Application of Artificial Neural Networks for Defect Detection in Ceramic Materials

Akıncı T. Ç., Nogay H. S., Yılmaz Ö.

ARCHIVES OF ACOUSTICS, cilt.37, sa.3, ss.279-286, 2012 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 37 Sayı: 3
  • Basım Tarihi: 2012
  • Doi Numarası: 10.2478/v10168-012-0036-1
  • Dergi Adı: ARCHIVES OF ACOUSTICS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.279-286
  • Anahtar Kelimeler: impulse noise, ANN, defect detection, ceramic materials
  • Bursa Uludağ Üniversitesi Adresli: Hayır

Özet

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.