A distributed fiber optic acoustic sensing security early warning system and method

Abstract

This invention belongs to the field of acoustic communication early warning technology. It discloses a distributed fiber optic acoustic sensing security early warning system and method, comprising: acquiring continuous acoustic signals along a distributed optical fiber; segmenting and mapping the distributed optical fiber to construct acoustic monitoring nodes distributed along the line; extracting local acoustic features from the acoustic signals of each monitoring node according to a time window to construct a node disturbance sequence; obtaining the propagation direction, propagation speed, and propagation path node links of the acoustic disturbance by analyzing the changes in the arrival time difference and characteristic intensity index between monitoring nodes; predicting the arrival time prediction interval and disturbance impact path of key security areas; and generating early warning information based on the disturbance impact path and arrival time prediction interval of key security areas. This invention more accurately detects the starting position, main propagation direction, and propagation trajectory along the line of disturbance, improving the spatial positioning accuracy and propagation trend judgment capability of security events.

Description

Technical Field

[0001] This invention relates to the field of acoustic communication early warning technology, and more specifically, to a distributed optical fiber acoustic sensing security early warning system and method. Background Technology

[0002] Distributed fiber optic acoustic sensing technology utilizes optical fibers as continuously distributed sensing carriers. By demodulating weak acoustic vibrations propagating along the fibers, it enables continuous monitoring of perimeters, long-distance pipelines, tunnels, and the areas surrounding important locations. Such systems typically use optical fibers laid near the perimeter of the monitored area as a "virtual sensor array," acquiring a large number of distance-distributed acoustic responses along the same fiber to identify security-related disturbances such as climbing, vandalism, digging, and knocking.

[0003] Existing distributed fiber optic acoustic wave security early warning technologies primarily focus on anomaly identification based on changes in acoustic characteristics within a single monitoring location or local time window. While these technologies can reflect the occurrence of local disturbances, they have limited analysis capabilities regarding the spatiotemporal evolution of acoustic disturbances among multiple monitoring units along the route, including arrival order, propagation direction, and propagation speed. This makes it difficult to utilize disturbance information from upstream or peripheral areas in a timely manner to proactively assess the potential impact on critical security areas and evaluate their paths. Especially in scenarios with complex boundaries and diverse paths, there is a lack of a comprehensive mechanism based on the topological relationships of monitoring nodes and the time difference of disturbance arrival to construct node links along the disturbance propagation path and predict the arrival time interval and impact path of disturbances for critical security areas. Therefore, it is necessary to propose a distributed fiber optic acoustic wave sensing security early warning method. This method estimates the propagation direction, propagation speed, and propagation path of acoustic disturbances by combining the arrival time and characteristic intensity of disturbances from multiple nodes, predicts the time window and impact path of disturbances reaching critical security areas, and thus achieves joint temporal and spatial early warning and proactive protection for critical areas. Summary of the Invention

[0004] To overcome the aforementioned deficiencies of the prior art and to achieve the above objectives, the present invention provides the following technical solution: a distributed fiber optic acoustic wave sensing security early warning method, comprising:

[0005] A distributed optical fiber is laid around the protected target within the monitored area to acquire continuous acoustic signals along the distributed optical fiber.

[0006] The distributed optical fiber is segmented and mapped to different regions to construct acoustic monitoring nodes distributed along the fiber.

[0007] Local acoustic features are extracted from the acoustic signals of each monitoring node according to a time window, the arrival time and feature intensity of disturbances at each monitoring node within the time window are identified, and a node disturbance sequence is constructed.

[0008] Based on the disturbance candidate sequences of different monitoring nodes, the propagation direction, propagation speed and propagation path node links of the acoustic disturbance are obtained by analyzing the changes in the time difference of arrival of the disturbance and the characteristic intensity index between the monitoring nodes.

[0009] By analyzing the propagation changes between adjacent monitoring nodes in the propagation path node link, the arrival time prediction interval and disturbance impact path of key security areas can be predicted.

[0010] Early warning information is generated based on the disturbance impact path and arrival time prediction interval of the key security area.

[0011] Preferably, the segmentation and region mapping processing of the distributed optical fiber includes:

[0012] Based on the fiber length information and the spatial distribution of the protected targets, the fiber is divided into multiple continuous monitoring segments, and different segment length configuration strategies are set for different functional areas to obtain a set of monitoring segments covering the entire line.

[0013] Obtain the spatial coordinates of each monitoring section, generate corresponding monitoring nodes, and establish a mapping relationship between the monitoring nodes and the actual security area;

[0014] The topological relationship between each monitoring node and its adjacent upstream and downstream monitoring nodes is marked according to the mapping relationship, the fiber optic route and connection order are recorded, and the monitoring node topology structure is constructed.

[0015] Preferably, the method for identifying the arrival time and feature intensity of disturbances at each monitoring node within a time window includes:

[0016] The fiber optic acoustic signal is divided into sliding windows, and three local characteristic parameters, namely acoustic energy, envelope rate of change and power ratio in the frequency band, are calculated in each time window.

[0017] The three feature parameters of each time window are concatenated and encoded into a feature vector; the feature vectors of different time windows are concatenated in chronological order of the time windows to generate a local feature time series of the monitoring segment.

[0018] Identify the arrival time of perturbation feature segments on the time axis;

[0019] By integrating disturbance feature segments within the same time window from monitoring nodes, the maximum acoustic energy, average envelope change rate, and average power ratio within the frequency band are calculated to obtain three characteristic intensity indices.

[0020] The disturbance data of each monitoring node are combined in chronological order to obtain the node disturbance sequence;

[0021] The propagation speed range is calculated based on the spatiotemporal relationship between monitoring nodes and the time difference of disturbance arrival.

[0022] Preferably, the method for calculating the propagation speed range includes:

[0023] Scan the node perturbation sequence to identify spatiotemporally adjacent monitoring nodes, and record them as neighboring nodes;

[0024] Calculate the time difference of arrival of the disturbance based on the arrival times of the disturbances at two neighboring nodes;

[0025] Based on the time difference of arrival and the spatial coordinates between the monitoring nodes, the propagation speed range of acoustic disturbances between two neighboring nodes is calculated.

[0026] Preferably, the method for calculating the propagation direction, propagation speed, and propagation path node links includes:

[0027] The monitoring nodes are sorted according to the arrival time of the disturbance to generate an arrival order list;

[0028] The earliest arrival time of the disturbance is retrieved from the arrival order list, and the corresponding monitoring node is marked as the initial node of the disturbance.

[0029] Based on the spatial coordinate differences between the initial disturbance node and subsequent monitoring nodes and the corresponding arrival time differences, the propagation velocity components of the disturbance in different directions are calculated; the propagation velocity components include the velocity along the fiber direction and the lateral velocity.

[0030] The fiber optic directional speed and lateral speed of multiple monitoring nodes in the arrival sequence list are statistically analyzed, and the ratio of the median fiber optic directional speed to the vertical speed is calculated to obtain the speed ratio.

[0031] When the velocity ratio is greater than the preset ratio threshold, the direction along the fiber optic cable is determined to be the main disturbance propagation direction.

[0032] The monitoring nodes along the direction of disturbance propagation are connected in series according to their arrival time to construct the propagation path node link of the acoustic disturbance.

[0033] Preferably, the method for predicting the arrival time interval of acoustic disturbances to critical security areas includes:

[0034] Identify key security areas, obtain the monitoring nodes corresponding to the key security areas, and record them as key nodes;

[0035] Obtain the adjacent upstream monitoring nodes of the key node in the monitoring node topology, and denote them as the target upstream node;

[0036] The monitoring node upstream of the target is searched in the propagation path node link and denoted as the precursor node;

[0037] Based on the arrival time, spatial coordinates, and main propagation direction of the disturbance at each monitoring node, and combined with the propagation speed, the shortest and longest time for the acoustic disturbance to propagate from the precursor node to the critical node are calculated, and the arrival time prediction interval is determined.

[0038] Preferably, the method for determining the arrival time prediction interval includes:

[0039] Calculate the fiber optic distance coordinates based on the spatial coordinates of the precursor node and the critical node respectively; mark the fiber optic distance coordinates corresponding to the critical node as the critical distance coordinates;

[0040] Compare the fiber-optic distance coordinates of different precursor nodes in the direction of disturbance propagation to determine whether the fiber-optic distance coordinates have increased.

[0041] As the distance coordinate along the fiber increases, retain the precursor nodes whose distance coordinate along the fiber is less than the critical distance coordinate.

[0042] When the distance coordinate along the fiber decreases, retain the precursor nodes whose distance coordinate along the fiber is less than the critical distance coordinate;

[0043] The difference between the fiber optic distance coordinates and the critical distance coordinates of each precursor node is calculated to obtain the propagation distance along the fiber optic path for the precursor node.

[0044] The propagation speed is obtained from the propagation speed range, and the arrival time prediction range is calculated by combining the propagation distance along the route.

[0045] Preferably, the method for calculating the arrival time prediction interval by combining the propagation distance along the route includes:

[0046] The lower limit of the propagation speed range is taken as the minimum propagation speed, and the upper limit is taken as the maximum propagation speed;

[0047] The longest and shortest arrival times are obtained by calculating the ratios of the propagation distance along the route to the minimum and maximum propagation speeds, respectively.

[0048] For several precursor nodes of the same critical node, the shortest arrival time and the longest arrival time corresponding to each precursor node are jointly statistically analyzed.

[0049] The minimum shortest arrival time and the maximum longest arrival time are taken as the overall shortest arrival time and the overall longest arrival time for the critical security area, respectively.

[0050] The overall shortest arrival time and the overall longest arrival time are superimposed with the disturbance arrival time of the precursor node to obtain the overall shortest arrival time and the overall longest arrival time, respectively.

[0051] The arrival time prediction interval is determined based on the overall shortest arrival time and the overall longest arrival time.

[0052] Preferably, the method for predicting the disturbance impact path of acoustic disturbances reaching critical security areas includes:

[0053] The precursor nodes distributed along the direction of disturbance propagation are taken as the starting point of the path, and the search is carried out in the direction of disturbance propagation according to the topology of the monitoring nodes;

[0054] The adjacent downstream monitoring nodes of the precursor node are searched sequentially to obtain candidate downstream nodes;

[0055] Calculate the fiber optic distance difference between each precursor node and its corresponding candidate downstream node;

[0056] The desired velocity is obtained by weighting the propagation velocity range between the precursor node and the candidate downstream node.

[0057] The predicted arrival time of disturbances at candidate downstream nodes is calculated based on the arrival time of disturbances at the precursor node, the fiber distance difference between the precursor node and the candidate downstream node, and the expected speed.

[0058] Monitor the actual arrival time of disturbances at candidate downstream nodes and calculate the time deviation between the actual arrival time and the predicted arrival time of disturbances.

[0059] Candidate downstream nodes and their corresponding gigabit nodes with time deviations less than a preset error threshold are marked as candidate path nodes;

[0060] Monitor and construct the actual feature strength index vector of candidate path nodes, and construct the expected feature strength index vector based on the output of the perturbation impact model;

[0061] Calculate the cosine similarity between the actual feature strength index vector and the expected feature strength index vector, and retain candidate path nodes whose cosine similarity is less than a preset similarity threshold.

[0062] Based on the monitoring nodes between each precursor node and the critical node, establish candidate impact paths corresponding to the precursor nodes;

[0063] Identify consecutive candidate path nodes in the candidate impact path, calculate the number of candidate path nodes, and obtain the effective path length;

[0064] By comparing the effective path lengths of different candidate impact paths, the candidate impact path corresponding to the maximum effective path length is marked as the disturbance impact path.

[0065] This invention also provides a distributed fiber optic acoustic wave sensing security early warning system, applied to the aforementioned distributed fiber optic acoustic wave sensing security early warning method, comprising:

[0066] The fiber optic signal acquisition module lays distributed optical fibers around the protected target within the monitored area to acquire continuous acoustic signals along the distributed optical fibers.

[0067] The region mapping processing module performs segmentation and region mapping processing on the distributed optical fiber to construct acoustic monitoring nodes distributed along the line.

[0068] The node feature extraction module extracts local acoustic features from the acoustic signal of each monitoring node according to a time window, identifies the arrival time and feature intensity of disturbances at each monitoring node within the time window, and constructs a node disturbance sequence.

[0069] The node link construction module, based on the disturbance candidate sequences of different monitoring nodes, obtains the propagation direction, propagation speed, and propagation path node links of acoustic disturbances by analyzing the changes in the disturbance arrival time difference and characteristic intensity index between monitoring nodes.

[0070] The prediction and disturbance path analysis module predicts the arrival time prediction interval and disturbance impact path of key security areas by analyzing the propagation changes between adjacent monitoring nodes in the propagation path node link.

[0071] The security early warning module generates early warning information based on the disturbance impact path and arrival time prediction interval of the key security area.

[0072] The technical effects and advantages of the distributed fiber optic acoustic sensing security early warning system and method of the present invention are as follows:

[0073] (1) By segmenting and mapping the distributed optical fiber into regions, an acoustic monitoring node with upstream and downstream topological relationships is constructed, and the arrival time and characteristic intensity of disturbances are extracted on each monitoring node to generate a node disturbance sequence. Based on this, the propagation speed range between adjacent nodes is calculated by combining the spatial coordinates between monitoring nodes and the time difference of arrival of disturbances. Then, the initial node of the disturbance is identified according to the arrival order list, and the propagation speed components along the optical fiber direction and the transverse direction are decomposed. The main propagation direction is then determined and the propagation path node link is constructed. By introducing acoustic energy transmission and attenuation balance constraints that conform to physical propagation characteristics between adjacent optical fiber segments, the starting position, main propagation direction and propagation trajectory along the line of disturbances are more accurately discovered, thereby improving the spatial positioning accuracy and propagation trend judgment ability of security events.

[0074] (2) Based on the construction of the propagation path node link, the monitoring nodes corresponding to the key security area are marked as key nodes, and the adjacent upstream monitoring nodes are identified as precursor nodes according to the topology of the monitoring nodes. Then, the shortest and longest arrival times of the whole are jointly calculated by the difference in fiber distance and propagation speed between the precursor nodes and the key nodes to obtain the arrival time prediction interval of the key area. Furthermore, candidate downstream nodes are searched along the direction of disturbance propagation. By time deviation verification and characteristic intensity index vector matching, candidate path nodes that are consistent with the characteristics of sound wave propagation in terms of arrival order, propagation distance and intensity attenuation are selected to form several candidate impact paths and select the path with the largest effective path length as the disturbance impact path. It can give a warning result with time advance before the disturbance reaches the key security area and clarify the spatial path and range that the disturbance may affect, which is conducive to realizing time-space joint early warning and active protection of the key area. Attached Figure Description

[0075] Figure 1 This is a schematic diagram of the process flow of a distributed optical fiber acoustic wave sensing security early warning system and method according to the present invention.

[0076] Figure 2 This is a schematic diagram of the method for calculating the propagation speed range in a distributed optical fiber acoustic wave sensing security early warning system and method of the present invention.

[0077] Figure 3 This is a schematic diagram of the method for calculating the propagation direction, propagation speed, and propagation path node links in a distributed optical fiber acoustic wave sensing security early warning system and method of the present invention.

[0078] Figure 4 This is a schematic diagram of the method for determining the arrival time prediction interval in a distributed optical fiber acoustic wave sensing security early warning system and method of the present invention.

[0079] Figure 5 This is a schematic diagram of the method for calculating the arrival time prediction interval by combining the propagation distance along the line in a distributed optical fiber acoustic wave sensing security early warning system and method of the present invention.

[0080] Figure 6-1 This is a flowchart illustrating the method for predicting the impact path of acoustic disturbances reaching critical security areas in a distributed fiber optic acoustic wave sensing security early warning system and method according to the present invention. Figure 1 .

[0081] Figure 6-2 This is a flowchart illustrating the method for predicting the impact path of acoustic disturbances reaching critical security areas in a distributed fiber optic acoustic wave sensing security early warning system and method according to the present invention. Figure 2 . Detailed Implementation

[0082] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0083] This application provides a distributed fiber optic acoustic wave sensing security early warning system and method. It acquires continuous acoustic wave signals along a distributed optical fiber; constructs acoustic monitoring nodes distributed along the fiber; extracts local acoustic features from the acoustic wave signals of each monitoring node according to a time window, constructing a node disturbance sequence; and obtains the propagation direction, propagation speed, and propagation path node links of the acoustic wave disturbance by analyzing the changes in the time difference of arrival of disturbances and characteristic intensity indices between monitoring nodes. It also predicts the arrival time prediction interval and the disturbance impact path for key security areas. This invention can more accurately detect the starting position, main propagation direction, and propagation trajectory along the fiber, improving the spatial positioning accuracy and propagation trend judgment capability of security events.

[0084] Example 1, please refer to Figures 1 to 5 , Figure 6-1 and Figure 6-2 In Embodiment 1 of the present invention, a distributed fiber optic acoustic wave sensing security early warning method is implemented in detail through the following steps: including:

[0085] Distributed optical fibers are laid around the protected target within the monitored area to acquire continuous acoustic signals along the distributed fibers. The distributed fibers are single-mode or multimode fibers continuously laid along the monitored object, using the entire fiber as a continuous sensing medium. Instead of simply placing point sensors at discrete locations, spatial resolution demodulation of the backscattered light signal in the fiber creates multiple equivalent sensing units divided by distance along the fiber's length. This allows each fiber segment to reflect vibration, temperature, or stress changes in its vicinity, enabling distributed sensing of long-distance monitored areas. The acoustic signals are acoustic disturbances generated when mechanical vibrations from the monitored object (such as boundaries, ground, or pipes) propagate through the medium. These acoustic disturbances, through contact with the distributed fibers, cause minute changes in the fiber... Deformation alters the phase, intensity, or polarization state of light waves within the optical fiber. Distributed fiber optic acoustic sensing systems demodulate these time-varying optical quantities, restoring them to equivalent acoustic signals that vary with time and spatial location. These signals are used to characterize security events such as intrusion, knocking, and digging. The distributed optical fiber connects to a distributed fiber optic acoustic sensing host, which injects modulated probe light into the fiber and periodically receives backscattered light signals generated within it. The host acquires and demodulates the amplitude and phase of the backscattered light, reconstructing the sampled data according to distance coordinates based on the light's propagation speed within the fiber. This yields a time-varying optical response sequence along each monitoring segment of the fiber, providing input data for subsequent disturbance identification, propagation trajectory analysis, and security early warning.

[0086] Segmentation and regional mapping of distributed optical fibers are performed to construct acoustic monitoring nodes distributed along the fiber optic line;

[0087] Segmentation and region mapping of distributed optical fibers include:

[0088] Based on the fiber optic length information and the spatial distribution of the protected targets, the fiber optic cable is divided into multiple continuous monitoring segments, and different segment length configuration strategies are set for different functional areas to obtain a set of monitoring segments covering the entire line. Among them, the spatial distribution of the protected targets is used to represent the planar position, extension range, and distance relationship between the protected targets such as the perimeter section, entrances and exits, and areas around key equipment within the monitored area. This can be obtained through the construction master plan, building layout plan, or line segments, areas, and points marked in the geographic information system. The set of monitoring segments serves as the spatial carrier for subsequent acoustic monitoring nodes. The segment length configuration strategy includes using shorter segments at corner positions, near entrances and exits, and around key areas, and longer segments in areas with relatively uniform environments, so as to enhance local positioning accuracy and disturbance identification sensitivity while ensuring the continuity of monitoring coverage.

[0089] The spatial coordinates of each monitoring segment are obtained, corresponding monitoring nodes are generated, and a mapping relationship is established between the monitoring nodes and the actual security area. The spatial coordinates are used to give the coordinate values ​​of the reference point or representative line segment of the monitoring segment in a unified coordinate system in numerical form. They can be planar coordinates or three-dimensional coordinates, which facilitates the calculation of the spatial distance and relative orientation between monitoring segments. The mapping relationship can be established by creating an index data and storing the spatial coordinates of the monitoring nodes and the number of the actual security area.

[0090] The topological relationship between each monitoring node and its adjacent upstream and downstream monitoring nodes is marked according to the mapping relationship. The fiber optic routing and connection sequence are recorded to construct the monitoring node topology. The upstream and downstream monitoring sections are determined according to the fiber optic laying direction. The monitoring node topology is used to calculate the propagation direction, propagation path and impact range of acoustic disturbances along the fiber optic cable.

[0091] Local acoustic features are extracted from the acoustic signals of each monitoring node according to the time window, the arrival time and feature intensity of disturbances at each monitoring node within the time window are identified, and a node disturbance sequence is constructed.

[0092] Methods for identifying the arrival time and characteristic intensity of disturbances at each monitoring node within a time window include:

[0093] The fiber optic acoustic signal is segmented into sliding windows, and three local characteristic parameters—acoustic energy, envelope rate of change, and power ratio within the frequency band—are calculated within each time window. The time window length and overlap ratio of the sliding window are configured based on the typical disturbance duration of the monitored target. The typical disturbance duration is obtained by collecting multiple representative security disturbance samples during system debugging or initial operation, statistically analyzing the time interval from the obvious start to the obvious end of each disturbance, and then performing frequency statistics or distribution analysis on the sample set to select the duration interval covering a preset proportion of historical disturbance events as the typical disturbance duration. The acoustic energy is obtained by squaring and summing the amplitudes of each sampling point within the time window, and is used to characterize the total acoustic disturbance within that time window. Volume strength; envelope change rate is obtained by smoothing the envelope curve after taking the absolute value of the acoustic signal within the time window, then calculating the difference between the mean envelope values ​​of adjacent time windows, and then calculating the ratio of the difference between the mean envelope values ​​to the time interval of the time window movement. This is used to characterize the speed and impact of the signal strength change; smoothing filtering is implemented using existing digital signal processing library functions such as the moving average filtering function moving() in MATLAB; frequency domain analysis of power ratio within the frequency band can be performed by performing a fast Fourier transform on the acoustic signal within the time window to obtain the power spectral density and integrating it in the target frequency band to obtain the power within the frequency band. This is used to distinguish the spectral characteristics of different types of sound sources; the fast Fourier transform can be implemented using existing digital signal processing algorithms such as the FFT function in MATLAB;

[0094] The three feature parameters of each time window are concatenated and encoded into a feature vector; the feature vectors of different time windows are concatenated in chronological order of the time windows to generate a local feature time series of the monitoring segment.

[0095] Based on local feature time series, segments with different feature parameter change rates exceeding preset change amplitude thresholds are identified and recorded as disturbance feature segments. A sudden increase in feature change is defined as an increase in acoustic energy, envelope change rate, or power ratio within the current time window relative to the mean of background features calculated from several preceding time window features exceeding the preset change amplitude threshold with a positive slope. A sudden decrease in feature change is defined as a decrease in the aforementioned features relative to the mean of background features exceeding the preset change amplitude threshold with a negative slope. By statistically analyzing the probability density of historical feature parameter change rates, the probabilities of the top three feature parameter change rate intervals are normalized to obtain the weights of the feature parameter change rate intervals. The median of the top three feature parameter change rate intervals is then weighted according to these weights, and the result is used as the preset change amplitude threshold. The duration is obtained by statistically analyzing the number of consecutive time windows in a sudden increase or decrease state and multiplying it by the time window length. This duration is used to eliminate short-term random disturbance segments with durations less than a preset lower limit and no security significance, retaining only disturbance feature segments with a certain duration.

[0096] Identify the arrival time of perturbation feature segments on the time axis;

[0097] By integrating disturbance feature segments within the same time window from monitoring nodes, the maximum acoustic energy, average envelope change rate, and average power ratio within the frequency band are calculated to obtain three feature intensity indices. Among them, the feature intensity indices are used to distinguish different disturbance events when subsequently associating multiple nodes.

[0098] The disturbance data of the monitoring node is obtained based on the disturbance arrival time, duration, and feature intensity index of each disturbance feature segment; where the disturbance arrival time refers to the moment corresponding to the start time position of the disturbance feature segment.

[0099] The disturbance data of each monitoring node are combined in chronological order to obtain the node disturbance sequence;

[0100] The propagation speed range is calculated based on the spatiotemporal relationship between monitoring nodes and the time difference of disturbance arrival.

[0101] Based on the disturbance candidate sequences of different monitoring nodes, the propagation direction, propagation speed and propagation path node links of the acoustic disturbance are obtained by analyzing the changes in the time difference of arrival of the disturbance and the characteristic intensity index between the monitoring nodes.

[0102] Methods for calculating the propagation speed range include:

[0103] The node disturbance sequence is scanned to identify monitoring nodes that are spatially and temporally close, and these nodes are recorded as neighboring nodes. The criteria for temporal proximity are based on the time difference between the arrival times of the disturbances, and the criteria for spatial proximity are based on the upstream and downstream relationships in the topology of the monitoring nodes, thereby limiting the spatial continuity of the candidate set. The acoustic disturbance dataset is used to initially determine multi-node combinations that may belong to the same acoustic disturbance.

[0104] The arrival time difference of the disturbance is calculated based on the arrival time of the disturbances at two neighboring nodes; the arrival time difference is used to calculate the propagation speed and to help identify the direction of disturbance propagation.

[0105] Based on the time difference of arrival and the spatial coordinates between monitoring nodes, the propagation speed range of acoustic disturbances between two adjacent nodes is calculated. The spatial distance between monitoring nodes is calculated using spatial coordinates and the topology of the monitoring nodes. When the monitoring segment is represented by one-dimensional distance coordinates along the fiber optic cable laying direction, the propagation path length between any two monitoring nodes along the fiber optic cable can be obtained by summing the absolute values ​​of the differences in distance coordinates between adjacent monitoring nodes. When monitoring nodes are represented by planar or three-dimensional coordinates and the fiber optic path is a polygonal line segment, the path length along the fiber optic cable can be obtained by summing the lengths of each polygonal line segment according to the connection order of adjacent monitoring nodes in the topology. The path length is used as the spatial distance between monitoring nodes, and divided by the corresponding time difference of arrival of the disturbance to obtain the estimated propagation speed of that node pair. The above calculation is repeated for all node pairs that satisfy the spatial adjacency relationship within the same acoustic disturbance dataset to form a set of propagation speed estimates. Statistical analysis is then performed on the propagation speed estimate set. By removing extreme values ​​outside the preset percentile, the minimum and maximum values ​​of the remaining samples are calculated to determine the propagation speed range of the acoustic event between different monitoring nodes.

[0106] Methods for calculating propagation direction, propagation speed, and propagation path nodes include:

[0107] The monitoring nodes are sorted according to the arrival time of the disturbance to generate an arrival order list; the arrival order list is used to characterize the propagation process of the acoustic disturbance in the distributed monitoring node array.

[0108] The earliest arrival time of the disturbance is retrieved from the arrival order list, and the corresponding monitoring node is marked as the initial disturbance node; where the initial disturbance node is used to indicate the position where the acoustic disturbance is first captured by the distributed fiber acoustic node array.

[0109] Based on the spatial coordinate differences between the initial disturbance node and subsequent monitoring nodes and the corresponding arrival time differences, the propagation velocity components of the disturbance in different directions are calculated. The propagation velocity components include the velocity along the fiber direction and the lateral velocity. Among them, the fiber direction velocity refers to the propagation velocity component along the fiber direction; the lateral velocity refers to the direction deviating from the fiber direction.

[0110] The fiber optic directional speed and lateral speed of multiple monitoring nodes in the arrival sequence list are statistically analyzed, and the ratio of the median fiber optic directional speed to the vertical speed is calculated to obtain the speed ratio.

[0111] When the velocity ratio exceeds a preset threshold, the direction along the fiber optic cable is determined to be the primary disturbance propagation direction. Specifically, the fiber optic path of each monitoring node is obtained in a unified coordinate system of the monitored area by querying the monitoring node topology. The fiber optic path is then approximated at a local location as a fiber optic path vector with a unit direction vector. For any pair of monitoring nodes with a disturbance arrival time difference, the displacement vector is calculated using the difference in the spatial coordinates of the two nodes, and the displacement vector is projected onto the fiber optic path vector to obtain the displacement component along the fiber optic cable. The displacement vector is then subtracted from the displacement component corresponding to the projection along the fiber optic cable. The displacement component is used to obtain the lateral displacement component perpendicular to the fiber optic cable's direction. The absolute values ​​of the fiber optic cable's direction velocity and the lateral displacement component are obtained by dividing the modulus of the displacement component along the fiber optic cable's direction and the modulus of the lateral displacement component by the time difference of the disturbance arrival. The fiber optic cable's direction velocity and the lateral displacement velocity of multiple monitoring nodes within the same acoustic disturbance are statistically analyzed, and the ratio of the median of the fiber optic cable's direction velocity and the perpendicular direction velocity is calculated to obtain the velocity ratio. When the velocity ratio is greater than a preset ratio threshold, it is determined that the acoustic disturbance mainly propagates along the fiber optic cable's laying direction. The preset ratio threshold is configured based on the typical propagation characteristics of acoustic waves in the medium near the fiber optic cable and the site layout.

[0112] The monitoring nodes along the direction of disturbance propagation are connected in series according to their arrival time to construct the propagation path node link of the acoustic disturbance.

[0113] To address the shortcomings of existing distributed fiber optic acoustic security monitoring systems, which primarily focus on acoustic characteristics within local time windows and lack sufficient analysis of the propagation direction, speed, and overall evolution of disturbances between adjacent segments, this invention constructs acoustic monitoring nodes with upstream and downstream topological relationships by segmenting and mapping distributed optical fibers. Disturbance arrival time and characteristic intensity are extracted from each monitoring node to generate a node disturbance sequence. Based on this, the propagation speed range between adjacent nodes is calculated by combining the spatial coordinates between monitoring nodes and the time difference of disturbance arrival. Then, the initial disturbance node is identified according to the arrival order list, and the propagation speed components along the fiber direction and lateral direction are decomposed to determine the main propagation direction and construct the propagation path node link. Through these steps, this embodiment introduces a sound energy transmission and attenuation balance constraint that conforms to physical propagation characteristics between adjacent fiber optic segments, more accurately detecting the starting position, main propagation direction, and propagation trajectory along the line of the disturbance, thereby improving the spatial positioning accuracy and propagation trend judgment capability of security events.

[0114] Calculate the propagation distance between each monitoring node in the propagation path link and the initial node of the disturbance, and denot it as the disturbance propagation distance;

[0115] A disturbance impact model is constructed by fitting the equivalent propagation distance attenuation relationship of the monitoring node's characteristic intensity index and the disturbance propagation distance. The equivalent propagation distance attenuation relationship fitting uses the characteristic intensity index of multiple monitoring nodes and the disturbance propagation distance as samples, and adopts a piecewise fitting method to obtain a functional relationship in which the disturbance characteristic intensity index decreases monotonically with the increase of the disturbance propagation distance, so as to reflect the influence of the field medium and the deployment environment on the sound wave attenuation characteristics.

[0116] By analyzing the propagation changes between adjacent monitoring nodes in the propagation path link, the arrival time prediction interval and disturbance impact path of key security areas can be predicted.

[0117] Methods for predicting the arrival time interval of acoustic disturbances to critical security areas include:

[0118] Identify key security areas, obtain the monitoring nodes corresponding to the key security areas, and record them as key nodes;

[0119] The adjacent upstream monitoring nodes of the key node in the monitoring node topology are obtained and denoted as the target upstream node; among them, the key security area includes the key section of the perimeter, the area around important equipment, and the personnel access control area;

[0120] The monitoring node upstream of the target is searched in the propagation path node link and denoted as the precursor node;

[0121] Based on the arrival time, spatial coordinates, and main propagation direction of the disturbance at each monitoring node, and combined with the propagation speed, the shortest and longest time for the acoustic disturbance to propagate from the precursor node to the critical node are calculated, and the arrival time prediction interval is determined. The arrival time prediction interval is used to describe the time range in which the acoustic disturbance may affect the critical node. The lower limit corresponds to the earliest arrival time, and the upper limit corresponds to the latest arrival time before a significant acoustic response can still be generated before attenuation.

[0122] Methods for determining the arrival time prediction interval include:

[0123] Calculate the fiber optic distance coordinates based on the spatial coordinates of the precursor node and the critical node respectively; mark the fiber optic distance coordinates corresponding to the critical node as the critical distance coordinates; where the fiber optic distance coordinates represent a one-dimensional coordinate of "how many meters along the fiber".

[0124] Compare the fiber-optic distance coordinates of different precursor nodes in the direction of disturbance propagation to determine whether the fiber-optic distance coordinates have increased.

[0125] As the distance coordinate along the fiber optic cable increases, precursor nodes whose distance coordinate along the fiber optic cable is less than the critical distance coordinate are retained; whereby, an outer precursor node indicates that the precursor node is located outside the critical security area.

[0126] When the distance coordinate along the fiber decreases, retain the precursor nodes whose distance coordinate along the fiber is less than the critical distance coordinate;

[0127] The difference between the fiber optic distance coordinates and the critical distance coordinates for each precursor node is calculated to obtain the fiber optic propagation distance of the precursor node; whereby the fiber optic propagation distance represents the propagation of acoustic disturbances from each precursor node to the critical security area; the fiber optic propagation distance is expressed by the formula: In the formula, The coordinates of the distance along the fiber optic cable from the precursor node; The key distance coordinates of the key nodes; denoted as , where is the propagation distance along the line from the precursor node; i is the precursor node number, and i is a positive integer;

[0128] The propagation speed is obtained based on the propagation speed range, and the arrival time prediction range is calculated by combining the propagation distance along the route; the method includes:

[0129] The lower limit of the propagation speed range is taken as the minimum propagation speed, and the upper limit is taken as the maximum propagation speed;

[0130] The longest and shortest arrival times are obtained by calculating the ratios of the propagation distance along the route to the minimum and maximum propagation speeds, respectively.

[0131] For several precursor nodes of the same critical node, the shortest arrival time and the longest arrival time corresponding to each precursor node are jointly statistically analyzed.

[0132] The minimum shortest arrival time and the maximum longest arrival time are taken as the overall shortest arrival time and the overall longest arrival time for the critical security area, respectively.

[0133] The overall shortest arrival time and the overall longest arrival time are superimposed with the disturbance arrival time of the precursor node to obtain the overall shortest arrival time and the overall longest arrival time, respectively.

[0134] The arrival time prediction interval is determined based on the overall shortest and longest arrival times; the formulas for calculating the shortest and longest arrival times are as follows:

[0135] ; ;

[0136] In the formula, and These are the shortest arrival time and the longest arrival time, respectively. and These are the maximum propagation speed and the minimum propagation speed, respectively. The arrival time of the disturbance at the preceding node;

[0137] Methods for predicting the impact path of acoustic disturbances reaching critical security areas include:

[0138] Using precursor nodes distributed along the disturbance propagation direction as the path starting point, a search is performed along the disturbance propagation direction based on the monitoring node topology.

[0139] The adjacent downstream monitoring nodes of the precursor node are searched sequentially to obtain candidate downstream nodes;

[0140] Calculate the fiber optic distance difference between each precursor node and its corresponding candidate downstream node;

[0141] The desired velocity is obtained by weighting the propagation velocity range between the precursor node and the candidate downstream node.

[0142] The predicted arrival time of disturbances at candidate downstream nodes is calculated based on the arrival time of disturbances at the precursor node, the fiber distance difference between the precursor node and the candidate downstream node, and the expected speed.

[0143] Monitor the actual arrival time of disturbances at candidate downstream nodes and calculate the time deviation between the actual arrival time and the predicted arrival time of disturbances.

[0144] Candidate downstream nodes and their corresponding gigabit nodes with time deviations less than a preset error threshold are marked as candidate path nodes. The preset error threshold is obtained by normalizing the probability density of historical time deviations and normalizing the probability of the three time deviation intervals that are in the bottom three. The weight of the time deviation interval is obtained by weighting the median of the three time deviation intervals according to the weight.

[0145] Monitor and construct the actual feature strength index vector of candidate path nodes, and construct the expected feature strength index vector based on the output of the perturbation impact model;

[0146] Calculate the cosine similarity between the actual feature strength index vector and the expected feature strength index vector, and retain candidate path nodes whose cosine similarity is less than a preset similarity threshold; where the preset similarity threshold is 0.6.

[0147] Based on the monitoring nodes between each precursor node and the critical node, establish candidate impact paths corresponding to the precursor nodes;

[0148] Identify consecutive candidate path nodes in the candidate impact path, calculate the number of candidate path nodes, and obtain the effective path length;

[0149] By comparing the effective path lengths of different candidate impact paths, the candidate impact path corresponding to the maximum effective path length is marked as the disturbance impact path;

[0150] Early warning information is generated based on the predicted range of disturbance impact paths and arrival times in key security areas.

[0151] To address the shortcomings of existing distributed fiber optic acoustic monitoring systems, which, while capable of identifying disturbance locations, lack the ability to assess whether disturbances, when still in the periphery or upstream, will affect critical areas within a certain timeframe, and through which path effective acoustic energy is transmitted, this embodiment addresses these limitations. Based on the construction of propagation path node links, monitoring nodes corresponding to critical security areas are marked as critical nodes, and adjacent upstream monitoring nodes are identified as precursor nodes according to the monitoring node topology. Subsequently, by combining the fiber optic distance difference between precursor nodes and critical nodes with the propagation speed range, the shortest and longest arrival times are jointly calculated to obtain the arrival time prediction range for critical areas. Furthermore, candidate downstream nodes are searched along the disturbance propagation direction. Through time deviation verification and characteristic intensity index vector matching, candidate path nodes that match the acoustic propagation characteristics in terms of arrival order, propagation distance, and intensity attenuation are selected, forming several candidate impact paths. The path with the longest effective path length is selected as the disturbance impact path. This approach provides early warning results with time lead before the disturbance reaches the critical security area, clearly defining the spatial path and range of the disturbance's potential impact, thus facilitating joint time-space early warning and proactive protection of critical areas.

[0152] Example 2: This invention provides a distributed fiber optic acoustic wave sensing security early warning system, applied to the distributed fiber optic acoustic wave sensing security early warning method provided in Example 1, and implemented based on the following modules:

[0153] The fiber optic signal acquisition module lays distributed optical fibers around the protected target within the monitored area to acquire continuous acoustic signals along the distributed optical fibers.

[0154] The region mapping processing module performs segmentation and region mapping processing on the distributed optical fiber to construct acoustic monitoring nodes distributed along the line.

[0155] The node feature extraction module extracts local acoustic features from the acoustic signal of each monitoring node according to the time window, identifies the arrival time and feature intensity of disturbances at each monitoring node within the time window, and constructs a node disturbance sequence.

[0156] The node link construction module, based on the disturbance candidate sequences of different monitoring nodes, analyzes the changes in the disturbance arrival time difference and characteristic intensity index between monitoring nodes to obtain the propagation direction, propagation speed and propagation path node links of acoustic disturbances;

[0157] The prediction and disturbance path analysis module predicts the arrival time prediction range and disturbance impact path of key security areas by analyzing the propagation changes between adjacent monitoring nodes in the propagation path link.

[0158] The security early warning module generates early warning information based on the predicted path and arrival time of disturbances in key security areas.

[0159] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

[0160] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0161] All formulas in this manual are dimensionless and calculated numerically. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters and thresholds in the formulas are set by those skilled in the art according to the actual situation.

[0162] Although embodiments of the invention have been shown and described, those skilled in the art will understand that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.

Claims

1. A distributed fiber optic acoustic sensing security early warning method, characterized in that, include: A distributed optical fiber is laid around the protected target within the monitored area to acquire continuous acoustic signals along the distributed optical fiber. The distributed optical fiber is segmented and mapped to different regions to construct acoustic monitoring nodes distributed along the fiber. Local acoustic features are extracted from the acoustic signals of each monitoring node according to a time window, the arrival time and feature intensity of disturbances at each monitoring node within the time window are identified, and a node disturbance sequence is constructed. Based on the disturbance candidate sequences of different monitoring nodes, the propagation direction, propagation speed and propagation path node links of the acoustic disturbance are obtained by analyzing the changes in the time difference of arrival of the disturbance and the characteristic intensity index between the monitoring nodes. By analyzing the propagation changes between adjacent monitoring nodes in the propagation path node link, the arrival time prediction interval and disturbance impact path of key security areas can be predicted. Early warning information is generated based on the disturbance impact path and arrival time prediction interval of the key security area.

2. The distributed fiber optic acoustic sensing security early warning method according to claim 1, characterized in that, The segmentation and region mapping processing of the distributed optical fiber includes: Based on the fiber length information and the spatial distribution of the protected targets, the fiber is divided into multiple continuous monitoring segments, and different segment length configuration strategies are set for different functional areas to obtain a set of monitoring segments covering the entire line. Obtain the spatial coordinates of each monitoring section, generate corresponding monitoring nodes, and establish a mapping relationship between the monitoring nodes and the actual security area; The topological relationship between each monitoring node and its adjacent upstream and downstream monitoring nodes is marked according to the mapping relationship, the fiber optic route and connection order are recorded, and the monitoring node topology structure is constructed.

3. The distributed fiber optic acoustic sensing security early warning method according to claim 2, characterized in that, The method for identifying the arrival time and feature intensity of disturbances at each monitoring node within a time window includes: The fiber optic acoustic signal is divided into sliding windows, and three local characteristic parameters, namely acoustic energy, envelope rate of change and power ratio in the frequency band, are calculated in each time window. The three feature parameters of each time window are concatenated and encoded into a feature vector; the feature vectors of different time windows are concatenated in chronological order of the time windows to generate a local feature time series of the monitoring segment. Identify the arrival time of perturbation feature segments on the time axis; By integrating disturbance feature segments within the same time window from monitoring nodes, the maximum acoustic energy, average envelope change rate, and average power ratio within the frequency band are calculated to obtain three characteristic intensity indices. The disturbance data of each monitoring node are combined in chronological order to obtain the node disturbance sequence; The propagation speed range is calculated based on the spatiotemporal relationship between monitoring nodes and the time difference of disturbance arrival.

4. The distributed fiber optic acoustic sensing security early warning method according to claim 3, characterized in that, The method for calculating the propagation speed range includes: Scan the node perturbation sequence to identify spatiotemporally adjacent monitoring nodes, and record them as neighboring nodes; Calculate the time difference of arrival of the disturbance based on the arrival times of the disturbances at two neighboring nodes; Based on the time difference of arrival and the spatial coordinates between the monitoring nodes, the propagation speed range of acoustic disturbances between two neighboring nodes is calculated.

5. A distributed fiber optic acoustic sensing security early warning method according to claim 4, characterized in that, The method for calculating the propagation direction, propagation speed, and propagation path node links includes: The monitoring nodes are sorted according to the arrival time of the disturbance to generate an arrival order list; The earliest arrival time of the disturbance is retrieved from the arrival order list, and the corresponding monitoring node is marked as the initial node of the disturbance. Based on the spatial coordinate differences between the initial disturbance node and subsequent monitoring nodes and the corresponding arrival time differences, the propagation velocity components of the disturbance in different directions are calculated; the propagation velocity components include the velocity along the fiber direction and the lateral velocity. The fiber optic directional speed and lateral speed of multiple monitoring nodes in the arrival sequence list are statistically analyzed, and the ratio of the median fiber optic directional speed to the vertical speed is calculated to obtain the speed ratio. When the velocity ratio is greater than the preset ratio threshold, the direction along the fiber optic cable is determined to be the main disturbance propagation direction. The monitoring nodes along the direction of disturbance propagation are connected in series according to their arrival time to construct the propagation path node link of the acoustic disturbance.

6. A distributed fiber optic acoustic sensing security early warning method according to claim 5, characterized in that, The method for predicting the arrival time interval of acoustic disturbances to critical security areas includes: Identify key security areas, obtain the monitoring nodes corresponding to the key security areas, and record them as key nodes; Obtain the adjacent upstream monitoring nodes of the key node in the monitoring node topology, and denote them as the target upstream node; The monitoring node upstream of the target is searched in the propagation path node link and denoted as the precursor node; Based on the arrival time, spatial coordinates, and main propagation direction of the disturbance at each monitoring node, and combined with the propagation speed, the shortest and longest time for the acoustic disturbance to propagate from the precursor node to the critical node are calculated, and the arrival time prediction interval is determined.

7. A distributed fiber optic acoustic sensing security early warning method according to claim 6, characterized in that, The method for determining the arrival time prediction interval includes: Calculate the fiber optic distance coordinates based on the spatial coordinates of the precursor node and the critical node respectively; mark the fiber optic distance coordinates corresponding to the critical node as the critical distance coordinates; Compare the fiber-optic distance coordinates of different precursor nodes in the direction of disturbance propagation to determine whether the fiber-optic distance coordinates have increased. As the distance coordinate along the fiber increases, retain the precursor nodes whose distance coordinate along the fiber is less than the critical distance coordinate. When the distance coordinate along the fiber decreases, retain the precursor nodes whose distance coordinate along the fiber is less than the critical distance coordinate; The difference between the fiber optic distance coordinates and the critical distance coordinates of each precursor node is calculated to obtain the propagation distance along the fiber optic path for the precursor node. The propagation speed is obtained from the propagation speed range, and the arrival time prediction range is calculated by combining the propagation distance along the route.

8. A distributed fiber optic acoustic sensing security early warning method according to claim 7, characterized in that, The method for calculating the arrival time prediction interval by combining the propagation distance along the route includes: The lower limit of the propagation speed range is taken as the minimum propagation speed, and the upper limit is taken as the maximum propagation speed; The longest and shortest arrival times are obtained by calculating the ratios of the propagation distance along the route to the minimum and maximum propagation speeds, respectively. For several precursor nodes of the same critical node, the shortest arrival time and the longest arrival time corresponding to each precursor node are jointly statistically analyzed. The minimum shortest arrival time and the maximum longest arrival time are taken as the overall shortest arrival time and the overall longest arrival time for the critical security area, respectively. The overall shortest arrival time and the overall longest arrival time are superimposed with the disturbance arrival time of the precursor node to obtain the overall shortest arrival time and the overall longest arrival time, respectively. The arrival time prediction interval is determined based on the overall shortest arrival time and the overall longest arrival time.

9. A distributed fiber optic acoustic sensing security early warning method according to claim 7, characterized in that, The method for predicting the impact path of acoustic disturbances reaching critical security areas includes: The precursor nodes distributed along the direction of disturbance propagation are taken as the starting point of the path, and the search is carried out in the direction of disturbance propagation according to the topology of the monitoring nodes; The adjacent downstream monitoring nodes of the precursor node are searched sequentially to obtain candidate downstream nodes; Calculate the fiber optic distance difference between each precursor node and its corresponding candidate downstream node; The desired velocity is obtained by weighting the propagation velocity range between the precursor node and the candidate downstream node. The predicted arrival time of disturbances at candidate downstream nodes is calculated based on the arrival time of disturbances at the precursor node, the fiber distance difference between the precursor node and the candidate downstream node, and the expected speed. Monitor the actual arrival time of disturbances at candidate downstream nodes and calculate the time deviation between the actual arrival time and the predicted arrival time of disturbances. Candidate downstream nodes and their corresponding gigabit nodes with time deviations less than a preset error threshold are marked as candidate path nodes; Monitor and construct the actual feature strength index vector of candidate path nodes, and construct the expected feature strength index vector based on the output of the perturbation impact model; Calculate the cosine similarity between the actual feature strength index vector and the expected feature strength index vector, and retain candidate path nodes whose cosine similarity is less than a preset similarity threshold. Based on the monitoring nodes between each precursor node and the critical node, establish candidate impact paths corresponding to the precursor nodes; Identify consecutive candidate path nodes in the candidate impact path, calculate the number of candidate path nodes, and obtain the effective path length; By comparing the effective path lengths of different candidate impact paths, the candidate impact path corresponding to the maximum effective path length is marked as the disturbance impact path.

10. A distributed fiber optic acoustic wave sensing security early warning system, applied to the distributed fiber optic acoustic wave sensing security early warning method described in any one of claims 1 to 9, characterized in that, include: The fiber optic signal acquisition module lays distributed optical fibers around the protected target within the monitored area to acquire continuous acoustic signals along the distributed optical fibers. The region mapping processing module performs segmentation and region mapping processing on the distributed optical fiber to construct acoustic monitoring nodes distributed along the line. The node feature extraction module extracts local acoustic features from the acoustic signal of each monitoring node according to a time window, identifies the arrival time and feature intensity of disturbances at each monitoring node within the time window, and constructs a node disturbance sequence. The node link construction module, based on the disturbance candidate sequences of different monitoring nodes, obtains the propagation direction, propagation speed, and propagation path node links of acoustic disturbances by analyzing the changes in the disturbance arrival time difference and characteristic intensity index between monitoring nodes. The prediction and disturbance path analysis module predicts the arrival time prediction interval and disturbance impact path of key security areas by analyzing the propagation changes between adjacent monitoring nodes in the propagation path node link. The security early warning module generates early warning information based on the disturbance impact path and arrival time prediction interval of the key security area.

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