, Volume 61, Issue 11–12, pp 1130–1134 | Cite as

Predicting the Risk of Destruction of Hard-Facing Alloys Based on the Morphology of Their Structure

  • A. S. Mel’nichenko
  • A. V. Kudrya
  • T. Sh. Akhmedova
  • E. A. Sokolovskaya

Wear resistance and fracture resistance are the main indicators of the quality of hard alloys. The risk of fracture of such materials is usually difficult to assess due to high hardness. However, this can be done by measuring the morphology of microstructure. The structure of hard alloys is diverse. Hardening particles (carbides, borides, particle clusters, dendrites, etc.) are located in the matrix. They have different geometries, the thickness of matrix interlayers varying. This assumes using a statistical approach to the analysis of structures. The statistical nature of structural elements is established with digital optical microscopy. Objective methods for the binarization and filtration of structure images are proposed. It is shown that the average thickness of the interlayers and the asymmetry of the thickness distribution can be used as an effective assessment of the risk of fracture of hard alloys. The prediction of the risk of fracture is validated by comparing the morphology of structures and fractures of hard alloys.


hard alloys hard-facing risk of fracture heterogeneity of microstructures statistics critical strain fracture 


  1. 1.
    M. A. Shtremel’, Fracture, Book 2, Fracture of Structures, ID MISiS, Moscow (2015).Google Scholar
  2. 2.
    E. A. Sokolovskaya, “Reproducibility of measurements of structures and fractures measurements using software procedures,” Vopr. Materialoved., No. 4, 143–153 (2013).Google Scholar
  3. 3.
    A. V. Kudrya, E. A. Sokolovskaya, V. Yu. Perezhogin, et al., “Use of computerized procedures for evaluating hard alloy structure inhomogeneity,” Metallurgist, 60, No. 11–12, 1285–1289 (2016).Google Scholar
  4. 4.
    Yu. A. Krupin and V. G. Sukhova, Computer-Aided Metallography, ID MISiS, Moscow (2009).Google Scholar
  5. 5.
    A. I. Sidorov, Restoration of Machine Components by Deposition and Surfacing, Kolos, Moscow (1993).Google Scholar
  6. 6.
    Yu. S. Karabasov (ed.), Steel at the Turn of the Century, MISiS, Moscow (2001).Google Scholar
  7. 7.
    M. A. Shtremel’, Strength of Alloys, Pt. 2, Deformation, MISiS, Moscow (1997).Google Scholar
  8. 8.
    A. V. Kudrya, E. A. Sokolovskaya, V. A. Trachenko, et al., “Measurement of nonuniformity of fracture in structural steels with heterogeneous structure,” Metal Sci. Heat Treat., 57, No. 3–4, 190–196 (2015).CrossRefGoogle Scholar
  9. 9.
    N. P. Klepikov and S. N. Sokolov, Analysis and Design of Experiments by the Maximum Likelihood Method, Nauka, Moscow (1964).Google Scholar
  10. 10.
    A. V. Kudrya and M. A. Shtremel’, “On the reliability of data analysis in quality control,” Metal Sci. Heat Treat., 52, No. 7–8, 341–346 (2010).CrossRefGoogle Scholar
  11. 11.
    M. A. Shtremel’, Fracture, Book 1, Fracture of Material, ID MISiS, Moscow (2014).Google Scholar
  12. 12.
    S. Yang, W.-J. Liu, M.-L. Zhong, and Z.-J. Wang, “TiC reinforced composite coating produced by powder feeding laser cladding,” Mater. Letters, 58, No. 24, 2958–2962 (2004).CrossRefGoogle Scholar
  13. 13.
    Yu. G. Bushuev, M. I. Persin, and V. A. Sokolov, Carbon–Carbon Composite Materials: Handbook, Metallurgiya, Moscow (1994).Google Scholar
  14. 14.
    A. S. Viktorov, Landscape Pattern, Mysl’, Moscow (1986).Google Scholar
  15. 15.
    M. A. Shtremel’, “Possibilities of fractography,” Metal Sci. Heat Treat., 47, No. 5–6, 193–201 (2005).CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • A. S. Mel’nichenko
    • 1
  • A. V. Kudrya
    • 1
  • T. Sh. Akhmedova
    • 1
  • E. A. Sokolovskaya
    • 1
  1. 1.National University of Science and Technology MISiSMoscowRussia

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