Fast botda system and demodulation method based on spectrum and dynamic signal compressed sensing

Abstract

The application provides a fast BOTDA system and a demodulation method based on spectrum and dynamic signal compressed sensing, and the demodulation method comprises the following steps: 1) performing Brillouin spectrum compressed sampling and reconstruction: Brillouin spectrum compressed sampling is realized by detecting light frequency Gaussian random scanning; Brillouin spectrum reconstruction is realized based on Brillouin spectrum compressed sampling transformation vectors according to an observation signal and a Brillouin spectrum transformation domain dictionary; 2) performing dynamic signal compressed sampling and reconstruction: dynamic signal compressed sampling is realized by controlling a pulse sequence and a corresponding microwave scanning sequence, and dynamic signal reconstruction is realized based on dynamic signal compressed sampling transformation vectors according to a dynamic signal transformation domain dictionary; 3) demodulating according to the reconstructed Brillouin spectrum and the reconstructed dynamic signal. The technical scheme of the application can solve the technical problem that the prior art cannot meet the data compression requirement of the fast BOTDA system.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of optical technology, and in particular to a fast BOTDA system and demodulation method based on spectrum and dynamic signal compression sensing. BACKGROUND

[0002] Fiber sensing has the characteristics of anti-electromagnetic interference and corrosion resistance, can work in extreme conditions, and the fiber material has the advantages of small volume, light weight, and easy to lay, etc., showing excellent engineering characteristics. The distributed fiber sensing technology based on scattering effect can simultaneously transmit and sense signals to realize spatial continuous measurement, and the monitoring points can reach millions. The scattering type distributed fiber sensing technology has become an important development direction of fiber sensors. The types of scattered light signals mainly include Rayleigh scattering, Brillouin scattering and Raman scattering, and the corresponding distributed fiber sensors have been widely studied. Brillouin optical time domain analysis (BOTDA) has the advantages of high spatial resolution, fast measurement, high precision, etc., and has become one of the typical representative technologies of distributed fiber sensing technology.

[0003] After more than ten years of technological development, the measurement time of the BOTDA system based on the frequency scanning scheme has approached the performance limit. In the measurement process, the frequency difference between the pump light and the probe light needs to be scanned, and the main factors affecting the measurement time of the BOTDA system are the fiber length, the average number, the frequency switching speed and the frequency scanning step number. The fiber length limits the trigger interval of the pulse signal, and it is necessary to ensure that there is only one pulse signal in the measured fiber to avoid signal overlap, and the measured Brillouin signal also needs a certain number of averages to improve the signal-to-noise ratio. For short-range sensing, the pulse interval and the required average number can be reduced, and at this time the last two factors (frequency switching time and frequency scanning step number) become the main limitation. The arbitrary waveform generator (AWG) can realize fast frequency switching using high-speed digital circuits, that is, optical agile frequency technology, which effectively solves the limitation of frequency switching time on the measurement time of the BOTDA system. The optical agile frequency technology is used to realize the fast scanning of the probe light frequency of the BOTDA system, and the required frequency is written into the memory of the arbitrary waveform generator once output, combined with IQ frequency raising to realize the fast scanning of the probe light frequency, and the timing of the pump pulse sequence and the probe light modulated by the optical agile frequency is input from both ends of the measured fiber. The length of the measured fiber is 100m, and under the condition of 10 times average, the system sampling rate can reach 10kHz. Therefore, the number of Brillouin frequency scanning becomes the main factor limiting the BOTDA system, especially for large temperature and large strain monitoring, which needs to further increase the number of frequency scanning, resulting in the increase of the measurement time of the frequency scanning BOTDA system.

[0004] On the other hand, the performance of the frequency scanning BOTDA is restricted by high data storage pressure. The BOTDA system needs to record the data of all fiber positions during the frequency scanning process to obtain the Brillouin gain spectrum of all fiber positions. However, in the dynamic signal measurement process, the Brillouin gain spectrum of a single measurement is a sampling of the dynamic signal, and needs to be recorded continuously for a certain period of time to complete the dynamic signal measurement. In the case of high-speed sampling, the frequency scanning based BOTDA system cannot realize fast processing of data, and can only record all the data first. The storage space of the high sampling rate (above 100 MHz) acquisition card also has a high requirement. In the traditional compression technology, the signal data is first collected completely, and then the redundant information in the data is removed by using an algorithm to realize data compression. In the process of data reconstruction, the original signal is recovered by using a decompression algorithm. In this acquisition-compression-transmission-decompression mode, the data compression technology only reduces the data amount stored and transmitted by the later processing equipment, and there is still great hardware pressure on the acquisition equipment.

[0005] The compression sensing technology directly realizes data compression in the acquisition process, and reduces the memory requirement of the acquisition card. The BOTDA sensing research based on the compression sensing technology has been preliminarily applied. The Brillouin gain spectrum is represented in the cosine domain and other sparse domains, and the Brillouin gain spectrum is reconstructed by using a small amount of collected samples combined with a reconstruction algorithm. In 2020, the researchers of Harbin Institute of Technology proposed a Brillouin spectrum compression sampling based on principal component analysis. In the case of a scanning step of 4 MHz, the distributed Brillouin fiber sensing can be completed by using 30% of the uniformly and equally spaced sampling data, which effectively improves the system sampling rate and reduces the data storage amount.

[0006] However, the existing technology still cannot meet the data compression requirement of the fast BOTDA system. How to further expand the application of the compression sensing algorithm in the fast BOTDA system has high scientific research and engineering application value. SUMMARY

[0007] The present application aims at at least solving one of the problems in the prior art.

[0008] According to an aspect of the present application, a demodulation method of a fast BOTDA system based on spectrum and dynamic signal compression sensing is provided, and the demodulation method comprises the following steps:

[0009] 1) Brillouin spectrum compression sampling and reconstruction: Brillouin spectrum compression sampling is realized by detecting the Gaussian random scanning of the light frequency; Brillouin spectrum reconstruction is realized based on the Brillouin spectrum compression sampling transformation vector according to the observation signal and the Brillouin spectrum transformation domain dictionary;

[0010] 2) Dynamic signal compressed sampling and reconstruction: dynamic signal compressed sampling is realized by controlling the pulse sequence and its corresponding microwave scanning sequence, and dynamic signal reconstruction is realized according to a dynamic signal transform domain dictionary and based on a dynamic signal compressed sampling transform vector;

[0011] 3) Demodulation is performed according to the reconstructed Brillouin spectrum and the reconstructed dynamic signal.

[0012] Further, in step 1), a Brillouin spectrum database of different frequency shifts is simulated and acquired according to Brillouin spectrum characteristics, Brillouin spectrum sparsification is realized based on a Brillouin spectrum transform domain dictionary, and Brillouin spectrum compressed sampling is realized based on a Brillouin spectrum measurement matrix.

[0013] Further, the Brillouin spectrum transform domain dictionary is obtained by a principal component analysis algorithm.

[0014] Further, the Brillouin spectrum measurement matrix is constructed by using a Gaussian random matrix.

[0015] Further, the Brillouin spectrum compressed sampling transform vector and the dynamic signal compressed sampling transform vector are solved by using a convex optimization algorithm, a combination algorithm, a statistical optimization algorithm, a greedy algorithm or a cross matching pursuit algorithm.

[0016] According to another aspect of the present application, a fast BOTDA system based on spectrum and dynamic signal compressed sensing is provided, which realizes demodulation by using the above-mentioned demodulation method. The fast BOTDA system comprises a first laser, a coupler, a first electro-optical modulator, a second electro-optical modulator, an arbitrary waveform generator, an amplifier, a second laser, a to-be-measured optical fiber, a photoelectric detector, a data acquisition card and a data processing module. The output signal of the first laser is divided into two signals after passing through the coupler, and the two signals enter the first electro-optical modulator and the second electro-optical modulator respectively. The arbitrary waveform generator provides loading electrical signals for the first electro-optical modulator and the second electro-optical modulator respectively. The first electro-optical modulator outputs a pump pulse light signal, and the second electro-optical modulator outputs an optical frequency agile signal, thereby realizing Brillouin spectrum compressed sampling and dynamic signal compressed sampling. The pump pulse light signal enters the to-be-measured optical fiber after being amplified by the amplifier, and the optical frequency agile signal enters the to-be-measured optical fiber after being shaped by the second laser. The signal in the to-be-measured optical fiber is subjected to stimulated Brillouin scattering, carries Brillouin gain spectrum information and is output to the photoelectric detector. The data acquisition card acquires data of the photoelectric detector. The data processing module reconstructs the Brillouin spectrum and the dynamic signal according to the data acquired by the data acquisition card, and demodulates according to the reconstructed Brillouin spectrum and the reconstructed dynamic signal.

[0017] Further, the fast BOTDA system further comprises a first circulator, the amplified pump pulse light signal is input into the to-be-measured optical fiber from a second port of the first circulator after passing through a first port of the first circulator, and a signal in the to-be-measured optical fiber is subjected to stimulated Brillouin scattering, and Brillouin gain spectrum information is output from a third port of the first circulator to the photodetector.

[0018] Further, the fast BOTDA system further comprises a second circulator, the optical signal output after being subjected to double-sideband modulation by the second electro-optic modulator is input into the second laser from a second port of the second circulator after passing through a first port of the second circulator, the lower sideband light signal is injected and locked to be output, and the probe light is filtered, amplified, and spectrum-shaped and then output from a third port of the second circulator.

[0019] Further, the fast BOTDA system further comprises an isolator, and the isolator is located between the second circulator and the to-be-measured optical fiber.

[0020] Further, the amplifier is an erbium-doped fiber amplifier.

[0021] The technical scheme of the present application provides a fast BOTDA system and a demodulation method based on spectrum and dynamic signal compression sensing, the demodulation method is used for compression sampling and reconstruction of Brillouin spectrum and dynamic signal, the number of frequencies required for Brillouin spectrum measurement and the number of Brillouin spectra required for dynamic signal are reduced, and the data storage space is greatly reduced. Compared with the existing compression sensing BOTDA system, the data storage space is further reduced, the requirement of the fast BOTDA system on the memory of the acquisition card is relieved, and the sampling capacity of the higher frequency dynamic signal is realized by breaking through the Nyquist sampling theorem. Compared with the prior art, the technical scheme of the present application can solve the technical problem that the prior art cannot meet the data compression requirement of the fast BOTDA system. BRIEF DESCRIPTION OF DRAWINGS

[0022] The accompanying drawings included to provide a further understanding of the embodiments of the present application, constitute a part of the specification and serve to explain the principles of the present application together with the text. Obviously, the accompanying drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0023] Figure 1 A structure schematic diagram of a compression sensing solution process schematic diagram provided by a specific embodiment of the present application is shown;

[0024] Figure 2 A Brillouin spectrum compression sampling schematic diagram provided by a specific embodiment of the present application is shown;

[0025] Figure 3A dynamic signal compression sampling schematic diagram provided according to one specific embodiment of the present application is shown;

[0026] Figure 4 A dynamic signal compression sampling schematic diagram provided according to another specific embodiment of the present application is shown;

[0027] Figure 5 A fast BOTDA system schematic diagram provided according to a specific embodiment of the present application is shown. DETAILED DESCRIPTION

[0028] It should be noted that the embodiments in the present application and the features in the embodiments can be combined with each other without conflict. The technical solutions in the embodiments of the present application will be described clearly and completely below in conjunction with the drawings of the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. The description of the at least one example embodiment is actually only illustrative, but not as any limitation on the present application and its application or use. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative labor fall within the scope of protection of the present application.

[0029] It should be noted that the terms used herein are only for describing specific embodiments, and are not intended to limit the example embodiments according to the present application. As used herein, the singular form is intended to include the plural form, unless the context clearly indicates otherwise, and it should also be understood that when the terms "comprise" and / or "include" are used in the specification, there is a presence of the features, steps, operations, devices, components and / or combinations thereof.

[0030] Unless specifically stated otherwise, the relative arrangement of the components and steps, numerical expressions, and values shown in these embodiments are not meant to limit the scope of the present application. At the same time, it should be understood that the sizes of the various parts shown in the drawings are not drawn in accordance with the actual proportion relationship. The technology, methods and devices known to those of ordinary skill in the relevant art can not be discussed in detail, but should be considered as part of the specification under appropriate circumstances. In all examples shown and discussed herein, any specific value should be interpreted as merely exemplary, and not as a limitation. Therefore, other examples of example embodiments can have different values. It should be noted that similar reference numbers and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further discussed in subsequent drawings.

[0031] According to a specific embodiment of the present application, a demodulation method of a fast BOTDA system based on spectrum and dynamic signal compression sensing is provided, which comprises:

[0032] 1) performing Brillouin spectrum compressed sampling and reconstruction: Brillouin spectrum compressed sampling is achieved by means of a Gaussian random scanning of the probe light frequency; Brillouin spectrum reconstruction is achieved based on a Brillouin spectrum compressed sampling transform vector according to an observation signal and a Brillouin spectrum transform domain dictionary;

[0033] 2) dynamic signal compressed sampling and reconstruction: dynamic signal compressed sampling is achieved by means of controlling a pulse sequence and a corresponding microwave scanning sequence; dynamic signal reconstruction is achieved based on a dynamic signal compressed sampling transform vector according to a dynamic signal transform domain dictionary;

[0034] 3) demodulation is performed according to the reconstructed Brillouin spectrum and the reconstructed dynamic signal.

[0035] By means of the configuration, a demodulation method of a fast BOTDA system based on spectrum and dynamic signal compressed sensing is provided, which performs compressed sampling and reconstruction on the Brillouin spectrum and the dynamic signal respectively, reduces the number of frequencies required for Brillouin spectrum measurement and the number of Brillouin spectra required for dynamic signal, and greatly reduces the data storage space. Compared with the existing compressed sensing BOTDA system, the data storage space is further reduced, the requirement of the memory of the acquisition card of the fast BOTDA system is alleviated, and the sampling capacity of the higher frequency dynamic signal is achieved by breaking through the Nyquist sampling theorem.

[0036] The compressed sensing theory shows that, under the prior condition that the sampled signal is sparse, the Nyquist sampling theorem can be broken through, the number of sampling points required for measuring the signal is reduced, and the original signal is accurately recovered by solving an optimization inverse problem. As shown in Figure 1 , since the observation signal, the measurement matrix and the transform domain dictionary are known, the reconstructed signal can be obtained by using the transform vector and the transform domain dictionary. It can be seen that the transform domain dictionary, the measurement matrix and the signal reconstruction algorithm are three important components for realizing compressed sampling of the Brillouin spectrum and the strain signal.

[0037] Further, in the present application, in the process of Brillouin spectrum compressed sampling, first, a Brillouin spectrum database with different frequency shifts is simulated and obtained according to the characteristics of the Brillouin spectrum, Brillouin spectrum sparsification is realized based on a Brillouin spectrum transform domain dictionary, and Brillouin spectrum compressed sampling is realized based on a Brillouin spectrum measurement matrix.

[0038] As a specific embodiment of the present application, a transform domain dictionary (Φ) can be obtained by a principal component analysis algorithm, which can adaptively construct a sparse transform dictionary according to data characteristics compared with other fixed transform domains such as a cosine domain, to realize the sparsification of Brillouin spectrum. Then, a Gaussian random matrix is used to construct a Brillouin spectrum measurement matrix (Ψ), and based on the Brillouin spectrum measurement matrix, Brillouin spectrum compressed sampling is realized, which meets the requirement of low correlation between the measurement matrix and the transform domain dictionary. As shown in FIG. 8, the randomly selected frequency of the Brillouin spectrum is represented by the circle in the figure. Figure 2

[0039] Further, in the present application, after the Brillouin spectrum compressed sampling is completed, the Brillouin spectrum is reconstructed based on the Brillouin spectrum compressed sampling transform vector according to the observation signal and the Brillouin spectrum transform domain dictionary.

[0040] Since the sensing matrix A is A = ΨΦ, and the dimension of the sensing matrix is much smaller than that of the transform vector X, the recovery of the Brillouin spectrum is a solution to a pathological equation. Generally, solving the transform vector is a process of finding the sparsest solution. As a specific embodiment of the present application, the main algorithms for solving the transform vector include convex optimization algorithm, combinatorial algorithm, statistical optimization algorithm, greedy algorithm and orthogonal matching pursuit (OMP) algorithm, etc. Among them, the core of the greedy algorithm is to reconstruct the transform vector by continuously iterating and comparing each time to select the local optimal solution, which has good convergence and fast reconstruction speed.

[0041] Taking the orthogonal matching pursuit (OMP) algorithm as an example, the core steps of the algorithm for realizing signal recovery are as follows:

[0042] Input: compressed sampling signal Y, sensing matrix A and sparsity K;

[0043] Output: estimated signal y and residual R;

[0044] Initialization: residual R0 = Y, support set F = [], transform vector X = [], and iteration number h = 1;

[0045] Loop steps 1-5:

[0046] Step 1: calculate the inner product of the residual R and the column of the sensing matrix A, and find the column j_h where the maximum value of the inner product is located;

[0047] Step 2: find the corresponding column of the sensing matrix A, update the support set: F = [F, A j_h ], and set the corresponding column of the sensing matrix to 0 after updating;

[0048] Step 3: solve the transform vector coefficient X h by the least square algorithm, X h = (F T F) -1 F T ​Y;

[0049] Step 4: update the residual R, R=Y-FX;

[0050] Step 5: judge whether the iteration termination condition h>K is met, if the condition is met, output X and R; otherwise, return to step 1.

[0051] Further, in the application, after the Brillouin spectrum compression sampling and reconstruction are completed, dynamic signal compression sampling is performed: dynamic signal compression sampling is realized by controlling the pulse sequence and the corresponding microwave scanning sequence. In the application, only the randomly sampled pulse sequence and the corresponding microwave sequence need to be output, and the microwave frequency in the microwave sequence is randomly sampled, so that dynamic signal compression sampling is realized.

[0052] In the compression sampling and reconstruction process of the dynamic signal, the dynamic strain generally has good sparsity in the frequency domain, and a dynamic signal transform domain dictionary is obtained by using discrete cosine transform. For BOTDA sensing, the strain is demodulated by the frequency shift of the Brillouin spectrum, and each Brillouin spectrum can be used as a sampling point of the dynamic signal. Similar to the compression sampling of the Brillouin gain spectrum, a Gaussian random matrix is selected as the measurement matrix, the correlation between the measurement matrix and the transform domain dictionary is low, and the compression sampling schematic diagram of different strain signals is shown in FIGS. Figure 3 and Figure 4 .

[0053] Further, in the application, after the dynamic signal compression sampling is completed, the dynamic signal is reconstructed based on the dynamic signal compression sampling transform vector according to the dynamic signal transform domain dictionary.

[0054] As a specific embodiment of the application, a convex optimization algorithm can be used to calculate the dynamic signal compression sampling transform vector.

[0055] By solving the convex optimization problem, the sparse coefficient x can be obtained from a small amount of observation results, and Y=A x. Here, the dynamic signal reconstruction is realized by solving the minimum L1 norm problem with linear equality constraints, and the mathematical expression of the problem is as follows:

[0056] min‖x‖1, s.t.(constraint condition): Ax=Y

[0057] The solution of the above formula is also called basis pursuit algorithm, that is, to find a vector with the minimum L1 norm:

[0058]

[0059] The principle of the algorithm is to constantly find the x with the minimum L1 norm to explain the sampled compressed signal Y, and if a group of sufficiently sparse signals (signals with a small enough L1 norm) is found, it is considered that the equation set has found the most suitable solution.

[0060] Further, in the present application, after the reconstruction of the dynamic signal is completed, demodulation is performed according to the reconstructed Brillouin spectrum and the reconstructed dynamic signal.

[0061] The present application firstly performs compressed sampling and reconstruction on the Brillouin spectrum, reduces the number of required frequency sweeps, improves the system sampling rate and reduces the data storage space, and then performs compressed sampling and reconstruction on the dynamic signal, further reduces the data storage space, and alleviates the requirement of the memory of the acquisition card of the fast BOTDA system, or effectively increases the recording time of the dynamic signal of the fast BOTDA system under the same hardware conditions.

[0062] As shown in Figure 5 According to another aspect of the present application, a fast BOTDA system based on spectrum and dynamic signal compressed sensing is provided, which realizes demodulation by using the above-mentioned demodulation method, and comprises a first laser, a coupler, a first electro-optical modulator, a second electro-optical modulator, an arbitrary waveform generator, an amplifier, a second laser, a fiber to be measured, a photodetector, a data acquisition card and a data processing module, the output signal of the first laser is divided into two signals after the coupler, and enters the first electro-optical modulator and the second electro-optical modulator respectively, the arbitrary waveform generator provides a loading electrical signal for the first electro-optical modulator and the second electro-optical modulator respectively, the first electro-optical modulator outputs a pump pulse light signal, and the second electro-optical modulator outputs an optical frequency shift signal, so as to realize compressed sampling of the Brillouin spectrum and compressed sampling of the dynamic signal; the pump pulse light signal enters the fiber to be measured after being amplified by the amplifier, and the optical frequency shift signal enters the fiber to be measured after being shaped by the second laser, the signal in the fiber to be measured is subjected to stimulated Brillouin scattering, carries Brillouin gain spectrum information and is output to the photodetector, the data acquisition card collects the data of the photodetector, the data processing module reconstructs the Brillouin spectrum and the dynamic signal according to the data collected by the data acquisition card, and performs demodulation according to the reconstructed Brillouin spectrum and the reconstructed dynamic signal.

[0063] In the fast BOTDA system of the present application, each pulse and its corresponding microwave signal can obtain the Brillouin gain signal at all positions, and the compressed sampling of the Brillouin spectrum is realized by the output of the frequency scanning signal of the arbitrary waveform generator. Each pulse sequence and its corresponding microwave scanning sequence can obtain the Brillouin spectrum at all positions at a certain time, which can be regarded as a sampling point of the dynamic signal, and the compressed sampling of the dynamic signal is realized by controlling the pulse sequence and its corresponding microwave scanning sequence.

[0064] Further, in the present application, in order to realize the detection and collection of the signal carrying the Brillouin gain spectrum information in the optical fiber to be measured, the configurable fast BOTDA system further comprises a first circulator, the amplified pump pulse light signal is input into the optical fiber to be measured from the second port of the first circulator through the first port of the first circulator, the signal in the optical fiber to be measured is subjected to stimulated Brillouin scattering, and the signal carrying the Brillouin gain spectrum information is output from the third port of the first circulator to the photodetector.

[0065] Further, in the present application, in order to realize the shaping of the optical heterodyne signal by the second laser, the configurable fast BOTDA system further comprises a second circulator, the output optical heterodyne signal after the double sideband modulation by the second electro-optical modulator is input into the second laser from the second port of the second circulator through the first port of the second circulator, the lower sideband light signal is injected into the locked output, and the detection light is filtered, amplified and spectrally shaped and then output from the third port of the second circulator.

[0066] Further, in the present application, in order to prevent the high-power pump pulse light amplified by the amplifier from entering the second laser and the second electro-optical modulator, the configurable fast BOTDA system further comprises an isolator, and the isolator is located between the second circulator and the optical fiber to be measured.

[0067] As a specific embodiment of the present application, the amplifier can be an erbium-doped fiber amplifier. The peak power of the pump pulse light after amplification by the erbium-doped fiber amplifier is hundreds of milliwatts.

[0068] The electro-optical modulator 1 and the electro-optical modulator 2 both work at the lowest output operating point, and the pulse width of the pump pulse light affects the spatial resolution of the system, for example, a 20 ns pulse width for a system spatial resolution of 2 m.

[0069] According to the preliminary experimental results, the conventional fast BOTDA measurement is scanned from 10.7 GHz to 11.2 GHz with a step of 4 MHz, a total of 126 frequencies, and the Brillouin spectrum compression sampling only needs 31.8% of the data amount of the conventional BOTDA system to realize the compression reconstruction of the Brillouin spectrum, the system sampling rate is increased by 3.3 times, the data amount is compressed by 68.2%, and further only 50% of the pulse sequence is needed to realize the compression sampling of the dynamic signal. Therefore, by using the proposed simultaneous compression sampling of the spectrum and the dynamic signal, the data amount of the fast BOTDA can be compressed by 84.1%, the dynamic signal sampling rate is increased by 3.3 times, and the system has the ability to break through the Nyquist sampling theorem to realize the sampling of a higher frequency dynamic signal.

[0070] The application provides a fast BOTDA system and a demodulation method based on spectrum and dynamic signal compressed sensing.

[0071] Compared with the prior art, the application has the following beneficial effects:

[0072] 1) The data storage space is greatly compressed, the Brillouin spectrum and the dynamic signal are compressed and reconstructed, the number of frequencies required for Brillouin spectrum measurement and the number of Brillouin spectra required for dynamic signal are reduced, and the data storage space is greatly reduced.

[0073] 2) The system sampling rate is improved, and the high-frequency vibration signal measurement capability is realized by breaking through the limitation of the Nyquist sampling theorem. Brillouin spectrum compressed sensing can effectively reduce the BOTDA system measurement time and improve the system sampling rate. Random compressed sensing of dynamic signal can break through the Nyquist sampling theorem and has high-frequency vibration signal measurement capability.

[0074] 3) Easy to apply and promote, the algorithm can be directly used in the existing BOTDA hardware system, and only the scanning frequency, pulse sequence and corresponding scanning frequency sequence output need to be changed, so that the Brillouin spectrum and dynamic signal compressed sensing can be realized.

[0075] In summary, the application provides a fast BOTDA system and a demodulation method based on spectrum and dynamic signal compressed sensing. The demodulation method compresses and reconstructs the Brillouin spectrum and the dynamic signal, reduces the number of frequencies required for Brillouin spectrum measurement and the number of Brillouin spectra required for dynamic signal, and greatly reduces the data storage space. Compared with the existing compressed sensing BOTDA system, the data storage space is further reduced, the requirement of the fast BOTDA system for the memory of the acquisition card is alleviated, and the higher frequency dynamic signal sampling capability is realized by breaking through the Nyquist sampling theorem. Compared with the prior art, the technical scheme of the application can solve the technical problem that the existing technology cannot meet the data compression requirement of the fast BOTDA system.

[0076] In addition, it should be noted that the use of "first", "second" and the like to define parts only facilitates the differentiation of the corresponding parts, and the above words have no special meaning unless otherwise stated, so they cannot be understood as limiting the scope of protection of the application.

[0077] The above description is only the preferred embodiment of the present application, and is not intended to limit the present application. The present application can have various changes and modifications for those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A demodulation method for a fast BOTDA system based on spectral and dynamic signal compressed sensing, characterized in that: The demodulation method comprises: 1) Perform Brillouin spectrum compression sampling and reconstruction: Brillouin spectrum compression sampling is achieved by Gaussian random scanning of the detection light frequency; Brillouin spectrum reconstruction is achieved based on the Brillouin spectrum compression sampling transformation vector according to the observed signal and the Brillouin spectrum transform domain dictionary; 2) Dynamic signal compression sampling and reconstruction: Dynamic signal compression sampling is achieved by controlling the pulse sequence and its corresponding microwave scanning sequence. Dynamic signal reconstruction is achieved based on the dynamic signal compression sampling transformation vector according to the dynamic signal transform domain dictionary. 3) Demodulation is performed based on the reconstructed Brillouin spectrum and the reconstructed dynamic signal.

2. The demodulation method of a fast BOTDA system based on spectrum and dynamic signal compressed sensing according to claim 1, characterized in that: In step 1), according to the Brillouin spectrum characteristics, a Brillouin spectrum database with different frequency shifts is obtained by simulation, Brillouin spectrum sparsification is achieved based on the Brillouin spectrum transform domain dictionary, and Brillouin spectrum compressed sampling is achieved based on the Brillouin spectrum measurement matrix.

3. The demodulation method of a fast BOTDA system based on spectrum and dynamic signal compressed sensing according to claim 2, characterized in that: The Brillouin spectrum transform domain dictionary is obtained through the principal component analysis algorithm.

4. The demodulation method of a fast BOTDA system based on spectrum and dynamic signal compressed sensing according to claim 2, characterized in that: The Brillouin spectroscopy measurement matrix is ​​constructed using Gaussian random matrix.

5. The demodulation method of a fast BOTDA system based on spectrum and dynamic signal compressed sensing according to claim 4, characterized in that: The Brillouin spectrum compressed sampling transformation vector and the dynamic signal compressed sampling transformation vector are solved by using a convex optimization algorithm, a combinatorial algorithm, a statistical optimization algorithm, a greedy algorithm or an intersection matching pursuit algorithm.

6. A fast BOTDA system based on spectral and dynamic signal compressed sensing, characterized in that: The fast BOTDA system uses the demodulation method according to any one of claims 1 to 5 to achieve demodulation. The fast BOTDA system includes: a first laser, a coupler, a first electro-optical modulator, a second electro-optical modulator, an arbitrary waveform generator, an amplifier, a second laser, an optical fiber to be tested, a photodetector, a data acquisition card, and a data processing module. The output signal of the first laser is divided into two signals after passing through the coupler, and enters the first electro-optical modulator and the second electro-optical modulator respectively. The arbitrary waveform generator provides loading electrical signals for the first electro-optical modulator and the second electro-optical modulator respectively. The first electro-optical modulator outputs a pump The pulse light signal is output by the second electro-optical modulator, and the optical frequency-agile signal is output to realize Brillouin spectrum compression sampling and dynamic signal compression sampling. The pump pulse light signal is amplified by the amplifier and enters the optical fiber to be tested. The optical frequency-agile signal is shaped by the second laser and enters the optical fiber to be tested. The signal in the optical fiber to be tested undergoes stimulated Brillouin scattering and is output to the photodetector carrying Brillouin gain spectrum information. The data acquisition card collects data from the photodetector. The data processing module reconstructs the Brillouin spectrum and dynamic signal according to the data collected by the data acquisition card, and demodulates according to the reconstructed Brillouin spectrum and the reconstructed dynamic signal.

7. The fast BOTDA system based on spectrum and dynamic signal compressed sensing according to claim 6, characterized in that: The fast BOTDA system also includes a first circulator. The pump pulse light signal amplified by the amplifier passes through the first port of the first circulator and then enters the optical fiber to be tested through the second port. The signal in the optical fiber to be tested undergoes stimulated Brillouin scattering and is output from the third port of the first circulator to the photodetector carrying Brillouin gain spectrum information.

8. The fast BOTDA system based on spectral and dynamic signal compressed sensing according to claim 6 or 7, characterized in that: The fast BOTDA system also includes a second circulator. The optical frequency-agile signal output after double-sideband modulation by the second electro-optical modulator passes through the first port of the second circulator and then enters the second laser through the second port. The lower sideband optical signal is injection-locked and output, and the detection light is filtered, amplified and spectrum-shaped before being output from the third port of the second circulator.

9. The fast BOTDA system based on spectrum and dynamic signal compressed sensing according to claim 8, characterized in that: The fast BOTDA system further includes an isolator, which is located between the second circulator and the optical fiber to be tested.

10. The fast BOTDA system based on spectral and dynamic signal compressed sensing according to any one of claims 6 to 9, characterized in that: The amplifier is an erbium-doped fiber amplifier.

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