Use of Artificial Neural Networks for Improving Fiber Optic Microbend Sensor Performance

Efendioglu H. S., Yildirim T., Fidanboylu K.

World Congress on Computational Intelligence (WCCI 2010), Barcelona, İspanya, 01 Ocak 2010 identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Cilt numarası:
  • Doi Numarası: 10.1109/ijcnn.2010.5596462
  • Basıldığı Şehir: Barcelona
  • Basıldığı Ülke: İspanya
  • Bursa Uludağ Üniversitesi Adresli: Hayır

Özet

This paper presents experimental results related with the behavior of fiber optic microbend sensors based on different configurations. Different types of deformer sets having different mechanical periodicities, corrugation size and number of deformations cycles have been used to test the validity of the proposed technique. Normalized output intensity of the microbend sensor as a function of applied force is later used in the prediction of desired sensor response using Artificial Neural Networks (ANNs). It is shown that, ANNs can detect measurement errors and can be used in the development of intelligent and robust sensors that can monitor and detect the abnormalities in the sensors state.