PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Tytuł artykułu

Assessment of the Possibility of Using Fractal Analysis to Describe the Surface Aluminum Composites After Turning

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The description of the characteristics of the surface using standardized roughness parameters can not fully predict its performance properties. One of the tools supporting the assessment of the surface layer of the treated surface may be fractal analysis. This applies both to surfaces with machining traces, which are created under conditions of high randomness and variability of process conditions, and to surfaces with directional traces and their distinct periodicity. The paper presents the results of surface roughness measurements of turned aluminium matrix composites reinforced with ceramic fibers. Carbide and diamond tools were used for turning the tested material. The trials were carried out under dry machining conditions and with minimal lubrication in the cutting zone. Surfaces were measured by the contact method, and surface roughness parameters were calculated by Gaussian filtration. Then, the values of the fractal dimension were calculated using the enclosing box method. On the basis of these calculations, the influence of machining conditions on the values of selected roughness parameters and the box fractal dimension was determined. It was found that the fractal dimension, i.e. the irregularity of the geometric structure of the surface after turning of composites, changes with the change of cutting parameters, the tool and the method of lubricating the cutting zone. Of these factors, the feed has the greatest influence. As it grows, the irregularity of the machined surface structure decreases. In addition, the correlation coefficients between the fractal dimension and the measured roughness parameters were determined. It was noticed that the fractal dimension, in the case of turning aluminum composites, best correlates with the roughness parameters Sa and Ssk and thus describes features similar to these parameters. Therefore, it was assumed that it is possible to use fractal analysis as a supplementary tool for the description of the surface condition of aluminum composites after turning in various machining conditions. On the other hand, the fractal dimension can be treated as an additional tool to describe the surface condition, especially its irregularity, which is not described by other standard roughness parameters.
Twórcy
autor
  • Wroclaw University of Science and Technology, Faculty of Mechanical Engineering, ul. Łukasiewicza 5, 50-371 Wrocław, Poland
autor
  • Wroclaw University of Science and Technology, Faculty of Mechanical Engineering, ul. Łukasiewicza 5, 50-371 Wrocław, Poland
autor
  • Wroclaw University of Science and Technology, Faculty of Mechanical Engineering, ul. Łukasiewicza 5, 50-371 Wrocław, Poland
Bibliografia
  • 1. Healey R., Wang J., Chiu W.K., Chowdhury N.M., Baker A., Wallbrink C. A review on aircraft spectra simplification techniques for composite structures. Composites Part C. 2021;5:100–131. https://doi. org/10.1016/j.jcomc.2021.100131
  • 2. Vijaya Ramnath B., Parswajinan C., Dharmaseelan R., Thileepan K., Nithin Krishna K. A review on aluminium metal matrix composites, Materials Today: Proceedings. 2021;46(9):4341–4343. https:// doi.org/10.1016/j.matpr.2021.03.600
  • 3. Ramakrishnan G., Vijaya Ramnath B., Naveen E., Gowtham S., Kumar Arun A., Muthuvel M.S., Akil R. A Review on Aluminium Metal Matrix Composites. Advanced Science, Engineering and Medicine. 2018;10(5):263–267.
  • 4. Das M., Mishra D., Mahapatra T.R. Machinability of Metal Matrix Composites: A Review. Materials Today: Proceedings. 2019;18(7):5373–5381. https://doi.org/10.1016/j.matpr.2019.07.564
  • 5. Bhardwaj Ajay R., Vaidya A.M., Shekhawat S.P. Machining of Aluminium Metal Matrix Composite: A Review. Materials Today: Proceedings. 2020;21(2):1396–1402 https://doi.org/10.1016/j. matpr.2020.01.179
  • 6. Mandelbrot B. Les objets fractals: Forme, hasard et dimension. Flammarion; 1975
  • 7. Zhang X., Zheng G., Cheng X., Li Y., Li L., Liu H. 2D fractal analysis of the cutting force and surface profile in turning of iron-based superalloy. Measurement. 2020;151:107–125. https://doi. org/10.1016/j.measurement.2019.107125
  • 8. Niu Z.K, Jiao L., Chen S.Q., Yan P., Wang X.B. Surface quality evaluation in orthogonal turn-milling based on box-counting method for image fractal dimension estimation. Nanomanufacturing Metrology. 2018;1:125–130. https://doi.org/10.1007/ s41871-018-0015-x.
  • 9. Panigrahy C., Seal A., Mahato N.K. Quantitative texture measurement of grayscale images: fractal dimension using an improved differential box counting method. Measurement. 2019;147:106859. https:// doi.org/10.1016/j.measurement.2019.106859
  • 10. Nayak S.R., Mishra J., Palai G. A modified approach to estimate fractal dimension of gray scale images. Optik. 2018;161:136–145. https://doi. org/10.1016/j.ijleo.2018.02.024.
  • 11. Nayak S.R., Mishra J., Khandual A., Palai G. Fractal dimension of RGB color images. Optik. 2018;162:196– 205. https://doi.org/10.1016/j.ijleo.2018.02.066
  • 12. Jing C.L., Tang W. Ga-doped ZnO thin film surface characterization by wavelet and fractal analysis. Applied Surface Science. 2016;364:843–849. http://dx.doi.org/10.1016/j.apsusc.2015.12.234
  • 13. Jiang C.X., Lu Z.X., Zhou J., Muhammad S.M. Evaluation of fractal dimension of soft terrain surface. Journal of Terramechanics. 2017;70:27–34. https://doi.org/10.1016/j.jterra.2017.01.003.
  • 14. Zuo X., Zhu H., Zhou Y.K., Ding C. Monofractal and multifractal behavior of worn surface in brass-steel tribosystem under mixed lubricated condition. Tribology International. 2016;93:306–317. https:// doi.org/10.1016/j.triboint.2015.09.035.
  • 15. Macek W., Marciniak Z., Branco R., Rozumek D., Królczyk G.M. A fractographic study exploring the fracture surface topography of S355J2 steel after pseudo-random bending-torsion fatigue tests. Measurement. 2021:178:109443. https://doi. org/10.1016/j.measurement.2021.109443
  • 16. Macek W. Fractal analysis of the bending-torsion fatigue fracture of aluminium alloy. Engineering Failure Analysis. 2019;99:97–107. https://doi. org/10.1016/j.engfailanal.2019.02.007.
  • 17. Karolczak P., Kowalski M., Wiśniewska M. Analysis of the possibility of using wavelet transform to assess the condition of the surface layer of elements with flat-top structures. Machines. 2020;8(4):1–21. https://doi.org/10.3390/machines8040065
  • 18. Grzesik W., Brol S. Wavelet and fractal approach to surface roughness characterization after finish turning of different workpiece materials. Journal of Materials Processing Technology. 2009;209:2522–2531. https://doi.org/10.1016/j. jmatprotec.2008.06.009
  • 19. Li G.X., Zhang K., Gong J.Z., Jin X. Calculation method for fractal characteristics of machining topography surface based on wavelet transform. Procedia CIRP. 2019;79:500–504.
  • 20. Altintas Y. Manufacturing Automation: Metal Cutting Mechanics, Machine Tool Vibrations, and CNC Design. Cambridge University Press, New York, 2012.
  • 21. Wang H., Chi G., Jia Y., Ge Ch., Yu F., Wang Z., Wang Z. Surface roughness evaluation and morphology reconstruction of electrical discharge machining by frequency spectral analysis. Measurement. 2021;172:108879. https://doi.org/10.1016/j. measurement.2020.108879
  • 22. Karolczak P., Kowalski M., Raszka K.H. The application of fractal analysis to description of brushed steel surfaces. Journal of Machine Engineering. 2020;20(4):99–115. https://doi. org/10.36897/jme/130618
  • 23. Papanikolaou M., Salonitis K. Fractal roughness effects on nanoscale grinding. Applied Surface Science. 2019;467–468:309–319. https://doi. org/10.1016/j.apsusc.2018.10.144
  • 24. Chang Q., Chen D.L., Ru H.Q., Yue X.Y., Yu L., Zhang C.P. Three-dimensional fractal analysis of fracture surfaces in titanium–iron particulate reinforced hydroxyapatite composites: relationship between fracture toughness and fractal dimension. Journal of Materials Science. 2011;46:6118–6123.
  • 25. Kuang X., Zhu Z., Carotenuto A.G., Nicolais L. Fractal Analysis and Simulation of Surface Roughness of Ceramic Particles for Composite Materials. Applied Composite Materials. 1997;4:69–81.
  • 26. Rimpault X., Chatelain J.F., Klemberg-Sapieha J.E., Balazinski M. Tool wear and surface quality assessment of CFRP trimming using fractal analyses of the cutting force signals. CIRP Journal of Manufacturing Science and Technology. 2017;16,;72–80. https://doi.org/10.1016/j.cirpj.2016.06.003
  • 27. Karolczak P., Kołodziej M., Kowalski M. Effectiveness of diamond blades in the turning of aluminium composites. Advances in Science and Technology Research Journal. 2020;14(4);262–272. https://doi. org/10.12913/22998624/127436
  • 28. www.accu-lube.com - Accu-Lube materials
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-4e917baf-fb8c-42fe-ba96-6a50b7017d40
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.