A multipoint optical fibre sensor system for use in process water systems based on artificial neural network pattern recognition techniques

Sensors and Actuators, A: Physical

Volumn 115, Issue 2-3 SPEC. ISS., 2004, Pages 293-302

  King, D ^a   Lyons, W B ^a   Flanagan, C ^a   Lewis, E ^a  

^a UNIVERSITY OF LIMERICK   (Ireland)

Author keywords

Artificial neural networks; Measurement; Optical fibre sensors; Optical time domain reflectometry; U bend configuration

Indexed keywords

ABSORPTION; BACKSCATTERING; COMPUTER SOFTWARE; FABRICATION; LIGHT PROPAGATION; MODULATION; NEURAL NETWORKS; OPTICAL FIBERS; PATTERN RECOGNITION; REFRACTIVE INDEX; SENSITIVITY ANALYSIS; SIGNAL PROCESSING; SURFACE REACTIONS;

OPTICAL FIBER SENSORS; OPTICAL TIME DOMAIN REFLECTOMETRY; REYLEIGH BACKSCATTERING; U-BEND CONFIGURATION;

OPTICAL SENSORS;

EID: 4544306945     PISSN: 09244247     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.sna.2004.03.068     Document Type: Conference Paper

References (38)

1. Kersey A.D. A review of recent developments in fiber optic sensor technology. Opt. Fiber Technol. 2:1996;291-317.
2. Udd E. An overview of fiber optic sensors. Rev. Sci. Instrum. 66:1995;4015-4030.
3. Grattan K.T.V., Sun T. Fiber optic sensor technology: an overview. Sens. Actuators A. 82:2000;40-61.
4. Davis C.M. Fibre optic sensors: an overview. Opt. Eng. 24(2):1985;347-351.
5. Barnoski M.K., Jensen S.N. Fiber waveguides: a novel technique for investigating attenuation characteristics. Appl. Opt. 15:1976;2112-2115.
6. Kersey A.D., Dandridge A. Distributed and multiplexed fibre optic sensor systems. J. Inst. Electron. Radio Eng. (JIERE). 58(5):1988;99-111.
7. Kersey A.D. Multiplexed fiber optic sensors. SPIE Proc. Distrib. Multiplexed Fiber Opt. Sens. II. 1797:1992;161-185.
8. Lyons W.B., Lewis E. Neural networks and pattern recognition techniques applied to optical fibre sensors. Trans. Inst. Meas. Contr. 22(5):2000;385-404.
9. D. King, W.B. Lyons, C. Flanagan, E. Lewis, An optical fibre sensor system for water quality monitoring utilising Fourier transform techniques and artificial neural network pattern recognition, in: Proceedings of the Irish Signals and Systems Conference 2003 (ISSC 2003), Limerick, Ireland, 30 June-2 July 2003, pp. 224-230.
10. King D., Lyons W.B., Flanagan C., Lewis E. An optical fibre ethanol concentration sensor utilizing Fourier transform signal processing analysis and artificial neural network pattern recognition. IOP J. Opt. A: Pure Appl. Opt. 5(4):2003;S69-S75.
11. Khijwania S.K., Gupta B.D. Fiber optic evanescent field adsorption sensor with high sensitivity and linear dynamic range. Opt. Commun. 152:1998;259-262.
12. Gupta B.D., Dodeja H., Tomar A.K. Fibre optic evanescent field absorption sensor based on a U-shaped probe. Opt. Quantum Electron. 28:1996;1629-1639.
13. A.W. Snyder, J.D. Love, Optical Waveguide Theory, Chapman & Hall, 1983.
14. Khijwania S.K., Gupta B.D. Maximum achievable sensitivity of the fibre optic evanescent field absorption sensor based on a U-shape probe. Opt. Commun. 175:2000;135-137.
15. Otsuki S., Adachi K., Taguchi T. A novel fibre optic gas-sensing configuration using extremely curved optical fibres and an attempt for optical humidity detection. Sens. Actuators B. 53:1998;91-96.
16. Tateda M., Horiguchi T. Advances in optical time domain reflectometry. IEEE J. Lightwave Technol. 7(8):1989;1217-1224.
17. Neumann E.G. Optical time domain reflectometry: comment. Appl. Opt. 17(11):1978;1675.
18. J.P. Dakin, A.J. King, Limitations of a single optical fibre fluorimeter system due to background fluorescence, in: Proceedings of the First International Conference on Optical Fibre Sensors, London, UK, 1983, pp. 195-199.
19. Neumann G. Analysis of the backscattering method for testing optical fibre cables. Arch. Elektron Ubertragungs. 34:1980;157-160.
20. EXFO IQ-7000 Optical Time Domain Reflectometer Instruction Manual, P/N: MAN-136-I.3ACE, December 1999.
21. EXFO IQ-200 Optical Test System Instruction Manual, P/N: MAN-056-I.6ACE, October 1998.
22. EXFO IQ-200 GPIB and IQ Applications Development Guide, P/N: MAN-075-I.3AN, January 2000.
23. Stuggart Neural Network Simulator (SNNS), User's Manual, Version 4.1, Report No. 6/95, 1995. http://www-ra.informatik.uni-tuebingen.de/SNNS/.
24. Lyons W.B., Ewald H., Flanagan C., Lochmann S., Lewis E. A neural networks based approach for determining fouling of multi-point optical fibre sensors in water systems. Meas. Sci. Technol. 12:2001;958-965.
25. P.A. Lynn, W. Fuerst, Introductory Digital Signal Processing, Wiley, July 1994.
26. W.H. Press, W.T. Vetterling, S.A. Teukolsky, B.P. Flannery, Numerical Recipes in C: The Art of Scientific Computing, Cambridge University Press, 1990.
27. Mc Culloch W.S., Pitts W. A logical calculus of the ideas immanent in nervous activity. Bull. Math. Biophys. 5:1945;115-133.
28. D.E. Rumelhart, J.L. Mc Clelland, (Eds.), Parallel Distributed Processing, MIT Press, Cambridge, MA, 1986.
29. Leiner M.J.P., Hartmann P. Theory and practice in optical pH sensing. Sens. Actuators B. 11(1):1993;281-289.
30. Taib M.N., Andres R., Narayanaswamy R. Extending the response of an optical fibre pH sensor using artificial neural networks. Anal. Chim. Acta. 330:1996;31-40.
31. Brook T.E., Taib M.N., Narayanaswamy R. Immobilization of ruthenium tris-bipyridyl complex for chlorine gas detection. Sens. Actuators B. 38-39:1997;195-201.
32. Massicotte D., Legendre S., Barweiz A. Neural network based method of calibration and measurand reconstruction for a high-pressure measuring system. IEEE Trans. Instrum. Meas. 47(2):1998;362-370.
33. Yang Q., Butler C. Sensor signal processing using neural networks for a 3-D fibre optic position sensor. Sens. Actuators A. 41-42:1994;103-109.
34. Jones R.T., Sirkis J.T., Freiebele E.J., Kersey A.D. Location of magnitude of impact detection in composite plated material using neural networks. SPIE Proc. Smart Struct. Mater.: Smart Struct. Process. Instrum. 2444:1995;469-480.
35. H. Simon, Neural Networks: A Comprehensive Foundation, Prentice-Hall, New Jersey, 1999.
36. W.B. Lyons, D. King, C. Flanagan, E. Lewis, A three sensor multipoint optical fibre water sensor utilising artificial neural network pattern recognition, in: Proceedings of the 15th Optical Fiber Sensor Conference (OFS 2002), Technical Digest, Portland, OR, USA, 6-10 May 2002, pp. 463-466.
37. T. Kohonen, Self-Organization and Associative Memory, 3rd ed., Springer-Verlag, New York, 1988.
38. G.A. Carpenter, S. Grossberg, Adaptive resonance theory (ART), in: M.A. Arbib (Ed.), The Handbook of Brain Theory and Neural Networks, MIT Press, Cambridge, MA, 1995, pp. 79-82.