A Highly Improved Long-Range BDTS for Nuclear Reactors Using Hybrid Algorithm

A Brillouin distributed temperature sensor (BDTS) is proposed in this article for measuring high temperatures at nuclear power plants, with a sensing range of 70 km, employing a numerical simulation technique. The proposed sensor is mathematically modeled using a technique known as optical time-domain reflectometry (OTDR). Temperature profiles are extracted using Landau–Placzek ratio (LPR) and Fourier deconvolution (FD) procedures. In addition, different filtering algorithms, such as 2-D Gaussian, average, Kalman, and hybrid, are employed for obtaining temperature profiles. The temperature resolution of the sensor being proposed has been calculated to be 11.02, 6.29, 3.12, 3.02, and 0.97 K for FD, 2-D Gaussian, average, Kalman, and hybrid algorithms, respectively, at a sensing distance of 70 km. Notably, the hybrid algorithm shows a significant improvement of 91.19% in temperature resolution compared with the FD algorithm. This is attributed to the effective noise reduction achieved by the hybrid algorithm, which combines Kalman and average algorithms. Moreover, the spatial resolution of the proposed sensor is obtained as 1 m, which exactly matches the theoretical value. Furthermore, the denoising capability and robustness of the proposed hybrid algorithm in this study are verified through experimental data. Thus, the proposed BDTS can accurately monitor high temperatures within the environment of a nuclear reactor in the real-time basis.