EXTENDING THE RESPONSE RANGE OF AN OPTICAL-FIBER PH SENSOR USING AN ARTIFICIAL NEURAL-NETWORK

An artificial neural network (ANN) has been applied for the analysis o f the response of an optical fibre pH sensor. The optrode was based on a 3,4,5,6-tetrabromophenol sulphonephthalein indicator, which was cov alently bound onto aminopropyl glass beads, then packed at the tip of a bifurcated fibre-optic bundle. A three layer feed forward network wa s used and network training was performed using the recursive predicti on error (RPE) algorithm. It was found that an optimised network with 13 hidden neurons was highly accurate in predicting the response of th e optical pH sensor, with the worst interpolation error of 0.08 pH for test data set and 0.07 pH for measuring unknown buffer solutions. Ove rall, the application of ANN enabled the extension of the useful pH re sponse range of the sensor from its narrow linear range (pH 5.0-7.25) to the full calibration response (pH 2.51-9.76).