Detection of invisible cracks in ceramic materials using by pre-trained deep convolutional neural network

HS Nogay, TC Akinci, M Yilmaz - Neural Computing and Applications, 2022 - Springer
Ceramic materials are an indispensable part of our lives. Today, ceramic materials are
mainly used in construction and kitchenware production. The fact that some deformations …

Acoustic structural integrity assessment of ceramics using supervised machine learning and uncertainty-based rejection

ML Nunes, M Barandas, H Gamboa… - ACM SIGKDD …, 2022 - dl.acm.org
Industry and Quality 4.0 pose the opportunity to integrate artificial intelligence-based
technology into the quality management of products/services. Particularly, quality control …

Implementation of heterodyning effect for monitoring the health of adhesively bonded and fastened composite joints

S Tashakori, A Baghalian, VY Senyurek, M Unal… - Applied Ocean …, 2018 - Elsevier
Composite materials are a preferred choice when high strength/weight ratio and resistance
to corrosion are needed. For assembly, composite parts are joined by using adhesives …

[PDF][PDF] Application of artificial neural networks for defect detection in ceramic materials

TC Akinci, HS Nogay, O Yilmaz - Archives of Acoustics, 2012 - acoustics.ippt.pan.pl
In this study, an artificial neural network application was performed to tell if 18 plates of the
same material in different shapes and sizes were cracked or not. The cracks in the cracked …

Diagnostics of construction defects in a building by using time-frequency analysis

V Volkovas, K Petkevičius, M Eidukevičiūtė, TC Akinci - Mechanika., 2012 - epubl.ktu.edu
Abstract [eng] The paper analyzes the problem of detection and identification of the defects
in the layers of the buildings. In order to analyze the behaviour of the damaged and un …

[PDF][PDF] Performance of deep learning approaches for detection and classification of ceramic tile defects

D Sivabalaselvamani, K Nanthini… - Journal of Ceramic …, 2023 - researchgate.net
Ceramic tiles are in high demand in the infrastructure and building development industries
due to their low cost, ease of installation, maintenance, moisture resistance, and availability …

Spectral and Statistical Analysis for Damage Detection in Ceramic Materials.

O Akgun - Traitement du Signal, 2020 - search.ebscohost.com
In this study, the internal or superficial cracks that may occur during the production of
ceramic plates were determined using the impact noise method. In the industry, ceramic …

[HTML][HTML] The defect detection in glass materials by using discrete wavelet packet transform and artificial neural network

G Gokmen - Journal of Vibroengineering, 2014 - extrica.com
In this study, a method based on impact tests was designed in order to determine
undamaged and broken glasses. By means of using an impact pendulum, impact was …

[PDF][PDF] Determining damages in ceramic plates by using discrete wavelet packet transform and support vector machine

M Yumurtaci, G GÖKMEN… - International Journal of …, 2020 - avesis.marmara.edu.tr
Özet Copyright© 2020 Institute of Advanced Engineering and Science. All rights reserved. In
this study, an analysis was conducted by using discrete wavelet packet transform (DWPT) …

[HTML][HTML] The defect detection in ceramic materials based on wavelet analysis by using the method of impulse noise

Ö Akgün, T Cetin Akinci, H Selcuk Nogay… - Journal of …, 2013 - extrica.com
In this experimental study, it was achieved to detect internal or surface cracks that can occur
in the production of ceramic plates by using the method of impulse noise. This method is a …