Temperature sensing in BOTDA system by using artificial neural network

Abstract

The use of an artificial neural network (ANN) for extraction of a temperature profile from a local Brillouin gain spectrum in a Brillouin optical time-domain analysis fibre sensor system is proposed and demonstrated. An ANN is applied to process the Brillouin timedomain trace in order to extract the temperature information along the fibre after the data acquisition process. The results show that the ANN provides higher accuracy and larger tolerance to measurement error than Lorentzian curve fitting does, especially for a large frequency scanning step. Hence the measurement time can be greatly reduced by adopting a larger frequency scanning step without sacrificing accuracy.