publication . Article . 2021

Автоматизированная система тепловой дефектометрии многослойных материалов на основе глубокого обучения

A. S. Momot; R. M. Galagan; V. Yu. Gluhovskii;
Open Access English
  • Published: 01 Jun 2021
  • Publisher: БНТУ
Abstract
Currently, along with growth in industrial production, the requirements for product quality testing are also increasing. In the tasks of defectoscopy and defectometry of multilayer materials, the use of thermal non-destructive testing method is promising. At the same time, interpretation of thermal testing data is complicated by a number of factors, which makes the use of traditional methods of data processing ineffective. Therefore, an urgent task is to search for new methods of thermal testing that will automate the diagnostic process and increase information content of obtained results. The purpose of article is to use the advances in deep learning for proces...
Subjects
free text keywords: thermal testing, multilayer materials, deep learning, neural networks, thermal testing, multilayer materials, deep learning, Engineering (General). Civil engineering (General), TA1-2040
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