AUTOMATED TISSUE SELECTION SYSTEM, TAKING INTO ACCOUNT THE CAPABILITIES OF EQUIPMENT IN THE PRODUCTION OF PATTERNED FABRICS
Keywords:
automation, textile production, selection of designs, mathematical modeling, patterned fabrics, optimization, artificial intelligenceAbstract
Abstract: This article discusses the development of an automated system for selecting fabrics, taking into account the technical capabilities of equipment for the production of patterned fabrics. The methodology for choosing drawings is presented, taking into account the restrictions of the technological process. An analysis of existing solutions has been carried out, a system of the system is proposed, a mathematical formalization of the design process is presented. The optimization algorithms and the software implementation of the system are considered. Examples of implementation and test results are given.
References
Иванов А.А., Петров Б.Б. Автоматизация текстильного производства. – М.: Наука, 2020.
Smith J., Taylor R. Textile Pattern Optimization. – London: Springer, 2019.
ISO 19227:2021. Standard for Textile Machinery Performance.
Zhang Y., Li H. Machine Learning in Textile Manufacturing. – New York: Elsevier, 2021.
OpenCV Documentation. https://docs.opencv.org
TensorFlow Guide. https://www.tensorflow.org
R.Zulunov, U.Akhundjanov, B.Soliyev, A.Kayumov, M.Asraev, Kh.Musayev. Building and predicting a neural network in PYTHON. E3S Web of Conferences, 508, 04005 (2024).
Р.Зулунов, Д.Ирматова. Использование технологий искусственного интеллекта. Журнал интегрированного образования и исследований. 2022, 1/6, с. 53-56.
R.Zulunov. Pythonda neyron tarmoqni qurish va bashorat qilish. Al-Farg'oniy avlodlari, 2023, 1/4, c. 22-26.
R.Zulunov, A.Kayumov. Идентификация и сортировка текстиля для автоматизированной обработки с помощью ближней инфракрасной спектроскопии. Universum: технические науки, 3(120), март 2024, с. 38-42
VV Byts', RM Zulunov. Specification of matrix algebra problems by reduction. Journal of Mathematical Sciences. T. 71, 2719–2726 (1994).
Hnatiienko, H., Hnatiienko, V., Zulunov R., Babenko, T., Myrutenko, L. Method for Determining the Level of Criticality Elements when Ensuring the Functional Stability of the System based on Role Analysis of Elements. CEUR Workshop Proceedings, 2024, 3654, p. 301–311
R.Zulunov, B.Soliyev, A.Kayumov, M.Asraev, Kh.Musayev, D.Abdurasulova. Detecting mobile objects with ai using edge detection and background subtraction techniques. E3S Web of Conferences, 508, 03004 (2024).
R.Zulunov, B.Soliev. Z.Ermatova. Enhancing Clarity with Techniques for Recognizing Blurred Objects in Low Quality Images Using Python. Потомки Аль-Фаргани, 2024, 1(2), 336–340.
U.Akhundjanov, R.Zulunov, A.Kayumov, X.Goipova, Z.Ermatova, M.Sobirov. Handwritten signature preprocessing for off-line recognition systems. E3S Web Conf., 587 (2024) 03019.
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Copyright (c) 2025 Dilnoza Abdurasulova, Равшанбек Зулунов
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