Lewis, E; Sheridan, C; O'Farrell, M; King, D; Flanagan, C; Lyons, WB; Fitzpatrick, C

2007

May

Sensors And Actuators A-Physical

Principal component analysis and artificial neural network based approach to analysing optical fibre sensors signals

Published

()

optical fibre temperature sensor food quality sensor optical fibre colour sensor artificial neural networks processing for sensor data PCA water quality measurement fluorescent coated optical fibres PATTERN-RECOGNITION TECHNIQUES U-SHAPED PROBE WATER-SYSTEMS QUALITY CLASSIFICATION SPECTROPHOTOMETRY REFLECTANCE IMAGES FOOD

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This paper investigates the use of artificial neural networks (ANNs) coupled with principal components analysis (PCA) to interpret complex optical spectrum and time resolved signals from optical fibre sensors. Specific reference is made to two application areas addressed by optical fibre sensors which are examples of systems deployed to measure food colour (reflection spectra) as it cooks in a full scale industrial oven and time resolved and Fourier transformed signals received from an optical time domain reflectometer (OTDR) for water monitoring. The method of analysis is different in each case but the same principles apply to each measurement. (C) 2007 Elsevier B.V. All rights reserved.

0924-4247

10.1016/j.sna.2007.02.012