An Artificial Neural Network Approach for the Prediction of Absorption Measurements of an Evanescent Field Fiber Sensor
This paper describes artificial neural network (ANN) based prediction of theresponse of a fiber optic sensor using evanescent field absorption (EFA). The sensingprobe of the sensor is made up a bundle of five PCS fibers to maximize the interaction ofevanescent field with the absorbing medium. Differ...
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| Format: | Article |
| Language: | English |
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MDPI AG
2008-03-01
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| Series: | Sensors |
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| Online Access: | http://www.mdpi.com/1424-8220/8/3/1585/ |
| Summary: | This paper describes artificial neural network (ANN) based prediction of theresponse of a fiber optic sensor using evanescent field absorption (EFA). The sensingprobe of the sensor is made up a bundle of five PCS fibers to maximize the interaction ofevanescent field with the absorbing medium. Different backpropagation algorithms areused to train the multilayer perceptron ANN. The Levenberg-Marquardt algorithm, aswell as the other algorithms used in this work successfully predicts the sensor responses. |
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| ISSN: | 1424-8220 |