A Dual Element Multipoint Optical Fibre Water Contamination Sensor System Utilising Artificial Neural Network Pattern Recognition

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

A Dual Element Multipoint Optical Fibre Water Contamination Sensor System Utilising Artificial Neural Network Pattern Recognition

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

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. The sensor system utilises a U-bend configuration for each sensor element in order to maximise the sensitivity of the system and is interrogated using a technique known as Optical Time Domain Reflectometry, OTDR, as this method is capable of detecting attenuation over distance. Analysis of the data arising from the sensor system is performed using Artificial Neural Network (ANN) pattern recognition techniques, coupled with Fourier Transform based signal processing. The signal processing techniques are applied to the obtained sensor system data, prior to the ANN analysis, with the aim of reducing the computational resources required by the implemented ANN in software.

Original language	English
Pages	397-402
Number of pages	6
Publication status	Published - 2003
Event	Second International Conference on Sensors: IEEE Sensors 2003 - Toronto, Ont., Canada Duration: 22 Oct 2003 → 24 Oct 2003

Conference

Conference	Second International Conference on Sensors: IEEE Sensors 2003
Country/Territory	Canada
City	Toronto, Ont.
Period	22/10/03 → 24/10/03

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 6 Clean Water and Sanitation

Keywords

Artificial Neural Networks
Discrete Fourier Transform
Measurement
Optical Fibre Sensor
Optical Time Domain Reflectometry
Pattern Recognition
U-Bend Configuration

Cite this

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title = "A Dual Element Multipoint Optical Fibre Water Contamination Sensor System Utilising Artificial Neural Network Pattern Recognition",

abstract = "A dual-element multipoint optical fibre sensor system capable of detecting ethanol in water supplies is reported. The sensor system utilises a U-bend configuration for each sensor element in order to maximise the sensitivity of the system and is interrogated using a technique known as Optical Time Domain Reflectometry, OTDR, as this method is capable of detecting attenuation over distance. Analysis of the data arising from the sensor system is performed using Artificial Neural Network (ANN) pattern recognition techniques, coupled with Fourier Transform based signal processing. The signal processing techniques are applied to the obtained sensor system data, prior to the ANN analysis, with the aim of reducing the computational resources required by the implemented ANN in software.",

keywords = "Artificial Neural Networks, Discrete Fourier Transform, Measurement, Optical Fibre Sensor, Optical Time Domain Reflectometry, Pattern Recognition, U-Bend Configuration",

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

year = "2003",

language = "English",

pages = "397--402",

note = "Second International Conference on Sensors: IEEE Sensors 2003 ; Conference date: 22-10-2003 Through 24-10-2003",

}

TY - CONF

T1 - A Dual Element Multipoint Optical Fibre Water Contamination Sensor System Utilising Artificial Neural Network Pattern Recognition

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. The sensor system utilises a U-bend configuration for each sensor element in order to maximise the sensitivity of the system and is interrogated using a technique known as Optical Time Domain Reflectometry, OTDR, as this method is capable of detecting attenuation over distance. Analysis of the data arising from the sensor system is performed using Artificial Neural Network (ANN) pattern recognition techniques, coupled with Fourier Transform based signal processing. The signal processing techniques are applied to the obtained sensor system data, prior to the ANN analysis, with the aim of reducing the computational resources required by the implemented ANN in software.

AB - A dual-element multipoint optical fibre sensor system capable of detecting ethanol in water supplies is reported. The sensor system utilises a U-bend configuration for each sensor element in order to maximise the sensitivity of the system and is interrogated using a technique known as Optical Time Domain Reflectometry, OTDR, as this method is capable of detecting attenuation over distance. Analysis of the data arising from the sensor system is performed using Artificial Neural Network (ANN) pattern recognition techniques, coupled with Fourier Transform based signal processing. The signal processing techniques are applied to the obtained sensor system data, prior to the ANN analysis, with the aim of reducing the computational resources required by the implemented ANN in software.

KW - Artificial Neural Networks

KW - Discrete Fourier Transform

KW - Measurement

KW - Optical Fibre Sensor

KW - Optical Time Domain Reflectometry

KW - Pattern Recognition

KW - U-Bend Configuration

UR - https://www.scopus.com/pages/publications/1542273552

M3 - Paper

AN - SCOPUS:1542273552

SP - 397

EP - 402

T2 - Second International Conference on Sensors: IEEE Sensors 2003

Y2 - 22 October 2003 through 24 October 2003

ER -

A Dual Element Multipoint Optical Fibre Water Contamination Sensor System Utilising Artificial Neural Network Pattern Recognition

Abstract

Conference

UN SDGs

Keywords

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