KEYWORDS: Signal to noise ratio, Optical fibers, Interference (communication), Denoising, Algorithms, Data modeling, Signal processing, Optical sensing, Optimization (mathematics), Sensing systems
There are anti-electromagnetic interference and electrical insulation of distributed optical fiber sensing technology. It is widely applicable to industrial fields. However, the fully distributed optical fiber sensing system produces a huge amount of data in the monitoring process. The compression of distributed optical fiber sensing data has become the focus of scholars at home and abroad. The time dimension of vibration signal is considered in the compression of Phase-OTDR vibration data. However, the spatio-temporal structure characteristics of distributed optical fiber vibration signals have not been considered. Therefore, phase OTDR vibration data are analyzed from two dimensions of time and space. The improved Otsu signal-to-noise separation method is applied to complete the signal-to-noise separation of vibration data. Firstly, the distributed optical fiber data is randomly divided into different parts. Secondly, the processed data is initialized to the threshold. Then the inter class variance is calculated, and the optimal threshold is determined by simulated annealing algorithm. The optimal solution obtained is regarded as the optimal solution of signal-to-noise separation. Finally, three different signals adopt EMD algorithm and improved algorithm for comparative experiment. The SNR evaluation index and visualization are adopted to show the advantages of the improved algorithm. The experimental results show that the algorithm has good signal-to-noise separation effect than other algorithms.
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