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Method for processing fibber Bragg grating (FBG) signals based on translation invariant wavelet

A translation invariant, signal processing technology, applied in the direction of using optical devices to transmit sensing components, to achieve the effect of eliminating additional oscillation, improving demodulation accuracy, and solving uncertainty and instability

Active Publication Date: 2013-02-27
CHONGQING UNIV OF POSTS & TELECOMM
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

The present invention overcomes the constant deviation between the estimated signal and the original signal produced by the traditional soft threshold denoising of wavelet analysis, eliminates the additional oscillation caused by the discontinuity of the function in the traditional hard threshold method, and solves the problem of the existing improved threshold function due to the expression Uncertainty and instability caused by the inclusion of regulatory factors

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  • Method for processing fibber Bragg grating (FBG) signals based on translation invariant wavelet
  • Method for processing fibber Bragg grating (FBG) signals based on translation invariant wavelet
  • Method for processing fibber Bragg grating (FBG) signals based on translation invariant wavelet

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Embodiment 1

[0051] figure 1 Flow chart of FBG spectral signal processing method based on translation invariant wavelet, figure 2 Flow chart of translation invariant wavelet denoising, image 3 Adaptive method to determine the optimal decomposition layer flow chart, Figure 4 Improved threshold function threshold processing flowchart, as shown in the figure: a kind of FBG signal processing method based on translation invariant wavelet provided by the present invention, comprises the following steps:

[0052] S1: get length 2 N The FBG spectral signal f(i)=s(i)+n(i), i=0,1,...N-1; where, s(i) represents the denoising signal, n(i) represents Gaussian white Noise, N represents the length of the data sequence;

[0053] S2: Perform J-layer translation invariant wavelet decomposition on the FBG spectral signal f(i) to obtain the wavelet coefficient w of each layer j，k , where J is the best decomposition layer, the initial value is 1, j=J-1, k=N / 2 j ;

[0054] The wavelet coefficient w of...

Embodiment 2

[0083] This embodiment 2 describes in detail the FBG signal processing method based on the translation invariant wavelet:

[0084] The data processing method provided by Embodiment 2 of the present invention is proposed for the problem that the noise contained in the FBG spectral signal seriously affects the accuracy of its wavelength demodulation. Among them, the wavelet denoising method with improved threshold can filter out the noise very well, and obtain the best approximate signal of the FBG pure spectral signal; , and has high precision and good stability, so the combination of high-efficiency denoising method and high-precision peak-finding algorithm can more accurately demodulate the parameter value of the physical quantity measured by FBG.

[0085] The flow chart of this FBG spectral signal processing method is as follows figure 1 As shown, its specific implementation steps are as follows:

[0086] Step 1: First collect a section of FBG spectral signal at a certain ...

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Abstract

The invention relates to a method for processing FBG signals based on a translation invariant wavelet of an improved threshold value. The method includes providing an improved threshold function and combining the threshold function with the translation invariant wavelet to denoise the FBG noisy signals; and fitting denoised FBG spectral signals through a Gaussian fitting formula so as to position the peak wavelength. The wavelet denoising portion mainly includes performing cycle spinning on the FBG noisy signals, performing discrete wavelet decomposition on the spun signals to extract the wavelet coefficient in each layer, performing threshold value quantization on the wavelet coefficients by using improved threshold function, reconstructing the wavelet coefficients after the threshold value quantization, performing reverse cycle spinning on the reconstructed signals, and averaging the reconstructed signals at different spinning positions to obtain the final denoised signals. A Gaussian fitting peak searching algorithm mainly includes fitting the denooised signals through the Gaussian formula and obtaining the wavelength corresponding to the peak to finish demodulation of the FBG spectral signals.

Description

technical field [0001] The invention relates to a signal processing method of optical fiber sensing, in particular to a FBG signal processing method based on translation invariant wavelet. Background technique [0002] Fiber Bragg Grating (FBG), as a kind of fiber passive device, has developed rapidly in the fields of fiber optic sensing and fiber optic communication in recent years, and its wavelength demodulation technology is the key technology in sensing applications. The existence of noise seriously affects the demodulation accuracy of the wavelength, thereby affecting the demodulation accuracy of the measured physical quantity. Therefore, the high-efficiency denoising method combined with the high-precision FBG peak-finding algorithm can realize the accurate demodulation of the FBG signal. [0003] For signal denoising, the denoising method based on wavelet analysis has achieved good results in the field of signal processing. The wavelet threshold denoising method can...

Claims

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Application Information

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IPC IPC(8): G01D5/26
Inventor 陈勇贺明玲刘焕淋王昆陈丽娟杨雪
Owner CHONGQING UNIV OF POSTS & TELECOMM
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