TY - GEN
T1 - A 3 sensor multipoint optical fibre water sensor utilising artificial neural network pattern recognition
AU - Lyons, W. B.
AU - King, D.
AU - Flanagan, C.
AU - Lewis, E.
AU - Ewald, H.
AU - Lochmann, S.
N1 - Publisher Copyright:
© 2002 IEEE.
PY - 2002
Y1 - 2002
N2 - A multipoint sensor on a 1 km continuous length of fibre has been investigated and proven to be capable of detecting the presence of air, ethanol and water at each of three independent sensing points using OTDR techniques. Artificial neural network signal processing techniques have allowed the resulting OTDR signals to be accurately determined using pattern recognition. Each of the U-bend evanescent wave absorption sensors were developed with 62.5 μm polymer-clad silica fibre, which had its cladding removed in the sensing region. Although the length of the fibre used in this investigation was 1 km, longer or shorter lengths may be used as required. Earlier results from a single U-bend sensor have shown that a multilayer perceptron is required to adequately classify the data. Initial results have shown that it is possible to train a network to recognise trends such as ageing of the bare fibre when immersed in water, and therefore possible to separate out such effects from genuine changes in the measurand. It is envisaged that a more sophisticated multipoint U-bend evanescent wave sensor system will be developed, with the resulting complex signals being processed using Artificial neural network pattern recognition techniques. This will result in the development of a 'smart system', with the ability to interpret and separate relevant measurand data from the data received from cross coupling signals from external or interfering parameters as well as faults or defects detected in the fibre.
AB - A multipoint sensor on a 1 km continuous length of fibre has been investigated and proven to be capable of detecting the presence of air, ethanol and water at each of three independent sensing points using OTDR techniques. Artificial neural network signal processing techniques have allowed the resulting OTDR signals to be accurately determined using pattern recognition. Each of the U-bend evanescent wave absorption sensors were developed with 62.5 μm polymer-clad silica fibre, which had its cladding removed in the sensing region. Although the length of the fibre used in this investigation was 1 km, longer or shorter lengths may be used as required. Earlier results from a single U-bend sensor have shown that a multilayer perceptron is required to adequately classify the data. Initial results have shown that it is possible to train a network to recognise trends such as ageing of the bare fibre when immersed in water, and therefore possible to separate out such effects from genuine changes in the measurand. It is envisaged that a more sophisticated multipoint U-bend evanescent wave sensor system will be developed, with the resulting complex signals being processed using Artificial neural network pattern recognition techniques. This will result in the development of a 'smart system', with the ability to interpret and separate relevant measurand data from the data received from cross coupling signals from external or interfering parameters as well as faults or defects detected in the fibre.
UR - http://www.scopus.com/inward/record.url?scp=84888304396&partnerID=8YFLogxK
U2 - 10.1109/OFS.2002.1000692
DO - 10.1109/OFS.2002.1000692
M3 - Conference contribution
AN - SCOPUS:84888304396
T3 - 2002 15th Optical Fiber Sensors Conference Technical Digest, OFS 2002
SP - 463
EP - 466
BT - 2002 15th Optical Fiber Sensors Conference Technical Digest, OFS 2002
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 15th Optical Fiber Sensors Conference Technical Digest, OFS 2002
Y2 - 6 May 2002 through 10 May 2002
ER -