681.2: 004

software, high-precision goniometric complex, artificial neural network, measurements running speed.

Software of high-precision goniometric complex with artificial intelligence developed by the authors, particularly with artificial neural networks, with advanced functionality, designed for non-contact high-precision measurements at the previous settings of navigation sensing elements, flat angles, pyramidal prisms, other production objects, refraction index of optical glass, etc. is presented in this paper. The proposed software product has advanced capabilities, particularly, allows high-precision analysis of the intensities of the spectral distribution of chemical elements in metal-containing materials. The structure of the software reproduces the paradigm of modular construction, which determines the flexibility, extensibility and variability of software components. As a result, neural network processing of measuring information, automatic filtering by the method of moving average output signal noisy by errors of different nature is implemented.

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9. Yakimov V. N., Mashkov A. V., and Zhelonkin A. V. Spetsializirovannoe programmnoe obespechenie izmeritelnoy sistemyi dlya operativnogo otsenivaniya spektralnogo sostava mnogokomponentnyih protsessov. Programmnyie produktyi i sistemyi. Vol. 32. No. 1. 2019. P. 159–166. DOI:10.15827/0236-235X.125.159-166
10. Cherepanska I., Koval Yu., Bezvesilna O., Sazonov A., Kedrovskyi S. Artificial neural network as a part of intelligent precise goniometric system of analysis of spectral distribution intensities for definition of chemical composition of metal-containing substances. Metallophysics and Advanced Technologies. 2020. Vol. 42. No. 10, P. 1441–1454. URL: https://doi.org/10.15407/mfint.42.10.1441.

1. Cherepanskaya I. Yu. Bezvesilna O. M, Sazonov A. Yu. Precision intelligent goniometric system. Bulletin of Vinnytsia Polytechnic Institute. Series Automation and information-measuring equipment. Vinnytsia NTU. 2019. No. 2. Р. 7–14.
2. Cherepanska I., Bezvesilna O., Koval Yu., Sazonov A. Intelligent precise goniometric system of analysis of spectral distribution intensities for definition of chemical composition of metal-containing substances. Металлофизика и новейшие технологии. 2019. No. 2 (41). Р. 263–278.
3. Pan, Y., Chen, Q., Chen, T. et al. Evaluation of a computer-aided method for measuring the Cobb angle on chest X-rays. Eur Spine J 28, 3035–3043 (2019).
4. Huang E., Skoufis A., Denning T., Qi J., Dagastine R., Tabor R. & Berry J. (2021). OpenDrop: Open-source software for pendant drop tensiometry contact angle measurements. Journal of Open Source Software. 6 (58). Р. 2604–2604.
5. Young-Soo Park, John Arbie Agbayani, Jong-Han Lee, and Jong-Jae Lee Rotational Angle Measurement of Bridge Support Using Image Processing Techniques. Hindawi Publishing Corporation. Journal of Sensors. 2016. Р. 1–9.
6. Hlembotska L., Balytska N., Melnychuk P., Melnyk O. Computer modeling power load of face mills with cylindrical rake face of inserts in machining difficult-to-cut materials. Scientific Journal of TNTU (Tern.). 2019. Vol. 93. No. 1. P. 70–80.
7. Hlembotska L., Balytska N., Melnychuk P., Vyhovskyi H. (2021) Structural improvement of face mills designs based on systems approach. Scientific Journal of TNTU (Tern.). Vol. 101. No. 1. Р. 102–114.
8. Petrov Yu. S., Petrova V. Yu., Rogachev L. V., Sokolov A. A., Sokolova O. A. Razrabotka i realizatsiya informatsionno-izmeritelnoy sistemyi predstavleniya i analiza informatsii po tehnogennyim tsiklam promyishlennogo predpriyatiya. Sovremennyie problemyi nauki i obrazovaniya. 2014. No. 5. URL: http://www.science-education.ru/ru/article/view?id=15123.
9. Yakimov V. N., Mashkov A. V., and Zhelonkin A. V. Spetsializirovannoe programmnoe obespechenie izmeritelnoy sistemyi dlya operativnogo otsenivaniya spektralnogo sostava mnogokomponentnyih protsessov. Programmnyie produktyi i sistemyi. Vol. 32. No. 1. 2019. P. 159–166. DOI:10.15827/0236-235X.125.159-166
10. Cherepanska I., Koval Yu., Bezvesilna O., Sazonov A., Kedrovskyi S. Artificial neural network as a part of intelligent precise goniometric system of analysis of spectral distribution intensities for definition of chemical composition of metal-containing substances. Metallophysics and Advanced Technologies. 2020. Vol. 42. No. 10, P. 1441–1454. URL: https://doi.org/10.15407/mfint.42.10.1441.