Segmented vibration location method, system and device based on vibrating optical fiber

Abstract

The application discloses a segmented vibration positioning method, system and equipment based on a vibrating optical fiber, and belongs to the technical field of optical fiber sensing and detection; the method adopts a dynamic calculation mode to update noise reduction thresholds and early warning thresholds of each segment of a DAS system in real time, effectively reduces the influence of environmental factors, improves the anti-interference ability of the DAS system, maintains the alarm sensitivity of the DAS system, and realizes reliable positioning of multiple point disturbances on a long distance, such as a transmission distance of 30 km or more; the method comprehensively considers factors such as the current segment optical fiber installation mode and the laying scene through the threshold setting of each segment, the threshold is updated in real time with the transmission of data, and the calculation method is simple and efficient; the method effectively suppresses steady-state background noise, is suitable for a real-time processing scene, and has strong environmental adaptability.

Description

Technical Field

[0001] This invention belongs to the field of fiber optic sensing and detection technology, and relates to a segmented vibration positioning method, system and device based on vibrating optical fiber. Background Technology

[0002] Distributed fiber optic acoustic sensing (DAS) technology utilizes Rayleigh backscattered light information from optical fibers to detect acoustic waves along the fiber optic cable. It leverages the fiber's sensitivity to sound (vibration); when external vibrations act on the sensing fiber, they cause a phase change in the transmitted signal within the fiber, thus enabling the detection of vibration events. However, current positioning algorithms for vibration-related optical fibers in distributed fiber optic acoustic sensing systems suffer from several problems, including a fixed and singular global noise reduction threshold, complex calculations, the need for repeated adjustments to the warning threshold, and poor environmental adaptability. Specifically:

[0003] 1. Currently, most positioning algorithms use threshold judgment to determine the vibration location of optical fibers. This method relies on empirical values ​​for setting the warning threshold, requiring adjustments to the static threshold based on different actual environments to achieve optimal performance in practical use. The entire parameter tuning process is complex, and a single fixed threshold cannot adapt to various severe weather changes. False alarms increase significantly under extreme weather conditions such as strong winds and heavy rain, leading to reduced system stability and reliability.

[0004] 2. The different installation methods and diverse laying carriers of optical fibers can lead to significant differences in the intensity of vibration signals generated by the same intrusion action. Setting multiple early warning thresholds according to different defense zone types is not only cumbersome, but also has poor algorithm adaptability. After deployment, it needs to be constantly adjusted according to the on-site weather conditions and surrounding environment, which is extremely time-consuming and labor-intensive.

[0005] 3. As the monitoring distance increases, the energy of light will attenuate. For long-distance scenarios such as more than 30km, the signal-to-noise ratio of the vibration signal at the front and rear ends of the optical fiber differs greatly. If the same noise reduction threshold and warning threshold are used for the entire signal, the actual vibration location cannot be accurately and reliably detected.

[0006] Therefore, a new technical solution is urgently needed to effectively address the problems in existing technologies, such as a fixed and singular global noise reduction threshold, complex calculations, the need for repeated adjustments to the warning threshold, and poor environmental adaptability. Summary of the Invention

[0007] This invention aims to provide a segmented vibration positioning method, system, and device based on vibrating optical fibers. The method effectively suppresses steady-state background noise, has high computational efficiency, is suitable for real-time processing scenarios, adapts to spatially uneven noise distribution, and has strong environmental adaptability.

[0008] To achieve the above objectives, the technical solution adopted by this invention is: a segmented vibration positioning method based on vibrating optical fiber, comprising:

[0009] S1. Acquire the fiber optic signal of the vibrating fiber, perform IQ quadrature demodulation after preprocessing, analyze the demodulated signal data, and extract the signal amplitude data.

[0010] S2. Perform two-dimensional rearrangement on the signal amplitude data, and apply windowing in the time dimension to obtain a spatiotemporal two-dimensional data matrix. The spatiotemporal two-dimensional data matrix is ​​subjected to first-order filtering and difference absolute value taking to obtain the two-dimensional data matrix. ;in, To handle the number of time frames per read using windowing, This represents the number of distance points in the space of the vibrating optical fiber;

[0011] S3, Based on the two-dimensional data matrix A sliding window is set in the spatial dimension to obtain the local noise reduction threshold of each spatial dimension window;

[0012] S4. Based on the local noise reduction threshold of each spatial dimension window, perform threshold judgment on the data of the two-dimensional data matrix of each spatial dimension window. If the data in the two-dimensional data matrix is ​​greater than the local noise reduction threshold, it is retained; otherwise, the data in the two-dimensional data matrix is ​​set to zero to obtain the noise-reduced data matrix.

[0013] S5. Perform incoherent accumulation and median filtering on the denoised data matrix to obtain a one-dimensional array; calibrate the fiber optic defense zone type according to the one-dimensional array; calculate the dynamic early warning threshold using sliding background estimation according to the fiber optic defense zone type.

[0014] S6. Based on the dynamic early warning threshold, find the peak position in the one-dimensional array to locate the actual vibration position.

[0015] The solution provided by this invention uses dynamic calculation to update the noise reduction threshold and early warning threshold of each segment of the DAS system in real time, effectively reducing the impact of environmental factors such as strong winds and heavy rains, improving the anti-interference capability of the DAS system, and maintaining the alarm sensitivity of the DAS system, enabling reliable location of multi-point disturbances over long distances such as 30km. The solution provided by this invention comprehensively considers various factors such as the current fiber optic installation method and deployment scenario when setting the thresholds for each segment. The thresholds can be updated in real time as data is continuously transmitted, and the calculation method is simple and efficient.

[0016] According to embodiments of the present invention, the present invention can be further optimized, and the optimized technical solution is as follows:

[0017] In one preferred embodiment, step S2, the windowing process in the time dimension, specifically includes: determining the size of the time window based on the light pulse repetition frequency, selecting a fixed number of time frames, and performing two-dimensional rearrangement of the signal amplitude data to obtain a spatiotemporal two-dimensional data matrix. Preferably, the time window size Set to one-tenth of the light pulse repetition frequency.

[0018] In one preferred embodiment, step S2, taking the absolute value of the difference, specifically includes: taking the absolute value of the data matrix after calculating the inter-frame difference to obtain a two-dimensional data matrix. The inter-frame difference refers to performing temporal difference calculations on each point in the vibrating optical fiber to obtain the change in signal amplitude data between two adjacent frames in time. The calculation formula is as follows:

[0019] ;

[0020] in, For the first The point at the th Frame and the The amount of change in the signal amplitude data of the frame. For the first The point at the th Frame signal amplitude data, For the first The point at the th Frame signal amplitude data, ; .

[0021] In one preferred embodiment, in step S3, the formula for calculating the local noise reduction threshold is:

[0022] ;

[0023] in, For the first The local noise reduction threshold of each spatial dimension window; For the first The adjustment coefficients of each spatial dimension window are used to control the local noise reduction threshold. Sensitivity; The length of the sliding window in the spatial dimension; For the first The signal amplitude data of each point in the first frame is used for background noise estimation; The index of the point within the spatial dimension window; .

[0024] The solution provided by this invention effectively suppresses steady-state background noise. The method accurately estimates the local noise level at each spatial location using the first frame (typically a no-event state), filtering out random fluctuations with amplitudes lower than the local noise level, significantly reducing the false alarm rate. The method is computationally efficient; based on the average value of the first frame data, the noise reduction threshold within each spatial dimension window only needs to be calculated once, and the threshold is reused for other frames within the spatial dimension window. Compared to existing adaptive methods that require recalculating the threshold for each frame and other complex noise reduction algorithms, the method provided by this invention is computationally simple, significantly reduces the computational load, and is suitable for real-time processing.

[0025] In one preferred embodiment, in step S5, the calculation formula for the one-dimensional array is:

[0026] ;

[0027] ;

[0028] ;

[0029] in, For the first The local noise reduction threshold of each spatial dimension window For the first The spatial dimension window index of each point This is the data matrix after noise reduction in step S4. The data matrix after noise reduction The one-dimensional array obtained after incoherent accumulation. The length of one side of the median filter window. A one-dimensional array The one-dimensional array obtained after median filtering This indicates the operation of taking the median of a set.

[0030] In one preferred embodiment, in step S6, the formula for calculating the dynamic early warning threshold is:

[0031] ;

[0032] in, For the first The dynamic warning threshold of each spatial dimension window For the first Influence factors of each spatial dimension window For the first The median of the signal in a spatial dimension window. Indicates the background noise level. These are adaptive coefficients; The average noise level, For pure noise samples, Indicates the first Within a spatial dimension window Points Sort in ascending order. This is the minimum warning threshold.

[0033] The solution provided by this invention adapts to spatially uneven noise distribution. Traditional global thresholding schemes cannot handle the inherent noise differences between different segments of the optical fiber, such as different amplitude values ​​for different protection zone types and amplitude attenuation with increasing transmission distance. By segmenting the optical fiber protection zone, a threshold is tailored to each segment interval, using a higher threshold in noisier areas and a lower threshold in quieter areas, thus maintaining sensitivity while suppressing noise.

[0034] The solution provided by this invention uses dynamic calculation to update the noise reduction threshold and early warning threshold of each segment of the DAS system in real time. The threshold setting for each segment comprehensively considers various factors such as the fiber optic installation method and deployment scenario of the current segment, resulting in strong environmental adaptability. After the equipment is installed, there is no need for repeated debugging by on-site testing personnel, saving labor costs and shortening the product delivery cycle.

[0035] In one preferred embodiment, when the fiber optic zone type is buried mode, The value is 1-1.5; when the fiber optic defense zone type is in network-attached mode, The value is 4-6; when the fiber optic zone type is fence mode, It is 2-3.

[0036] In one preferred embodiment, step S5, which involves calibrating the fiber optic defense zone type according to the one-dimensional array, specifically includes: simulating external disturbances to the reserved fiber optic cable at the fiber optic scene boundary, finding the disturbance point in the cumulative curve, and calibrating the fiber optic defense zone type of the vibrating fiber optic cable according to the disturbance point, for segmenting the vibrating fiber optic cable; wherein the cumulative curve is drawn based on the one-dimensional array.

[0037] Based on the same concept, the present invention also provides a segmented vibration positioning system based on vibrating optical fiber, comprising:

[0038] The data acquisition module is used to acquire the fiber optic signal of the vibrating fiber optic cable, perform IQ quadrature demodulation after preprocessing, analyze the demodulated signal data, and extract the signal amplitude data.

[0039] The data processing and dynamic early warning threshold acquisition module is used to perform two-dimensional rearrangement of the signal amplitude data and obtain a spatiotemporal two-dimensional data matrix by windowing in the time dimension. The two-dimensional data matrix is ​​obtained by performing first-order filtering and difference absolute value taking on the spatiotemporal two-dimensional data matrix. ;in, To handle the number of time frames per read using windowing, The number of distance points in the space of the vibrating optical fiber; used to determine the distance based on the two-dimensional data matrix. A sliding window is set in the spatial dimension to obtain the local noise reduction threshold of each spatial dimension window; based on the local noise reduction threshold of each spatial dimension window, a threshold judgment is performed on the data of the two-dimensional data matrix of each spatial dimension window. If the data of the two-dimensional data matrix is ​​greater than the local noise reduction threshold, it is retained; otherwise, the data of the two-dimensional data matrix is ​​set to zero to obtain a noise-reduced data matrix; incoherent accumulation and median filtering are performed on the noise-reduced data matrix to obtain a one-dimensional array; the one-dimensional array is used to calibrate the fiber optic defense zone type; and a dynamic early warning threshold is calculated using sliding background estimation based on the fiber optic defense zone type.

[0040] The vibration positioning module is used to locate the actual vibration position by finding the peak position in the one-dimensional array based on the dynamic early warning threshold.

[0041] Based on the same concept, the present invention also provides an electronic device, including a memory, a processor, and a computer program / instructions stored in the memory, wherein the processor executes the computer program / instructions to implement the segmented vibration positioning method based on vibrating optical fiber as described above.

[0042] Compared with existing technologies, the beneficial effects of this invention are as follows: This invention provides a segmented vibration positioning method, system, and device based on vibrating optical fibers. The method uses dynamic calculation to update the noise reduction threshold and early warning threshold of each segment of the DAS system in real time, effectively reducing the influence of environmental factors, improving the anti-interference capability of the DAS system, maintaining the alarm sensitivity of the DAS system, and realizing reliable positioning of multi-point disturbances over long distances such as 30km and above. The method comprehensively considers factors such as the current fiber optic installation method and deployment scenario through the threshold setting of each segment. The threshold is updated in real time with data transmission, and the calculation method is simple and efficient. The method effectively suppresses steady-state background noise, is suitable for real-time processing scenarios, and has strong environmental adaptability. Attached Figure Description

[0043] Figure 1 These are schematic diagrams illustrating fiber optic installation methods in different scenarios;

[0044] Figure 2 This is a flowchart of a segmented vibration positioning method based on a vibrating optical fiber according to an embodiment of the present invention;

[0045] Figure 3 This is a schematic diagram of fiber optic scene segmentation according to an embodiment of the present invention;

[0046] Figure 4This is a comparison diagram of vibration positioning effects before and after dynamic threshold noise reduction of long-distance 30km data according to an embodiment of the present invention. Detailed Implementation

[0047] The present invention will now be described in detail with reference to the accompanying drawings and embodiments. It should be noted that, unless otherwise specified, the embodiments and features described herein can be combined with each other.

[0048] Example 1

[0049] like Figure 1 The diagram shows three common fiber optic cable laying methods for different scenarios: a straight-line laying method for fences, a wavy laying method for buried fiber optic cables, and a wavy laying method for isolation nets. At least 20 meters of fiber optic cable should be reserved at the boundary between each scenario. Since there are significant differences in environmental noise and the ability to sense external vibrations among the three methods, using a single global threshold for the entire fiber optic cable is insufficient to meet actual detection needs. Therefore, different warning thresholds should be used for different sections based on the defense zone.

[0050] This invention provides a method for rapid, accurate, high signal-to-noise ratio, threshold-adaptive vibration localization based on signal amplitude data. For example... Figure 2 As shown, the specific implementation steps are as follows:

[0051] S1. Acquire the fiber optic signal of the vibrating fiber, perform IQ quadrature demodulation after preprocessing, analyze the demodulated signal data, and extract the signal amplitude data.

[0052] S2. Perform two-dimensional rearrangement on the signal amplitude data, and apply windowing in the time dimension to obtain a spatiotemporal two-dimensional data matrix. The spatiotemporal two-dimensional data matrix is ​​subjected to first-order filtering and difference absolute value taking to obtain the two-dimensional data matrix. ;in, To handle the number of time frames per read using windowing, This represents the number of distance points in the space of the vibrating optical fiber;

[0053] In the time dimension, based on the optical pulse repetition frequency of the DAS system By determining the time window size and selecting a fixed number of time frames, the signal amplitude data is rearranged in two dimensions to obtain a spatiotemporal two-dimensional data matrix. In this embodiment 1, the time window size... Set as light pulse repetition frequency One-tenth of the original. Taking the absolute value of the data matrix after inter-frame differencing yields a two-dimensional data matrix. Inter-frame differential calculation refers to performing temporal differential calculations on each point in the entire vibrating optical fiber to obtain the change in signal amplitude data between two adjacent frames at that point in time. The calculation formula is as follows:

[0054] ;

[0055] in, For the first The point at the th Frame and the The change in the signal amplitude data of the frame can be positive or negative. In this embodiment 1, the absolute value is processed on the differential data matrix. For the first The point at the th Frame signal amplitude data, For the first The point at the th Frame signal amplitude data, ; .

[0056] S3, Based on the two-dimensional data matrix A sliding window is set in the spatial dimension to obtain the local noise reduction threshold of each window;

[0057] The formula for calculating the local noise reduction threshold is:

[0058] ;

[0059] in, For the first The local noise reduction threshold of each spatial dimension window; For the first The adjustment coefficients of each spatial dimension window are used to control the local noise reduction threshold. The sensitivity, in high-noise environments such as extreme environments and severe weather, The larger the value, the more obvious the noise reduction effect; however, it shouldn't be too large, otherwise the vibration signal will also be filtered out. In practical applications, generally... Take 3-10; The length of the sliding window in the spatial dimension; For the first The signal amplitude data of each point in the first frame is used for background noise estimation; The index of the point within the spatial dimension window; .

[0060] S4. Based on the local noise reduction threshold of each spatial dimension window, process the two-dimensional data matrix of each spatial dimension window. Threshold judgment is performed on the data in the two-dimensional data matrix. If the data in the matrix is ​​greater than the local noise reduction threshold, it is retained; otherwise, the data in the two-dimensional data matrix is ​​set to zero to obtain the noise-reduced data matrix.

[0061] The expression for the denoised data matrix is: ;

[0062] in, For the first The local noise reduction threshold of each spatial dimension window; For the first The spatial dimension window index of each point; in the actual environment, the amplitude difference between frames caused by human intrusion and environmental noise is significantly different in data size. By setting a local noise reduction threshold, the amplitude change caused by environmental noise can be filtered out to a certain extent, and only the amplitude difference caused by human intrusion can be retained, thus eliminating background noise and improving the positioning signal-to-noise ratio.

[0063] S5. Perform incoherent accumulation and median filtering on the denoised data matrix to obtain a one-dimensional array; calibrate the fiber optic defense zone type according to the one-dimensional array; calculate the dynamic early warning threshold using sliding background estimation according to the fiber optic defense zone type.

[0064] The formula for calculating a one-dimensional array is:

[0065] ;

[0066] ;

[0067] in, The data matrix after noise reduction After performing incoherent accumulation, the size is obtained as A one-dimensional array, in this embodiment 1, is obtained by processing a matrix. Each spatial point The frame data is obtained by performing integration calculations. The median filter window is the length of one side, and its size is determined by the spatial sampling rate of the DAS system. For example, if the spatial sampling rate of the DAS system is 0.4 and the spatial resolution is 10 meters, it corresponds to 25 spatial points. The value is 12; A one-dimensional array The one-dimensional array obtained after median filtering is then subjected to noise reduction processing through median filtering to eliminate individual persistent noise interference points. This indicates the operation of taking the median of the set. Due to the inherent noise in the DAS system, isolated and random high-response channels will be generated in the spatial dimension, which will manifest as narrow spike signals in the accumulation curve. Median filtering in the distance dimension can effectively suppress this narrow spike noise.

[0068] like Figure 3The diagram shows the segmentation of optical fiber in different scenarios and the sliding window within each segment. After actual deployment, the optical fiber is calibrated for protection zones. External disturbances are simulated at the boundaries of the optical fiber scenarios, such as knocking by on-site personnel. Disturbance points are located in the cumulative curve, and the optical fiber protection zone type of the vibrating optical fiber is calibrated based on these points. This is used to segment and calibrate different scenarios along the entire vibrating optical fiber line. The cumulative curve is drawn based on the one-dimensional array. Combining the calibrated optical fiber protection zone types, the dynamic warning threshold for each spatial dimension window within each segment scenario is calculated using sliding background estimation. The calculation formula is as follows:

[0069] ;

[0070] in, For the first The dynamic warning threshold for each spatial dimension window; For the first The influence factors of each spatial dimension window; when the optical fiber is in buried mode, the DAS system has lower noise, and the detectable vibration signal is also relatively weak, requiring a smaller... To set a lower warning threshold, a higher value should be used to prevent missed alarms; when the fiber optic cable is in network-connected mode, the DAS system experiences high noise and strong vibration signals, requiring a larger value. This is to prevent a large number of false alarms; in addition, when in network mode, The selection of values ​​needs to be adjusted according to different scenarios such as isolation nets and fences. Generally speaking, the isolation net... The value should be greater than that at the fence; in this embodiment 1, when the optical fiber is in buried mode, The value is 1-1.5; under the network connection mode, 4-6; Fence mode, 2-3; For the first The median of the signal (background baseline) for each spatial dimension window; Indicates the background noise level; The adaptive coefficients do not require manual adjustment and are automatically updated based on the statistics of data within the segments, ensuring a stable false alarm rate. In this embodiment 1, the adaptive coefficients... Pure noise samples represented as the 99th percentile With average noise level The ratio; This represents the average noise level. For pure noise samples, This indicates the segmented window. Each signal data point Sort in ascending order; This is the minimum warning threshold, used for lower-limit protection to avoid false judgments caused by excessively low thresholds in extremely quiet environments.

[0071] S6. Based on the dynamic early warning threshold, find the peak position in the one-dimensional array to locate the actual vibration position.

[0072] Based on each dynamic early warning threshold in a one-dimensional array The vibration point can be located by searching for the peak position. If no peak is found, it means there is no vibration information and no alarm is needed; if multiple peaks are found, it means there are multiple vibration locations. Record the position index of each peak and locate the actual vibration location using the position index.

[0073] like Figure 4 The image shows a comparison of vibration localization effects before and after dynamic threshold noise reduction for long-distance 30km data. Figure 4 (a) is a positioning effect diagram before data threshold denoising over a long distance of 30km. It can be seen that before denoising, the cumulative intensity of vibration at the actual vibration point is about 50,000, while the cumulative intensity of noise is also very high. It is difficult to set a suitable warning threshold to distinguish between vibration signals and noise, and the signal-to-noise ratio is not high. Figure 4 (b) is the positioning effect after using dynamic noise reduction threshold. After noise reduction, although the vibration intensity of the actual vibration point is reduced to about 12,000, the noise is also significantly suppressed, and false alarms caused by environmental and system noise are basically eliminated, and the signal-to-noise ratio is effectively improved.

[0074] Example 2

[0075] This embodiment 2 also provides a segmented vibration positioning system based on a vibrating optical fiber, including:

[0076] The data acquisition module is used to acquire the fiber optic signal of the vibrating fiber optic cable, perform IQ quadrature demodulation after preprocessing, analyze the demodulated signal data, and extract the signal amplitude data.

[0077] The data processing and dynamic early warning threshold acquisition module is used to perform two-dimensional rearrangement of the signal amplitude data and obtain a spatiotemporal two-dimensional data matrix by windowing in the time dimension. The two-dimensional data matrix is ​​obtained by performing first-order filtering and difference absolute value taking on the spatiotemporal two-dimensional data matrix. ;in, To handle the number of time frames per read using windowing, The number of distance points in the space of the vibrating optical fiber; used to determine the distance based on the two-dimensional data matrix. A sliding window is set in the spatial dimension to obtain the local noise reduction threshold of each spatial dimension window; based on the local noise reduction threshold of each spatial dimension window, a threshold judgment is performed on the data of the two-dimensional data matrix of each spatial dimension window. If the data of the two-dimensional data matrix is ​​greater than the local noise reduction threshold, it is retained; otherwise, the data of the two-dimensional data matrix is ​​set to zero to obtain a noise-reduced data matrix; incoherent accumulation and median filtering are performed on the noise-reduced data matrix to obtain a one-dimensional array; the one-dimensional array is used to calibrate the fiber optic defense zone type; and a dynamic early warning threshold is calculated using sliding background estimation based on the fiber optic defense zone type.

[0078] The vibration positioning module is used to locate the actual vibration position by finding the peak position in the one-dimensional array based on the dynamic early warning threshold.

[0079] This embodiment 2 also provides an electronic device, which includes: a memory, a processor, and a computer program or instructions stored in the memory. The processor executes the computer program or instructions to implement the segmented vibration positioning method based on vibration optical fiber in embodiment 1.

[0080] Although not shown, the electronic device includes a processor that can perform various appropriate operations and processes based on programs and / or data stored in read-only memory (ROM) or loaded from a storage portion into random access memory (RAM). The processor can be a multi-core processor or may contain multiple processors. In some embodiments, the processor may include a general-purpose main processor and one or more specialized coprocessors, such as a central processing unit, graphics processing unit (GPU), neural network processor (NPU), digital signal processor (DSP), etc. Various programs and data required for device operation are also stored in RAM. The processor, ROM, and RAM are interconnected via a bus. Input / output (I / O) interfaces are also connected to the bus.

[0081] The above embodiments should be understood as being used only to illustrate the present invention more clearly, and not to limit the scope of the present invention. After reading the present invention, any modifications of the present embodiments by those skilled in the art will fall within the scope defined by the appended claims.

Claims

1. A segmented vibration positioning method based on vibrating optical fiber, characterized in that, include: S1. Acquire the fiber optic signal of the vibrating fiber, perform IQ quadrature demodulation after preprocessing, analyze the demodulated signal data, and extract the signal amplitude data. S2. Perform two-dimensional rearrangement on the signal amplitude data, and apply windowing in the time dimension to obtain a spatiotemporal two-dimensional data matrix. ; The two-dimensional spatiotemporal data matrix is ​​subjected to first-order filtering and difference absolute value taking to obtain the two-dimensional data matrix. ;in, To handle the number of time frames per read using windowing, This represents the number of distance points in the space of the vibrating optical fiber; S3, Based on the two-dimensional data matrix A sliding window is set in the spatial dimension to obtain the local noise reduction threshold of each spatial dimension window; S4. Based on the local noise reduction threshold of each spatial dimension window, perform threshold judgment on the data of the two-dimensional data matrix of each spatial dimension window. If the data of the two-dimensional data matrix is ​​greater than the local noise reduction threshold, it is retained; otherwise, the data of the two-dimensional data matrix is ​​set to zero to obtain the noise-reduced data matrix. S5. Perform incoherent accumulation and median filtering on the denoised data matrix to obtain a one-dimensional array; calibrate the fiber optic defense zone type according to the one-dimensional array; calculate the dynamic early warning threshold using sliding background estimation according to the fiber optic defense zone type. S6. Based on the dynamic early warning threshold, find the peak position in the one-dimensional array to locate the actual vibration position.

2. The segmented vibration positioning method based on vibrating optical fiber according to claim 1, characterized in that, In step S2, the windowing process in the time dimension specifically includes: determining the size of the time window based on the light pulse repetition frequency, selecting a fixed number of time frames, and performing two-dimensional rearrangement of the signal amplitude data to obtain a spatiotemporal two-dimensional data matrix. .

3. The segmented vibration positioning method based on vibrating optical fiber according to claim 1, characterized in that, In step S2, taking the absolute value of the difference specifically includes: taking the absolute value of the data matrix after calculating the inter-frame difference to obtain a two-dimensional data matrix. The inter-frame difference refers to performing temporal difference calculations on each point in the vibrating optical fiber to obtain the change in signal amplitude data between two adjacent frames in time. The calculation formula is as follows: ； in, For the first The point at the th Frame and the The amount of change in the signal amplitude data of the frame. For the first The point at the th Frame signal amplitude data, For the first The point at the th Frame signal amplitude data, , .

4. The segmented vibration positioning method based on vibrating optical fiber according to claim 3, characterized in that, In step S3, the formula for calculating the local noise reduction threshold is: ； in, For the first The local noise reduction threshold of each spatial dimension window For the first The adjustment coefficient for each spatial dimension window. The length of the sliding window in the spatial dimension. For the first The signal amplitude data of each point in the first frame, The index of the point within the spatial dimension window. .

5. The segmented vibration positioning method based on vibrating optical fiber according to claim 3, characterized in that, In step S5, the calculation formula for the one-dimensional array is: ； ； ； in, For the first The local noise reduction threshold of each spatial dimension window For the first The spatial dimension window index of each point This is the data matrix after noise reduction in step S4. The data matrix after noise reduction The one-dimensional array obtained after incoherent accumulation. The length of one side of the median filter window. A one-dimensional array The one-dimensional array obtained after median filtering This indicates the operation of taking the median of a set.

6. The segmented vibration positioning method based on vibrating optical fiber according to claim 5, characterized in that, In step S6, the formula for calculating the dynamic early warning threshold is: ； in, For the first The dynamic warning threshold of each spatial dimension window For the first Influence factors of each spatial dimension window For the first The median of the signal in a spatial dimension window. Indicates the background noise level. For adaptive coefficients, The average noise level, For pure noise samples, Indicates the first Within a spatial dimension window Points Sort in ascending order. This is the minimum warning threshold.

7. The segmented vibration positioning method based on vibrating optical fiber according to claim 6, characterized in that, When the fiber optic defense zone type is buried mode The value is 1-1.5; when the fiber optic defense zone type is in network-attached mode, The value is 4-6; when the fiber optic zone type is fence mode, It is 2-3.

8. The segmented vibration positioning method based on vibrating optical fiber according to claim 1, characterized in that, In step S5, the fiber optic defense zone type is calibrated according to the one-dimensional array, specifically including: simulating external disturbances to the reserved fiber optic cable at the fiber optic scene boundary, finding the disturbance point in the cumulative curve, and calibrating the fiber optic defense zone type of the vibrating fiber optic cable according to the disturbance point, which is used to segment the vibrating fiber optic cable; wherein, the cumulative curve is drawn according to the one-dimensional array.

9. A segmented vibration positioning system based on vibrating optical fiber, characterized in that, include: The data acquisition module is used to acquire the fiber optic signal of the vibrating fiber optic cable, perform IQ quadrature demodulation after preprocessing, analyze the demodulated signal data, and extract the signal amplitude data. The data processing and dynamic early warning threshold acquisition module is used to perform two-dimensional rearrangement of the signal amplitude data and obtain a spatiotemporal two-dimensional data matrix by windowing in the time dimension. The two-dimensional data matrix is ​​obtained by performing first-order filtering and difference absolute value taking on the spatiotemporal two-dimensional data matrix. ;in, To handle the number of time frames per read using windowing, The number of distance points in the space of the vibrating optical fiber; used to determine the distance based on the two-dimensional data matrix. A sliding window is set in the spatial dimension to obtain the local noise reduction threshold of each spatial dimension window; based on the local noise reduction threshold of each spatial dimension window, a threshold judgment is performed on the data of the two-dimensional data matrix of each spatial dimension window. If the data of the two-dimensional data matrix is ​​greater than the local noise reduction threshold, it is retained; otherwise, the data of the two-dimensional data matrix is ​​set to zero to obtain a noise-reduced data matrix; incoherent accumulation and median filtering are performed on the noise-reduced data matrix to obtain a one-dimensional array; the one-dimensional array is used to calibrate the fiber optic defense zone type; and a dynamic early warning threshold is calculated using sliding background estimation based on the fiber optic defense zone type. The vibration positioning module is used to locate the actual vibration position by finding the peak position in the one-dimensional array based on the dynamic early warning threshold.

10. An electronic device comprising a memory, a processor, and a computer program / instructions stored in the memory, characterized in that, The processor executes the computer program / instructions to implement the segmented vibration positioning method based on vibrating optical fiber as described in any one of claims 1 to 8.

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