Журнал Российского общества по неразрушающему контролю и технической диагностике
The journal of the Russian society for non-destructive testing and technical diagnostic
 
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17 | 05 | 2024
2023, 06 June

DOI: 10.14489/td.2023.06.pp.020-027

Abramov A. D.
EVALUATION OF THE QUALITY OF MACHINE PARTS' MICRORELIEF BY THE METHOD OF CORRELATION-SPECTRAL ANALYSIS OF THEIR IMAGES
(pp. 20-27)

Abstract. The article considers a method for estimating the parameters of the microrelief of the surface of machine parts by optoelectronic and computer means, as an integral part of the technological process of manufacturing machine parts with precision surfaces. The method is based on computer processing of images of the studied microreliefs, considered as a set of realizations of a stationary random process. The number of realizations of the random process is assumed to be equal to the number of lines in the analyzed microrelief image. The microrelief image is considered as a matrix of random numbers. For this matrix, mathematical expectations, variances, standard deviations, correlation moments and the normalized autocorrelation coefficient of honey are calculated for the columns of the matrix. To conduct research on the proposed method, an optical-electronic complex was used, consisting of an instrumental microscope with a video camera and a computer for digital processing of the obtained images of the microrelief f reference samples with different roughness. The surface roughness was estimated by standard methods on a profilograph and ranged from Ra = 0.025 µm to Ra = 0.130 µm. When developing software for correlation-spectral image processing, OpenCV tools and the C++ language were used. According to the research results, it was found that the nature of the correlation functions is largely determined by the parameters of the studied microreliefs. To identify the studied microreliefs, we determined the analytical dependences of the arithmetic mean deviation of the microrelief surface profile both on the average value of the variable component of the autocorrelation function and on the values of its spectral density. It has been established that for the identification of a microrelief by optical-electronic means, the most promising is the use of the spectral density of its autocorrelation function, calculated from its halftone image. The results of applying the correlation-spectral method for assessing the microrelief the working surface of an aircraft blade are presented.

Keywords: optoelectronic method, technology, grinding, polishing, parameters, evaluation, surface, micro-relief, correlation, spectrum.

A. D. Abramov (Samara State Technical University, Samara, Russia) Е-mail: Данный адрес e-mail защищен от спам-ботов, Вам необходимо включить Javascript для его просмотра.  

1. State program of the Russian Federation "Scientific and technological development of the Russian Federation". (2019). Moscow. [in Russian language]
2. Main directions of economic and social development of the Russian Federation until 2020. (2008). Moscow. [in Russian language]
3. Fedorov V. P., Suslov A. G., Nagorkin M. N. (2019). Engineering methods of technological support of regulated roughness parameters of functional surfaces of machine parts during machining. Naukoemkie tekhnologii v mashinostroenii, 94(4), pp. 40 – 48. [in Russian language]
4. Suslov A. G., Fedorov V. P., Nagorkin M. N., Pyrikov I. L. (2018). An integrated approach to experimental studies of technological systems of metalworking to ensure quality parameters and operational properties of the surfaces of machine parts. Naukoemkie tekhnologii v mashinostroenii, (10), pp. 3 – 13. [in Russian language]
5. Dunin-Barkovskiy I. V. (1978). Measurements and analysis of surface roughness, sinuosity and non-roundness. Moscow: Mashinostroenie. [in Russian language]
6. Vinogradova G. N., Zaharov V. V. (2020). Fundamentals of microscopy: textbook: in two parts. Part 2. Saint Petersburg: Universitet ITMO. [in Russian language]
7. Azarova V. V., Tsvetkova T. V. (2014). Roughness analysis of precision optical surfaces using interference microscopy. Izvestiya vuzov. Priborostroenie, Vol. 57 (6), pp. 83 – 86. [in Russian language]
8. Liesenborghs L., Peetermans M., Claes J. et al. (2016). Shear-Resistant Binding to von Willebrand Factor Allows Staphylococcus lugdunensisto Adhere to the Cardiac Valves and Initiate Endocarditis. Journal of Infectious Diseases, Vol. 213 (7), pp. 1148 – 1156. DOI: 10.1093/infdis/jiv773
9. Kelly R. Ch. (2009). Microscopy: Everincreasing resolution. Nature, Vol. 462, 7273, pp. 675 – 678. DOI: 10.1038/462675a
10. Abramov A. D. (2016). The analysis and correlation method of elimination errors of optiсal-electronic determination of microrelief parameters. Vestnik komp'yuternyh i informatsionnyh tekhnologiy, (9), pp. 19 – 25. [in Russian language] DOI: 10.14489/vkit.2016.09.pp.019-025
11. Venttsel' E. S. (2010). Probability Theory: Textbook for Higher Education Institutions. 11th ed. Moscow: KNORUS. [in Russian language]
12. Keler A., Bredski G. (2017). Learning OpenCV 3. Moscow: DMK-Press. [in Russian language]

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