CN113155267A - OFDR system vibration detection method and system based on secondary correlation, storage medium and terminal - Google Patents
OFDR system vibration detection method and system based on secondary correlation, storage medium and terminal Download PDFInfo
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Abstract
The invention discloses a method, a system, a storage medium and a terminal for detecting OFDR system vibration based on secondary correlation, wherein the method comprises the following steps: acquiring a reference signal and a test signal of an OFDR system; preprocessing the reference signal and the test signal to obtain respective segmented wavelength domain signals of the reference signal and the test signal; processing the wavelength domain signals of all the corresponding segmented reference signals and the wavelength domain signals of the test signals to obtain vibration information, wherein the processing comprises the following steps: performing autocorrelation operation on the wavelength domain data of the reference signal to obtain autocorrelation operation data; performing cross-correlation operation on the wavelength domain data of the reference signal and the wavelength domain data of the test signal to obtain first cross-correlation operation data; and performing cross-correlation operation on the auto-correlation operation data and the first cross-correlation operation data. In the quadratic correlation calculation process, the influence of noise on signals is reduced, and compared with a basic cross-correlation algorithm, the method can realize vibration detection in a lower signal-to-noise ratio environment.
Description
Technical Field
The invention relates to a method, a system, a storage medium and a terminal for detecting OFDR system vibration based on secondary correlation.
Background
In recent years, distributed optical fiber sensing systems using optical fibers as sensing elements and signal transmission media have attracted more and more attention in the aspects of national defense, military, civil facilities, and the like, because optical fibers have strong electromagnetic interference resistance, good electrical insulation and light transmission characteristics. Distributed fiber optic sensing technology measures characteristic information along an optical fiber by detecting and analyzing optical effects within the fiber. The distributed optical fiber measurement and sensing technology has the irreplaceable advantages of multi-parameter, intellectualization, large capacity, multiple channels, high sensitivity and the like. As a representative example of a distributed optical fiber sensing system, the Optical Frequency Domain Reflectometry (OFDR) has the advantages of light weight, small volume, high sensitivity, strong electromagnetic interference resistance, and the like, and can continuously detect time variation and spatial distribution information of external interference such as vibration, strain, temperature, and the like in a transmission process.
The OFDR principle is: light emitted by the tunable laser source is divided into two beams by the coupler, one beam enters the optical fiber to be measured, and the other beam enters the reference optical fiber. Interference signals respectively generated by backward Rayleigh scattering signals of the optical fiber to be detected and the reference optical fiber are used as frequency functions, and the interference signals are collected and subjected to fast Fourier transform processing, so that distance domain mapping of reflection constructed along the sensing optical fiber can be obtained.
In the prior art as shown in fig. 1, the reference signal and the measurement signal are processed in the same manner and then directly subjected to cross-correlation operation, thereby obtaining vibration detection data. However, in long-distance measurement, due to the influence of noise, the signal-to-noise ratio is reduced by taking a sliding window with a small size, and further, measurement of external disturbance cannot be realized.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provides a method, a system, a storage medium and a terminal for detecting the vibration of an OFDR system based on secondary correlation.
The purpose of the invention is realized by the following technical scheme:
the invention provides a vibration detection method of an OFDR system based on secondary correlation, which comprises the following steps:
acquiring a reference signal and a test signal of an OFDR system;
preprocessing the reference signal and the test signal to obtain respective segmented wavelength domain signals of the reference signal and the test signal;
processing the wavelength domain signals of all the corresponding segmented reference signals and the wavelength domain signals of the test signals to obtain vibration information, wherein the processing comprises the following steps:
performing autocorrelation operation on the wavelength domain data of the reference signal to obtain autocorrelation operation data;
performing cross-correlation operation on the wavelength domain data of the reference signal and the wavelength domain data of the test signal to obtain first cross-correlation operation data;
and performing cross-correlation operation on the auto-correlation operation data and the first cross-correlation operation data.
Further, the preprocessing the reference signal and the test signal to obtain respective segmented wavelength domain signals of the reference signal and the test signal includes:
respectively carrying out fast Fourier transform on the reference signal and the measurement signal, namely converting optical frequency domain information into distance domain information corresponding to each position in the sensing optical fiber;
the obtained two groups of distance domain information are divided into N equal parts on a distance domain by sliding with a window with a certain size, wherein each part is a segmented signal;
and performing inverse Fourier transform on the segmented signals to obtain respective local Rayleigh scattering spectra of the reference signal and the test signal, namely respective segmented wavelength domain signals of the reference signal and the test signal.
Further, the autocorrelation operation is performed on the wavelength domain data of the reference signal to obtain autocorrelation operation data, and the autocorrelation operation data is specifically calculated as follows:
R11(τ)＝E[x1(t)x1(t+τ)]
in the formula, x1(t) and x1(t + τ) represents wavelength region data of the reference signal at time t and time t + τ, respectively, E [ [ deg. ] ]]To represent
Wherein M is the total number of sampling points;
performing cross-correlation operation on the wavelength domain data of the reference signal and the wavelength domain data of the test signal to obtain first cross-correlation operation data, specifically calculating as follows:
R12(τ)＝E[x1(t)x2(t+τ)]
in the formula, x2(t + τ) represents wavelength domain data of the test signal at time t + τ;
the cross-correlation operation is performed on the autocorrelation operation data and the first cross-correlation operation data, and the specific calculation is as follows:
RRR(τ)＝E[R11(τ)R12(τ)]
further, the system vibration detection method is replaced by a system strain detection method, and the vibration information is replaced by strain information; or:
the system vibration detection method is replaced by a system temperature detection method, and the vibration information is replaced by temperature information.
In a second aspect of the present invention, there is provided a vibration detection system for OFDR system based on secondary correlation, comprising:
the signal acquisition module is used for acquiring a reference signal and a test signal of the OFDR system;
the preprocessing module is used for preprocessing the reference signal and the test signal to obtain respective segmented wavelength domain signals of the reference signal and the test signal;
the vibration information calculation module is used for processing the wavelength domain signals of all the corresponding segmented reference signals and the wavelength domain signals of the test signals to obtain vibration information, and comprises the following steps:
the autocorrelation operation sub-module is used for carrying out autocorrelation operation on the wavelength domain data of the reference signal to obtain autocorrelation operation data;
the first cross-correlation operation sub-module is used for carrying out cross-correlation operation on the wavelength domain data of the reference signal and the wavelength domain data of the test signal to obtain first cross-correlation operation data;
and the second cross-correlation operation sub-module is used for performing cross-correlation operation on the auto-correlation operation data and the first cross-correlation operation data.
Further, the preprocessing module comprises:
the fast Fourier transform submodule is used for respectively carrying out fast Fourier transform on the reference signal and the measurement signal, namely converting the optical frequency domain information into distance domain information corresponding to each position in the sensing optical fiber;
the segmentation submodule is used for dividing the obtained two groups of distance domain information into N equal parts by using a window with a certain size to slide on a distance domain, wherein each part is a segmentation signal;
and the inverse Fourier transform submodule is used for performing inverse Fourier transform on the segmented signals to obtain respective local Rayleigh scattering spectra of the reference signal and the test signal, namely respective segmented wavelength domain signals of the reference signal and the test signal.
Further, the autocorrelation operation submodule specifically calculates as follows:
R11(τ)＝E[x1(t)x1(t+τ)]
in the formula, x1(t) and x1(t + τ) represents wavelength region data of the reference signal at time t and time t + τ, respectively, E [ [ deg. ] ]]To represent
Wherein M is the total number of sampling points;
the specific calculation of the first cross-correlation operation submodule is as follows:
R12(τ)＝E[x1(t)x2(t+τ)]
in the formula, x2(t + τ) represents wavelength domain data of the test signal at time t + τ;
the specific calculation of the second cross-correlation operation sub-module is as follows:
RRR(τ)＝E[R11(τ)R12(τ)]。
further, the system vibration detection system is replaced by a system strain detection system, the vibration information calculation module is replaced by a strain information calculation module, and the vibration information is replaced by strain information; or:
the system vibration detection system is replaced by a system temperature detection system, the vibration information calculation module is replaced by a temperature information calculation module, and the vibration information is replaced by temperature information.
In a third aspect of the present invention, a storage medium is provided, on which computer instructions are stored, which when executed perform the steps of the method for detecting OFDR system vibration based on quadratic correlation.
In a fourth aspect of the present invention, there is provided a terminal, comprising a memory and a processor, wherein the memory stores computer instructions executable on the processor, and the processor executes the steps of the method for detecting OFDR system vibration based on second order correlation when executing the computer instructions.
The invention has the beneficial effects that:
in an exemplary embodiment of the invention, in the process of the second correlation calculation, the influence of noise on signals is reduced by the autocorrelation calculation and the first cross correlation calculation, the amount of the cross correlation peak shift at each position can be obtained by the cross correlation calculation, the shift of the cross correlation peak exists at the data where the disturbance information exists, and the deviation value corresponds to the sensing quantity. Therefore, compared with the basic cross-correlation algorithm shown in fig. 1, the vibration detection can be realized in a lower signal-to-noise ratio environment, more accurate vibration detection is realized, and the spatial resolution is improved.
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FIG. 1 is a flow chart of a method disclosed in the prior art;
fig. 2 is a flowchart of a method disclosed in an exemplary embodiment of the invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the accompanying drawings, and it should be understood that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used in this application and the appended claims, the singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items.
It is to be understood that although the terms first, second, third, etc. may be used herein to describe various information, such information should not be limited to these terms. These terms are only used to distinguish one type of information from another. For example, first information may also be referred to as second information, and similarly, second information may also be referred to as first information, without departing from the scope of the present application. The word "if" as used herein may be interpreted as "at … …" or "when … …" or "in response to a determination", depending on the context.
In addition, the technical features involved in the different embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.
Referring to fig. 2, fig. 2 shows that an exemplary embodiment of the present invention provides a method for detecting OFDR system vibration based on secondary correlation, which includes the following steps:
s11: acquiring a reference signal and a test signal of an OFDR system;
s13: preprocessing the reference signal and the test signal to obtain respective segmented wavelength domain signals of the reference signal and the test signal;
s15: processing the wavelength domain signals of all the corresponding segmented reference signals and the wavelength domain signals of the test signals to obtain vibration information, wherein the processing comprises the following steps:
s151: performing autocorrelation operation on the wavelength domain data of the reference signal to obtain autocorrelation operation data;
s153: performing cross-correlation operation on the wavelength domain data of the reference signal and the wavelength domain data of the test signal to obtain first cross-correlation operation data;
s155: and performing cross-correlation operation on the auto-correlation operation data and the first cross-correlation operation data.
Specifically, in this exemplary embodiment, the reference signal is a signal that does not contain vibration information, and the test signal is a signal that contains vibration information.
The signal is subjected to autocorrelation operation, and the signal-to-noise ratio is improved by utilizing the characteristics of the signal and the noise and the mutual independence between the noise and the noise. Assuming a wavelength domain signal x of a reference signal1(t)＝s1(t) + n (t), where s1(t) is an ideal signal, and n (t) is a noise signal. Then the wavelength domain signal of the reference signal self-operates as:
wherein
And
as a result of the cross-correlation of the ideal signal with noise,
in order to be a result of the noise autocorrelation,
is the result of the autocorrelation of the ideal signal. If the noise signal is ideally white Gaussian and uncorrelated with the signal, in the above formula
And
is 0. Known from the nature of Gaussian white noise
Is the shock function at τ -0. In practice, however, the noise may not be ideal. Therefore, the temperature of the molten metal is controlled,
and
not strictly 0, and in the case where τ ≠ 0,
always present, but its amplitude is necessarily reduced substantially compared to the original noise, since noise and signal are usually seen as uncorrelated. Therefore, after the signal is subjected to autocorrelation once, the signal-to-noise ratio is improved.
Performing cross-correlation operation on the wavelength domain data of the reference signal and the wavelength domain data of the test signal to obtain first cross-correlation operation data, wherein the specific calculation is as follows:
suppose a signal x1(t)＝s1(t)+n1(t) in which s1(t) is an ideal signal, n1(t) is a noise signal. x is the number of2(t)＝s2(t)+n2(t) in which s2(t) is an ideal signal, n2(t) is a noise signal. Wherein
And
as a result of the cross-correlation of the ideal signal with noise,
in order to be a result of the noise cross-correlation,
is the cross-correlation result of the ideal signal. Assuming that the noise is random white Gaussian noise and is not correlated with the signal, two noises n1(t) and n2(t) are also independent of each other. Thus, it is possible to provide
And
are both 0. Thus, it is possible to obtain:
before the vibration occurs, the wavelength domain data of the reference signal and the wavelength domain data of the test signal are almost the same, so that s is also present before the vibration occurs1(t)＝s2(t) then there are
Then there is
In fact still being the signal s1(t) the autocorrelation function, as described above, cross-correlating the two signals still actually correlates the signals once, improving the signal-to-noise ratio.
In the calculation process of the quadratic correlation algorithm, the influence of noise on signals is reduced, and compared with the basic cross-correlation algorithm, the vibration detection can be realized in the environment with lower signal-to-noise ratio. More accurate vibration detection can be achieved while improving spatial resolution. In addition to step S151 and step S153, the cross correlation calculation in step S155 can obtain the amount of cross correlation peak shift at each position, and the data having disturbance information has a shift of the cross correlation peak and a deviation value corresponding to the sensing amount.
Preferably, in an exemplary embodiment, the preprocessing the reference signal and the test signal to obtain respective segmented wavelength domain signals of the reference signal and the test signal includes:
respectively carrying out fast Fourier transform on the reference signal and the measurement signal, namely converting optical frequency domain information into distance domain information corresponding to each position in the sensing optical fiber;
the obtained two groups of distance domain information are divided into N equal parts on a distance domain by sliding with a window with a certain size, wherein each part is a segmented signal;
and performing inverse Fourier transform on the segmented signals to obtain respective local Rayleigh scattering spectra of the reference signal and the test signal, namely respective segmented wavelength domain signals of the reference signal and the test signal.
Specifically, in the exemplary embodiment, the preprocessing mainly includes domain conversion and segmentation operations.
Preferably, in an exemplary embodiment, the autocorrelation operation is performed on the wavelength domain data of the reference signal to obtain autocorrelation operation data, and specifically, the autocorrelation operation data is calculated as follows:
R11(τ)＝E[x1(t)x1(t+τ)]
in the formula, x1(t) and x1(t + τ) represents wavelength region data of the reference signal at time t and time t + τ, respectively, E [ [ deg. ] ]]To represent
Wherein M is the total number of sampling points;
performing cross-correlation operation on the wavelength domain data of the reference signal and the wavelength domain data of the test signal to obtain first cross-correlation operation data, specifically calculating as follows:
R12(τ)＝E[x1(t)x2(t+τ)]
in the formula, x2(t + τ) represents wavelength domain data of the test signal at time t + τ;
the cross-correlation operation is performed on the autocorrelation operation data and the first cross-correlation operation data, and the specific calculation is as follows:
RRR(τ)＝E[R11(τ)R12(τ)]。
preferably, in an exemplary embodiment, the system vibration detection method is replaced by a system strain detection method, and the vibration information is replaced by strain information; or:
the system vibration detection method is replaced by a system temperature detection method, and the vibration information is replaced by temperature information.
Specifically, in this exemplary embodiment, the detection method is applicable not only to vibration detection but also to detection of strain and temperature.
Having the same inventive concept as the above-described exemplary embodiment, still another exemplary embodiment of the present invention provides a secondary correlation-based OFDR system vibration detection system, comprising:
the signal acquisition module is used for acquiring a reference signal and a test signal of the OFDR system;
the preprocessing module is used for preprocessing the reference signal and the test signal to obtain respective segmented wavelength domain signals of the reference signal and the test signal;
the vibration information calculation module is used for processing the wavelength domain signals of all the corresponding segmented reference signals and the wavelength domain signals of the test signals to obtain vibration information, and comprises the following steps:
the autocorrelation operation sub-module is used for carrying out autocorrelation operation on the wavelength domain data of the reference signal to obtain autocorrelation operation data;
the first cross-correlation operation sub-module is used for carrying out cross-correlation operation on the wavelength domain data of the reference signal and the wavelength domain data of the test signal to obtain first cross-correlation operation data;
and the second cross-correlation operation sub-module is used for performing cross-correlation operation on the auto-correlation operation data and the first cross-correlation operation data.
More preferably, in an exemplary embodiment, the preprocessing module includes:
the fast Fourier transform submodule is used for respectively carrying out fast Fourier transform on the reference signal and the measurement signal, namely converting the optical frequency domain information into distance domain information corresponding to each position in the sensing optical fiber;
the segmentation submodule is used for dividing the obtained two groups of distance domain information into N equal parts by using a window with a certain size to slide on a distance domain, wherein each part is a segmentation signal;
and the inverse Fourier transform submodule is used for performing inverse Fourier transform on the segmented signals to obtain respective local Rayleigh scattering spectra of the reference signal and the test signal, namely respective segmented wavelength domain signals of the reference signal and the test signal.
Preferably, in an exemplary embodiment, the autocorrelation calculation sub-module specifically calculates as follows:
R11(τ)＝E[x1(t)x1(t+τ)]
in the formula, x1(t) and x1(t + τ) represents wavelength region data of the reference signal at time t and time t + τ, respectively, E [ [ deg. ] ]]To represent
Wherein M is the total number of sampling points;
the specific calculation of the first cross-correlation operation submodule is as follows:
R12(τ)＝E[x1(t)x2(t+τ)]
in the formula, x2(t + τ) represents wavelength domain data of the test signal at time t + τ;
the specific calculation of the second cross-correlation operation sub-module is as follows:
RRR(τ)＝E[R11(τ)R12(τ)]。
preferably, in an exemplary embodiment, the system vibration detection system is replaced by a system strain detection system, the vibration information calculation module is replaced by a strain information calculation module, and the vibration information is replaced by strain information; or:
the system vibration detection system is replaced by a system temperature detection system, the vibration information calculation module is replaced by a temperature information calculation module, and the vibration information is replaced by temperature information.
Preferably, based on any one of the above method exemplary embodiments, in a further exemplary embodiment of the present invention, a storage medium is provided, on which computer instructions are stored, which when executed perform the steps of the method for detecting OFDR system vibration based on second order correlation.
Still preferably, based on any one of the above method exemplary embodiments, in a further exemplary embodiment of the present invention, there is provided a terminal, including a memory and a processor, where the memory stores computer instructions executable on the processor, and the processor executes the steps of the method for detecting OFDR system vibration based on quadratic correlation when executing the computer instructions.
Based on such understanding, the technical solutions of the present embodiments may be essentially implemented or make a contribution to the prior art, or may be implemented in the form of a software product stored in a storage medium and including several instructions for causing an apparatus to execute all or part of the steps of the methods according to the embodiments of the present invention. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-only memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
It is to be understood that the above-described embodiments are illustrative only and not restrictive of the broad invention, and that various other modifications and changes in light thereof will be suggested to persons skilled in the art based upon the above teachings. And are neither required nor exhaustive of all embodiments. And obvious variations or modifications of the invention may be made without departing from the spirit or scope of the invention.
Claims (10)
1. A vibration detection method of an OFDR system based on secondary correlation is characterized in that: the method comprises the following steps:
acquiring a reference signal and a test signal of an OFDR system;
preprocessing the reference signal and the test signal to obtain respective segmented wavelength domain signals of the reference signal and the test signal;
processing the wavelength domain signals of all the corresponding segmented reference signals and the wavelength domain signals of the test signals to obtain vibration information, wherein the processing comprises the following steps:
performing autocorrelation operation on the wavelength domain data of the reference signal to obtain autocorrelation operation data;
performing cross-correlation operation on the wavelength domain data of the reference signal and the wavelength domain data of the test signal to obtain first cross-correlation operation data;
and performing cross-correlation operation on the auto-correlation operation data and the first cross-correlation operation data.
2. The OFDR system vibration detection method based on quadratic correlation of claim 1, wherein: the preprocessing the reference signal and the test signal to obtain respective segmented wavelength domain signals of the reference signal and the test signal includes:
respectively carrying out fast Fourier transform on the reference signal and the measurement signal, namely converting optical frequency domain information into distance domain information corresponding to each position in the sensing optical fiber;
the obtained two groups of distance domain information are divided into N equal parts on a distance domain by sliding with a window with a certain size, wherein each part is a segmented signal;
and performing inverse Fourier transform on the segmented signals to obtain respective local Rayleigh scattering spectra of the reference signal and the test signal, namely respective segmented wavelength domain signals of the reference signal and the test signal.
3. The OFDR system vibration detection method based on quadratic correlation of claim 1, wherein: the autocorrelation operation is performed on the wavelength domain data of the reference signal to obtain autocorrelation operation data, and the autocorrelation operation data is specifically calculated as follows:
R11(τ)＝E[x1(t)x1(t+τ)]
in the formula, x1(t) and x1(t + τ) represents wavelength region data of the reference signal at time t and time t + τ, respectively, E [ [ deg. ] ]]To represent
Performing cross-correlation operation on the wavelength domain data of the reference signal and the wavelength domain data of the test signal to obtain first cross-correlation operation data, specifically calculating as follows:
R12(τ)＝E[x1(t)x2(t+τ)]
in the formula, x2(t + τ) represents wavelength domain data of the test signal at time t + τ;
the cross-correlation operation is performed on the autocorrelation operation data and the first cross-correlation operation data, and the specific calculation is as follows:
RRR(τ)＝E[R11(τ)R12(τ)]。
4. the OFDR system vibration detection method based on quadratic correlation of claim 1, wherein: replacing the system vibration detection method with a system strain detection method, and replacing the vibration information with strain information; or:
the system vibration detection method is replaced by a system temperature detection method, and the vibration information is replaced by temperature information.
5. The utility model provides a vibration detecting system of OFDR system based on quadratic dependence which characterized in that: the method comprises the following steps:
the signal acquisition module is used for acquiring a reference signal and a test signal of the OFDR system;
the preprocessing module is used for preprocessing the reference signal and the test signal to obtain respective segmented wavelength domain signals of the reference signal and the test signal;
the vibration information calculation module is used for processing the wavelength domain signals of all the corresponding segmented reference signals and the wavelength domain signals of the test signals to obtain vibration information, and comprises the following steps:
the autocorrelation operation sub-module is used for carrying out autocorrelation operation on the wavelength domain data of the reference signal to obtain autocorrelation operation data;
the first cross-correlation operation sub-module is used for carrying out cross-correlation operation on the wavelength domain data of the reference signal and the wavelength domain data of the test signal to obtain first cross-correlation operation data;
and the second cross-correlation operation sub-module is used for performing cross-correlation operation on the auto-correlation operation data and the first cross-correlation operation data.
6. The vibration detection system for OFDR system based on secondary correlation as claimed in claim 5, wherein: the preprocessing module comprises:
the fast Fourier transform submodule is used for respectively carrying out fast Fourier transform on the reference signal and the measurement signal, namely converting the optical frequency domain information into distance domain information corresponding to each position in the sensing optical fiber;
the segmentation submodule is used for dividing the obtained two groups of distance domain information into N equal parts by using a window with a certain size to slide on a distance domain, wherein each part is a segmentation signal;
and the inverse Fourier transform submodule is used for performing inverse Fourier transform on the segmented signals to obtain respective local Rayleigh scattering spectra of the reference signal and the test signal, namely respective segmented wavelength domain signals of the reference signal and the test signal.
7. The vibration detection system for OFDR system based on secondary correlation as claimed in claim 5, wherein: the autocorrelation operation submodule is specifically calculated as follows:
R11(τ)＝E[x1(t)x1(t+τ)]
in the formula, x1(t) and x1(t + τ) represents wavelength region data of the reference signal at time t and time t + τ, respectively, E [ [ deg. ] ]]To represent
Wherein M is the total number of sampling points;
the specific calculation of the first cross-correlation operation submodule is as follows:
R12(τ)＝E[x1(t)x2(t+τ)]
in the formula, x2(t + τ) represents wavelength domain data of the test signal at time t + τ;
the specific calculation of the second cross-correlation operation sub-module is as follows:
RRR(τ)＝E[R11(τ)R12(τ)]。
8. the vibration detection system for OFDR system based on secondary correlation as claimed in claim 5, wherein: the system vibration detection system is replaced by a system strain detection system, the vibration information calculation module is replaced by a strain information calculation module, and the vibration information is replaced by strain information; or:
the system vibration detection system is replaced by a system temperature detection system, the vibration information calculation module is replaced by a temperature information calculation module, and the vibration information is replaced by temperature information.
9. A storage medium having stored thereon computer instructions, characterized in that: the computer instructions when executed perform the steps of a method for vibration detection in an OFDR system based on quadratic dependence of any one of claims 1 to 4.
10. A terminal comprising a memory and a processor, said memory having stored thereon computer instructions executable on said processor, wherein said processor when executing said computer instructions performs the steps of a method for vibration detection in an OFDR system based on quadratic correlation according to any one of claims 1 to 4.
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|---|---|---|---|---|
| CN117168337A (en) * | 2023-07-04 | 2023-12-05 | 哈尔滨工业大学 | OFDR strain edge optimization method and measurement method |
| CN117168337B (en) * | 2023-07-04 | 2024-06-04 | 哈尔滨工业大学 | OFDR strain edge optimization method and measurement method |
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