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Proceedings Paper

Intelligent fiber optic statistical mode sensors using novel features and artificial neural networks
Author(s): Hasan Seckin Efendioglu; Onur Toker; Tulay Yildirim; Kemal Fidanboylu
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Paper Abstract

In this paper, intelligent statistical mode sensors are proposed and analyzed. Several statistical features are used in design of intelligent sensor systems. Force measurement experiments are conducted and experimental data is analyzed using newly proposed statistical features. After that, Artificial Neural Networks (ANNs) with sensor data fusion, which is an intelligent sensor architecture, was proposed to estimate the force values. Multilayer perceptron (MLP) with different algorithms are used in the ANN model, and all of them can predict the force values with acceptable error levels. Using sensor fusion with ANNs, statistical mode sensors can be calibrated and fault tolerance of the sensor can be decreased, hence more reliable intelligent sensors can be designed.

Paper Details

Date Published: 11 April 2013
PDF: 6 pages
Proc. SPIE 8693, Smart Sensor Phenomena, Technology, Networks, and Systems Integration 2013, 86930B (11 April 2013); doi: 10.1117/12.2009836
Show Author Affiliations
Hasan Seckin Efendioglu, Fatih Univ. (Turkey)
Onur Toker, Fatih Univ. (Turkey)
Tulay Yildirim, Yildiz Technical Univ. (Turkey)
Kemal Fidanboylu, Fatih Univ. (Turkey)

Published in SPIE Proceedings Vol. 8693:
Smart Sensor Phenomena, Technology, Networks, and Systems Integration 2013
Kara J. Peters; Wolfgang Ecke; Theodoros E. Matikas, Editor(s)

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