MATEC Web Conf.
Volume 292, 201923rd International Conference on Circuits, Systems, Communications and Computers (CSCC 2019)
|Number of page(s)||5|
|Published online||24 September 2019|
Data encoding and reconstruction of thermal imaging maps of impact damaged composite Structures using feature space and neural networks
Faculty of Engineering, Al-Ahliyya Amman University, 19328, Amman, Jordan
* Corresponding author: firstname.lastname@example.org
A new approach to characterizing and predicting impact damage level in (Reaction Injection Molding) RIM structures is presented. The technique encodes thermal images maps and extracts features from presented thermal images. Complex Neural Networks structure is employed to reconstruct thermal imaging maps and predict the extent of damage an impact can cause. Neural network weigh elimination algorithm is used and proved effective in predicting areas of damage.
© The Authors, published by EDP Sciences, 2019
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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