A method for improving the spatial resolution of a Brillouin optical time domain reflectometer

Abstract

The present invention discloses a method for improving the spatial resolution of a Brillouin optical time domain reflectometer, belonging to the field of distributed optical fiber sensing. The method for improving the spatial resolution of a Brillouin optical time domain reflectometer includes: S1, recording the Brillouin scattering signal collected by the data acquisition module of the BOTDR system; S2, performing short-time Fourier transform on the Brillouin scattering signal to construct a three-dimensional spectrum; S3, constructing a Brillouin frequency shift map through a maximum search algorithm and combining a peak search factor to determine the Brillouin frequency shift; S4, correcting the temperature or stress segment information in the Brillouin frequency shift curve; S5, calculating the uncertainty of the Brillouin frequency shift value in the temperature segment to obtain the frequency resolution. In the field of engineering applications, it can not only save costs, but also greatly improve the monitoring accuracy and the spatial resolution of the system.

Description

Technical Field

[0001] The present invention belongs to the field of distributed optical fiber sensing, and particularly relates to a method for improving the spatial resolution of a Brillouin optical time domain reflectometer. Background Art

[0002] A Brillouin optical time domain reflectometer (BOTDR) is a distributed optical fiber sensing technology based on self-published Brillouin scattering. Compared with traditional point-type sensing technologies, distributed optical fiber sensing can not only achieve accurate measurement of strain and temperature values at each position along the fiber length, but also has the advantages of high temperature resistance, small floor area, good electromagnetic resistance, and long laying distance, which has attracted wide attention from researchers and is widely used in the civil engineering field for structural health monitoring. Currently, there are two types of time-frequency analysis for Brillouin optical time domain reflectometers, namely the swept-frequency method and the short-time Fourier transform method; because the short-time Fourier transform performs signal processing on the entire broadband signal, the system operation time is short, the response is fast, and it is more suitable for engineering applications.

[0003] Spatial resolution is an important performance parameter of a Brillouin optical time domain reflectometer, usually proportional to the pulse width. For incident light with a pulse time width of t and a transmission speed of v, its spatial resolution z is:

[0004]

[0005] The resolution of the short-time Fourier transform is related to both the window length and the sliding window spacing. Selecting a short window function will improve the time resolution, but fewer signals in the window will result in poor frequency resolution; selecting a long window function will improve the frequency resolution, but a long signal in the window will result in poor time resolution; according to the uncertainty principle, the time resolution and the frequency resolution cannot be arbitrarily small at the same time, and their product is limited by a certain value. To improve the time resolution, the frequency resolution needs to be reduced, and vice versa. Therefore, when the information of a small segment length within the spatial resolution changes, the traditional system cannot recognize it.

[0006] Without any system modification, post-processing techniques can achieve higher spatial resolution of the sensing system. Currently, researchers have proposed various methods. One is the pulse segmentation technique, which requires a reference fiber with a stable frequency shift before the temperature change region; the second is to use a quadratic time-frequency transform instead of the commonly used short-time Fourier transform; the third is to use a filtering function of equivalent spatial resolution to deconvolve the Brillouin signal. However, these post-processing methods are equivalent processing of the original Brillouin gain spectrum, which requires the original Brillouin gain spectrum to have good linearity, that is, the system needs to have a sufficiently large signal-to-noise ratio and a standard pulse shape, which will increase the cost of the system and reduce the application scenarios of these methods.

[0007] Currently, the price of commercially available BOTDR finished instruments is generally relatively expensive. For some civil engineering projects with a low budget for structural health monitoring, purchasing a BOTDR instrument will cost most of the budget. Therefore, many construction sites use the same instrument through scheduling to achieve monitoring, but this cannot achieve continuous and real-time measurement of the structure, cannot timely detect health problems in the structure, and is prone to damage the instrument during the scheduling process. Currently, most of the low-cost BOTDR systems selected in engineering will choose to reduce the budget of the pulse modulator, such as replacing the electro-optic modulator (EOM) with a semiconductor optical amplifier (SOA) whose price is 10 times that of the SOA, which will reduce the pulse quality and deteriorate the spatial resolution. Against this background, improving the spatial resolution of the system while maintaining low cost has become an urgent problem to be solved currently. Summary of the Invention

[0008] Aiming at the deficiencies of the prior art, the purpose of the present invention is to provide a method for improving the spatial resolution of a Brillouin optical time domain reflectometer, which improves the spatial resolution of the system while maintaining low cost.

[0009] The purpose of the present invention can be achieved through the following technical solutions:

[0010] A method for improving the spatial resolution of a Brillouin optical time domain reflectometer includes the following steps:

[0011] S1, record the Brillouin scattering signal collected by the data acquisition module of the BOTDR system;

[0012] S2, perform short-time Fourier transform on the Brillouin scattering signal to construct a three-dimensional spectrum;

[0013] S3, construct a Brillouin frequency shift map through a maximum search algorithm, and combine a peak search factor to judge the Brillouin frequency shift;

[0014] S4, correct the temperature or stress segment information in the Brillouin frequency shift curve;

[0015] S5, calculate the uncertainty of the Brillouin frequency shift value in the temperature segment to obtain the frequency resolution.

[0016] Further, in the step S2, the steps of constructing a three-dimensional spectrum are as follows:

[0017] S21, perform Fourier transform on the signal along the optical fiber with a certain window length h and a certain sliding window spacing Δt. The discrete short-time Fourier transform can be written as:

[0018]

[0019] h = iΔt - t

[0020] Among them, K(v,t) is the three-dimensional spectrum constructed by Fourier transform, s(i) is the original Brillouin scattering signal, and w(iΔt - t) is the window function;

[0021] S22. If the window length is divided into m parts, the Brillouin gain spectrum at time t0 is:

[0022]

[0023] Among them, K i (v,t) is the Brillouin gain spectrum generated by each sub-window length; a i represents the weight coefficient;

[0024] S23. When there is both room temperature information and temperature or strain information within one window length, the Brillouin gain spectrum at time t0 is:

[0025]

[0026] Among them, v1 is the Brillouin frequency shift of the optical fiber in the room temperature section, and v2 is the Brillouin frequency shift of the optical fiber in the section affected by temperature or strain.

[0027] Furthermore, in S3, the maximum value search algorithm is to judge the maximum value of each point of the spectrogram constructed by the short-time Fourier transform on the MATLAB system.

[0028] Furthermore, the maximum value judgment condition is:

[0029] v(x) - v(x - Δv)>0 && v(x + Δv) - v(x)<0

[0030] Among them, v(x) is the function of the light intensity corresponding to each frequency in the Brillouin gain spectrum of a single position of the optical fiber, Δv is the frequency step, and && represents the coexistence of two conditions.

[0031] Furthermore, in S3, the peak search factor σ is calculated by the following formula:

[0032]

[0033] Among them, SNR is the signal-to-noise ratio of the system, E is the magnitude of the system noise intensity, β is the frequency step of the algorithm, and FWHM is the full width at half maximum of the Brillouin gain spectrum;

[0034] Then judge the number of maximum values greater than the peak search factor σ. If there is only one, it is the magnitude of the Brillouin frequency shift. If there are multiple, the second maximum value is the magnitude of the Brillouin frequency shift. These data together construct the Brillouin frequency shift curve.

[0035] Further, in the step S4, the curve length of the temperature or stress information is longer than the length of the true temperature or stress segment by a window function length h. The temperature or stress information in the Brillouin frequency shift curve is corrected, and both the start and end positions of the Brillouin frequency shift curve of the temperature segment are offset inward by a length of h / 2.

[0036] Further, when the length of the temperature or stress information is less than half of the window function length, the curve length including the temperature or stress information is longer than the length of the true temperature or stress segment by λl, where λ is a correction coefficient, which is obtained from the following formula:

[0037]

[0038] where l is the length of the true temperature or stress segment, h is the window function length, and t is the sub-pulse length into which the window function length is subdivided.

[0039] Further, the formula for calculating the uncertainty δT in the step S5 is:

[0040]

[0041] where N1 is the number of data points at the start position of the temperature or stress segment on the Brillouin frequency shift curve, N2 is the number of data points at the end position, V n is the magnitude of the Brillouin frequency shift at each position of the temperature or stress segment, is the average value of the magnitudes of the Brillouin frequency shifts at each position of the temperature or stress segment.

[0042] Advantages of the present invention: This patent uses a Brillouin optical time domain reflectometer device based on short-time Fourier transform (STFT) to collect and construct a Brillouin gain spectrum, and uses a maximum search algorithm to improve the spatial resolution in Brillouin frequency shift detection; in the field of engineering applications, it can not only save costs, but also greatly improve the monitoring accuracy and the spatial resolution of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, for those of ordinary skill in the art, other drawings can also be obtained based on these drawings without creative efforts.

[0044] Figure 1 It is a schematic diagram of a Brillouin splicing spectrum constructed from the Brillouin gain spectra of the temperature segment and the normal temperature segment within one window length;

[0045] Figure 2 It is a schematic diagram of the novel low-cost Brillouin optical time domain reflectometer device in the embodiment of the present invention;

[0046] Figure 3Schematic diagram of the optical fiber to be measured in the embodiment of the present invention;

[0047] Figure 4 Brillouin frequency shift curve constructed by the traditional peak-seeking algorithm in the embodiment of the present invention;

[0048] Figure 5 Brillouin frequency shift curve constructed by the maximum-seeking algorithm in the embodiment of the present invention. Specific implementation manner

[0049] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0050] A method for improving the spatial resolution of a Brillouin optical time domain reflectometer includes the following steps:

[0051] S1. Record the Brillouin scattering signal s(t) collected by the data acquisition module of the BOTDR system;

[0052] S2. Perform a short-time Fourier transform on the original signal to construct a three-dimensional spectrum;

[0053] The short-time Fourier transform process performs a Fourier transform on the signals along the optical fiber with a certain window length h and a certain sliding window spacing Δt. The discrete short-time Fourier transform can be written as:

[0054]

[0055] h = iΔt - t

[0056] where K(v,t) is the three-dimensional spectrum constructed by the Fourier transform, s(i) is the original Brillouin scattering signal, and w(iΔt - t) is the window function;

[0057] The Brillouin gain spectrum obtained within one window length can be equivalently regarded as a set of signals at different positions within this window length. If the window length is divided into m parts, the Brillouin gain spectrum at time t0 is:

[0058]

[0059] where K i (v,t) is the Brillouin gain spectrum generated by each sub-window length; a i represents the weight coefficient;

[0060] When there is both normal temperature information and temperature or strain information within a window length, the constructed Brillouin gain spectrum is a combination of the two. The Brillouin gain spectrum at time point t0 is as follows:

[0061]

[0062] Among them, v1 is the Brillouin frequency shift of the optical fiber in the normal temperature section, and v2 is the Brillouin frequency shift of the optical fiber in the section affected by temperature or strain; the Brillouin gain spectra with two different central frequencies v1 and v2 are superimposed on the frequency spectrum diagram, and two peaks will appear on the spliced spectrum, as Figure 1 shown;

[0063] In the Brillouin optical reflectometer system based on the short-time Fourier algorithm, if the peak value of the Brillouin gain spectrum generated by the temperature or strain information on the frequency spectrum diagram within a window length is not larger than that of the normal temperature section, the peak-seeking algorithm cannot identify the temperature or strain information at the corresponding position; therefore, the minimum spatial resolution exists when the peak value in the temperature section within a window length is just larger than that of the normal temperature section. Its size is not only related to the length corresponding to the temperature section but also related to the weighting coefficient; the weighting coefficient of each sub-pulse within the pulse is affected by the short-time Fourier window function and the pulse shape, so the coefficient values are different but centrosymmetric. Therefore, the spatial resolution of the Brillouin optical reflectometer system based on the short-time Fourier algorithm is half of the window function.

[0064] S3. Construct a Brillouin frequency shift diagram through the maximum-seeking algorithm;

[0065] When the Brillouin gain spectrum of the temperature or strain within a window length is lower in intensity than the Brillouin gain spectrum of the normal temperature, the information corresponding to its length cannot be identified, resulting in a decrease in spatial resolution; we can directly find the Brillouin gain spectrum generated by the temperature or strain section through the maximum-seeking algorithm to improve the spatial resolution;

[0066] On the MATLAB system, perform a maximum value judgment on each point of the frequency spectrum diagram constructed by the short-time Fourier transform, and record the maximum value and the corresponding frequency when the following conditions are met.

[0067] v(x) - v(x - Δv) > 0 && v(x + Δv) - v(x) < 0

[0068] Among them, v(x) is the function of the optical intensity corresponding to each frequency in the Brillouin gain spectrum at a single position of the optical fiber, Δv is the frequency step, and && represents the conjunction of the two conditions.

[0069] The maximum-seeking algorithm will not only find the normal temperature peak and the temperature frequency shift peak but also find the noise peak caused by signal fluctuations in the system itself. Therefore, a peak-seeking factor σ needs to be introduced for judgment to find the peak value of the Brillouin gain spectrum caused by small changes within the spatial resolution; the peak-seeking factor σ is calculated by the following formula:

[0070]

[0071] Where SNR is the signal-to-noise ratio of the system, E is the noise intensity of the system, β is the frequency step of the algorithm, and FWHM is the full width at half maximum of the Brillouin gain spectrum;

[0072] Judge the number of maxima greater than the peak search factor σ. If there is only one, it is the Brillouin frequency shift value. If there are multiple, the second maximum is the Brillouin frequency shift value. These data together construct the Brillouin frequency shift curve.

[0073] S4, length correction;

[0074] For the Brillouin frequency shift curve constructed by the maximum search algorithm, since the window function itself has a certain length, when it moves, the length of the curve containing temperature or stress information will be longer than the length of the real temperature or stress section by a window function length h. Therefore, it is necessary to correct the temperature or stress information in the Brillouin frequency shift curve, and offset the positions at the beginning and end of the temperature section Brillouin frequency shift curve inward by a length of h / 2.

[0075] However, for the case where the length of the temperature or stress information is less than half of the window function length, since the weight coefficients of each sub-pulse within the pulse are different, if the weight coefficient of the temperature section information is low, no temperature or strain Brillouin gain spectrum will be generated. Therefore, the length of the curve containing temperature or stress information will be longer than the length of the real temperature or stress section by λl, where λ is the correction coefficient, which is obtained from the following formula:

[0076]

[0077] Where l is the length of the real temperature or stress section, h is the window function length, and t is the length of the sub-pulse into which the window function length is subdivided.

[0078] S5, calculation of system accuracy

[0079] Calculate the uncertainty of the Brillouin frequency shift value in the temperature section to obtain the frequency resolution. The formula for the uncertainty δT is:

[0080]

[0081] Where N1 is the number of data points at the start position of the temperature or stress section on the Brillouin frequency shift curve, N2 is the number of data points at the end position, and V n is the magnitude of the Brillouin frequency shift at each position of the temperature or stress section, is the average value of the magnitudes of the Brillouin frequency shifts at each position of the temperature or stress section.

[0082] Example:

[0083] Step 1, build the system

[0084] Build a system as Figure 2 shown, turn on all devices, set the pulse length to 100 ns, and the frequency to 50 kHz to ensure the normal operation of the device;

[0085] The laser with a linewidth of 3 kHz is split into two paths by a 9:1 coupler. 90% of the probe light is modulated by an SOA (semiconductor optical amplifier) into a pulse with a pulse width of 100 ns and an extinction ratio of about 30 dB, and enters the fiber under test through a circulator. The Brillouin scattered light generated by the fiber under test is amplified by an EDFA and the ASE noise is filtered by an FBG; 10% of the reference light passes through a polarization scrambler (PS) to disrupt the polarization state of the reference path to make it easier to beat with the probe path. The two paths of light are detected by a PD, and then the high-frequency signal is down-converted to an intermediate-frequency signal of 400 MHz by a signal down-conversion processing module, and finally enters a data acquisition card for acquisition and further processing.

[0086] Step 2, Brillouin signal acquisition and spectrum construction

[0087] Design the fiber under test as Figure 3 shown, wind four segments of optical fibers with lengths of 16 m, 5 m, 2 m, and 1 m every 15 m; put these four segments of optical fibers into a water bath and heat them to 40 °C, and use a data acquisition card to collect the reflected Brillouin signals; perform a short-time Fourier transform on the original time-domain signal on the MATLAB platform to construct a three-dimensional Brillouin gain spectrum.

[0088] Step 3, construct a Brillouin frequency shift curve using the maximum search algorithm

[0089] Perform a maximum search algorithm on the three-dimensional Brillouin gain spectrum to obtain a Brillouin frequency shift curve; and correct the curve; there is a relationship of the following formula between the measured temperature section length H and the true temperature section length l:

[0090]

[0091] Given the measured temperature section length H, we can calculate the true temperature section length l, and correct it on the Brillouin frequency shift curve to obtain the true Brillouin frequency shift curve as Figure 5 shown; use the traditional peak search algorithm to obtain a Brillouin frequency shift curve as Figure 4 shown by the curve; by comparing the two, it can be seen that in the case of a 100-ns pulse, the traditional peak search algorithm can only identify the temperature change of a 5-m length at minimum and cannot detect the temperature change of the 1-m and 2-m length sections, while the maximum search algorithm can clearly identify the temperature change of the 1-m and 2-m length sections.

[0092] Step 4, calculation of system accuracy

[0093] Calculate the uncertainty of the Brillouin frequency shift value in the temperature range to obtain the frequency resolution. For the traditional peak-seeking algorithm, the frequency resolution of the 10m segment is 1.5692 MHz, and that of the 5m segment is 1.4153 MHz. For the peak-seeking maximum value algorithm, the frequency resolution of the 10m segment is 1.6238 MHz, that of the 5m segment is 1.8803 MHz, that of the 2m segment is 1.9248 MHz, and that of the 1m segment is 2.0040 MHz. It can be seen that the peak-seeking maximum value algorithm can achieve an improvement in the spatial resolution from 10m to 1m under the condition of 100 ns pulses, while the change in the frequency resolution deteriorates very little.

[0094] In the description of this specification, the descriptions referring to terms such as "one embodiment", "example", "specific example", etc. mean that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0095] The above shows and describes the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments. The above embodiments and the descriptions in the specification only illustrate the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention will have various changes and improvements, and all these changes and improvements fall within the scope of the present invention claimed.

Claims

1. A method for improving the spatial resolution of a Brillouin optical time domain reflectometer, characterized in that, It includes the following steps: S1. Record the Brillouin scattering signals collected by the data acquisition module of the BOTDR system; S2. Perform short-time Fourier transform on the Brillouin scattering signals to construct a three-dimensional spectrum; S3. Construct a Brillouin frequency shift map through a maximum search algorithm, and combine the peak search factor to judge the Brillouin frequency shift; S4. Correct the temperature or stress segment information in the Brillouin frequency shift curve; S5. Calculate the uncertainty of the Brillouin frequency shift value in the temperature segment to obtain the frequency resolution; In the said S2, the steps for constructing the three-dimensional spectrum are as follows: S21. Perform Fourier transform on the signals along the optical fiber with a certain window length h and a certain sliding window spacing Δt. The discrete short-time Fourier transform can be written as: h = iΔt - t where K(v, t) is the three-dimensional spectrum constructed through Fourier transform, s(i) is the original Brillouin scattering signal, and w(iΔt - t) is the window function; S22. Divide the window length into m parts, then the Brillouin gain spectrum at time t0 is: Among them, K i (v, t) is the Brillouin gain spectrum generated by each molecular window length; a i represents the weight coefficient; S23. When there is both normal temperature information and temperature or strain information within one window length, the Brillouin gain spectrum at time t0 is: where v1 is the Brillouin frequency shift of the optical fiber in the normal temperature segment, and v2 is the Brillouin frequency shift of the optical fiber in the temperature or strain segment; In the said S4, the curve length of the temperature or stress information is longer than the true temperature or stress segment length by one window function length h. Correct the temperature or stress information in the Brillouin frequency shift curve, and offset the start and end positions of the temperature segment Brillouin frequency shift curve inward by a length of h / 2; The calculation formula for the uncertainty δT in the said S5 is: Where N1 is the number of data points at the starting position of the temperature or stress segment on the Brillouin frequency shift curve, N2 is the number of data points at the ending position, and V n is the magnitude of the Brillouin frequency shift at each position of the temperature or stress segment, is the average value of the magnitudes of the Brillouin frequency shift at each position of the temperature or stress segment.

2. A method for improving the spatial resolution of a Brillouin optical time domain reflectometer according to claim 1, characterized in that, In the said S3, the maximum search algorithm is to judge the maximum value of each point in the spectrum diagram constructed by short-time Fourier transform on the MATLAB system.

3. A method for improving the spatial resolution of a Brillouin optical time domain reflectometer according to claim 2, characterized in that, The conditions for judging the maximum value are: v(x) - v(x - Δv) > 0 && v(x + Δv) - v(x) < 0 where v(x) is a function of the optical intensity corresponding to each frequency in the Brillouin gain spectrum at a single position of the optical fiber, Δv is the frequency step, and && represents the coexistence of two conditions.

4. A method for improving the spatial resolution of a Brillouin optical time domain reflectometer according to claim 3, characterized in that In the said S3, the peak search factor σ is calculated by the following formula: where SNR is the signal-to-noise ratio of the system, E is the magnitude of the system noise intensity, β is the frequency step of the algorithm, and FWHM is the full width at half maximum of the Brillouin gain spectrum; Then judge the number of maximum values greater than the peak search factor σ. If there is only one, it is the magnitude of the Brillouin frequency shift. If there are multiple, the second maximum value is the magnitude of the Brillouin frequency shift. These data together construct the Brillouin frequency shift curve.

5. A method for improving the spatial resolution of a Brillouin optical time domain reflectometer according to claim 1, characterized in that, If the length of the temperature or stress information is less than half of the window function length, the curve length containing the temperature or stress information is longer than the true temperature or stress segment length by λl, where λ is the correction coefficient, and is obtained by the following formula: where l is the length of the true temperature or stress segment, h is the window function length, and t is the sub-pulse length into which the window function length is subdivided.

Images