CN105181300A - Self-adaptive interference term extraction method of low coherence frequency domain interferogram - Google Patents

Abstract

The invention discloses a self-adaptive interference term extraction method of a low-coherence frequency domain interferogram. The method comprises the following steps: obtaining the low-coherence frequency domain interferogram; carrying out set experience modal decomposition, searching for an appropriate characteristic parameter and determining a K value; performing experience modal decomposition; obtaining psi1(omega); finally, determining whether the psi1(omega) accords with cosine distribution, and if the psi1(omega) accords with the cosine distribution, accurately extracting an interference term, and ending a program; and if the psi1(omega) does not accord with the cosine distribution, the program returning to step two for searching for the appropriate k value until the interference term is extracted. According to the invention, a set experience modal decomposition algorithm and an experience modal decomposition algorithm are combined together, such that the frequency domain low-coherence interference term can be adaptively extracted, the data processing process does not require manual parameter arrangement, and extraction of interference terms can be carried out on polarization maintaining fibers with different lengths. The method provided by the invention employs a frequency spectrum interference measurement method, the measuring time is short, the signal-to-noise ratio is high, and full-spectrum information can be obtained.

Description

The self-adaptation interference term extracting method of Low coherence frequency domain interferogram

Technical field

The present invention relates to the interference term extracting method of Low coherence frequency-domain interferometry, particularly relate to a kind of data processing method of frequency domain interference signal based on set empirical mode decomposition and empirical mode decomposition algorithm, belong to field of optical measuring technologies.

Background technology

Polarization maintaining optical fibre a kind ofly causes the perturbation birefringence of polarization state instability, to realize the optical fiber of polarization hold facility by artificially introducing intrinsic birefringence to eliminate.Although polarization maintaining optical fibre has possessed good guarantor's bias energy, reach degree of being practical, in some high precision interference systems, polarization coupled phenomenon still can show as the phenomenons such as noise, drift, signal attenuation, and influential system overall performance, as optical fibre gyro.So particularly important for the research of polarization maintaining optical fibre polarization coupled test.

Low coherence interference method, is also called partial coherence interferometric method, is a kind of interfere measurement technique using wide spectrum light source as coherent source.Because it has high precision and highly sensitive feature, low coherence interference method is used widely in precision measurement and sensory field, can carry out the test of polarization maintaining optical fibre polarization coupled.

Low coherence frequency-domain interferometry is by spectrometer collection interference light spectrogram, compared with traditional time domain interferometry, without the need to mechanical scanning compensating light path difference, so have the advantage that system noise is little, Measuring Time is short.Wherein, the frequency domain low coherence interference system based on Michelson interferometer is simple with its structure, and measuring accuracy is high and be widely used.

At present, for the extracting method of frequency domain interference spectrum interference term mainly based on the extracting method of Fourier transform.By Fourier transform, interference spectrum is transformed to group delay time domain, group delay time domain can obtain DC terms and interfere the pulse signal exchanging item, the wave filter of suitable width being artificially set in pulse place exchanging item correspondence, being extracted, carry out inverse Fourier transform again, can interference term be obtained.But the method is very responsive to the Selecting parameter of wave filter, need position and the width of considering wave filter.At the Data processing of reality, this extracting method based on Fourier transform is often very consuming time, is unfavorable for processing a large amount of data.

Empirical mode decomposition is a kind of according to the feature of signal own, the adaptive algorithm of decomposing signal.Different with wavelet transformation from conventional Fourier transform, the method does not decompose basis function, is to decompose according to the yardstick of signal itself.Therefore, the method is specially adapted to non-stationary and nonlinear properties.But when processing actual signal, there will be mode collection and fold phenomenon, namely the signal of different frequency bands is decomposed in same intrinsic mode function, thus makes intrinsic mode function lose physical significance.Fold to eliminate mode collection, the set empirical mode decomposition algorithm average based on white noise is put forward by people such as Huang, by repeatedly adding white noise, utilizes the mean effort of white noise, avoid mode collection to fold, obtain the intrinsic mode function with actual physical meaning.Patent CN102819750A proposes a kind of hyperspectral image classification method based on gathering empirical mode decomposition fast, goes out land detailed information by spectral image data being gathered fast empirical mode decomposition extraction characteristic retrieval.Patent CN104375973A proposes a kind of blind source signal denoising method based on set empirical mode decomposition, the method have modified the definition of dialogue noise amplitude and iterations in former algorithm, and utilize classical progressively analytical approach IMF component to be carried out to differentiation and the removal of chaff component, thus eliminate chaff component to the interference of follow-up denoise algorithm.Although these two patents all relate to the method for set empirical mode decomposition, the interference term in Low coherence frequency-domain interference spectrum cannot be extracted.

Summary of the invention

The present invention seeks to the above-mentioned deficiency overcoming prior art, find the method for interference term in a kind of more efficiently extraction frequency-domain interference spectrum, avoid the dependence that in Fourier transformation method, data processed result is selected wave filter, propose a kind of self-adaptation interference term extracting method of interfering based on the Low coherence frequency domain gathering empirical mode decomposition and empirical mode decomposition algorithm.The method is applicable to different experiment conditions, can adaptively accurately be extracted by interference term, is different from conventional fourier transform method, without the need to artificially arranging wave filter, avoid the impact of wave filter Select Error on experimental result, therefore the method stability is better, accuracy is higher.

Technical scheme

The concrete steps of the extracting method of the self-adaptation interference term of Low coherence frequency domain interferogram provided by the invention are as follows:

1st step: obtain Low coherence frequency domain interferogram.

Build Low coherence frequency domain interferometer measuration system, light source adopts Gaussian spectrum wideband light source, then broadband optical-fiber source is connected to polarization maintaining optical fibre to be measured, and the other end of polarization maintaining optical fibre, by after a compensating interferometer instrument, is connected to spectrometer.The Low coherence frequency domain interferogram collected with spectrometer, is expressed as:

Wherein, ω is light field angular frequency, I ₀(ω) represent that light source power is composed, h is coupling strength factor, be the phase differential of two light beams, n (ω) is the noise in real system.

2nd step: carry out set empirical mode decomposition, finds suitable characteristic parameter and determines k value.

Decomposable process comprises three parts:

A. add white noise sequence, carry out set empirical mode decomposition and obtain:

$I_1\left(\mathrm{\ω}\right)=\underset{i=1}{\overset{k}{\mathrm{\Σ}}}{f}_i\left(\mathrm{\ω}\right)+\underset{i=k+1}{\overset{N}{\mathrm{\Σ}}}{f}_i\left(\mathrm{\ω}\right)+{\stackrel{\‾}{r}}_N\left(\mathrm{\ω}\right)$

Wherein f _i(ω) be the intrinsic mode function (IMF) that set empirical mode decomposition obtains, N is natural number, and represent the number of decomposing the IMF obtained, k is the number of noise intrinsic mode function, 1≤k≤N-1, be a front k IMF and, represent noise signal n (ω), represent I ₁(ω) IMFs that in, interference term decomposed obtains, for I ₀(ω).

B. the related coefficient of each intrinsic mode function and original signal is calculated.

$CC=\frac{f\left(\mathrm{\ω}\right)\⊗I_1\left(\mathrm{\ω}\right)}{\sqrt{D\left(f\right(\mathrm{\ω}\left)\right)}\·\sqrt{D\left(I_1\right(\mathrm{\ω}\left)\right)}}$

$f\left(\mathrm{\ω}\right)\⊗I_1\left(\mathrm{\ω}\right)=\∫{\∫}_{-\mathrm{\∞}}^{+\mathrm{\∞}}f\left({\mathrm{\ω}}^{\′}\right)\·I_1*({\mathrm{\ω}}^{\′}-\mathrm{\ω}){\mathrm{d\ω}}^{\′}$

Wherein, represent the computing cross-correlation of intrinsic mode function and original signal, I ₁ ^*(ω '-ω) represents signal I ₁conjugation after (ω ') translation ω, represent f (ω) and I respectively ₁(ω) standard deviation, the order of magnitude of CC, between 0 and 1, characterizes the similarity degree of intrinsic mode function and original signal.

C. find suitable characteristic parameter and determine k value.

Due to the intrinsic mode function of noise and the similarity degree of original signal lower and be distributed in a front k IMF, the related coefficient of kth+1 IMF is much larger than the related coefficient of a kth IMF, then this interval is that first CC value changes maximum interval, can by the optimization method Automatic-searching of iteration to this interval, and select suitable value as characteristic parameter in this is interval, the intrinsic mode function making related coefficient be less than characteristic parameter is identified as noise signal, this noise signal is removed.

3rd step: obtain new spectral signal.

Namely the interference spectum after denoising:

4th step: empirical mode decomposition.

Empirical mode decomposition is carried out to new interference spectum spectral signal:

$I_2\left(\mathrm{\ω}\right)=\underset{j=1}{\overset{M}{\mathrm{\Σ}}}{\mathrm{\ψ}}_j\left(\mathrm{\ω}\right)+r_M\left(\mathrm{\ω}\right)$

Wherein, ψ _j(ω) be decompose the intrinsic mode function obtained, M is natural number, represents the number of decomposing the intrinsic mode function obtained, r _m(ω) be nubbin.

5th step: obtain ψ ₁(ω).

Because the noise in system obtains good suppression through set empirical mode decomposition, therefore frequency-domain interference spectrum figure can avoid mode collection to fold phenomenon in empirical mode decomposition, makes each decompose the intrinsic mode function obtained and has physical significance.The intrinsic mode function obtained due to empirical mode decomposition is arranged in order according to frequency size, therefore the intrinsic mode function being decomposed out is at first ψ ₁(ω) be I ₁(ω) interference term in.

6th step: judge ψ ₁(ω) whether meet cosine distribution, if meet, interference term accurately extracts, EOP (end of program); If do not meet, then program jumps in the 2nd step again, finds suitable k value, until interference term is extracted.

Advantage of the present invention and good effect:

Set empirical mode decomposition algorithm combines with empirical mode decomposition algorithm by the present invention, frequency domain low coherence interference item can be extracted adaptively, data handling procedure, without the need to artificial parameters, can carry out the extraction of interference term to the polarization maintaining optical fibre of different length.The present invention adopts frequency spectrum interference mensuration, and Measuring Time is short, and Signal-to-Noise is high, can obtain full spectral information.

Accompanying drawing explanation

Fig. 1 is the self-adaptation extraction method process flow diagram of interfering interference term based on the Low coherence frequency domain gathering empirical mode decomposition and empirical mode decomposition algorithm;

Fig. 2 is that frequency domain interference term of the present invention extracts experimental provision;

In fig. 2,1 is SLD wideband light source, and 2 is optical fiber polarizers, 3 is joint flanges of the optical fiber polarizer and polarization maintaining optical fibre, and 4 is polarization maintaining optical fibres to be measured, and 5 is collimation lenses, 6 is half-wave plates, 7 is analyzers, and 8 is stationary mirrors, and 9 is scanning reflection mirrors, 10 is beam splitters, 11 is convergent lenses, and 12 is the single-mode fibers connected, and 13 is spectrometers;

Fig. 3, Fig. 4, Fig. 5 are respectively the frequency-domain interference spectrum signal that when tested optical fiber length is 1m, 110m, 750m, spectrometer collects;

Fig. 6, Fig. 7, Fig. 8 are respectively interference term when fiber lengths is 1m, 110m, 750m and extract result.

The contrast of the result that when Fig. 9, Figure 10, Figure 11 are respectively fiber lengths 1m, 110m, 750m, the inventive method extracts and the result obtained by Fourier transformation method, wherein, A represents the interference term contrast that two kinds of methods are extracted, and B represents the phase correlation in interference term.

The assertive evidence mode function that when table 1 is under different tested optical fiber length, set empirical mode decomposition obtains and the related coefficient of original signal.

Embodiment

Embodiment 1:

Fig. 1 is the self-adaptation extraction method process flow diagram of interfering interference term based on the Low coherence frequency domain gathering empirical mode decomposition and empirical mode decomposition algorithm; Fig. 2 is that the frequency domain interference term adopted in the present invention extracts experimental provision;

Principle of the present invention and workflow as follows:

In Fig. 2, Gauss's spectral pattern low-coherent light that centre wavelength is 1310nm is sent from SLD wideband light source 1, linearly polarized light (excitation mode) is become through the optical fiber polarizer 2, be mapped in polarization maintaining optical fibre 4 to be measured by connecting into of ring flange 3 again, can polarization coupled be there is in this tie point place, part energy is coupled on polarization direction vertical with it by the mould that excites originally, and this pattern is called coupled modes, and stiffness of coupling coefficient h characterizes.Due to birefringence, the velocity of propagation on two polarization directions is different, at fiber exit end, can produce the phase differential relevant with the length of polarization maintaining optical fibre 4 therebetween.By collimation lens 5, optical fiber is converted to spatial light, in order to enable two bunch polarisations interfere, by half-wave plate 6 and analyzer 7, two polarized light equal proportions is projected on a polarization direction, interferes.In order to compensate the optical path difference of two-beam, utilizing the mobile reflection arm in Michelson Interferometer device to scan, obtaining interference fringe.The effect of convergent lens 11 is entered in optical fiber space optical coupling, then enter into spectrometer 13 by single-mode fiber 12, obtains frequency domain interference light spectrogram.Finally carry out data processing in a computer.

In order to prove the adaptivity that the method is extracted and validity, respectively the testing fiber of different length is detected.

1st step: obtain Low coherence frequency domain interferogram.

Select 1m, 110m, 750m polarization maintaining optical fibre, respectively by spectrometer collection interference spectum data, as shown in Fig. 3, Fig. 4, Fig. 5.

2nd step: carry out set empirical mode decomposition, finds suitable characteristic parameter and determines k value.

A. add white noise sequence, carry out set empirical mode decomposition.The white noise sequence number added in program is 100 and standard deviation size is 1/4 of original signal.

B. the related coefficient of each intrinsic mode function and original signal is calculated.Result of calculation is as table 1.

The related coefficient of each IMF of table 1 different fiber length and original signal

C. find suitable characteristic parameter and determine k value.Analytical table 1, characteristic parameter is taken as 0.1, k=2.Namely the first two intrinsic mode function is noise signal.

3rd step: obtain new spectral signal.Namely the new signal obtained after removing IMF1 and IMF2.

4th step: empirical mode decomposition.Empirical mode decomposition is carried out to new signal, due to the removal of noise, avoids modal overlap.

5th step: obtain ψ ₁(ω).IMF1 and ψ that empirical mode decomposition obtains ₁(ω) item is exchanged for interfering.Experimental result is as shown in Fig. 6, Fig. 7, Fig. 8.

6th step: judge ψ ₁(ω) whether cosine distribution is met.Clearly, the interference term extracted all meets.

Then the result extracted and the result obtained by Fourier transformation method are contrasted, respectively as shown in Fig. 9, Figure 10, Figure 11, as can be seen from the figure the method accurately can extract interference term, and the phase information that the two obtains near centre wavelength is almost identical, can find out that this method has good adaptivity simultaneously, effect can not be lost because of the change of tested optical fiber length.

Adopt frequency domain interference term extracting method of the present invention, interference term can be extracted by set empirical mode decomposition and empirical mode decomposition algorithm adaptively, compare traditional extracting method based on Fourier transform more efficient, without the need to artificially setting filter parameter, greatly save data processing time, and avoid because the position of the different wave filter of tested optical fiber length and size need the problem reselected, in extracting method principle of the present invention rationally, Data Processing in Experiment reliable results, accurately, and whole processing procedure adaptive ability is strong.The stability of the results show of many experiments the method and accuracy.

Claims (1)

1. a self-adaptation interference term extracting method for Low coherence frequency domain interferogram, is characterized in that the concrete steps of the method are as follows:

1st step: obtain Low coherence frequency domain interferogram;

The Low coherence frequency domain interferogram collected with spectrometer, is expressed as:

Wherein, ω is light field angular frequency, I ₀(ω) represent that light source power is composed, h is coupling strength factor, be the phase differential of two light beams, n (ω) is the noise in real system;

2nd step: carry out set empirical mode decomposition, finds suitable characteristic parameter and determines k value;

Decomposable process comprises three parts:

A. add white noise sequence, carry out set empirical mode decomposition and obtain:

$I_1\left(\mathrm{\ω}\right)=\underset{i=1}{\overset{k}{\mathrm{\Σ}}}{f}_i\left(\mathrm{\ω}\right)+\underset{i=k+1}{\overset{N}{\mathrm{\Σ}}}{f}_i\left(\mathrm{\ω}\right)+{\stackrel{\‾}{r}}_N\left(\mathrm{\ω}\right)$

Wherein f _i(ω) be the intrinsic mode function (IMF) that set empirical mode decomposition obtains, N is natural number, and represent the number of decomposing the IMF obtained, k is the number of noise intrinsic mode function, be a front k IMF and, represent noise signal n (ω), represent I ₁(ω) IMFs that in, interference term decomposed obtains,

B. the related coefficient of each intrinsic mode function and original signal is calculated,

$CC=\frac{f\left(\mathrm{\ω}\right)\⊗I_1\left(\mathrm{\ω}\right)}{\sqrt{D\left(f\right(\mathrm{\ω}\left)\right)}\·\sqrt{D\left(I_1\right(\mathrm{\ω}\left)\right)}}$

$f\left(\mathrm{\ω}\right)\⊗I_1\left(\mathrm{\ω}\right)=\∫{\∫}_{-\mathrm{\∞}}^{+\mathrm{\∞}}f\left({\mathrm{\ω}}^{\′}\right)\·I_1*({\mathrm{\ω}}^{\′}-\mathrm{\ω}){\mathrm{d\ω}}^{\′}$

Wherein, represent the computing cross-correlation of intrinsic mode function and original signal, I ₁ ^*(ω '-ω) represents signal I ₁conjugation after (ω ') translation ω, represent f (ω) and I respectively ₁(ω) standard deviation, the order of magnitude of CC, between 0 and 1, characterizes the similarity degree of intrinsic mode function and original signal;

C. find suitable characteristic parameter and determine k value;

Due to the intrinsic mode function of noise and the similarity degree of original signal lower and be distributed in a front k IMF, the related coefficient of kth+1 IMF is much larger than the related coefficient of a kth IMF, then this interval is that first CC value changes maximum interval, by the optimization method of iteration can Automatic-searching to this interval, and select suitable value as characteristic parameter in this is interval, the intrinsic mode function making related coefficient be less than characteristic parameter is identified as noise signal, this noise signal is removed;

3rd step: obtain new spectral signal;

Interference spectum after denoising:

4th step: empirical mode decomposition;

Empirical mode decomposition is carried out to new interference spectum spectral signal:

$I_2\left(\mathrm{\ω}\right)=\underset{j=1}{\overset{M}{\mathrm{\Σ}}}{\mathrm{\ψ}}_j\left(\mathrm{\ω}\right)+r_M\left(\mathrm{\ω}\right)$

Wherein, ψ _j(ω) be decompose the intrinsic mode function obtained, M is natural number, represents the number of decomposing the intrinsic mode function obtained, r _m(ω) be nubbin;

5th step: obtain ψ ₁(ω);

Because the noise in system obtains good suppression through set empirical mode decomposition, therefore frequency-domain interference spectrum figure can avoid mode collection to fold phenomenon in empirical mode decomposition, makes each decompose the intrinsic mode function obtained and has physical significance; The intrinsic mode function obtained due to empirical mode decomposition is arranged in order according to frequency size, therefore the intrinsic mode function being decomposed out is at first ψ ₁(ω) be I ₁(ω) interference term in;

6th step: judge ψ ₁(ω) whether meet cosine distribution, if meet, interference term accurately extracts, EOP (end of program); If do not meet, then program jumps in the 2nd step again, finds suitable k value, until interference term is extracted.