Three-dimensional vibration signal noise reduction method oriented to phi-OTDR technology

Abstract

The invention discloses a three-dimensional vibration signal noise reduction method oriented to the phi-OTDR technology. The noise reduction method realizes the noise reduction treatment on two kindsof noises. In the noise reduction aspect of coherent noises, coherent noises are regular in the time domain, so that a periodic transformation function is established based on the method. Finally, coherent noises are effectively counteracted. In the noise reduction aspect of random noises, the windowing smooth-wiener process-based filtering algorithm is adopted, so that the signal-to-noise ratio and the signal effective range can be ensured to be improved at the same time. The method comprises the following specific steps: step 1, determining an average signal-to-noise ratio and a signal effective range of an original signal; 2, filtering and denoising coherent noises; 3, filtering and denoising random noises.

Description

technical field [0001] The invention relates to a Φ-OTDR technology-oriented three-dimensional vibration signal denoising method, which belongs to the field of signal processing in the fully distributed optical fiber sensing technology. Background technique [0002] With the rapid development of optical fiber communication technology, optical fiber sensing technology has been deeply studied in recent years and has been widely used in health monitoring problems in many fields. Fully distributed optical fiber sensing technology, as a kind of optical fiber sensing technology, has attracted more and more attention because of its good distributed characteristics. In principle, fully distributed optical fiber sensing technology can be divided into three categories, namely Brillouin scattering, Rayleigh scattering, and Raman scattering. Brillouin scattering is mainly used to monitor deformation and temperature, Raman scattering is mainly used to monitor temperature, and Rayleigh s...

AI Technical Summary

Problems solved by technology

Some of the above random noise filtering methods focus on signal smoothing, some focus on improving the signal-to-noise ratio, and some focus on the separation of signal and noise, but these methods cannot balance the relationship between the above two evaluation indicators well, and cannot guarantee the signal Simultaneously improved noise ratio and effective signal range

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