A Brillouin Optical Time Domain Analyzer Denoising Method and System Based on Dictionary Learning

Abstract

The invention discloses a Brillouin optical time domain analyzer denoising method. The method comprises the following steps: S1, scanning the frequency of probe light and detecting an intensity gain of the probe light to obtain a Brillouin gain spectrum distributed along the length of a fiber; S2, training the Brillouin gain spectrum based on a dictionary learning algorithm to obtain a sparse representation coefficient and a sparse representation dictionary corresponding to each position of the Brillouin gain spectrum; S3, decomposing the Brillouin spectrum into a plurality of sub-matrix blocks, adding global prior conditions to the local sparse representation of the Brillouin gain spectrum, carrying out global averaging by using the sparse representation coefficients and the sparse representation dictionaries of the Brillouin gain spectrum; and S4, reforming the average sub-matrix blocks to obtain a denoised Brillouin gain spectrum. According to the invention, because of the characteristic of not having sparsity by the noise, sparse representation of the Brillouin gain spectrum as well as the noise filtering is performed. A novel data processing method is provided for the Brillouin optical time domain analyzer system; and the processing speed is fast and the consumed time is short.

Description

technical field [0001] The invention belongs to the technical field of distributed optical fiber sensing, and more specifically relates to a denoising method and system for a Brillouin optical time domain analyzer. Background technique [0002] In recent years, the Brillouin optical time-domain analyzer has attracted much attention because it can be used for distributed monitoring of optical fiber strain and temperature. This analyzer has the advantages of high spatial resolution, long sensing distance, and low equipment cost. It is widely used in Oil and gas pipeline leak detection, bridge safety monitoring and fire alarm and other fields. [0003] In the sensing fiber, the pulsed pump light interacts with the backpropagating continuous probe light via stimulated Brillouin scattering. When the frequency offset of the two beams of light is within the Brillouin gain spectrum, the energy of the high-frequency pulsed pump light will be transferred to the continuous probe light...

AI Technical Summary

Problems solved by technology

These image processing algorithms (such as non-local mean, wavelet denoising and 3D block matching, etc.) have good denoising effects in Brillouin optical time domain analyzers, but these algorithms do not consider the redundancy of the Brillouin gain spectrum itself. The remaining characteristics require constant adjustment of algorithm parameters in the denoising process, which is not universally applicable in practical applications

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