An optical fibre sensor for use in process water systems utilising FFT based techniques and artificial neural network pattern recognition

An optical fibre sensor is reported which is capable of detecting ethanol in water supplies. A single optical fibre sensor was incorporated into a 1km length of 62.5 μm core diameter polymer-clad silica (PCS) optical fibre. In order to maximise sensitivity, a U bend configuration was used for the sensor where the cladding was removed and the core exposed directly to the fluid under test. The sensor was interrogated using Optical Time Domain Reflectrometry, OTDR as it is intended to extend this work to multiple sensors on a single fibre. In this investigation the sensor was exposed to Air, Water and Alcohol. The signal processing technique has been designed to optimise the neural network adopted in the existing sensor system. In this investigation the Fast Fourier Transform (FFT) is used and its application leads to an improvement in efficiency of the neural network i.e. minimising the computing resources. Using SNNS, a feed forward three layer neural network was constructed with the number of input nodes corresponding to the number of points required to represent the sensor frequency domain response.