We examine the use of state-of-the-art distributed sensing systems to extract temperature information from the optical fibre infrastructure already of the Electricity Authority of Cyprus power distribution network (~25-year old installation); as a means of optical fibre distributed sensing in the underground cables. The optical fibres are collocated with existing power distribution cables, for the purpose of power line monitoring cable joints that are prone to failure, along with general monitoring for unusual behaviour and potential cable fault conditions. Detection is achieved using DTS: Distributed Temperature Sensors (Silixa Ltd) that use RAMAN-based measurements in combination with BOTDR (Brillouin Optical Time-domain Reflectometry) for high-precision temperature detection. We examine the correlation between the temperature of the power cable with the power consumption provided by the EAC and the weather conditions. Furthermore, our data will give an indication of how important is uniform spacing between power and optical cables. The real-time and continuous monitoring of the temperature of the optical cables through the distributed sensing systems may help identifying abnormal cable behavior (hot spots) and possible future network failures in the power network.
KEYWORDS: Signal to noise ratio, Data acquisition, Tolerancing, Temperature metrology, Computing systems, Tunable filters, Sensing systems, Laser frequency, Data analysis, Statistical analysis
A Brillouin Optical Time-Domain Analysis (BOTDA) Lorentzian data fitting method to estimate the Brillouin Frequency Shift (BFS) is proposed. Data is obtained from an experimental setup used to conduct the temperature and strain measurements. Before Lorentzian fitting the noisy data is averaged and filtered. The proposed method attempts to lower computational complexity in determining the Brillouin frequency. The resulting parameters of a completed BGS curve fitting are used as initial set of parameters for the next location point BGS fitting. Completion of the Lorentzian fitting using the Levenberg-Marquardt nonlinear curve fitting algorithm is achieved in a small number of iterations which improves the performance in obtaining the Brillouin frequency shift.
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