A Signal Demodulation Method for Fiber Bragg Grating Sensing System

Abstract

A signal demodulation method of a fiber Bragg grating sensing system, the method adopts a noise reduction method compatible with smoothing and edge preservation to remove noise in the FBG sensing signal; and then performs iterative fitting region segmentation on the data after noise reduction , to determine all the unimodal regions; finally, the slope ratio of the corrected spectral curve is normalized to 1 degree as the objective function of each iteration, and the asymmetric spectrum in the unimodal region is sharpened and corrected by using the weighted first-order derivative, and the corrected The symmetrical spectrum is demodulated to obtain the central wavelength position of the FBG signal. The invention adopts a noise reduction method compatible with smoothness and edge preservation, which can protect the characteristic information of the signal from being lost while removing noise interference; iterative fitting region segmentation overcomes the shortcomings of traditional methods such as complex recursion and asymmetrical segmented regions. The segmentation efficiency and accuracy are improved; the accuracy of spectral peak demodulation is improved by sharpening and correcting the asymmetric spectrum, thereby improving the detection accuracy of the fiber Bragg grating sensing system.

Description

technical field [0001] The invention relates to a signal demodulation method of a fiber Bragg grating sensing system, which is not only suitable for the symmetric Gaussian spectrum type sensing signal with high signal-to-noise ratio, but also suitable for the asymmetric Gaussian spectrum type sensing signal with serious noise influence A signal belongs to the field of measurement technology. Background technique [0002] At present, sensing systems based on Fiber Bragg Gratings (FBG) are widely used in the measurement and monitoring of physical parameters such as strain, temperature and acceleration. Through the FBG demodulation algorithm, the accurate center wavelength position is obtained, which plays a vital role in the measurement accuracy of the sensing system. The traditional demodulation algorithm extracts the central wavelength feature, which has a good effect on the symmetric Gaussian spectral sensing signal with high signal-to-noise ratio, but it is not suitable f...

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Problems solved by technology

The traditional demodulation algorithm extracts the central wavelength feature, which has a good effect on the symmetric Gaussian spectral sensing signal with high signal-to-noise ratio, but it is not suitable for the asymmetrical Gaussian spectral sensing signal which is seriously affected by noise.

[0003] For the FBG sensing system with a large number of nodes, the signal-to-noise ratio of the sensing signal is low. The traditional demodulation method has the problems of blurring the feature points of the FBG signal, losing the detailed information of the spectrum, asymmetrical single peak area, long operation time, and non-linearity. Problems such as poor measurement accuracy of symmetrical Gaussian spectral signals

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