employee
Novocherkassk, Rostov-on-Don, Russian Federation
employee
Novocherkassk, Rostov-on-Don, Russian Federation
UDK 62 Инженерное дело. Техника в целом. Транспорт
GRNTI 55.03 Машиноведение и детали машин
The suggested approach provides an opportunity under the conditions of enterprises to give a comprehensive view of products defects and functional coatings imperfections. The application of the computer program developed in the Microsoft Visual Studio environment, which allows digital image processing of the studied surfaces to estimate the area of external defects of materials, regardless of the nature of the origin of defects and the method of image acquisition, is proved. Research methods. Digital images of metal surfaces and coatings obtained by energy dispersive microanalysis, electron and optical microscopy have been tested. Research results and novelty. The possibility of using the program for evaluation of surface bands with local chemical and morphological inhomogeneities, determination of the porosity of materials is shown. The possibility of express evaluation of digital images of objects at macro-, meso- and microstructural levels for automated diagnostic control of surface defects within 1-2 seconds is implemented. Disaggregation of brightness, texture and color components of the image significantly increases the speed and efficiency of image processing structures. Conclusions: The proposed program is versatile, does not require special user skills and serves as a convenient tool for analyzing and controlling the quality of objects of various physico-chemical nature. The results of the study indicate that the application of the developed computer program makes effective quantitative calculation of the area of local defects, areas of distribution of chemical elements, various inclusions, surface porosity of products and coatings possible.
digital processing, images, defect, surface, express analysis
1. GOST 31149-2014. Materialy lakokrasochnye. Opredelenie adgezii metodom reshetchatogo nadreza: = Paint materials. Determination of adhesive by cross-cut method: nacional'nyy standart Rossiyskoy Federacii: izdanie oficial'noe: utverzhden i vveden v deystvie Prikazom Federal'nogo agentstva po tehnicheskomu regulirovaniyu i metrologii ot 08 sentyabrya 2014 g № 1017-st: data vvedeniya 2015- 09-01. g. / - Moskva: Standartinform, 2014. - 12 s.
2. Tkal', V. A. Cifrovye metody obrabotki rentgenotopograficheskih i polyarizacionno-opticheskih izobrazheniy defektov struktury monokristallicheskih poluprovodnikov: special'nost' 01.04.01 «Pribory i metody eksperimental'noy fiziki»: avtoreferat dissertacii na soiskanie uchenoy stepeni doktora fiziko-matematicheskih nauk / Tkal' Valeriy Alekseevich; FTI im. A.F. Ioffe RAN. - Izhevsk, 2007. - 48 s. Bibliogr.: s. 3 - 4. - Mesto zaschity: Udmurtskiy gosudarstvennyy universitet. - Tekst: neposredstvennyy.
3. Zhukovskaya, A. A. Kolichestvennye kriterii ocenki kachestva cifrovoy obrabotki izobrazheniy veschestv razlichnoy fiziko-himicheskoy prirody: special'nost' 01.04.01 «Pribory i metody eksperimental'noy fiziki»: dis. na soiskanie uchenoy stepeni kand. tehn. nauk /Zhukovskaya Inga Anatol'evna; FTI im. A.F. Ioffe RAN. - Izhevsk, 2014. - 207 s. Bibliogr.: s. 54 - 64.
4. Cifrovye metody ekspress-diagnostiki kachestva veschestv razlichnoy fiziko-himicheskoy prirody (obobschayuschaya stat'ya) / V. A. Tkal', I. A. Zhukovskaya, A. V. Sharaeva, N. N. Vodolazova. // Radioelektronika. Nanosistemy. Informacionnye tehnologii. - 2016. - № 8(1). - S. 55-72. - DOI:https://doi.org/10.17725/rensit.2016.08.055.
5. Fast computational depth segmentation using orthogonal fringe patterns without pattern sequence changing / Y. Xiao, W. Han, X. Zhang [ i dr.] // Journal of the Optical Society of America A: Optics and Image Science, and Vision. - 2021. - № 38(4). - P. 564-572- DOI: org/10.1364/JOSAA.414326.
6. Multi-modal semantic image segmentation / A. Pemasiri, K. Nguyen, S. Sridharan, C. Fookes // Computer Vision and Image Understanding. - 2021. - № 202. - 103085. - DOI: org/10.1016/j.cviu.2020.103085.
7. Ma, J. Infrared and visible image fusion via gradientlet filter / J. Ma, Y. Zhou // Computer Vision and Image Understanding. - 2020. - № 103016. - R. 197-198. - DOIhttps://doi.org/10.1016/j.cviu.2020.103016.
8. Galvao, F. L. Image segmentation using dense and sparse hierarchies of superpixels / F. L. Galvao, S. J. F. Guimaraes, A. X. Falcao // Pattern Recognition. - 2020. - № 108. - 107532. - DOI: org/10.1016/j.patcog.2020.107532.
9. Neural Image Compression for Gigapixel Histopathology Image Analysis / D. Tellez, G. Litjens, Van Der Laak J. F. Ciompi. // IEEE Transactions on Pattern Analysis and Machine Intelligence. - 2021. - № 43(2). - 8809829. - R. 567 - 5781. - DOI: https://doi.org/10.1109/TPAMI.2019.2936841.
10. Gupta, S. Recognition of varying size scene images using semantic analysis of deep activation maps / S. Gupta, A. D. Dileep, V. Thenkanidiyoor // Machine Vision and Applications. - 2021. - № 32(2). P. 52. - DOIhttps://doi.org/10.1007/s00138-021-01168-8.
11. Wu, Z. Edge missing image inpainting with compression-decompression network in low similarity images / Z. Wu, Y. Cui // Machine Vision and Applications. - 2021. - № 32(1). - P. 37. - DOIhttps://doi.org/10.1007/s00138-020-01151-9.
12. Image deblurring via enhanced local maximum intensity prior / D. Hu, J. Tan, Zhang L., X. Ge [i dr.] // Signal Processing: Image Communication. - 2021. - № 96. - 116311. - DOI:https://doi.org/10.1016/j.image.2021.116311.
13. Wu, H. A pruning method based on the measurement of feature extraction ability / H. Wu, Y. Tang, X. Zhang // Machine Vision and Applications. - 2021. - № 32(1). - P. 20. - DOI:https://doi.org/10.1007/s00138-020-01148-4.
14. Xiao M. Research on defect detection method of powder metallurgy gear based on machine vision / M. Xiao, W. Wang, X. Shen [i dr.] // Machine Vision and Applications. - 2021. - № 32(2). P. 51. - DOIhttps://doi.org/10.1007/s00138-021-01177-7.
15. Saeedi J. Measurement and inspection of electrical discharge machined steel surfaces using deep neural networks / J. Saeedi, M. Dotta, A. Galli [ i dr.] // Machine Vision and Applications. - 2021. - № 32(1). P. 21. DOI:https://doi.org/10.1007/s00138-020-01142-w.
16. Zhukovskaya, I. A. Discrete Fourier analysis of images of structural defects in single crystals / I. A. Zhukovskaya, V. A Tkal., V. A. Bushuev // Journal of Surface Investigation: X-Ray, Synchrotron and Neutron Techniques. - 2016. - № 10(1). - R. 231-240.
17. Feature-Driven Viewpoint Placement for Model-Based Surface Inspection / D. Mosbach, P. Gospodnetić, M. Rauhut [ i dr.] // Machine Vision and Applications. - 2021. - № 32(11). - P. 8. - DOI:https://doi.org/10.1007/s00138-020-01116-y.
18. Finogenov L. V. Vysokoproizvoditel'nyy optiko-elektronnyy kontrol' bokovoy poverhnosti toplivnyh tabletok s opredeleniem glubiny defektov / L. V. Finogenov, P. S. Zav'yalov, V. E. Karlin, D. R. Hakimov // Datchiki i sistemy. - 2016. - № 7(205). - S. 53-59.
19. Analiz cifrovogo izobrazheniya povrezhdennogo lakokrasochnogo pokrytiya (ADID) / Svidetel'stvo o gosudarstvennoy registracii programmy dlya EVM 2021660153 Rossiyskaya Federaciya /Antonova N. M, Haustova E. Yu, Nebrat A. A, Puzanova A. S.; zayavitel' i pravoobladatel' Federal'noe gosudarstvennoe byudzhetnoe obrazovatel'noe uchrezhdenie vysshego obrazovaniya «Yuzhno-Rossiyskiy gosudarstvennyy politehnicheskiy universitet (NPI) imeni M.I. Platova». - № 2021619195; zayavl. 11.06.2021; opubl 22.06.2021. - 1 s.
20. Antonova N. M. Adgeziya vibracionnogo mehanohimicheskogo pokrytiya MoS2 v processe treniya / N. M. Antonova, V. S. Shorkin, S. N. Romashin, A. P. Babichev // Poverhnost'. Rentgenovskie, sinhrotronnye i neytronnye issledovaniya. - 2019. - № 9. - S. 67-74.
21. Tamarkin, M. A. Obosnovanie granulometricheskih harakteristik rabochey sredy pri vibracionnoy obrabotke detaley s malymi pazami i otverstiyami / M. A. Tamarkin, E. N. Kolganova, M. A. Yagmurov // Advanced Engineering Research. - 2020. - T. 20, № 4. - S. 382-389. - DOIhttps://doi.org/10.23947/2687-1653-2020-20-4-382-389.
22. Kolganova, E. N. Teoreticheskie i eksperimental'nye issledovaniya processa udaleniya zausenca svobodnymi abrazivami / E. N. Kolganova // Uprochnyayuschie tehnologii i pokrytiya. - 2020. - T. 16, № 7(187). - S. 300-305.
23. Tamarkin, M. A. Analiz sovremennogo sostoyaniya finishnyh metodov obrabotki v srede svobodnyh abrazivov detaley, imeyuschih malye pazy i otverstiya / M. A. Tamarkin, E. V. Smolencev, E. N. Kolganova // Vestnik Voronezhskogo gosudarstvennogo tehnicheskogo universiteta. - 2019. - T.15, № 1. - S. 122-129.
24. Il'inyh S. A. Uprochnenie detaley mashin i mehanizmov, izgotovlennyh iz alyuminievyh splavov, metodom sverhzvukovogo plazmennogo napyleniya / S. A. Il'inyh, A. S. Krivorogova, N. I. Il'inyh [i dr.] // Novye materialy i tehnologii: poroshkovaya metallurgiya, kompozicionnye materialy, zaschitnye pokrytiya, svarka: materialy 14-y Mezhdunarodnoy nauchno-tehnicheskoy konferencii, posvyaschennoy 60-letiyu poroshkovoy metallurgii Belarusi, Minsk, 09-11 sentyabrya 2020; pod red. A.F. Il'yuschenko. - Minsk: Respublikanskoe unitarnoe predpriyatie «Izdatel'skiy dom «Belorusskaya nauka», 2020. - S. 473-479. - ISBN 978-985-08-2628-2.
25. Krivorogova A. S. Teoreticheskoe i eksperimental'noe issledovanie samoflyusuyuschihsya materialov na osnove nikelya / A. S. Krivorogova, N. I. Il'inyh, S. A. Il'inyh, B. R. Gel'chinskiy // Rasplavy. - 2020. - № 1. - S. 87-97.
26. Antonova, N. Formation the structure of porous carboxymethylcellulose films for developing materials with antifriction properties / N. Antonova, A. Kameneva // Materials Today: Proceedings. - 2019. - V.19. - P. 1856-1860. - DOI:https://doi.org/10.1016/j.matpr.2019.07.027.
