Signal-to-noise separation method for identical weak grating reflection signal
A signal-to-noise separation and reflection signal technology, which is applied in the direction of transmitting sensing components, converting sensor output, and instruments by using optical devices, to achieve the effects of reducing computational complexity, reducing computational time, and intelligent algorithms
Active Publication Date: 2020-12-18
BEIHANG UNIV +1
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[0005] The technical problem to be solved by the present invention is to realize the extraction of identical weak grating reflection signals under strong noise, and facilitate the demodulation and analysis processing of subsequent grating reflection signals
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[0039] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.
[0040] figure 1 It is a flowchart of the signal-to-noise separation method for identical weak grating reflection signals of the present invention, which includes a three-stage algorithm and mainly has three steps:
[0041] Step 1: The first-level algorithm module compares the collected photoelectric signal x 0 (t) Use multi-scale morphological filters for preprocessing to obtain the preprocessed signal x 1 (t), initially improve the signal-to-noi...
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The invention discloses a signal-to-noise separation method for an identical weak grating reflection signal, and the method comprises the following steps: A, a primary algorithm module: preprocessinga collected photoelectric signal x0(t) by adopting a multi-scale morphological filter to obtain a preprocessed signal x1(t), and preliminarily improving a signal-to-noise ratio; B, a secondary algorithm module: carrying out improved noise-assisted complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) on the preprocessed signal x1(t), introducing time predictability to carryout autonomous truncation and dimensionality reduction reconstruction to improve the adaptability, obtaining a dimensionality reduction reconstruction signal x2(t) and a reflection grating, and enabling the noise and the grating reflection signal; C, a third-level algorithm module: performing signal-to-noise separation on the signal x2(t) after dimension reduction reconstruction by adopting a blind source separation algorithm based on time predictability to obtain a final signal x3(t). By means of the method, the identical weak grating reflection signals annihilated by noise can be extracted in a strong noise environment, and then measurement information of grating reflection measurement points is effectively analyzed.
Description
technical field [0001] The invention relates to the technical field of identical weak grating reflection signal processing, in particular to an identical weak grating reflection signal processing method based on optical frequency domain reflection (OFDR) testing technology. Background technique [0002] Fiber Bragg Grating (FBG) sensing technology is a typical quasi-distributed optical fiber sensing technology. The change of external parameters can be measured by monitoring the center wavelength shift of FBG reflection spectrum. Due to the small coupling loss of optical fiber, It has many advantages such as strong reusability, good real-time performance and wide range of measurable parameters. It is widely used in the measurement and monitoring of mechanical quantities such as strain and temperature, and is suitable for long-term safety monitoring. [0003] The identical weak grating test system based on Optical Frequency Domain Reflectometry (OFDR) can realize multi-point r...
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IPC IPC(8): G01D5/26G06K9/62
CPCG01D5/268G06F18/21
Inventor 程伟杨云熙杨宁
Owner BEIHANG UNIV