cu-SiC composites containing graphite by using artificial neural networks, Tribology Transactions57 (2014), No. 3, pp. 455–47110.1080/10402004.2014.880979Search in Google Scholar
24 A. K. F. Hassan , S.Mohammed: Artificial neural network model for estimation of wear and temperature in pin-disc contact, Universal Journal of Mechanical Engineering4 (2016), No. 2, pp. 39–4910.13189/ujme.2016.040204Search in Google Scholar
25 Ž. Ćojbašić , D.Petković, S.Shamshirband, C. W.Tong, S.Ch, P.Janković, N.Dučić, J.Baralić: Surface roughness prediction by extreme learning machine constructed with abrasive water jet, Precision Engineering43 (2016), pp. 86–9210.1016/j.precisioneng.2015.06.013Search in Google Scholar
26 S. Cho , S.Asfour, A.Onar, N.Kaundinya: Tool breakage detection using support vector machine learning in a milling process, International Journal of Machine Tools and Manufacture45 (2005), No. 3, pp. 241–24910.1016/j.ijmachtools.2004.08.016Search in Google Scholar
27 L. Ward , A.Agrawal, A.Choudhary, C.Wolverton: A general-purpose machine learning framework for predicting properties of inorganic materials, Computational Materials2 (2016), pp. 1–710.1038/npjcompumats.2016.28Search in Google Scholar
28 O. Altay , M.Ulas, Prediction of the autism spectrum disorder diagnosis with linear discriminant analysis classifier and K-nearest neighbor in children, A.Varol, M.Karabatak, CihanVarol (Eds.): Proc. of the IEEE 6th International Symposium on Digital Forensic and Security, IEEE, New York (2018), pp. 1–4Search in Google Scholar
29 M. Açikgenç , M.Ulaş, K. E.Alyamaç: Using an artificial neural network to predict mix compositions of steel fiber-reinforced concrete, Arabian Journal for Science and Engineering40 (2015), No. 2, pp. 407–41910.1007/s13369-014-1549-xSearch in Google Scholar
30 K. V. Rao , B.Murthy, N. M.Rao: Prediction of cutting tool wear, surface roughness and vibration of work piece in boring of AISI 316 steel with artificial neural network, Measurement51 (2014), pp. 63–7010.1016/j.measurement.2014.01.024Search in Google Scholar
31 D. C. Montgomery , E. A.Peck, G. G.Vining: Introduction to Linear Regression Analysis, 5th Ed., John Wiley & Sons, New York, USA (2012)Search in Google Scholar
32 J. Sun , M.Rahman, Y.Wong, G.Hong: Multiclassification of tool wear with support vector machine by manufacturing loss consideration, International Journal of Machine Tools and Manufacture44 (2004), No. 11, pp. 1179–118710.1016/j.ijmachtools.2004.04.003Search in Google Scholar
33 Q.-Y. Zhu , A. K.Qin, P. N.Suganthan, G.-B.Huang: Evolutionary extreme learning machine, Pattern Recognition38 (2005), No. 10, pp. 1759–176310.1016/j.patcog.2005.03.028Search in Google Scholar
34 G.-B. Huang , Q.-Y.Zhu, C.-K.Siew: Extreme learning machine: Theory and applications, Neurocomputing70 (2006), No. 1–3, pp. 489–50110.1016/j.neucom.2005.12.126Search in Google Scholar
35 G.-B. Huang , H.Zhou, X.Ding, R.Zhang: Extreme learning machine for regression and multiclass classification, IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics42 (2012), No. 2, pp. 513–52910.1109/TSMCB.2011.2168604Search in Google Scholar
36 O. Bilhan , M. E.Emiroglu, C. J.Miller, M.Ulas: The evaluation of the effect of nappe breakers on the discharge capacity of trapezoidal labyrinth weirs by ELM and SVR approaches, Flow Measurement and Instrumentation64 (2018), pp. 71–8210.1016/j.flowmeasinst.2018.10.009Search in Google Scholar
37 G.-B. Huang , Q.-Y.Zhu, C.-K.Siew, Extreme learning machine: A new learning scheme of feedforward neural networks, Proc. of the IEEE Intern. Conf. on Neural Networks, Vol. 2, IEEE, New York (2004), pp. 985–990Search in Google Scholar
38 O. Altay , M.Ulas, The use of Kernel-based extreme learning machine and well-known classification algorithms for fall detection, Advances in Computer Communication and Computational Sciences (2019),Search in Google Scholar
39 O. Altay , M.Ulas, Location determination by processing signal strength of Wi-Fi routers in the indoor environment with linear discriminant classifier, Proc. of the IEEE 6th Intern. Symposium on Forensics and Security, A.Varol, M.Karabatak, CihanVarol (Eds.): Proc. of the IEEE 6th International Symposium on Digital Forensic and Security, IEEE, New York (2018), pp. 1–4Search in Google Scholar
40 K. Yang , X.Zhou, H.Zhao, S.Tao: Microstructure and mechanical properties of Al2O3–Cr2O3 composite coatings produced by atmospheric plasma spraying, Surface and Coatings Technology206 (2011), No. 6, pp. 1362–137110.1016/j.surfcoat.2011.08.061Search in Google Scholar
41 K. F. Ahmed , M. A.Shoeib: Development of Air Plasma Thermal Spray Coating for Thermal Barrier Coating and Oxidation Resistance Applications on Ni-Base Super Alloys, Scholar Journal of Applied Sciences and Research1 (2018), No. 3, pp. 20–3510.3619/SJASR.1000120Search in Google Scholar
42 S. P. Buyakova , E. S.Kalatur, A. S.Buyakov, S. S.Kulkov: Structure and properties of ZrO2-MgO powders, Epitoanyag-Journal of Silicate Based & Composite Materials68 (2016), No. 3, pp. 70–7310.14382/epitoanyag-jsbcm.2016.12Search in Google Scholar
43 S. Banerjee , P.Mukhopadhyay: Phase transformations: examples from titanium and zirconium alloys, 1st Ed., MukhopadhyayP., 2010, Elsevier, Amsterdam, Netherlands (2010)Search in Google Scholar
44 S. Kar , P. P.Bandyopadhyay, S.Paul: Effect of arc–current and spray distance on elastic modulus and fracture toughness of plasma-sprayed chromium oxide coatings, Friction6 (2018), No. 4, pp. 387–39410.1007/s40544-017-0166-6Search in Google Scholar
45 E. P. Song , J.Ahn, S.Lee, N. J.Kim: Effects of critical plasma spray parameter and spray distance on wear resistance of Al2O3–8 wt.% TiO2 coatings plasma-sprayed with nanopowders, Surface and Coatings Technology202 (2008), No. 15, pp. 3625–363210.1016/j.surfcoat.2008.01.002Search in Google Scholar
46 C. Özel , T.Gürgenç: Effect of heat input on microstructure, wear and friction behavior of (wt.-%) 50FeCrC-20FeW-30FeB coating on AISI 1020 produced by using PTA welding, PloS one13 (2018), No. 1, e0190243 10.1371/journal.pone.0190243Search in Google Scholar
47 T. Yue , T.Li: Laser cladding of Ni/Cu/Al functionally graded coating on magnesium substrate, Surface and Coatings Technology202 (2008), No. 13, pp. 3043–304910.1016/j.surfcoat.2007.11.007Search in Google Scholar
48 W. Deng , X.Zhao, Y.An, E.Hao, S.Li, H.Zhou, J.Chen: Improvement of tribological properties of as-sprayed 8YSZ coatings by in-situ synthesis C/MoS2 composite lubricant, Tribology International128 (2018), pp. 260–27010.1016/j.triboint.2018.07.038Search in Google Scholar
49 C. Özel , G.Akgün, T.Gürgenc: Microstructure, wear and friction behavior of AISI 1045 steel surfaces coated with mechanically alloyed Fe16Mo2C0.25Mn/Al2O3-3TiO2 powders, Materials Testing59 (2017), No. 10, pp. 921–92810.1016/j.surfcoat.2013.10.027Search in Google Scholar
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