Physical and chemical aspects of the study of clusters, nanostructures and nanomaterials
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Correlation-spectral analysis of the topography of engineering surfaces at the nanoscale level

V.V. Izmailov, M.V. Novoselova

Tver State Technical University

DOI: 10.26456/pcascnn/2021.13.457

Original article

Abstract: The nanotopography of some typical technical surfaces is investigated and the characteristics of the nanoroughness profile as a random process are experimentally determined – the autocorrelation function and spectral density. It is shown that for the investigated surfaces, their profilograms can be considered as realizations of a random stationary normal ergodic process. A visual check of the process normality was carried out by comparing the experimental values of the profile ordinates with theoretical values obeying the normal distribution, as well as by comparing the frequency polygon with the theoretical probability density function of the normal distribution. Quantitative confirmation of the process normality was carried out using the Kolmogorov goodness-of-fit test. It is shown that at the significance level p=0,05, the hypothesis about the normality of a random process (surface nanoroughness profile) does not contradict the experimental results. The correlation intervals of the considered processes are determined. The form of the autocorrelation functions and the values of the correlation intervals indicate the random nature of the surface profile: in the interval equal to one or two average values of the step of the irregularities of the profile, its ordinates become practically uncorrelated. Spectral density plots indicate that the surface profile can be considered as a wide-band random noise with a predominance of low-frequency components.

Keywords: surface, nanotopography, profile method, random process, normal distribution, autocorrelation function, spectral density, correlation interval

  • Vladimir V. Izmailov – Dr. Sc., Professor, Department of Applied Physics, Tver State Technical University
  • Marina V. Novoselova – Ph. D., Docent, Department of Applied Physics, Tver State Technical University

Reference:

Izmailov, V.V. Correlation-spectral analysis of the topography of engineering surfaces at the nanoscale level / V.V. Izmailov, M.V. Novoselova // Physical and chemical aspects of the study of clusters, nanostructures and nanomaterials. — 2021. — I. 13. — P. 457-464. DOI: 10.26456/pcascnn/2021.13.457. (In Russian).

Full article (in Russian): download PDF file

References:

1. Izmailov V.V., Novoselova M.V. O parametrakh nanotopografii tekhnicheskoj poverkhnosti i ee profilya [On nanotopographic parameters of engineering surface and its profile], Fiziko-khimicheskie aspekty izucheniya klasterov, nanostruktur i nanomaterialov [Physical and chemical aspects of the study of clusters, nanostructures and nanomaterials], 2018, issue 10, pp. 313-321. DOI: 10.26456/pcascnn/2018.10.313. (In Russian).
2. Izmailov V.V., Novoselova M.V. Nekotorye statisticheskie raspredeleniya, kharakterizuyushchie nanotopografiyu tekhnicheskikh poverkhnostej [Some statistical distributions, which describe the nanotopography of technical surfaces], Fiziko-khimicheskie aspekty izucheniya klasterov, nanostruktur i nanomaterialov [Physical and chemical aspects of the study of clusters, nanostructures and nanomaterials], 2020, issue 12, pp. 609-616. DOI: 10.26456/pcascnn/2020.12.609. (In Russian).
3. Whitehouse D. Surfaces and their measurement. Oxford, Elsevier Science & Technology, 2004. 432 p.
4. Grigor'ev A.Ya. Fizika i mikrogeometriya tekhnicheskikh poverkhnostej [Physics and microgeometry of engineering surfaces]. Minsk, Belaruskaya navuka, 2016. 247 p. (In Russian).
5. Thomas T.R. Rough surfaces. London, Imperial College Press, 1999. 278 p.
6. Bendat J.S., Piersol A.G. Random data: analysis and measurement procedures. New Jersey, John Wiley & Sons, 2010. 640 p.
7. GOST R ISO 4287-2014. Geometricheskie kharakteristiki izdelij (GPS). Struktura poverkhnosti. Profil'nyj metod. Terminy, opredeleniya i parametry struktury poverkhnosti [Russian State Standard ISO 4287-2014 Geometrical Product Specifications (GPS). Surface texture. Profile method. Terms, definitions and surface texture parameters]. Moscow, Standartinform Publ., 2014. 20 p. (In Russian).
8. Dvorkovich V.P., Dvorkovich A.V. Okonnye funktsii dlya garmonicheskogo analiza signalov [Window functions for harmonic signal analysis]. Moscow, Tekhnosfera Publ., 2014. 112 p. (In Russian).
9. Ivchenko G.I., Medvedev Yu.I. Vvedenie v matematicheskuyu statistiku [Introduction to mathematical statistics]. Moscow: LKI Publ., 2017. 600 p. (In Russian).
10. Wentzel E.S. Teoriya veroyatnostej [Probability theory]. Moscow, Vysshaya Shkola Publ., 2006. 575 p. (In Russian).
11. Khrushchev I.V., Shcherbakov V.I., Levanov D.S. Osnovy matematicheskoj statistiki i teorii sluchajnykh protsessov [Fundamentals of mathematical statistics and theory of random processes]. Saint Petersburg, Lan' Publ., 2021. 336 p. (In Russian).
12. Chernov N.N., Morozov A.P. Signaly: formirovanie, obnaruzhenie i obrabotka: uchebno-metodicheskoe posobie [Signals: formation, detection and processing: study guide]. Taganrog: SFedU Publ., 2016. 51 p. (In Russian).

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