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ЖУРНАЛЫ // Информационные технологии и вычислительные системы // Архив

ИТиВС, 2020, выпуск 3, страницы 13–29 (Mi itvs415)

ПРИКЛАДНЫЕ АСПЕКТЫ ИНФОРМАТИКИ

Automatic estimation of defects in composite structures as disturbances based on machine learning classifiers oriented mathematical models with uncertainties

A. A. Zhilenkova, S. G. Chernybc

a St. Petersburg State Marine Technical University, St.Petersburg, Russia
b Kerch State Maritime Technological University, Kerch, Russia
c Admiral Makarov State University of Maritime and Inland Shipping, St. Petersburg, Russia

Аннотация: The proposed system for detecting defects in composite materials, such as carbon fiber or textile fabric, is described. Defects in the structure of the product are detected using a computer vision system based on optical sensors, i.e. a visual inspection is carried out — a necessary stage in the production process of composite materials. The difference of the proposed method from the existing solutions is the unique model of the sensor-material interaction and its strict mathematical description. A comparison with the reference model of the structure specified analytically is used.

Ключевые слова: mathematical modeling, flaw detection, inspection, sensors, composites, machine learning.

Язык публикации: английский

DOI: 10.14357/20718632200302



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