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

• Published in: IEEE sensors journal Vol. 23; no. 18; p. 1
• Main Authors: Pradhan, Himansu Shekhar, Mahajan, Pratik, Vislawath, Navneeth, Prasad, VSDN
• Format: Journal Article
• Language: English
• Published: New York IEEE 15.09.2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Average Filter; Brillouin Distributed Sensors; Brillouin Scattering; Fiber gratings; Gaussian Filter; High temperature; Hybrid Algorithm; Kalman Filter; LPR; Mathematical models; Nuclear power plants; Nuclear reactors; Optical fiber sensors; Optical fibers; OTDR; Robustness (mathematics); Sensors; Spatial resolution; Temperature; Temperature measurement; Temperature Profile; Temperature profiles; Temperature sensors
• ISSN: 1530-437X; 1558-1748
• DOI: 10.1109/JSEN.2023.3298353

A Brillouin Distributed Temperature Sensor (BDTS) is proposed in this paper for measuring high temperatures at nuclear power plants, with a sensing range of 70 km, employing 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 procedures. Additionally, 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 °K, 6.29 °K, 3.12 °K, 3.02 °K and 0.97 °K for Fourier deconvolution, 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 to the Fourier deconvolution 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.