MATEC Web Conf.
Volume 346, 2021International Conference on Modern Trends in Manufacturing Technologies and Equipment (ICMTMTE 2021)
|Number of page(s)||7|
|Published online||26 October 2021|
Method of Predicting the Polymer Composites’ Properties Using Neural Network Modeling
Bauman Moscow State Technical University (BMSTU), 105005, Moscow, Russia
* Corresponding author: email@example.com
A neural network modelling technique and its training to diagnose polymer composite materials based on tomography data is introduced. As an object of study, carbon fiber made by vacuum infusion technology using an epoxy binder is considered. X-ray microtomography was used to analyze its structure and the provided images were used as a database for creating a neural network. A neural network modelling technique and its training was developed, including an algorithm for converting tomograph images into data on the structure of the phase composition and the physical and mechanical properties of the object under study.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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