TY - JOUR
T1 - Utilisation of pattern recognition techniques to interpret complex data from a multipoint optical fibre ethanol concentration sensor system
AU - King, Damien
AU - Lyons, William B.
AU - Flanagan, Colin
AU - Lewis, Elfed
PY - 2007/5/1
Y1 - 2007/5/1
N2 - A multipoint optical fibre sensor system, capable of detecting various concentrations of ethanol in water is reported. The sensor system is based on a 500 m length of 62.5 μm diameter core silica clad silica core optical fibre and includes five sensing elements located along the fibre length. The sensing elements are based on evanescent wave absorption sensors and each sensor utilises a U-bend sensor configuration in order to maximise its sensitivity. The sensor system is interrogated using a technique known as optical time domain reflectometry, as this method is capable of measuring attenuation as a function of distance. Analysis of the data arising from the sensor system is performed using artificial neural network pattern recognition techniques, coupled with discrete Fourier transform-based signal processing. The signal processing techniques are applied to the obtained sensor system data, prior to the artificial neural network analysis, with the aim of reducing the computational resources required by the implemented artificial neural network in software.
AB - A multipoint optical fibre sensor system, capable of detecting various concentrations of ethanol in water is reported. The sensor system is based on a 500 m length of 62.5 μm diameter core silica clad silica core optical fibre and includes five sensing elements located along the fibre length. The sensing elements are based on evanescent wave absorption sensors and each sensor utilises a U-bend sensor configuration in order to maximise its sensitivity. The sensor system is interrogated using a technique known as optical time domain reflectometry, as this method is capable of measuring attenuation as a function of distance. Analysis of the data arising from the sensor system is performed using artificial neural network pattern recognition techniques, coupled with discrete Fourier transform-based signal processing. The signal processing techniques are applied to the obtained sensor system data, prior to the artificial neural network analysis, with the aim of reducing the computational resources required by the implemented artificial neural network in software.
KW - Artificial neural networks
KW - Discrete Fourier transform
KW - Measurement
KW - Multipoint optical fibre sensor system
KW - Optical time domain reflectometry
KW - Pattern recognition
UR - http://www.scopus.com/inward/record.url?scp=34247126449&partnerID=8YFLogxK
U2 - 10.1016/j.sna.2006.10.035
DO - 10.1016/j.sna.2006.10.035
M3 - Article
AN - SCOPUS:34247126449
SN - 0924-4247
VL - 136
SP - 144
EP - 153
JO - Sensors and Actuators, A: Physical
JF - Sensors and Actuators, A: Physical
IS - 1
ER -