Data intelligent simulation processing method and system for breach emergency rescue

Abstract

The invention discloses a data intelligent simulation processing method and system for breach emergency rescue, and belongs to the technical field of simulation processing. The method comprises the following steps: at a dike breach, acquiring breach depth data, breach width data and breach length data of the breach in real time by using an unmanned aerial vehicle and a multi-mode sensor, and constructing a three-dimensional distribution matrix of the breach; collecting water velocity data and sediment content data of the breach; calculating a release disturbance risk value corresponding to a single row, a single column and a single layer in the three-dimensional distribution matrix; calculating a putting disturbance risk weight; taking a single row and a single column of the breach as a putting path, and calculating a putting disturbance safety coefficient of the putting path based on a putting disturbance risk weight; and presetting a putting disturbance safety coefficient threshold value, and analyzing and performing dynamic updating management on a putting path. Through a three-in-one technical system of spatial modeling, data fusion and simulation evaluation, the scientificity, safety and real-time adaptability of throwing path selection in the breach rescue process are effectively improved.

Description

Technical Field

[0001] The present invention relates to the field of simulation processing technology, and in particular to a data intelligent simulation processing method and system for breach rescue. Background Art

[0002] Levee breaches, one of the most sudden and devastating disasters in water conservancy projects, have long been a key topic in flood control and hydrological engineering research. Traditional breach rescue methods rely primarily on field experience, manual inspections, and static deployment strategies. Material placement and methods are determined through manual mapping, empirical judgment, and post-event analysis. However, these methods suffer from slow response times, insufficient decision-making evidence, and uncertain intervention effectiveness. In recent years, the advancement of remote sensing technology, sensor networks, and unmanned aerial vehicle (UAV) platforms has significantly enhanced the ability to acquire real-time data about breach areas, gradually driving the transition from empirically driven to data-driven rescue approaches. Simultaneously, breach evolution modeling methods based on numerical simulation and simulation techniques have emerged, capable of simulating breach expansion, water flow, and sediment distribution, providing theoretical support for emergency response deployment. However, these simulation methods currently suffer from lags in model updates, difficulties in parameter estimation, and insufficient integration with real-time field data, making it difficult to accurately assess dynamic risks and intelligently plan rescue routes.

[0003] Most existing research focuses on breach hydrodynamic simulation or sediment transport analysis, lacking the precise characterization and quantitative analysis of microscopic disturbance risks in three-dimensional space. Current methods struggle to integrate spatially integrated modeling of breach depth, width, and length data, and are even more incapable of integrating disturbance factors such as water velocity and sediment content to construct fine-grained delivery disturbance models. Consequently, path planning still relies primarily on manual judgment, making it difficult to address sudden disturbances and delivery failures that arise during breach evolution. Summary of the Invention

[0004] The purpose of the present invention is to provide a data intelligent simulation processing method and system for breach rescue, so as to solve the problems raised in the above background technology.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0006] A data intelligent simulation processing method for breach rescue comprises the following steps: step S1: at the breach of the embankment, using drones and multimodal sensors to collect breach depth data, breach width data and breach length data of the breach in real time, and constructing a three-dimensional distribution matrix of the breach; step S2: using a buoy sensor chain to deploy buoys on the breach surface to collect water flow velocity data and sediment content data of the breach; step S3: calculating the delivery disturbance risk value corresponding to a single row, single column and single layer in the three-dimensional distribution matrix; based on the single row and single column, extracting all delivery disturbance risk values in the corresponding layer, and calculating the delivery disturbance risk weight of the single row and single column; step S4: using the single row and single column of the breach as a delivery path, and calculating the delivery disturbance safety factor of the delivery path based on the delivery disturbance risk weight; presetting a delivery disturbance safety factor threshold, analyzing and performing dynamic update management of the delivery path.

[0007] As a preferred solution of the data intelligent simulation processing method for breach rescue described in the present invention, at the embankment breach, a drone and a multimodal sensor are used to collect basic breach data in real time, the basic data including breach depth data, breach width data, and breach length data. The multimodal sensor includes a laser detection sensor, which is used to collect breach depth data of the breach; the drone is equipped with an optical camera, which is used to collect breach width data and breach length data of the breach;

[0008] Based on the breach depth data, breach width data and breach length data, the breach depth data, breach width data and breach length data are evenly divided into N depth segments, I width segments and J length segments respectively, and a three-dimensional distribution matrix of the breach is constructed, wherein the row dimension of the three-dimensional distribution matrix is the J length segments, the column dimension of the three-dimensional distribution matrix is the I width segments, and the layer dimension of the three-dimensional distribution matrix is the N depth segments.

[0009] As a preferred embodiment of the intelligent simulation processing method for data used in breach rescue described in the present invention, a buoy sensor chain is used to deploy I×J buoys along I width segments and J length segments on the breach surface, and N water flow sensors and sediment content sensors are suspended below each buoy along N depth segments. The water flow sensors are used to collect water flow velocity data, and the sediment content sensors are used to collect sediment content data.

[0010] Obtain the water velocity data and sediment content data corresponding to the jth row, ith column, and nth layer in the three-dimensional distribution matrix, and record the water velocity data and sediment content data corresponding to the jth row, ith column, and nth layer as WFR j,i,n and SC j,i,n .

[0011] As a preferred solution of the data intelligent simulation processing method for breach rescue described in the present invention, a cell in the three-dimensional distribution matrix represents a disturbance risk value, based on the water flow velocity data WFR corresponding to the j-th row, i-th column, and n-th layer j,i,n and sediment content data SC j,i,n , calculate the placement disturbance risk value corresponding to the j-th row, i-th column, and n-th layer in the three-dimensional distribution matrix. The calculation formula is as follows:

[0012]

[0013] Among them, TDRF j,i,n represents the disturbance risk value corresponding to the jth row, ith column, and nth layer in the three-dimensional distribution matrix, and α represents the preset water flow velocity data WFR j,i,n Impact Factor, WFR max represents the preset maximum reference value of water velocity, and β represents the preset sediment content data SC j,i,n Impact factor, SC max Indicates the preset maximum reference value of sediment content;

[0014] In the present invention, the formula comprehensively considers the impact of water velocity and sediment content on the risk of disturbance caused by placement. The characteristic of the exponential function exp(x) is that when x is larger, the value of exp(x) is larger, and the value of 1-exp(-x) is also larger. In the formula, and Respectively represent the ratio of water velocity and sediment content at the current position (j, i, n) relative to the maximum reference value. α and β are preset influencing factors used to adjust the relative importance of water velocity and sediment content in risk calculation. When the water velocity WFR j,i,n Or sediment content SC j,i,n The bigger it is, The larger the value of The closer the value is to 1, the higher the deployment disturbance risk. This formula can be used to convert the flow velocity and sediment content at different locations of the breach into corresponding deployment disturbance risk values, providing basic data for subsequent safety assessments of the deployment path. The risk value corresponding to each cell reflects the risk level of the material deployment location due to the impact of water flow and sediment, helping to identify areas with higher and lower deployment risks.

[0015] Based on the j-th length segment and the i-th width segment, the corresponding row dimension and column dimension are locked in the three-dimensional distribution matrix. According to the locked row dimension and column dimension, all corresponding placement disturbance risk values in the corresponding layer dimension are extracted, and the placement disturbance risk weight of the j-th length segment and the i-th width segment is calculated. The calculation formula is as follows:

[0016]

[0017] Among them, ARWD j,i represents the risk weight of the disturbance of the j-th length segment and the i-th width segment in the breach, and N represents the total number of depth segments.

[0018] As a preferred solution of the data intelligent simulation processing method for breach rescue described in the present invention, the j-th length segment and the i-th width segment of the breach are used as the delivery path, and the delivery disturbance risk weight ARWD based on the j-th length segment and the i-th width segment is calculated. j,i , the delivery path is simulated as follows:

[0019] Calculate the delivery disturbance safety factor of the delivery path, and the calculation formula is as follows:

[0020]

[0021] Among them, ISFD j,i represents the delivery disturbance safety factor of the delivery path;

[0022] In the present invention, the formula is to put the disturbance risk weight ARWD j,i On this basis, the safety factor of the delivery path is calculated by further combining the comprehensive influence of water flow velocity and sediment content. It indicates the ratio of the average water flow velocity on the delivery path to the maximum reference value. Indicates the ratio of the average sediment content on the delivery path to the maximum reference value. The safety factor is obtained by multiplying the risk weight by these two proportional factors, and takes into account the correction term of the sediment content proportional factor\ to more comprehensively reflect the impact of various factors on delivery safety. Delivery disturbance safety factor ISFD j,i This formula is used to quantitatively assess the safety of each deployment path. The safety factor calculated using this formula allows for intuitive comparison of the safety of different deployment paths. By presetting a threshold for the deployment disturbance safety factor, this factor can be used to determine the safety of a particular deployment path, thereby selecting safe deployment paths for rescue operations. These paths are dynamically updated and managed to ensure that relatively safe deployment paths are consistently selected despite evolving breach conditions, improving the safety and effectiveness of rescue efforts.

[0023] Preset delivery disturbance safety factor threshold, if the delivery disturbance safety factor ISFD of the delivery path j,i If the value is greater than or equal to the delivery disturbance safety factor threshold, it indicates that the simulation result of the delivery path is safe and the delivery path is a safe delivery path;

[0024] Calculate the delivery disturbance safety factors of all I×J delivery paths, obtain all delivery paths whose delivery disturbance safety factors are greater than or equal to the delivery disturbance safety factor threshold, and manage them in a unified manner, obtain the delivery disturbance risk value in real time, and perform dynamic update management of safe delivery paths.

[0025] A data intelligent simulation processing system for breach rescue, the system includes: a data acquisition and matrix construction module, a water flow and sediment data acquisition module, a risk value and weight calculation module, and a safety factor calculation and analysis processing module;

[0026] The data acquisition and matrix construction module: at the breach site of the embankment, using drones and multimodal sensors to collect breach depth data, breach width data, and breach length data in real time, and construct a three-dimensional distribution matrix of the breach;

[0027] The water flow and sediment data acquisition module uses a buoy sensor chain to place buoys on the breach surface to collect water flow velocity data and sediment content data of the breach;

[0028] The risk value and weight calculation module calculates the delivery disturbance risk value corresponding to a single row, single column, and single layer in the three-dimensional distribution matrix; based on the single row and single column, extracts all delivery disturbance risk values in the corresponding layer, and calculates the delivery disturbance risk weight of the single row and single column;

[0029] The safety factor calculation and analysis processing module: takes the single row and single column of the breach as the delivery path, and calculates the delivery disturbance safety factor of the delivery path based on the delivery disturbance risk weight; presets the delivery disturbance safety factor threshold, analyzes and performs dynamic update management of the delivery path.

[0030] Furthermore, the data acquisition and matrix construction module includes a data acquisition unit and a matrix construction unit;

[0031] The data acquisition unit: uses a drone and a multimodal sensor to collect basic breach data in real time at the breach site, the basic data including breach depth data, breach width data, and breach length data. The multimodal sensor includes a laser detection sensor for collecting breach depth data of the breach; the drone is equipped with an optical camera for collecting breach width data and breach length data of the breach;

[0032] The matrix construction unit: based on the breach depth data, breach width data and breach length data, the breach depth data, breach width data and breach length data are evenly divided into N depth segments, I width segments and J length segments, and a three-dimensional distribution matrix of the breach is constructed, wherein the row dimension of the three-dimensional distribution matrix is the J length segments, the column dimension of the three-dimensional distribution matrix is the I width segments, and the layer dimension of the three-dimensional distribution matrix is the N depth segments.

[0033] Furthermore, the water flow and sediment data acquisition module includes a water flow and sediment data acquisition unit;

[0034] The water flow and sediment data acquisition unit uses a buoy sensor chain to deploy I×J buoys along I width segments and J length segments on the breach surface, and hang N water flow sensors and sediment content sensors along N depth segments under each buoy. The water flow sensor is used to collect water flow velocity data, and the sediment content sensor is used to collect sediment content data.

[0035] Furthermore, the risk value and weight calculation module includes a risk value calculation unit and a weight calculation unit;

[0036] The risk value calculation unit: each cell in the three-dimensional distribution matrix represents a delivery disturbance risk value, and based on the water velocity data and sediment content data corresponding to the j-th row, i-th column, and n-th layer, calculates the delivery disturbance risk value corresponding to the j-th row, i-th column, and n-th layer in the three-dimensional distribution matrix;

[0037] The weight calculation unit: based on the j-th length segment and the i-th width segment, locks the corresponding row dimension and column dimension in the three-dimensional distribution matrix, extracts all corresponding delivery disturbance risk values in the corresponding layer dimension according to the locked row dimension and column dimension, and calculates the delivery disturbance risk weight of the j-th length segment and the i-th width segment.

[0038] Furthermore, the safety factor calculation and analysis processing module includes a safety factor calculation unit and an analysis processing unit;

[0039] The safety factor calculation unit: takes the j-th length segment and the i-th width segment of the breach as the delivery path, and simulates the delivery path based on the delivery disturbance risk weights of the j-th length segment and the i-th width segment, specifically: calculates the delivery disturbance safety factor of the delivery path;

[0040] The analysis and processing unit: presets a delivery disturbance safety factor threshold. If the delivery disturbance safety factor of the delivery path is greater than or equal to the delivery disturbance safety factor threshold, it indicates that the simulation result of the delivery path is safe and the delivery path is a safe delivery path; calculates the delivery disturbance safety factors of all I×J delivery paths, obtains all delivery paths with delivery disturbance safety factors greater than or equal to the delivery disturbance safety factor threshold, and manages them in a unified manner, obtains delivery disturbance risk values in real time, and performs dynamic update management of safe delivery paths.

[0041] Compared with the existing technology, the beneficial effects achieved by the present invention are as follows: in the data intelligent simulation processing method and system for breach rescue provided by the present invention, the depth, width and length of the breach are collected in real time by using a drone equipped with a laser detection sensor and an optical camera, and the data are divided into multiple spatial segments to construct a three-dimensional distribution matrix with spatial resolution, thereby realizing the visual modeling of the breach spatial structure and providing high-precision basic data support for subsequent simulations; by deploying a buoy sensor chain in the breach area, key dynamic information such as water flow velocity and sediment content is collected and accurately mapped to the three-dimensional matrix. Each spatial unit in the array realizes the three-dimensional perception of the dynamic environment of the breach and enhances the system's response ability to local disturbance factors; by integrating multi-source data, the disturbance risk value is calculated based on the flow velocity and sediment content of each cell, and the risk weight of each deployment path is further extracted on the two-dimensional surface, so that the risk assessment has hierarchical and regional focus, effectively supporting the detailed evaluation of the deployment path; the two-dimensional path is integrated with the corresponding disturbance risk weight to construct a deployment disturbance safety factor model, and a safety threshold mechanism is introduced to screen and dynamically update all potential paths, thus realizing real-time management and intelligent optimization of safe deployment paths. In summary, the present invention effectively improves the scientificity, safety and real-time adaptability of deployment path selection in the breach rescue process through the three-in-one technical system of spatial modeling, data fusion and simulation evaluation, and has important emergency rescue application value and promotion potential. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] The accompanying drawings are used to provide further understanding of the present invention and constitute a part of the specification. They are used to explain the present invention together with the embodiments of the present invention and do not constitute a limitation of the present invention.

[0043] Figure 1 This is a schematic diagram of the steps of a data intelligent simulation processing method for breach rescue according to the present invention;

[0044] Figure 2 It is a structural schematic diagram of a data intelligent simulation processing system for breach rescue according to the present invention. DETAILED DESCRIPTION

[0045] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0046] See also Figure 1 In the first embodiment, a data intelligent simulation processing method for breach rescue is provided, the method comprising the following steps:

[0047] Step S1: At the breach site of the embankment, a drone and a multimodal sensor are used to collect breach depth data, breach width data, and breach length data in real time, and a three-dimensional distribution matrix of the breach is constructed.

[0048] Specifically, at the breach site of the embankment, a drone and a multimodal sensor are used to collect basic breach data in real time. The basic data includes breach depth data, breach width data, and breach length data. The multimodal sensor includes a laser detection sensor for collecting breach depth data of the breach. The drone is equipped with an optical camera for collecting breach width data and breach length data of the breach.

[0049] Furthermore, based on the breach depth data, breach width data and breach length data, the breach depth data, breach width data and breach length data are evenly divided into N depth segments, I width segments and J length segments, respectively, and a three-dimensional distribution matrix of the breach is constructed, the row dimension of the three-dimensional distribution matrix is the J length segments, the column dimension of the three-dimensional distribution matrix is the I width segments, and the layer dimension of the three-dimensional distribution matrix is the N depth segments.

[0050] Step S2: Utilize a buoy sensor chain to deploy buoys on the breach surface to collect water velocity data and sediment content data of the breach.

[0051] Specifically, a buoy sensor chain is used to deploy I×J buoys along I width segments and J length segments on the breach surface. N water flow sensors and sediment content sensors are suspended below each buoy along N depth segments. The water flow sensors are used to collect water flow velocity data, and the sediment content sensors are used to collect sediment content data.

[0052] Furthermore, the water velocity data and sediment content data corresponding to the j-th row, i-th column, and n-th layer in the three-dimensional distribution matrix are obtained, and the water velocity data and sediment content data corresponding to the j-th row, i-th column, and n-th layer are recorded as WFR j,i,n and SC j,i,n .

[0053] Step S3: Calculate the delivery disturbance risk value corresponding to a single row, single column, and single layer in the three-dimensional distribution matrix; based on the single row and single column, extract all delivery disturbance risk values in the corresponding layer, and calculate the delivery disturbance risk weight of the single row and single column.

[0054] Specifically, a cell in the three-dimensional distribution matrix represents a disturbance risk value, based on the water flow velocity data WFR corresponding to the j-th row, i-th column, and n-th layer. j,i,n and sediment content data SC j,i,n , calculate the placement disturbance risk value corresponding to the j-th row, i-th column, and n-th layer in the three-dimensional distribution matrix. The calculation formula is as follows:

[0055]

[0056] Among them, TDRF j,i,n represents the disturbance risk value corresponding to the jth row, ith column, and nth layer in the three-dimensional distribution matrix, and α represents the preset water flow velocity data WFR j,i,n Impact Factor, WFR max represents the preset maximum reference value of water velocity, and β represents the preset sediment content data SC j,i,n Impact factor, SC max Indicates the preset maximum reference value of sediment content;

[0057] It should be noted that this formula takes the water flow velocity WFR as j,i,n and sediment content SC j,i,n By comparing them with their respective maximum reference values and combining them with the preset influencing factors α and β, the risk of a specific location can be accurately reflected. For example, in areas with turbulent water flow and high sediment content, the risk value calculated by the formula will increase significantly, intuitively showing the high risk of deployment operations in that area. The formula also uses the characteristics of exponential functions to characterize the nonlinear changes in risk. When the water flow rate or sediment content increases slightly, the risk value will slowly increase; but when these factors approach or exceed certain limits, the risk value will increase rapidly. This characteristic is in line with reality, because during breach rescue, once the water flow and sediment conditions deteriorate to a certain extent, the risk of deployment operations will increase sharply.

[0058] Furthermore, based on the j-th length segment and the i-th width segment, the corresponding row dimension and column dimension are locked in the three-dimensional distribution matrix. According to the locked row dimension and column dimension, all corresponding placement disturbance risk values in the corresponding layer dimension are extracted, and the placement disturbance risk weight of the j-th length segment and the i-th width segment is calculated. The calculation formula is as follows:

[0059]

[0060] Among them, ARWDj,i represents the risk weight of the disturbance of the j-th length segment and the i-th width segment in the breach, and N represents the total number of depth segments.

[0061] It should be noted that by averaging the risk values at different depths in a specific two-dimensional area, the overall risk level of that area is fully reflected. In actual breach rescue operations, water flow and sediment conditions at different depths at the same horizontal location vary. This formula integrates these differences to avoid misjudging risks by focusing only on a single depth. For example, in some areas, surface water flows quickly but deep water flows more slowly. Averaging can produce a more reasonable risk weight. Furthermore, simplifying the complex risk distribution in three-dimensional space into a single risk weight indicator for a two-dimensional area facilitates subsequent calculations and analysis. When planning deployment paths, different paths can be directly compared based on this weight, improving decision-making efficiency.

[0062] Step S4: taking the single row and single column of the breach as the delivery path, and calculating the delivery disturbance safety factor of the delivery path based on the delivery disturbance risk weight; presetting the delivery disturbance safety factor threshold, analyzing and performing dynamic update management of the delivery path.

[0063] Specifically, the j-th length segment and the i-th width segment of the breach are used as the delivery path, and the delivery disturbance risk weight ARWD is calculated based on the j-th length segment and the i-th width segment. j,i , the delivery path is simulated as follows:

[0064] Calculate the delivery disturbance safety factor of the delivery path, and the calculation formula is as follows:

[0065]

[0066] Among them, ISFD j,i represents the delivery disturbance safety factor of the delivery path;

[0067] It's important to note that the safety factor is calculated by combining risk weight, average flow velocity ratio, and average sediment content ratio, comprehensively considering key factors affecting deployment safety. For example, a path with a high risk weight but relatively low flow velocity and sediment content will not necessarily have a low safety factor. Conversely, even if the risk weight is low, the safety factor will be affected if the flow velocity or sediment content is too high. During the breach rescue process, flow velocity and sediment content constantly change, and this formula can recalculate the safety factor based on real-time data. By comparing it with preset thresholds, the deployment path can be adjusted in a timely manner to ensure that rescue operations are always carried out along a relatively safe path.

[0068] Furthermore, a threshold value of the delivery disturbance safety factor is preset. If the delivery disturbance safety factor ISFD of the delivery path is j,iIf the value is greater than or equal to the delivery disturbance safety factor threshold, it indicates that the simulation result of the delivery path is safe and the delivery path is a safe delivery path;

[0069] Furthermore, the delivery disturbance safety factors of all I×J delivery paths are calculated, and all delivery paths whose delivery disturbance safety factors are greater than or equal to the delivery disturbance safety factor threshold are obtained, and unified management is performed, and the delivery disturbance risk value is obtained in real time, and dynamic update management of safe delivery paths is performed.

[0070] See also Figure 2 In the second embodiment, a data intelligent simulation processing system for breach rescue is provided, which includes: a data acquisition and matrix construction module, a water flow and sediment data acquisition module, a risk value and weight calculation module, and a safety factor calculation and analysis processing module;

[0071] The data acquisition and matrix construction module: at the breach site of the embankment, using drones and multimodal sensors to collect breach depth data, breach width data, and breach length data in real time, and construct a three-dimensional distribution matrix of the breach;

[0072] The water flow and sediment data acquisition module uses a buoy sensor chain to place buoys on the breach surface to collect water flow velocity data and sediment content data of the breach;

[0073] The risk value and weight calculation module calculates the delivery disturbance risk value corresponding to a single row, single column, and single layer in the three-dimensional distribution matrix; based on the single row and single column, extracts all delivery disturbance risk values in the corresponding layer, and calculates the delivery disturbance risk weight of the single row and single column;

[0074] The safety factor calculation and analysis processing module: takes the single row and single column of the breach as the delivery path, and calculates the delivery disturbance safety factor of the delivery path based on the delivery disturbance risk weight; presets the delivery disturbance safety factor threshold, analyzes and performs dynamic update management of the delivery path.

[0075] Furthermore, the data acquisition and matrix construction module includes a data acquisition unit and a matrix construction unit;

[0076] The data acquisition unit: uses a drone and a multimodal sensor to collect basic breach data in real time at the breach site, the basic data including breach depth data, breach width data, and breach length data. The multimodal sensor includes a laser detection sensor for collecting breach depth data of the breach; the drone is equipped with an optical camera for collecting breach width data and breach length data of the breach;

[0077] The matrix construction unit: based on the breach depth data, breach width data and breach length data, the breach depth data, breach width data and breach length data are evenly divided into N depth segments, I width segments and J length segments, and a three-dimensional distribution matrix of the breach is constructed, wherein the row dimension of the three-dimensional distribution matrix is the J length segments, the column dimension of the three-dimensional distribution matrix is the I width segments, and the layer dimension of the three-dimensional distribution matrix is the N depth segments.

[0078] Furthermore, the water flow and sediment data acquisition module includes a water flow and sediment data acquisition unit;

[0079] The water flow and sediment data acquisition unit uses a buoy sensor chain to deploy I×J buoys along I width segments and J length segments on the breach surface, and hang N water flow sensors and sediment content sensors along N depth segments under each buoy. The water flow sensor is used to collect water flow velocity data, and the sediment content sensor is used to collect sediment content data.

[0080] Furthermore, the risk value and weight calculation module includes a risk value calculation unit and a weight calculation unit;

[0081] The risk value calculation unit: each cell in the three-dimensional distribution matrix represents a delivery disturbance risk value, and based on the water velocity data and sediment content data corresponding to the j-th row, i-th column, and n-th layer, calculates the delivery disturbance risk value corresponding to the j-th row, i-th column, and n-th layer in the three-dimensional distribution matrix;

[0082] The weight calculation unit: based on the j-th length segment and the i-th width segment, locks the corresponding row dimension and column dimension in the three-dimensional distribution matrix, extracts all corresponding delivery disturbance risk values in the corresponding layer dimension according to the locked row dimension and column dimension, and calculates the delivery disturbance risk weight of the j-th length segment and the i-th width segment.

[0083] Furthermore, the safety factor calculation and analysis processing module includes a safety factor calculation unit and an analysis processing unit;

[0084] The safety factor calculation unit: takes the j-th length segment and the i-th width segment of the breach as the delivery path, and simulates the delivery path based on the delivery disturbance risk weights of the j-th length segment and the i-th width segment, specifically: calculates the delivery disturbance safety factor of the delivery path;

[0085] The analysis and processing unit: presets a delivery disturbance safety factor threshold. If the delivery disturbance safety factor of the delivery path is greater than or equal to the delivery disturbance safety factor threshold, it indicates that the simulation result of the delivery path is safe and the delivery path is a safe delivery path; calculates the delivery disturbance safety factors of all I×J delivery paths, obtains all delivery paths with delivery disturbance safety factors greater than or equal to the delivery disturbance safety factor threshold, and manages them in a unified manner, obtains delivery disturbance risk values in real time, and performs dynamic update management of safe delivery paths.

[0086] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus.

[0087] Finally, it should be noted that 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 aforementioned embodiments, those skilled in the art will be able to modify the technical solutions described in the aforementioned embodiments or substitute equivalents for some of the technical features. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. A data intelligent simulation processing method for breach rescue, characterized in that: The method comprises the following steps: Step S1: At the breach site of the embankment, using drones and multimodal sensors to collect breach depth data, breach width data, and breach length data in real time, and construct a three-dimensional distribution matrix of the breach; Step S2: using a buoy sensor chain to deploy buoys on the breach surface to collect water velocity data and sediment content data of the breach; Step S3: Calculate the delivery disturbance risk value corresponding to a single row, single column, and single layer in the three-dimensional distribution matrix; based on the single row and single column, extract all delivery disturbance risk values in the corresponding layer, and calculate the delivery disturbance risk weight of the single row and single column; Step S4: taking the single row and single column of the breach as the delivery path, and calculating the delivery disturbance safety factor of the delivery path based on the delivery disturbance risk weight; presetting the delivery disturbance safety factor threshold, analyzing and performing dynamic update management of the delivery path.

2. The data intelligent simulation processing method for breach rescue according to claim 1 is characterized in that: The specific implementation process of step S1 includes: At the breach of the embankment, a drone and a multimodal sensor are used to collect basic breach data in real time, the basic data including breach depth data, breach width data, and breach length data. The multimodal sensor includes a laser detection sensor for collecting breach depth data of the breach; the drone is equipped with an optical camera for collecting breach width data and breach length data of the breach; Based on the breach depth data, breach width data and breach length data, the breach depth data, breach width data and breach length data are evenly divided into N depth segments, I width segments and J length segments respectively, and a three-dimensional distribution matrix of the breach is constructed, wherein the row dimension of the three-dimensional distribution matrix is the J length segments, the column dimension of the three-dimensional distribution matrix is the I width segments, and the layer dimension of the three-dimensional distribution matrix is the N depth segments.

3. The data intelligent simulation processing method for breach rescue according to claim 2 is characterized in that: The specific implementation process of step S2 includes: Using a buoy sensor chain, I×J buoys are deployed along I width segments and J length segments on the breach surface. N water flow sensors and sediment content sensors are suspended below each buoy along N depth segments. The water flow sensors are used to collect water flow velocity data, and the sediment content sensors are used to collect sediment content data. Obtain the water velocity data and sediment content data corresponding to the jth row, ith column, and nth layer in the three-dimensional distribution matrix, and record the water velocity data and sediment content data corresponding to the jth row, ith column, and nth layer as WFR j,i,n and SC j,i,n .

4. The data intelligent simulation processing method for breach rescue according to claim 3 is characterized in that: The specific implementation process of step S3 includes: A cell in the three-dimensional distribution matrix represents a disturbance risk value, based on the water velocity data WFR corresponding to the j-th row, i-th column, and n-th layer. j,i,n and sediment content data SC j,i,n , calculate the placement disturbance risk value corresponding to the j-th row, i-th column, and n-th layer in the three-dimensional distribution matrix. The calculation formula is as follows: Among them, TDRF j,i,n represents the disturbance risk value corresponding to the jth row, ith column, and nth layer in the three-dimensional distribution matrix, and α represents the preset water flow velocity data WFR j,i,n Impact Factor, WFR max represents the preset maximum reference value of water velocity, and β represents the preset sediment content data SC j,i,n Impact factor, SC max Indicates the preset maximum reference value of sediment content; Based on the j-th length segment and the i-th width segment, the corresponding row dimension and column dimension are locked in the three-dimensional distribution matrix. According to the locked row dimension and column dimension, all corresponding placement disturbance risk values in the corresponding layer dimension are extracted, and the placement disturbance risk weight of the j-th length segment and the i-th width segment is calculated. The calculation formula is as follows: Among them, ARWD j,i represents the risk weight of the disturbance of the j-th length segment and the i-th width segment in the breach, and N represents the total number of depth segments.

5. The data intelligent simulation processing method for breach rescue according to claim 4 is characterized in that: The specific implementation process of step S4 includes: The j-th length segment and the i-th width segment of the breach are used as the delivery path, and the delivery disturbance risk weight ARWD is calculated based on the j-th length segment and the i-th width segment. j,i , the delivery path is simulated as follows: Calculate the delivery disturbance safety factor of the delivery path, and the calculation formula is as follows: Among them, ISFD j,i represents the delivery disturbance safety factor of the delivery path; Preset delivery disturbance safety factor threshold, if the delivery disturbance safety factor ISFD of the delivery path j,i If the value is greater than or equal to the delivery disturbance safety factor threshold, it indicates that the simulation result of the delivery path is safe and the delivery path is a safe delivery path; Calculate the delivery disturbance safety factors of all I×J delivery paths, obtain all delivery paths whose delivery disturbance safety factors are greater than or equal to the delivery disturbance safety factor threshold, and manage them uniformly, obtain the delivery disturbance risk value in real time, and perform dynamic update management of safe delivery paths.

6. A data intelligent simulation processing system for breach rescue, which executes a data intelligent simulation processing method for breach rescue according to any one of claims 1 to 5, characterized in that: The system includes: a data acquisition and matrix construction module, a water flow and sediment data acquisition module, a risk value and weight calculation module, and a safety factor calculation and analysis processing module; The data acquisition and matrix construction module: at the breach site of the embankment, using drones and multimodal sensors to collect breach depth data, breach width data, and breach length data in real time, and construct a three-dimensional distribution matrix of the breach; The water flow and sediment data acquisition module uses a buoy sensor chain to place buoys on the breach surface to collect water flow velocity data and sediment content data of the breach; The risk value and weight calculation module calculates the delivery disturbance risk value corresponding to a single row, single column, and single layer in the three-dimensional distribution matrix; based on the single row and single column, extracts all delivery disturbance risk values in the corresponding layer, and calculates the delivery disturbance risk weight of the single row and single column; The safety factor calculation and analysis processing module: takes the single row and single column of the breach as the delivery path, and calculates the delivery disturbance safety factor of the delivery path based on the delivery disturbance risk weight; presets the delivery disturbance safety factor threshold, analyzes and performs dynamic update management of the delivery path.

7. The data intelligent simulation processing system for breach rescue according to claim 6 is characterized by: The data acquisition and matrix construction module includes a data acquisition unit and a matrix construction unit; The data acquisition unit: uses a drone and a multimodal sensor to collect basic breach data in real time at the breach site, the basic data including breach depth data, breach width data, and breach length data. The multimodal sensor includes a laser detection sensor for collecting breach depth data of the breach; the drone is equipped with an optical camera for collecting breach width data and breach length data of the breach; The matrix construction unit: based on the breach depth data, breach width data and breach length data, the breach depth data, breach width data and breach length data are evenly divided into N depth segments, I width segments and J length segments, and a three-dimensional distribution matrix of the breach is constructed, wherein the row dimension of the three-dimensional distribution matrix is the J length segments, the column dimension of the three-dimensional distribution matrix is the I width segments, and the layer dimension of the three-dimensional distribution matrix is the N depth segments.

8. The data intelligent simulation processing system for breach rescue according to claim 7 is characterized by: The water flow and sediment data acquisition module includes a water flow and sediment data acquisition unit; The water flow and sediment data acquisition unit uses a buoy sensor chain to deploy I×J buoys along I width segments and J length segments on the breach surface, and hang N water flow sensors and sediment content sensors along N depth segments under each buoy. The water flow sensor is used to collect water flow velocity data, and the sediment content sensor is used to collect sediment content data.

9. The data intelligent simulation processing system for breach rescue according to claim 8 is characterized by: The risk value and weight calculation module includes a risk value calculation unit and a weight calculation unit; The risk value calculation unit: each cell in the three-dimensional distribution matrix represents a delivery disturbance risk value, and based on the water velocity data and sediment content data corresponding to the j-th row, i-th column, and n-th layer, calculates the delivery disturbance risk value corresponding to the j-th row, i-th column, and n-th layer in the three-dimensional distribution matrix; The weight calculation unit: based on the j-th length segment and the i-th width segment, locks the corresponding row dimension and column dimension in the three-dimensional distribution matrix, extracts all corresponding delivery disturbance risk values in the corresponding layer dimension according to the locked row dimension and column dimension, and calculates the delivery disturbance risk weight of the j-th length segment and the i-th width segment.

10. The data intelligent simulation processing system for breach rescue according to claim 9 is characterized by: The safety factor calculation and analysis processing module includes a safety factor calculation unit and an analysis processing unit; The safety factor calculation unit: takes the j-th length segment and the i-th width segment of the breach as the delivery path, and simulates the delivery path based on the delivery disturbance risk weights of the j-th length segment and the i-th width segment, specifically: calculates the delivery disturbance safety factor of the delivery path; The analysis and processing unit is configured to preset a delivery disturbance safety factor threshold value. If the delivery disturbance safety factor of the delivery path is greater than or equal to the delivery disturbance safety factor threshold value, it indicates that the simulation result of the delivery path is safe and the delivery path is a safe delivery path. Calculate the delivery disturbance safety factors of all I×J delivery paths, obtain all delivery paths whose delivery disturbance safety factors are greater than or equal to the delivery disturbance safety factor threshold, and manage them uniformly, obtain the delivery disturbance risk value in real time, and perform dynamic update management of safe delivery paths.

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