High‐performance Brillouin distributed temperature sensor using Fourier wavelet regularised deconvolution algorithm

Abstract

In this study, the authors presented a distributed optical fibre temperature sensor whose performance is improved using the optimisation techniques and Fourier wavelet regularised deconvolution (ForWaRD) method. As the input power launched into the sensing fibre is critical, the authors have considered both conventional optimisation technique and evolutionary optimisation techniques namely: genetic algorithm, differential evolution algorithm and particle swarm optimisation algorithm to increase the stimulated Brillouin scattering (SBS) threshold power. Using the optimised value of the parameters and employing evolutionary computing techniques, the proposed 50 km long temperature sensing system offers a 4.7 dB improvement in SBS threshold power over the design of experiment based system. It is being verified that power of the backscattered signals approximately are the convolution of the input pulsed power and corresponding backscatter optical fibre impulse responses. The Fourier wavelet regularised deconvolution (ForWaRD) method is employed to improve the spatial resolution of the proposed sensing system without reducing the pulse width of the input pulse. Employing ForWaRD technique a 10 m better spatial resolution observed as compared with the Fourier deconvolution technique. The proposed 50 km long temperature sensing system exhibits a temperature resolution of 1.85 K because of suppression of SBS threshold and noise reduction.

Measurement of temperature and strain simultaneously with high spatial resolution for a long sensing range

“…We have considered α B = 1.17 × 10 −6 m −1 for the simulation process [14]. The backward capture coefficient S can be calculated using the numerical aperture of the fibre core NA and the fibre core refractive index n, and is expressed as…”