An artificial neural network approach for the prediction of absorption measurements of an evanescent field fiber sensor

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Saracoglu O. G.

SENSORS, cilt.8, sa.3, ss.1585-1594, 2008 (SCI-Expanded) identifier identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 8 Sayı: 3
  • Basım Tarihi: 2008
  • Doi Numarası: 10.3390/s8031585
  • Dergi Adı: SENSORS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.1585-1594
  • Anahtar Kelimeler: fiber optic sensor, evanescent field, absorption, artificial neural networks, RELATIVE-HUMIDITY SENSOR, OPTICAL-FIBER, SENSITIVITY, RANGE, DESIGN
  • Erciyes Üniversitesi Adresli: Evet

Özet

This paper describes artificial neural network ( ANN) based prediction of the response of a fiber optic sensor using evanescent field absorption (EFA). The sensing probe of the sensor is made up a bundle of five PCS fibers to maximize the interaction of evanescent field with the absorbing medium. Different backpropagation algorithms are used to train the multilayer perceptron ANN. The Levenberg-Marquardt algorithm, as well as the other algorithms used in this work successfully predicts the sensor responses.