Abstract
This paper presents a design technique for smart hetero-core fiber optic macrobend displacement sensors using Artificial Neural Networks. Experimental results for several macrobend displacement sensors are used for measuring the ability of Artificial Neural Networks (ANNs) to predict sensor measurand. Multilayer Perceptron algorithm was used as an ANN model. It is shown that all the algorithms are able to predict the displacement values with acceptable errors. Furthermore, a smart sensor architecture composed of multiple macrobend sensors using ANNs is proposed.
Keywords
Artificial neural network
Displacement (psychology)
Core (optical fiber)
Multilayer perceptron
Computer science
Optical fiber
Fiber optic sensor
Intelligent sensor
Perceptron
Artificial intelligence
Electronic engineering
Wireless sensor network
Engineering
Telecommunications
Subject Areas
Advanced Fiber Optic Sensors
·Electrical and Electronic Engineering ·Physical Sciences
Photonic and Optical Devices
·Electrical and Electronic Engineering ·Physical Sciences
Semiconductor Lasers and Optical Devices
·Electrical and Electronic Engineering ·Physical Sciences
Citations by Year
2017: 1
2018: 1
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