Vibration source transverse distance determination method and device based on distributed optical fibers

Abstract

The invention relates to a vibration source transverse distance determination method and device based on a distributed optical fiber, and belongs to the technical field of pipeline optical fiber early warning, and the method comprises the steps: obtaining a vibration original signal based on the distributed optical fiber, and extracting a high-frequency signal set and a low-frequency signal set of the vibration original signal; respectively calculating an energy value of the high-frequency signal set and an energy value of the low-frequency signal set, and obtaining a ratio characteristic of the high-frequency energy value and the low-frequency energy value; and based on different influence degrees of vibration sources with different distances on attenuation filtering of high and low frequency vibration, determining the transverse distance of the vibration source according to the ratio characteristics. The technical problem of how to improve the transverse positioning efficiency and accuracy of the vibration source under the embedding condition of a heterogeneous complex underground structure in the prior art is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of pipeline optical fiber early warning technology, and in particular to a method and device for determining the lateral distance of a vibration source based on distributed optical fiber. Background Art

[0002] Distributed fiber optic vibration measurement technology uses the communication optical cable laid in the same trench as the oil and gas pipeline as a vibration sensor and signal transmission element. It has the advantages of long distance, real-time, and anti-electromagnetic, and has been successfully applied in the field of oil and gas pipeline safety monitoring. Due to the high sensitivity of the system's vibration detection, in some cases, vibration signals hundreds of meters away from the pipeline can also be detected and trigger system alarms, but vibration signals hundreds of meters away from the pipeline do not pose a threat to oil and gas pipelines. Therefore, it is the key to improve the system's operating effect to effectively alarm for destructive external excitations that occur close to the pipeline, while reducing the alarm rate for non-destructive excitation vibrations that are far away from the pipeline.

[0003] Patent CN103954349B is a method for lateral positioning of a distributed optical fiber vibration sensing system. It uses the time delay difference of the vibration wave reaching different positions of the optical fiber and the propagation speed of the vibration signal in the soil to infer the distance of the excitation source from the optical fiber, but does not provide a method for obtaining vibration wave velocity information. Patent CN 103954349 B is a method for lateral positioning of a distributed optical fiber vibration sensing system. This method is the most basic positioning principle, but it is necessary to know the exact propagation speed of the vibration wave in the soil, but the vibration wave sensing speed is different in different soils (soil type, water content, etc.). Patent CN103292889 B is a method for locating the vibration source of a distributed optical fiber vibration sensor. This method has a large amount of data and high requirements for real-time processing. Patent CN114046867B, a vibration source lateral distance estimation method based on a distributed optical fiber vibration sensing system, and patent CN113984182B, a distributed lateral vibration source distance positioning method for oil and gas pipelines, are both based on the time delay difference model to locate the lateral distance of the vibration source. However, during the underground propagation of the ground vibration source, it is propagated to the optical cable through multiple layers of mixed soil media, cement or metal pipes, air and other media. The propagation speed of the vibration wave underground is not fixed and is also affected by complex multipath interference, resulting in the array signal positioning method (water / air uniform medium) based on time delay difference and wave arrival direction estimation cannot be effectively applied.

[0004] Therefore, facing the burial conditions of heterogeneous and complex underground structures, lateral positioning of ground vibration sources based on DVS signals is a challenging problem. Summary of the invention

[0005] In view of this, it is necessary to provide a method and device for determining the lateral distance of a vibration source based on distributed optical fiber to solve the technical problem in the prior art of how to improve the lateral positioning efficiency and accuracy of the vibration source under the burial conditions of heterogeneous and complex underground structures.

[0006] In order to solve the above problems, the present invention provides a method for determining the lateral distance of a vibration source based on a distributed optical fiber, comprising: Acquire an original vibration signal based on a distributed optical fiber, and extract a high-frequency signal set and a low-frequency signal set of the original vibration signal; Calculate the energy value of the high-frequency signal set and the energy value of the low-frequency signal set respectively, and obtain the ratio feature of the high-frequency energy value to the low-frequency energy value; Based on the different degrees of influence of vibration sources at different distances on the attenuation filtering of high and low frequency vibrations, the lateral distance of the vibration source is determined according to the ratio characteristics.

[0007] In a possible implementation, extracting the high-frequency signal set and the low-frequency signal set of the original vibration signal includes: Perform bandpass filtering on the original signals respectively to obtain filtering results; The filtering results are spliced ​​in a spatial sequence to obtain a low-frequency signal waterfall diagram and a high-frequency signal waterfall diagram.

[0008] In a possible implementation, respectively calculating the energy value of the high-frequency signal set and the energy value of the low-frequency signal set includes: Performing standardization processing on the high-frequency signal set and the low-frequency signal set respectively to obtain a target high-frequency signal waterfall diagram and a target low-frequency signal waterfall diagram; Extracting foreground images of the target high-frequency signal waterfall diagram and the target low-frequency signal waterfall diagram respectively to obtain a high-frequency foreground image and a low-frequency foreground image; Based on the high-frequency foreground image, a high-frequency time-domain energy waterfall diagram is calculated; and based on the low-frequency foreground image, a low-frequency time-domain energy waterfall diagram is calculated; Determine the high-frequency signal block area of ​​each independent excitation according to the high-frequency time-domain energy waterfall diagram; and determine the low-frequency signal block area of ​​each independent excitation according to the low-frequency time-domain energy waterfall diagram; The energy value of the high-frequency signal set is determined according to the total amount of the high-frequency signal block area, and the energy value of the low-frequency signal set is determined according to the total amount of the low-frequency signal block area.

[0009] In a possible implementation, the step of respectively extracting the foreground images of the target high-frequency signal waterfall diagram and the target low-frequency signal waterfall diagram includes: The preset OTSU algorithm is used to extract the foreground image of the target high-frequency signal waterfall diagram according to the size relationship between the pixels in the target high-frequency signal waterfall diagram and the pixel threshold; The preset OTSU algorithm is used to extract the foreground image of the target low-frequency signal waterfall diagram according to the size relationship between the pixels in the target low-frequency signal waterfall diagram and the pixel threshold.

[0010] In a possible implementation, determining the high-frequency signal block area of ​​each independent excitation according to the high-frequency time-domain energy waterfall diagram includes: Using a connected domain segmentation method, scanning the high-frequency time domain energy waterfall diagram line by line, and obtaining a labeled cluster; According to the marker group, the high-frequency signal block area of ​​each independent excitation is determined.

[0011] In a possible implementation, the influence of vibration sources at different distances on the attenuation filtering of high and low frequency vibrations is different, and the lateral distance of the vibration source is determined according to the ratio feature, including: Obtain mechanical excitation vibration signals at different known lateral distances, and calculate the high-frequency energy area and the low-frequency energy area respectively to obtain the high- and low-frequency energy ratio characteristics; Based on the different influences of vibration sources at different distances on the attenuation filtering of high and low frequency vibrations, a training set is constructed according to the known lateral distance and its corresponding high and low frequency energy ratio characteristics; The training set is used to train a lateral distance calculation model to obtain a fully trained lateral distance calculation model; The high- and low-frequency energy ratio characteristics acquired in real time are input into a well-trained lateral distance calculation model to obtain the lateral distance of the vibration source.

[0012] In a possible implementation, the lateral distance calculation model is a neural network model.

[0013] In a second aspect, the present invention further provides a device for determining the lateral distance of a vibration source based on a distributed optical fiber, comprising: A signal acquisition module, used to acquire an original vibration signal based on a distributed optical fiber, and extract a high-frequency signal set and a low-frequency signal set of the original vibration signal; A ratio feature determination module is used to calculate the energy value of the high-frequency signal set and the energy value of the low-frequency signal set, and obtain a ratio feature of the high-frequency energy value and the low-frequency energy value; The lateral distance determination module is used to determine the lateral distance of the vibration source based on the different influences of vibration sources at different distances on the attenuation filtering of high and low frequency vibrations and the ratio characteristics.

[0014] In a third aspect, the present invention further provides an electronic device, comprising: a processor and a memory; The memory stores a computer-readable program executable by the processor; When the processor executes the computer-readable program, the steps in the method for determining the lateral distance of a vibration source based on distributed optical fiber as described above are implemented.

[0015] In a fourth aspect, the present invention further provides a computer-readable storage medium storing one or more programs, which can be executed by one or more processors to implement the steps in the method for determining the lateral distance of a vibration source based on distributed optical fiber as described above.

[0016] The beneficial effects of the present invention are as follows: first, the original vibration signal is obtained based on the distributed optical fiber, and the high-frequency signal set and the low-frequency signal set of the original vibration signal are extracted; then, the energy value of the high-frequency signal set and the energy value of the low-frequency signal set are calculated respectively, and the ratio characteristics of the high-frequency energy value and the low-frequency energy value are obtained. By analyzing the ratio characteristics, noise and irrelevant signals can be effectively filtered out, and the reliability of signal processing can be improved; finally, based on the different degrees of influence of vibration sources at different distances on the attenuation filtering of high and low frequency vibrations, the lateral distance of the vibration source is determined according to the ratio characteristics. The present invention utilizes the attenuation characteristics of high and low frequency signals to accurately determine the lateral distance of the vibration source and achieve high-precision vibration source positioning, thereby effectively reducing the calculation error caused by the burial conditions of heterogeneous and complex underground structures, and has high robustness. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 A method flow chart of an embodiment of a method for determining the lateral distance of a vibration source based on distributed optical fiber provided by the present invention; Figure 2 In the method for determining the lateral distance of a vibration source based on distributed optical fiber provided by the present invention, a near-field / far-field high and low frequency waterfall diagram; Figure 3 A method flow chart of an embodiment of step S102 in the method for determining the lateral distance of a vibration source based on a distributed optical fiber provided by the present invention; Figure 4 A schematic diagram of near-field / far-field high and low frequency energy region extraction in the method for determining the lateral distance of a vibration source based on distributed optical fiber provided by the present invention; Figure 5 A method flow chart of an embodiment of step S103 in the method for determining the lateral distance of a vibration source based on a distributed optical fiber provided by the present invention; Figure 6 It is a schematic diagram of an embodiment of a device for determining the lateral distance of a vibration source based on a distributed optical fiber provided by the present invention; Figure 7 It is a schematic diagram of the operating environment of an electronic device provided by the present invention. DETAILED DESCRIPTION

[0018] The preferred embodiments of the present invention are described in detail below in conjunction with the accompanying drawings, wherein the accompanying drawings constitute a part of this application and are used together with the embodiments of the present invention to illustrate the principles of the present invention, but are not used to limit the scope of the present invention.

[0019] A specific embodiment of the present invention discloses a method for determining the lateral distance of a vibration source based on distributed optical fiber. Figure 1 ,include: S101, obtaining an original vibration signal based on a distributed optical fiber, and extracting a high-frequency signal set and a low-frequency signal set of the original vibration signal; S102, respectively calculating the energy value of the high-frequency signal set and the energy value of the low-frequency signal set, and obtaining a ratio feature of the high-frequency energy value to the low-frequency energy value; S103. Based on the different influences of vibration sources at different distances on the attenuation filtering of high and low frequency vibrations, determine the lateral distance of the vibration source according to the ratio characteristics.

[0020] In this embodiment, firstly, the original vibration signal is obtained based on the distributed optical fiber, and the high-frequency signal set and the low-frequency signal set of the original vibration signal are extracted; then, the energy value of the high-frequency signal set and the energy value of the low-frequency signal set are calculated respectively, and the ratio characteristic of the high-frequency energy value to the low-frequency energy value is obtained. By analyzing the ratio characteristic, noise and irrelevant signals can be effectively filtered out, and the reliability of signal processing can be improved; finally, based on the different degrees of influence of vibration sources at different distances on the attenuation filtering of high and low frequency vibrations, the lateral distance of the vibration source is determined according to the ratio characteristic. The present invention utilizes the attenuation characteristics of high and low frequency signals, can accurately determine the lateral distance of the vibration source, and realize high-precision vibration source positioning, thereby effectively reducing the calculation error caused by the burial conditions of heterogeneous and complex underground structures, and has high robustness.

[0021] Furthermore, the method provided by the present invention realizes accurate measurement of the lateral distance of the vibration source, thereby solving the practical problem of long-distance non-threatening vibration sources interfering with the system alarm effect in the pipeline safety monitoring application scenario, improving the accuracy of identifying threatening third-party construction events, and optimizing the system operation effect.

[0022] It should be noted that in step S103, the attenuation of high-frequency vibration in the soil is greater than that of the low-frequency part. For vibration sources at different distances, the low-frequency energy is relatively close, while the high-frequency energy is quite different. The longer the distance, the more obvious the high-frequency attenuation. By analyzing and comparing the proportions of high- and low-frequency vibration energies, the lateral distance can be estimated.

[0023] In some embodiments, extracting the high-frequency signal set and the low-frequency signal set of the vibration original signal includes: Perform bandpass filtering on the original signals respectively to obtain filtering results; The filtering results are spliced ​​in a spatial sequence to obtain a low-frequency signal waterfall diagram and a high-frequency signal waterfall diagram.

[0024] In this embodiment, the original signal is band-pass filtered for the low-frequency part and the high-frequency part, respectively, to separate the high-frequency and low-frequency components of the signal. For a 500Hz sampling rate signal, the low-frequency filter passband can be set to 0.1Hz-20Hz, and the high-frequency filter passband can be set to 180Hz-200Hz. The filtering results are spliced ​​in spatial sequence to form waterfall diagrams of high- and low-frequency vibration signals, respectively. Figure 2 As shown in the figure, the original signals and high- and low-frequency signal separation results of the near-field mechanical excitation signal and the far-field mechanical excitation signal are respectively. It can be seen that in the low-frequency signal waterfall diagram, the coverage areas of the near-field and far-field vibration signals are relatively close, while in the high-frequency signal waterfall diagram, the coverage areas of the near-field and far-field vibration signals are quite different, and the coverage area of ​​the far-field high-frequency signal is significantly smaller than the coverage area of ​​the near-field high-frequency signal.

[0025] In some embodiments, the energy values ​​of the high-frequency signal set and the energy values ​​of the low-frequency signal set are calculated separately. Figure 3 ,include: S301, performing standardization processing on the high-frequency signal set and the low-frequency signal set respectively to obtain a target high-frequency signal waterfall diagram and a target low-frequency signal waterfall diagram; S302, respectively extracting foreground images of a target high-frequency signal waterfall diagram and a target low-frequency signal waterfall diagram to obtain a high-frequency foreground image and a low-frequency foreground image; S303, calculating a high-frequency time-domain energy waterfall diagram based on the high-frequency foreground image; and calculating a low-frequency time-domain energy waterfall diagram based on the low-frequency foreground image; S304, determining the high-frequency signal block area of ​​each independent excitation according to the high-frequency time-domain energy waterfall diagram; and determining the low-frequency signal block area of ​​each independent excitation according to the low-frequency time-domain energy waterfall diagram; S305 : Determine the energy value of the high-frequency signal set according to the total amount of the high-frequency signal block area, and determine the energy value of the low-frequency signal set according to the total amount of the low-frequency signal block area.

[0026] In this embodiment, through standardization processing, foreground image extraction, time domain energy waterfall diagram calculation, signal block area determination and energy value calculation, accurate calculation of energy values ​​of high-frequency signal sets and low-frequency signal sets is achieved, the consistency and comparability of signal processing are improved, background noise is removed, an intuitive energy distribution diagram is provided, the signal area of ​​each independent excitation is accurately identified, and the energy distribution of high-frequency and low-frequency signal sets is quantified. It has broad application prospects and significant technical benefits in many fields such as earthquake monitoring, structural health monitoring, and industrial equipment vibration monitoring.

[0027] Furthermore, the extracting of the foreground images of the target high-frequency signal waterfall diagram and the target low-frequency signal waterfall diagram respectively includes: The preset OTSU algorithm is used to extract the foreground image of the target high-frequency signal waterfall diagram according to the size relationship between the pixels in the target high-frequency signal waterfall diagram and the pixel threshold; The preset OTSU algorithm is used to extract the foreground image of the target low-frequency signal waterfall diagram according to the size relationship between the pixels in the target low-frequency signal waterfall diagram and the pixel threshold.

[0028] In this embodiment, data normalization is performed on the high-frequency and low-frequency signal waterfall graphs respectively, and the values ​​are mapped to the interval [0, 1]. Then, the following steps are performed on the high-frequency waterfall graph and the low-frequency waterfall graph respectively: The OTSU method is used to extract the foreground of the image; the OTSU algorithm includes: Using the set threshold Classify the pixels in the matrix image into two categories: (less than )and (greater than ), then the mean of these two types of pixels is , , the global mean of the image is . At the same time, the probability of pixels being divided into and classes are , .in: (1) (2) According to the concept of variance, the expression of between-class variance is: (3) Simplifying the above formula and substituting formula (1) into formula (3), we can get: (4) The value k (k < ∈ (0, 255)) that maximizes equation (4) is the OTSU threshold, where , ,

[0029] According to formula (4), the values ​​0 to 255 are traversed to find the k that maximizes formula (4), which is the global threshold. The matrix image is divided into foreground and background parts according to the global threshold.

[0030] Furthermore, a window with a length of 1 second is slid along the vertical axis in the image matrix in turn to calculate the time domain energy waterfall diagrams of the high and low frequency signals.

[0031] In some embodiments, determining the high-frequency signal block area of ​​each independent excitation according to the high-frequency time-domain energy waterfall diagram includes: Using a connected domain segmentation method, scanning the high-frequency time domain energy waterfall diagram line by line, and obtaining a labeled cluster; According to the marker group, the high-frequency signal block area of ​​each independent excitation is determined.

[0032] In this embodiment, the signal block area of ​​each independent excitation in the time domain energy waterfall diagram is extracted to facilitate subsequent statistical analysis, and the following method is adopted: Scan the image line by line: The continuous monitoring units in each line are grouped into a sequence (called a group), and the starting point, end point and line number of the group are recorded.

[0033] Mark the cliques: For the cliques in all rows except the first row: If there is no overlap with any clique in the previous row, give it a new label. If there is only one clique in the previous row, give it the label of the clique in the previous row. If there is overlap with more than two cliques in the previous row, give it the smallest label of the cliques with overlap, and write the labels of the connected cliques into the equivalent pair.

[0034] Convert equivalent pairs to equivalent sequences: give each sequence the same label.

[0035] Relabeling: Starting from 1, give each equivalent sequence a label and fill the label of each group into the matrix image.

[0036] Finally, the ratio of the high-frequency block area to the low-frequency block area of ​​each signal sample is calculated, and the ratio is matched with the known horizontal distance of the signal sample and stored in the database as the same sample data. Figure 4 As shown, there are schematic diagrams of the high- and low-frequency energy extraction results and the basis for proportion calculation of near-field and far-field vibration signals, respectively.

[0037] In some embodiments, the influence of different distances of vibration sources on the attenuation filtering of high and low frequency vibrations is different. According to the ratio characteristics, the lateral distance of the vibration source is determined. Please refer to Figure 5 ,include: S501, obtaining mechanical excitation vibration signals at different known lateral distances, and respectively calculating the high-frequency energy area and the low-frequency energy area to obtain a high-frequency and low-frequency energy ratio feature; S502, based on the different degrees of influence of vibration sources at different distances on the attenuation filtering of high and low frequency vibrations, a training set is constructed according to known lateral distances and their corresponding high and low frequency energy ratio characteristics; S503, using the training set to train a lateral distance calculation model to obtain a fully trained lateral distance calculation model; S504, inputting the high-frequency and low-frequency energy ratio characteristics acquired in real time into a well-trained lateral distance calculation model to obtain the lateral distance of the vibration source.

[0038] In this embodiment, the ratio of the high-frequency band energy to the low-frequency band energy of the vibration signal is converted into a specific characteristic value. This characteristic value decreases as the lateral distance increases. A mathematical model is established for this corresponding relationship, and the lateral distance can be estimated through this mathematical model.

[0039] Collect a large number of mechanical excitation signals at different lateral distances, calculate their high and low frequency energy areas respectively, and obtain the characteristic value of the high and low frequency energy ratio. Then use the feature-distance sample data to train the lateral distance estimation model. The models that can be selected are: nonlinear fitting, random forest, SVM support vector machine, deep neural network model, etc.

[0040] For example, when a nonlinear fitting model is used, multiple sets of "feature (high-low frequency ratio)-lateral distance" correspondences in an existing database are used to train fitting parameters, where the feature (high-low frequency ratio) is the input x and the lateral distance is the output y, to obtain a curve fitting model.

[0041] The trained lateral distance estimation model is stored in the optical fiber early warning system. When the system detects and identifies a new mechanical excitation signal, it automatically calculates the high-frequency and low-frequency energy ratio of this signal according to the above steps, and then substitutes it into the lateral distance estimation model to obtain the lateral distance estimation value of this mechanical excitation signal. The system determines whether the vibration source is in the far field or near field based on the lateral distance and issues an alarm message of the corresponding level.

[0042] Based on the above-mentioned method for determining the lateral distance of a vibration source based on distributed optical fiber, an embodiment of the present invention further provides a device for determining the lateral distance of a vibration source based on distributed optical fiber, see Figure 6 ,include: A signal acquisition module 610 is used to acquire an original vibration signal based on a distributed optical fiber, and extract a high-frequency signal set and a low-frequency signal set of the original vibration signal; The ratio feature determination module 620 is used to calculate the energy value of the high-frequency signal set and the energy value of the low-frequency signal set respectively, and obtain the ratio feature of the high-frequency energy value and the low-frequency energy value; The lateral distance determination module 630 is used to determine the lateral distance of the vibration source according to the ratio characteristics based on the different degrees of influence of vibration sources at different distances on the attenuation filtering of high and low frequency vibrations.

[0043] like Figure 7As shown, based on the above-mentioned method for determining the lateral distance of the vibration source based on the distributed optical fiber, the present invention also provides an electronic device, which can be a computing electronic device such as a mobile terminal, a desktop computer, a notebook, a palm computer, and a server. The electronic device includes a processor 710, a memory 720, and a display 730. Figure 7 Only some components of the electronic device are shown, but it should be understood that it is not required to implement all of the components shown, and more or fewer components may be implemented instead.

[0044] In some embodiments, the memory 720 may be an internal storage unit of the electronic device, such as a hard disk or memory of the electronic device. In other embodiments, the memory 720 may also be an external storage electronic device of the electronic device, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (SecureDigital, SD) card, a flash card (Flash Card), etc. equipped on the electronic device. Further, the memory 720 may also include both an internal storage unit of the electronic device and an external storage electronic device. The memory 720 is used to store application software and various types of data installed in the electronic device, such as program codes for installing the electronic device. The memory 720 may also be used to temporarily store data that has been output or is to be output. In one embodiment, a vibration source lateral distance determination program 740 based on distributed optical fiber is stored on the memory 720, and the vibration source lateral distance determination program 740 based on distributed optical fiber can be executed by the processor 710, thereby realizing the vibration source lateral distance determination method based on distributed optical fiber in each embodiment of the present application.

[0045] In some embodiments, the processor 710 may be a central processing unit (CPU), a microprocessor or other data processing chip, used to run program codes or process data stored in the memory 720, such as executing a method for determining the lateral distance of a vibration source based on a distributed optical fiber.

[0046] In some embodiments, the display 730 may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch device, etc. The display 730 is used to display information of the electronic device for determining the lateral distance of the vibration source based on the distributed optical fiber and to display a visual user interface. The components 710-730 of the electronic device communicate with each other via a system bus.

[0047] Those skilled in the art will appreciate that all or part of the processes of the above-mentioned embodiments can be implemented by instructing related hardware through a computer program, and the program can be stored in a computer-readable storage medium, wherein the computer-readable storage medium is a disk, an optical disk, a read-only storage memory, or a random access memory, etc.

[0048] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by any technician familiar with the technical field within the technical scope disclosed by the present invention should be covered within the protection scope of the present invention.

Claims

1. A method for determining the lateral distance of a vibration source based on distributed optical fiber, characterized in that: include: Acquire an original vibration signal based on a distributed optical fiber, and extract a high-frequency signal set and a low-frequency signal set of the original vibration signal; Calculate the energy value of the high-frequency signal set and the energy value of the low-frequency signal set respectively, and obtain the ratio feature of the high-frequency energy value to the low-frequency energy value; Based on the different degrees of influence of vibration sources at different distances on the attenuation filtering of high and low frequency vibrations, the lateral distance of the vibration source is determined according to the ratio characteristics.

2. The method for determining the lateral distance of a vibration source based on distributed optical fiber according to claim 1, characterized in that: The step of extracting the high-frequency signal set and the low-frequency signal set of the original vibration signal comprises: Perform bandpass filtering on the original signals respectively to obtain filtering results; The filtering results are spliced ​​in a spatial sequence to obtain a low-frequency signal waterfall diagram and a high-frequency signal waterfall diagram.

3. The method for determining the lateral distance of a vibration source based on distributed optical fiber according to claim 2, characterized in that: The separately calculating the energy value of the high-frequency signal set and the energy value of the low-frequency signal set comprises: Performing standardization processing on the high-frequency signal set and the low-frequency signal set respectively to obtain a target high-frequency signal waterfall diagram and a target low-frequency signal waterfall diagram; Extracting foreground images of the target high-frequency signal waterfall diagram and the target low-frequency signal waterfall diagram respectively to obtain a high-frequency foreground image and a low-frequency foreground image; Based on the high-frequency foreground image, a high-frequency time-domain energy waterfall diagram is calculated; and based on the low-frequency foreground image, a low-frequency time-domain energy waterfall diagram is calculated; Determine the high-frequency signal block area of ​​each independent excitation according to the high-frequency time-domain energy waterfall diagram; and determine the low-frequency signal block area of ​​each independent excitation according to the low-frequency time-domain energy waterfall diagram; The energy value of the high frequency signal set is determined according to the total amount of the high frequency signal block area, and the energy value of the low frequency signal set is determined according to the total amount of the low frequency signal block area.

4. The method for determining the lateral distance of a vibration source based on distributed optical fiber according to claim 3, characterized in that: The foreground images of the target high-frequency signal waterfall diagram and the target low-frequency signal waterfall diagram are extracted separately, including: The preset OTSU algorithm is used to extract the foreground image of the target high-frequency signal waterfall diagram according to the size relationship between the pixels in the target high-frequency signal waterfall diagram and the pixel threshold; The preset OTSU algorithm is used to extract the foreground image of the target low-frequency signal waterfall diagram according to the size relationship between the pixels in the target low-frequency signal waterfall diagram and the pixel threshold.

5. The method for determining the lateral distance of a vibration source based on distributed optical fiber according to claim 3, characterized in that: Determining the high-frequency signal block area of ​​each independent excitation according to the high-frequency time-domain energy waterfall diagram includes: Using a connected domain segmentation method, scanning the high-frequency time domain energy waterfall diagram line by line, and obtaining a labeled cluster; According to the marker group, the high-frequency signal block area of ​​each independent excitation is determined.

6. The method for determining the lateral distance of a vibration source based on distributed optical fiber according to claim 1, characterized in that: The influence of vibration sources at different distances on the attenuation filtering of high and low frequency vibrations is different, and the lateral distance of the vibration source is determined according to the ratio feature, including: Obtain mechanical excitation vibration signals at different known lateral distances, and calculate the high-frequency energy area and the low-frequency energy area respectively to obtain the high- and low-frequency energy ratio characteristics; Based on the different influences of vibration sources at different distances on the attenuation filtering of high and low frequency vibrations, a training set is constructed according to the known lateral distance and its corresponding high and low frequency energy ratio characteristics; The training set is used to train a lateral distance calculation model to obtain a fully trained lateral distance calculation model; The high- and low-frequency energy ratio characteristics acquired in real time are input into a well-trained lateral distance calculation model to obtain the lateral distance of the vibration source.

7. The method for determining the lateral distance of a vibration source based on distributed optical fiber according to claim 6, characterized in that: The lateral distance calculation model is a neural network model.

8. A device for determining the lateral distance of a vibration source based on distributed optical fiber, characterized in that: include: A signal acquisition module, used to acquire an original vibration signal based on a distributed optical fiber, and extract a high-frequency signal set and a low-frequency signal set of the original vibration signal; A ratio feature determination module is used to calculate the energy value of the high-frequency signal set and the energy value of the low-frequency signal set, and obtain a ratio feature of the high-frequency energy value and the low-frequency energy value; The lateral distance determination module is used to determine the lateral distance of the vibration source based on the different influences of vibration sources at different distances on the attenuation filtering of high and low frequency vibrations and the ratio characteristics.

9. An electronic device, characterized in that: include: Processor and memory; The memory stores a computer-readable program executable by the processor; When the processor executes the computer-readable program, the processor implements the steps in the method for determining the lateral distance of a vibration source based on distributed optical fiber as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to implement the steps in the method for determining the lateral distance of a vibration source based on a distributed optical fiber as described in any one of claims 1-7.

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