Archives of Acoustics, 37, 3, pp. 279–286, 2012

Application of Artificial Neural Networks for Defect Detection in Ceramic Materials

Tahir Cetin AKINCI
Department of Electrical & Electronics Engineering, Faculty of Engineering, Kirklareli University

H. Selcuk NOGAY
Department of Electrical & Electronics Engineering, Faculty of Engineering, Kirklareli University

Ozgur YILMAZ
Department of Computer Education & Instructional Technology Hasan Ali ucel Education Faculty, Istanbul University

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 plates were of
different depth and sizes and were non-identical deformations. This ANN model was developed to detect
whether the plates under test are cracked or not, when four plates have been selected randomly from
among a total of 18 ones. The ANN model used in the study is a model uniquely tailored for this study,
but it can be applied to all systems by changing the weight values and without changing the architecture
of the model. The developed model was tested using experimental data conducted with 18 plates and the
results obtained mainly correspond to this particular case. But the algorithm can be easily generalized
for an arbitrary number of items.
Keywords: impulse noise; ANN; defect detection; ceramic materials
Full Text: PDF


Copyright © Polish Academy of Sciences & Institute of Fundamental Technological Research (IPPT PAN)