Recent development in artificial neural network based distributed fiber optic sensors

Distributed fiber optic sensors are promising technique for measuring strain, temperature and vibration over tens of kilometres by utilizing the backscattered Rayleigh, Raman and Brillouin signals. Recently, the use of an artificial neural network (ANN) has been adopted into the distributed fiber sensors for advanced data analytics, fast data processing time, high sensing accuracy and event classification. In this paper, the recent developments of ANN-based distributed fiber sensors and their operating principles are reviewed. Moreover, the performance of ANN is compared with the conventional signal processing algorithms. The future perspective view that can be extended further research development has also been discussed.