Interpreting complex data from a dual element multipoint optical fibre sensor system for use in process water systems

D. King; W. B. Lyons; C. Flanagan; E. Lewis

Interpreting complex data from a dual element multipoint optical fibre sensor system for use in process water systems

D. King, W. B. Lyons, C. Flanagan, E. Lewis

Department of Electronics & Computer Engineering

University of Limerick

Research output: Contribution to conference › Paper › peer-review

Abstract

A dual element multipoint optical fibre sensor system capable of detecting ethanol in water supplies is reported. A U-bend configuration is used for each sensor element in order to maximize sensitivity and the sensor system is interrogated using Optical Time Domain Reflectometry (OTDR). It has been proposed to apply Artificial Neural Network Pattern Recognition Techniques to the optical fibre sensor system to accurately classify each sensor element test condition. Novel signal processing techniques utilising Fourier Transform methods are applied to the resulting OTDR data, with the aim of reducing the computational resources of the ANN required to accurately classify the sensor system data.

Original language	English
Pages	975-980
Number of pages	6
Publication status	Published - 2003
Event	Smart Engineering System Design: Neural Networks, Fuzzy Logic, Evolutionary Programming, Complex Systems and Artificial Life - Proceedings of the Artificial Neural Networks in Engineering Conference - St. Louis, MO., United States Duration: 2 Nov 2003 → 5 Nov 2003

Conference

Conference	Smart Engineering System Design: Neural Networks, Fuzzy Logic, Evolutionary Programming, Complex Systems and Artificial Life - Proceedings of the Artificial Neural Networks in Engineering Conference
Country/Territory	United States
City	St. Louis, MO.
Period	2/11/03 → 5/11/03

Keywords

ANN
Backpropagation Algorithm
Discrete Signals Fourier Transform
Fast Fourier Transform
Feedforward Neural Networks
Multi-Layer Perceptron
Optimisation
Pattern Recognition
Sensor Recognition
Signal Processing
Supervised Training

Cite this

King, D., Lyons, W. B., Flanagan, C., & Lewis, E. (2003). Interpreting complex data from a dual element multipoint optical fibre sensor system for use in process water systems. 975-980. Paper presented at Smart Engineering System Design: Neural Networks, Fuzzy Logic, Evolutionary Programming, Complex Systems and Artificial Life - Proceedings of the Artificial Neural Networks in Engineering Conference, St. Louis, MO., United States.

King, D. ; Lyons, W. B. ; Flanagan, C. et al. / Interpreting complex data from a dual element multipoint optical fibre sensor system for use in process water systems. Paper presented at Smart Engineering System Design: Neural Networks, Fuzzy Logic, Evolutionary Programming, Complex Systems and Artificial Life - Proceedings of the Artificial Neural Networks in Engineering Conference, St. Louis, MO., United States.6 p.

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title = "Interpreting complex data from a dual element multipoint optical fibre sensor system for use in process water systems",

abstract = "A dual element multipoint optical fibre sensor system capable of detecting ethanol in water supplies is reported. A U-bend configuration is used for each sensor element in order to maximize sensitivity and the sensor system is interrogated using Optical Time Domain Reflectometry (OTDR). It has been proposed to apply Artificial Neural Network Pattern Recognition Techniques to the optical fibre sensor system to accurately classify each sensor element test condition. Novel signal processing techniques utilising Fourier Transform methods are applied to the resulting OTDR data, with the aim of reducing the computational resources of the ANN required to accurately classify the sensor system data.",

keywords = "ANN, Backpropagation Algorithm, Discrete Signals Fourier Transform, Fast Fourier Transform, Feedforward Neural Networks, Multi-Layer Perceptron, Optimisation, Pattern Recognition, Sensor Recognition, Signal Processing, Supervised Training",

author = "D. King and Lyons, {W. B.} and C. Flanagan and E. Lewis",

year = "2003",

language = "English",

pages = "975--980",

note = "Smart Engineering System Design: Neural Networks, Fuzzy Logic, Evolutionary Programming, Complex Systems and Artificial Life - Proceedings of the Artificial Neural Networks in Engineering Conference ; Conference date: 02-11-2003 Through 05-11-2003",

}

King, D, Lyons, WB, Flanagan, C & Lewis, E 2003, 'Interpreting complex data from a dual element multipoint optical fibre sensor system for use in process water systems', Paper presented at Smart Engineering System Design: Neural Networks, Fuzzy Logic, Evolutionary Programming, Complex Systems and Artificial Life - Proceedings of the Artificial Neural Networks in Engineering Conference, St. Louis, MO., United States, 2/11/03 - 5/11/03 pp. 975-980.

Interpreting complex data from a dual element multipoint optical fibre sensor system for use in process water systems. / King, D.; Lyons, W. B.; Flanagan, C. et al.
2003. 975-980 Paper presented at Smart Engineering System Design: Neural Networks, Fuzzy Logic, Evolutionary Programming, Complex Systems and Artificial Life - Proceedings of the Artificial Neural Networks in Engineering Conference, St. Louis, MO., United States.

Research output: Contribution to conference › Paper › peer-review

TY - CONF

T1 - Interpreting complex data from a dual element multipoint optical fibre sensor system for use in process water systems

AU - King, D.

AU - Lyons, W. B.

AU - Flanagan, C.

AU - Lewis, E.

PY - 2003

Y1 - 2003

N2 - A dual element multipoint optical fibre sensor system capable of detecting ethanol in water supplies is reported. A U-bend configuration is used for each sensor element in order to maximize sensitivity and the sensor system is interrogated using Optical Time Domain Reflectometry (OTDR). It has been proposed to apply Artificial Neural Network Pattern Recognition Techniques to the optical fibre sensor system to accurately classify each sensor element test condition. Novel signal processing techniques utilising Fourier Transform methods are applied to the resulting OTDR data, with the aim of reducing the computational resources of the ANN required to accurately classify the sensor system data.

AB - A dual element multipoint optical fibre sensor system capable of detecting ethanol in water supplies is reported. A U-bend configuration is used for each sensor element in order to maximize sensitivity and the sensor system is interrogated using Optical Time Domain Reflectometry (OTDR). It has been proposed to apply Artificial Neural Network Pattern Recognition Techniques to the optical fibre sensor system to accurately classify each sensor element test condition. Novel signal processing techniques utilising Fourier Transform methods are applied to the resulting OTDR data, with the aim of reducing the computational resources of the ANN required to accurately classify the sensor system data.

KW - ANN

KW - Backpropagation Algorithm

KW - Discrete Signals Fourier Transform

KW - Fast Fourier Transform

KW - Feedforward Neural Networks

KW - Multi-Layer Perceptron

KW - Optimisation

KW - Pattern Recognition

KW - Sensor Recognition

KW - Signal Processing

KW - Supervised Training

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M3 - Paper

AN - SCOPUS:2442531042

SP - 975

EP - 980

T2 - Smart Engineering System Design: Neural Networks, Fuzzy Logic, Evolutionary Programming, Complex Systems and Artificial Life - Proceedings of the Artificial Neural Networks in Engineering Conference

Y2 - 2 November 2003 through 5 November 2003

ER -

King D, Lyons WB, Flanagan C , Lewis E. Interpreting complex data from a dual element multipoint optical fibre sensor system for use in process water systems. 2003. Paper presented at Smart Engineering System Design: Neural Networks, Fuzzy Logic, Evolutionary Programming, Complex Systems and Artificial Life - Proceedings of the Artificial Neural Networks in Engineering Conference, St. Louis, MO., United States.

Interpreting complex data from a dual element multipoint optical fibre sensor system for use in process water systems

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Keywords

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