Interferometric spectral demodulation method based on windowed peak estimation and phase wrapping integer

Abstract

The present application relates to a kind of interference spectrum demodulation methods based on windowed peak estimation and phase wrapping integerization, the method specifically includes: interference spectrum windowed modulation light source envelope;Fast Fourier transform, respectively take amplitude spectrum and phase spectrum;Amplitude spectrum calculates rough peak number;Phase spectrum takes integer and makes peak number accurate;Calculate the recovery sensor optical path difference information.The present application only needs to carry out single non-zero padding fast Fourier positive transformation to spectral signal, can extract the information from the light signal that the fiber-optic F-P sensor transmits, which can reflect the physical quantity to be measured.The operation complexity is low, and the operation speed of spectral demodulation algorithm is greatly improved.The high-precision real-time monitoring of kilohertz frequency signal can be realized, which is beneficial to the use of fiber-optic F-P sensor in more scenarios.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of optical fiber sensing, and particularly relates to an interference spectrum demodulation method based on windowed peak estimation and phase wrapping integerization. BACKGROUND

[0002] In various physical parameter monitoring based on fiber Fabry-Perot sensors, the demodulation process is responsible for extracting information reflecting the to-be-measured physical quantity from the light signal emitted by the sensor, and according to different technical routes, it is respectively divided into a device part and a method part. The spectrum demodulation method generally has the characteristics of high precision and wide dynamic range, but has high computational complexity and slow speed. SUMMARY

[0003] The application provides an interference spectrum demodulation method based on windowed peak estimation and phase wrapping integerization, and the technical problem to be solved is to solve the problem of slow calculation speed of the traditional spectrum demodulation method.

[0004] In order to solve the above technical problems, the application provides an interference spectrum demodulation method based on windowed peak estimation and phase wrapping integerization, and the specific steps are as follows:

[0005] Step S1: windowing the interference spectrum to modulate the light source envelope to obtain a preprocessed interference spectrum signal;

[0006] Step S2: performing fast Fourier transform on the preprocessed interference spectrum signal to obtain frequency spectrum information, and taking the amplitude spectrum and the phase spectrum, respectively;

[0007] Step S3: calculating a rough peak sequence number according to the amplitude spectrum of the interference spectrum;

[0008] Step S4: taking an integer accurate peak sequence number according to the phase spectrum of the interference spectrum;

[0009] Step S5: obtaining the optical path difference information of the recovered sensor according to the physical unit of each sequence number of the frequency spectrum information.

[0010] In step S1, the preprocessed interference spectrum signal is obtained as follows:

[0011]

[0012] Wherein, N represents the total number of discrete data points of a spectrum, n represents the nth number of a time series spectrum signal, l is the optical path difference of a sensor to be analyzed Fabry-Perot cavity, Δk is the Fourier transform period correction value of the maximum range of spectral wavenumber, and k1 is the minimum wavenumber value of the spectrum.

[0013] In step S2, the frequency spectrum information F(ξ)=fft{I(n)} is obtained.

[0014] Beneficial effects: the present application only needs to perform single non-zero padding fast Fourier forward transformation on the spectrum signal, and can extract information reflecting the to-be-measured physical quantity from the light signal transmitted by the fiber Fabry-Perot sensor.

[0015] The operation complexity is low, the repetition frequency of 17 kHz can be realized on the 8th generation Intel i7 processor, and the operation speed of the spectrum demodulation algorithm is greatly improved.

[0016] The interference spectrum demodulation method based on windowed peak estimation and phase wrapping integerization of the present application can realize high-precision real-time monitoring of signals below kilohertz frequency, and is beneficial to the use of fiber Fabry-Perot sensors in more scenarios. BRIEF DESCRIPTION OF DRAWINGS

[0017] Figure 1 is a flowchart of an embodiment of the interference spectrum demodulation method based on windowed peak estimation and phase wrapping integerization of the present application;

[0018] Figure 2 is the interference spectrum of a single Fabry-Perot cavity sensor and the corresponding light source envelope;

[0019] Figure 3 is the amplitude-frequency spectrum distribution of the preprocessed interference spectrum. DETAILED DESCRIPTION

[0020] In order to make the purpose, content and advantages of the present application clearer, the specific embodiments of the present application are described in further detail below.

[0021] The interference spectrum demodulation method based on windowed peak estimation and phase wrapping integerization proposed by the present application can extract information reflecting the to-be-measured physical quantity from the light signal transmitted by the fiber Fabry-Perot sensor, and the specific steps are as follows:

[0022] Step S1: windowing the interference spectrum and the light source envelope to obtain the preprocessed interference spectrum signal.

[0023] The present method involves Fourier transformation, and the original interference signal is modulated by the light source shape envelope. Different signal envelope waveforms will introduce different sidelobe distributions in the frequency domain distribution after Fourier transformation, thereby interfering with the normal demodulation of the signal. Therefore, the present method needs to window the light source envelope, thereby effectively reducing the sidelobe aliasing effect.

[0024] The preprocessed interference spectrum signal is obtained:

[0025]

[0026] Wherein: N represents the total number of discrete data points of a spectrum, n represents the nth number of time series spectrum signal; l is the optical path difference of the sensor to be analyzed Fabry-Perot cavity, Δk: Fourier transform period correction value of the maximum range of spectral wavenumber; k1: the minimum wavenumber value of the spectrum;

[0027] Step S2: the preprocessed interference spectrum signal is subjected to fast Fourier transform to obtain frequency spectrum information F(ξ)=fft(I(n)}.

[0028] Step S3: according to the amplitude spectrum of the interference spectrum, the rough peak value sequence number ξ is calculated

[0029] After Fourier transform of the wavenumber domain spectrum, the peak position of the target signal on the amplitude spectrum can reflect the optical path difference information of the Fabry-Perot cavity to be analyzed, which is embodied in the Fourier transform result of the discrete signal, that is, the peak value sequence number of the target signal is obtained. Due to the limited extraction ability of the amplitude spectrum, only the rough value of the peak value sequence number is obtained in this step, which is specifically:

[0030]

[0031] Wherein:

[0032] m is the lower sequence number of the nearest neighbor of the analyzed peak on the amplitude spectrum |F(ξ)| of the spectrum signal;

[0033] q is the ratio of the two discrete numbers of the nearest neighbor of the analyzed peak on the amplitude spectrum |F(ξ)| of the spectrum signal;

[0034] β is the estimated value of the difference between the real peak and the nearest lower sequence number on the amplitude spectrum |F(ξ)| of the spectrum signal;

[0035] ξ p : the estimated value of the real peak sequence number on the amplitude spectrum |F(ξ)| of the spectrum signal;

[0036] Step S4: according to the phase spectrum of the interference spectrum, the integral peak value sequence number ξ is obtained p .

[0037] After Fourier transform of the wavenumber domain spectrum, the target signal in the phase is related to the optical path difference of the corresponding Fabry-Perot cavity, and there is a certain difference between the phase calculated by using the rough peak value sequence number and the actual phase spectrum distribution after Fourier transform, which is embodied as the period number of phase wrapping is not an integer. But according to the mathematical expression after Fourier transform of the interference spectrum, the value should be an integer, so the integral processing is carried out according to , so as to obtain the real phase wrapping period number a, and according to which the real peak value sequence number ξ is calculated p .

[0038] Specifically:

[0039]

[0040] k1: the wave number value of the minimum spectrum;

[0041] k2: the wave number value of the maximum spectrum;

[0042] Δk: the Fourier transform period correction value of the maximum range of the spectrum wave number;

[0043] δ l : the change amount of the optical path difference corresponding to each unit increase in the ordinal number in the spectrum space;

[0044] : the change amount of the phase corresponding to each unit decrease in the ordinal number in the spectrum space;

[0045] : the initial phase value;

[0046] ψ·: the phase spectrum of the spectrum signal, with period wrapping;

[0047] : the estimated value of the phase wrapping period number of the phase difference between the unwrapped phase true value and the wrapped phase value;

[0048] a: the phase wrapping period number of the phase difference between the unwrapped phase true value and the wrapped phase value;

[0049] ξ p : the true peak position ordinal number on the spectrum signal amplitude spectrum |F(ξ)|;

[0050] l: the optical path difference of the sensor to be analyzed Fabry-Perot cavity.

[0051] Step S5: according to the physical unit of each ordinal number of the spectrum information, the optical path difference information l = δl·ξ of the recovered sensor is calculated p , and finally the optical path difference is output, thereby reflecting the change of the signal phase.

[0052] The meanings of the symbols involved in the method are as follows:

[0053] I(n): the spectrum signal after envelope modulation of the light source;

[0054] F(ξ): the spectrum information after fast Fourier transform of the spectrum signal I(n);

[0055] m: the lower ordinal number of the nearest peak position to be analyzed on the spectrum signal amplitude spectrum |F(ξ)|;

[0056] F(m): the spectrum signal amplitude value corresponding to the lower ordinal number m;

[0057] q: the ratio of two discrete numbers closest to the real peak position on the amplitude spectrum |F(ξ)| of the spectrum signal;

[0058] β: the estimated value of the difference between the real peak position and the next lower number on the amplitude spectrum |F(ξ)| of the spectrum signal;

[0059] the estimated value of the real peak position on the amplitude spectrum |F(ξ)| of the spectrum signal;

[0060] N: the total number of discrete data points of a spectrum;

[0061] k1: the minimum wave number value of the spectrum;

[0062] k2: the maximum wave number value of the spectrum;

[0063] Δk: the Fourier transform period correction value of the maximum range of the wave number of the spectrum;

[0064] δl: the change amount of the optical path difference corresponding to each unit increase in the order number in the spectrum space;

[0065] the change amount of the phase corresponding to each unit decrease in the order number in the spectrum space;

[0066] the initial phase value;

[0067] ψ·: the phase spectrum of the spectrum signal with period wrapping;

[0068] the estimated value of the phase wrapping period number of the difference between the true value of the unwrapped phase and the value of the wrapped phase;

[0069] a: the phase wrapping period number of the difference between the true value of the unwrapped phase and the value of the wrapped phase;

[0070] ξ p : the order number of the real peak position on the amplitude spectrum |F(ξ)| of the spectrum signal;

[0071] l: the optical path difference of the Fabry-Perot cavity to be analyzed of the sensor.

[0072] In the embodiment of the application, since only a single non-zero-padded fast Fourier transform needs to be performed on the original spectrum signal, compared with the traditional spectrum demodulation method, the operation complexity is greatly reduced, thereby improving the operation repetition speed of the method, and being conducive to realizing real-time demodulation of external signals.

[0073] As shown in FIG. 1, it is the interference spectrum of a single Fabry-Perot cavity sensor and the corresponding light source envelope. Figure 2

[0074] As shown in FIG. 2, it is the interference spectrum of a single Fabry-Perot cavity sensor and the corresponding light source envelope. Figure 3 ​The amplitude-frequency spectrum distribution of the fast Fourier transform after the pre-processing of the interference spectrum is shown.

[0075] As shown in the case, m = 6 can be analyzed, so that q = 1.021, β = 0.4844, According to the further calculation of the parameters of the spectrum, the following is obtained Therefore, a = 114, so that ξ p = 6.4692, so the accurate to-be-demodulated Fabry-Perot cavity interference optical path difference l = 1793.788 μm.

[0076] The above only describes the preferred embodiments of the present application, and it should be noted that for those skilled in the art, without departing from the technical principles of the present application, a number of improvements and modifications can be made, and these improvements and modifications should also be considered as the protection scope of the present application.

Claims

1. An interferometric spectroscopy demodulation method based on windowed peak estimation and phase wrapping integerization, characterized in that: The specific steps are as follows: Step S1: windowing the interference spectrum and modulating the light source envelope to obtain a pre-processed interference spectrum signal; Step S2: Perform fast Fourier transform on the pre-processed interference spectrum signal to obtain spectrum information, and take amplitude spectrum and phase spectrum respectively; Step S3: Calculate the rough peak number based on the amplitude spectrum of the interference spectrum Step S4: According to the phase spectrum of the interference spectrum, the peak number is rounded to obtain the true peak position number; the true peak position number ξ p The calculation is as follows: N represents the total number of discrete data points in a spectrum; m is the lower ordinal number of the nearest peak to be analyzed on the amplitude spectrum of the frequency spectrum signal |F(ξ)|; k1: minimum wave value of the spectrum; k2: the maximum wave value of the spectrum; Δk: Fourier transform period correction value of the maximum range of spectral wavenumbers; δl: In the spectrum space, the change in optical path difference corresponds to each increase of one unit in the ordinal number; In the spectrum space, each decrease of one unit in the ordinal number corresponds to a change in the phase; Initial phase value; ψ(m): phase spectrum of the spectrum signal, with periodic wrapping; An estimate of the number of phase wrapping cycles that is the difference between the true phase value without wrapping and the phase value with wrapping; a: The number of phase wrapping cycles between the true value of the phase without wrapping and the phase value with wrapping; Step S5: Obtain the optical path difference information of the restored sensor according to the physical unit of each ordinal number of the spectrum information.

2. The interferometric spectroscopy demodulation method based on windowed peak estimation and phase wrapping integerization according to claim 1, characterized in that: In step S1, the interference spectrum signal after preprocessing is obtained as: Where: N represents the total number of discrete data points in a spectrum, n represents the nth number of the time series spectrum signal; l is the optical path difference of the sensor's Fabry-Perot cavity to be analyzed, Δk is the Fourier transform period correction value of the maximum range of spectral wavenumbers; k1 is the minimum wavenumber value of the spectrum.

3. The interferometric spectroscopy demodulation method based on windowed peak estimation and phase wrapping integerization according to claim 1, characterized in that: In step S2, spectrum information F(ξ)=fft{I(n)} is obtained.

4. The interferometric spectroscopy demodulation method based on windowed peak estimation and phase wrapping integerization according to claim 1, characterized in that: In step S3, the rough peak number The calculation method is as follows: in: m is the lower ordinal number of the nearest peak to be analyzed on the amplitude spectrum of the frequency spectrum signal |F(ξ)|; q is the ratio of the two discrete numbers closest to the peak to be analyzed on the amplitude spectrum of the frequency spectrum signal |F(ξ)|; β is the estimated value of the difference between the true peak position and the nearest lower ordinal number on the amplitude spectrum of the spectral signal |F(ξ)|.

5. The interferometric spectroscopy demodulation method based on windowed peak estimation and phase wrapping integerization according to claim 1, characterized in that: In step S4, the number of cycles of the phase wrapping in the phase spectrum obtained in step S2 is Perform the rounding process to obtain the true phase wrapping period number a, and then calculate the true peak position number ξ based on it p .

6. The interferometric spectroscopy demodulation method based on windowed peak estimation and phase wrapping integerization according to claim 1, characterized in that: In step S5, the optical path difference information of the sensor is restored: l = δl·ξ p .

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