Method and system for evaluating post-earthquake wounded person rescue difficulty based on building collapse form

Abstract

The invention discloses a post-earthquake wounded person rescue difficulty assessment method and system based on a building collapse form, and relates to the technical field of post-earthquake rescue, and the method comprises the steps: extracting the geometric form and attribute information of a damaged building based on the earthquake damage analysis of a target earthquake region, and building a to-be-collapsed simulation building model; seismic oscillation is loaded on the to-be-collapsed simulation building model, and a post-earthquake ruin model reflecting the collapse form is generated based on an explicit time integration method; geometric and spatial features of the post-earthquake ruin model are extracted, and collapse form types of the post-earthquake ruin model are divided; based on the survival space evaluation index and the rescue channel complexity index, calculating a comprehensive rescue difficulty index of the post-earthquake ruin model; based on the comprehensive rescue difficulty index, determining rescue difficulty levels of different areas in the post-earthquake ruin model; and determining the estimated rescue time of the post-earthquake ruin model based on the comprehensive rescue difficulty index and the collapse form type. According to the invention, the technical problem that the post-earthquake ruins are difficult to quantitatively evaluate in the prior art is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of post-earthquake rescue, and in particular to a method and system for assessing the difficulty of rescuing injured persons after an earthquake based on the form of building collapse. Background Art

[0002] Earthquake disasters are one of the most serious natural disasters, which often lead to the collapse of a large number of buildings and casualties. The ruins formed after the collapse of buildings not only directly threaten the lives of survivors, but also block the rescue channels, delay rescue operations, and further aggravate losses. The core goal of post-earthquake rescue work is to quickly assess the feasibility of the living space and rescue channels of the wounded inside the ruins, formulate scientific rescue priorities, and save lives to the greatest extent. However, due to the complex and changeable forms of ruins, the existing rescue difficulty assessment methods have obvious deficiencies and are difficult to meet the actual needs of rapid response and efficient rescue after the earthquake. Therefore, studying the collapse form of buildings in earthquakes and their impact on rescue is of great significance to improving the efficiency of post-earthquake rescue and optimizing resource allocation.

[0003] In recent years, some progress has been made in the study of the morphology of post-earthquake building ruins (Shan Ruochen. Study on the earthquake collapse mode of typical bottom frame masonry structure and its ruins structural characteristics [D]. Heilongjiang: Institute of Engineering Mechanics, China Earthquake Administration, 2015; Wang Nan, Ma Shugen, Li Bin, et al. Synchronous positioning and map creation for the earthquake damage morphology inside the ruins [J]. Science Bulletin, 2013(S2): 104-111; Pollino M, Cappucci S, Giordano L, et al. Assessingearthquake-induced urban rubble by means of multiplatform remotely senseddata [J]. ISPRS International Journal of Geo-Information, 2020, 9(4): 262; Moya L, Yamazaki F, Liu W, et al. Detection of collapsed buildings due to the 2016Kumamoto, Japan, earthquake from Lidar data [J]. Nat. Hazards Earth Syst. Sci, 2017, 18: 65; Wang Yu. Research on multi-scale earthquake damage identification and assessment of buildings enhanced by deep learning with geometric constraints [D]. Gansu: Lanzhou University, 2023;). However, these studies mainly focus on the detection and classification of collapsed buildings, and the analysis of the geometric characteristics, living space and complexity of rescue channels inside the ruins is relatively scarce. In addition, existing methods mostly rely on experience to qualitatively classify the morphology of ruins, lacking a systematic quantitative evaluation standard. There is a lack of a unified analysis method for the geometric characteristics and component distribution characteristics of different collapse types (such as inclined type, interlayer type, and fragmentation accumulation type), making it difficult to accurately describe the complexity of the ruins. Summary of the invention

[0004] In order to solve the above technical problems existing in the prior art, the embodiment of the present invention provides a method and system for assessing the difficulty of rescuing injured persons after an earthquake based on the form of building collapse. The technical solution is as follows:

[0005] On the one hand, a method for assessing the difficulty of rescuing the injured after an earthquake based on the collapse morphology of buildings is provided, comprising: generating a post-earthquake ruins model of the target earthquake zone based on the geometric and mechanical properties of the building structures in the target earthquake zone and the component distribution of the ruins after the building collapses; extracting the geometric and spatial features of the post-earthquake ruins model, and dividing the collapse morphology types of the post-earthquake ruins model based on the geometric and spatial features; the collapse morphology types include inclined collapse, sandwich collapse and fragmented accumulation collapse; calculating the survival space assessment index and the rescue channel complexity index of the post-earthquake ruins model based on the geometric and spatial features; calculating the comprehensive rescue difficulty index of the post-earthquake ruins model based on the survival space assessment index and the rescue channel complexity index; determining the rescue difficulty levels of different areas in the post-earthquake ruins model based on the comprehensive rescue difficulty index; and determining the estimated rescue time of the post-earthquake ruins model based on the comprehensive rescue difficulty index and the collapse morphology type.

[0006] Furthermore, based on the geometric and mechanical properties of the building structures in the target earthquake zone and the component distribution of the ruins after the building collapses, a post-earthquake ruins model of the target earthquake zone is generated, including: establishing a simulated building model to be collapsed based on the geometric and mechanical properties of the building structures in the target earthquake zone; loading seismic motion on the simulated building model to be collapsed, reproducing the entire process of building collapse based on the explicit time integration method, and generating a post-earthquake ruins model reflecting the collapse morphology based on a voxelization method and nonlinear behavior of components.

[0007] Furthermore, the geometric and spatial characteristics of the post-earthquake ruins model include: relative height ratio, area expansion ratio, interlayer void ratio, component density distribution and component size distribution index; extracting the geometric and spatial characteristics of the post-earthquake ruins model includes: calculating the relative height ratio based on the height of the original building model before collapse and the height of the ruins model after collapse, including:

[0008]

[0009] In the formula, H r is the relative height ratio, is the maximum height of the ruins model after collapse, is the height of the original building model before the collapse; based on the projection area of ​​the original building model before the collapse and the projection area of ​​the ruins after the collapse, the area expansion ratio is calculated, including:

[0010]

[0011] In the formula, A r is the area expansion ratio, is the projected area of ​​the ruins after collapse, is the projection area of ​​the original building model before collapse; based on the three-dimensional model characteristic data of the post-earthquake ruins model, the interlayer void ratio is calculated, including:

[0012]

[0013] In the formula, ρ g is the interlayer void ratio, V component is the component volume, V region is the volume of the main building after collapse; based on the number of components in the unit volume of the post-earthquake ruins model, the component density distribution is calculated, including:

[0014]

[0015] In the formula, is the component density distribution, is the number of components; is the volume of collapsed ruins; based on the size characteristics of building components in the post-earthquake ruins model, the component size distribution index is calculated, including:

[0016]

[0017] In the formula, is the component size distribution index, is the size of the i-th type component, is the number frequency of the i-th type component.

[0018] Furthermore, based on the geometric and spatial characteristics, the collapse form types of the post-earthquake ruins model are divided, including: the identification index of inclined collapse: relative height ratio: H r ≥0.6; Area expansion ratio: A r ≤1.5; interlayer void ratio: ρ g ≥0.4; Component density distribution: ρ component Has significant directional distribution characteristics (directional distribution deviation exceeds the preset deviation threshold); component size distribution index: S d ≥0.7; Identification index of sandwich type collapse: relative height ratio: 0.3≤H r <0.6; Area expansion ratio: 1.2≤A r ≤2.0; interlayer void ratio: 0.2≤ρ g <0.4; Component density distribution: ρ component Layered distribution; component size distribution index: 0.4≤S d <0.7; Discrimination index of fragmentation and accumulation type collapse: relative height ratio: H r <0.3; Area expansion ratio: A r >2.0; interlayer void ratio: ρ g<0.2; Component density distribution: ρ component Irregular distribution (its distribution entropy is calculated to be close to random distribution characteristics); component size distribution index: S d <0.4.

[0019] Furthermore, the calculation formula of the living space evaluation index includes:

[0020]

[0021] Wherein, SSI is the living space assessment index, and Respectively represent the weight coefficients of relative height ratio and area expansion ratio in living space assessment, and satisfy + =1,0< , <1;

[0022] The calculation formula of the rescue channel complexity index includes:

[0023]

[0024] Wherein, RCI is the rescue channel complexity index, and They represent the weight coefficients of component density distribution, component size distribution and interlayer void ratio in the complexity analysis of rescue channels, and satisfy , 0< <1;

[0025] The calculation formula of the comprehensive rescue difficulty index includes:

[0026]

[0027] Wherein, DRI is the comprehensive rescue difficulty index, and are the weight coefficients of the survival space evaluation index and the rescue channel complexity index, respectively, and satisfy =1,0< , <1.

[0028] Furthermore, the calculation formula for estimating the rescue time includes:

[0029] T = T0 × (1 + k × DRI)

[0030] Among them, T is the estimated rescue time, T0 is the benchmark rescue time, k is the rescue difficulty correction coefficient related to the collapse shape type, and DRI is the comprehensive rescue difficulty index.

[0031] Furthermore, the method further includes revising the estimated rescue time and dynamically revising the remaining rescue time; including:

[0032] T actual =T×α

[0033] α=α1×α2×α3

[0034] In the formula, α is the time extension coefficient, α1 is the component scale influence coefficient, α2 is the space restriction influence coefficient, α3 is the rescue channel influence coefficient, T actual This is the estimated rescue time after correction;

[0035] T revised =T remaining / β

[0036] β = (V actual / V plan )×100%

[0037] Among them, β is the rescue progress evaluation index, T revised T is the corrected remaining rescue time, remaining is the original estimated remaining time, V actual is the actual rescue speed, V plan To plan rescue speed.

[0038] Furthermore, the method further includes: determining a rescue priority based on the estimated rescue time; including:

[0039] P i =w i ×(1 / T i )

[0040] Among them, P i is the priority of the i-th rescue point, w i is the life feature weight of the i-th rescue point, T i is the estimated rescue time of the i-th rescue point.

[0041] On the other hand, a post-earthquake casualty rescue difficulty assessment system based on building collapse morphology is also provided, comprising: a ruins model generation module, a collapse morphology analysis module, a post-earthquake casualty rescue difficulty assessment module and a rescue priority and time optimization module; wherein the ruins model generation module is used to generate a post-earthquake ruins model of the target earthquake zone based on the geometric and mechanical properties of the building structure in the target earthquake zone and the component distribution of the ruins after the building collapses; the collapse morphology analysis module is used to extract the geometric and spatial features of the post-earthquake ruins model, and divide the collapse morphology types of the post-earthquake ruins model based on the geometric and spatial features; the collapse morphology types include Inclined collapse, sandwich collapse and fragmented accumulation collapse; the post-earthquake casualty rescue difficulty assessment module is used to calculate the survival space assessment index and the rescue channel complexity index of the post-earthquake ruins model based on the geometric and spatial characteristics; based on the survival space assessment index and the rescue channel complexity index, the comprehensive rescue difficulty index of the post-earthquake ruins model is calculated; the rescue priority and time optimization module is used to determine the rescue difficulty level of different areas in the post-earthquake ruins model based on the comprehensive rescue difficulty index; based on the comprehensive rescue difficulty index and the collapse morphology type, the estimated rescue time of the post-earthquake ruins model is determined.

[0042] On the other hand, an electronic device is provided, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method provided in the embodiment of the present invention when executing the computer program.

[0043] The present invention provides a method and system for assessing the difficulty of rescuing the injured after an earthquake based on the collapsed morphology of buildings. The method and system can extract and quantify the geometric characteristics and component distribution characteristics of the ruins, consider the geometric characteristics, component distribution characteristics and collapse morphology classification of the ruins, scientifically assess the complexity of the living space and rescue channels, and generate a comprehensive rescue difficulty assessment index and rescue priority recommendations, thereby effectively improving the efficiency of post-earthquake rescue. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0045] Figure 1 A flowchart of a method for assessing the difficulty of rescuing injured persons after an earthquake based on the form of building collapse provided by an embodiment of the present invention;

[0046] Figure 2 A three-dimensional schematic diagram of a post-earthquake ruins model provided by an embodiment of the present invention;

[0047] Figure 3 A schematic diagram of the collapse morphology type provided by an embodiment of the present invention;

[0048] Figure 4 A schematic diagram of the distribution of the comprehensive rescue difficulty index provided by an embodiment of the present invention;

[0049] Figure 5 A schematic diagram of a system for assessing the difficulty of rescuing injured persons after an earthquake based on building collapse patterns provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0050] The technical solution of the present invention is described below in conjunction with the accompanying drawings.

[0051] In the embodiments of the present invention, words such as "exemplarily" and "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "example" in the present invention should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of the word "example" is intended to present the concept in a specific way. In addition, in the embodiments of the present invention, the meaning expressed by "and / or" can be both, or it can be either of the two.

[0052] In order to make the technical problems, technical solutions and advantages to be solved by the present invention more clear, a detailed description will be given below with reference to the accompanying drawings and specific embodiments.

[0053] Embodiment 1

[0054] Figure 1 FIG. 1 is a flowchart of a method for assessing the difficulty of rescuing injured persons after an earthquake based on the form of building collapse according to an embodiment of the present invention. Figure 1 As shown, the method specifically comprises the following steps:

[0055] Step S102, generating a post-earthquake ruins model of the target earthquake zone based on the geometric and mechanical properties of the building structures in the target earthquake zone and the component distribution of the ruins after the building collapses.

[0056] Step S104, extracting geometric and spatial features of the post-earthquake ruins model, and classifying the collapse morphological types of the post-earthquake ruins model based on the geometric and spatial features; the collapse morphological types include inclined collapse, sandwich collapse and fragmentation accumulation collapse.

[0057] Step S106, calculating the survival space evaluation index and rescue channel complexity index of the post-earthquake ruins model based on geometric and spatial features.

[0058] Step S108, calculating the comprehensive rescue difficulty index of the post-earthquake ruins model based on the living space evaluation index and the rescue channel complexity index.

[0059] Step S110, determining the rescue difficulty levels of different areas in the post-earthquake ruins model based on the comprehensive rescue difficulty index.

[0060] Step S112, determining the estimated rescue time of the post-earthquake ruins model based on the comprehensive rescue difficulty index and the collapse morphology type.

[0061] Specifically, step S102 also includes the following steps:

[0062] Step S1021, establishing a simulated building model to be collapsed based on the geometric and mechanical characteristics of the building structure in the target earthquake zone;

[0063] Step S1022, applying earthquake motion to the simulated building model to be collapsed, reproducing the entire building collapse process based on the explicit time integration method, and generating a post-earthquake ruins model reflecting the collapse morphology based on the voxelization method and the nonlinear behavior of the components.

[0064] In an optional implementation provided by an embodiment of the present invention, the geometric and spatial characteristics of the post-earthquake ruins model include: relative height ratio, area expansion ratio, interlayer void ratio, component density distribution and component size distribution index; in step S104, the geometric and spatial characteristics of the post-earthquake ruins model are extracted, including:

[0065] Based on the height of the original building model before collapse and the height of the ruins model after collapse, the relative height ratio is calculated, including:

[0066]

[0067] In the formula, H r is the relative height ratio, is the maximum height of the ruins model after collapse, is the height of the original building model before collapse;

[0068] Based on the projected area of ​​the original building model before collapse and the projected area of ​​the ruins after collapse, the area expansion ratio is calculated, including:

[0069]

[0070] In the formula, A r is the area expansion ratio, is the projected area of ​​the ruins after collapse, It is the projection area of ​​the original building model before collapse;

[0071] Based on the 3D model characteristic data of the post-earthquake ruins model, the interlayer void ratio is calculated, including:

[0072]

[0073] In the formula, ρ g is the interlayer void ratio, Vcomponent is the component volume, V region is the volume of the main building after collapse;

[0074] Based on the number of components per unit volume of the post-earthquake ruins model, the component density distribution is calculated, including:

[0075]

[0076] In the formula, is the component density distribution, is the number of components; is the volume of collapsed ruins;

[0077] Based on the size characteristics of building components in the post-earthquake ruins model, the component size distribution index is calculated, including:

[0078]

[0079] In the formula, is the component size distribution index, is the size of the i-th type component, is the number frequency of the i-th type component.

[0080] Specifically, in step S104, the collapse form types of the post-earthquake ruins model are classified based on geometric and spatial features, including: qualitative classification of the collapse form types and quantitative classification of the collapse form types.

[0081] In an optional implementation manner provided by an embodiment of the present invention, the qualitative classification of collapse morphology types includes:

[0082] (1) Overall configuration characteristics:

[0083] Tilt-type collapse: The building maintains a certain degree of integrity, but tilts or collapses as a whole;

[0084] Sandwich collapse: the distance between floors is significantly reduced, and the floors are stacked in a "pancake" shape;

[0085] Destruction and accumulation type collapse: the building is completely broken and loses its original shape;

[0086] (2) Local damage characteristics:

[0087] Inclined collapse: The connections between components are basically intact and the main structure is not completely broken;

[0088] Sandwich type collapse: a stacking state with very small spacing between floors;

[0089] Fragmentation and accumulation type collapse: components are severely damaged, forming irregular fragments;

[0090] (3) Spatial distribution characteristics:

[0091] Inclined collapse: overall tilt or displacement, with some geometric configurations maintained;

[0092] Sandwich type collapse: obvious compression in the vertical direction, but little change in the horizontal direction;

[0093] Fragmentation accumulation type collapse: random accumulation state, chaotic spatial distribution.

[0094] In an optional implementation provided by an embodiment of the present invention, the quantitative classification index of the collapse morphology type is as follows:

[0095] Determining index of tilt type collapse: relative height ratio: H r ≥0.6; Area expansion ratio: A r ≤1.5; interlayer void ratio: ρ g ≥0.4; Component density distribution: ρ component Has significant directional distribution characteristics (directional distribution deviation exceeds the preset deviation threshold); component size distribution index: S d ≥0.7;

[0096] Identification index of sandwich type collapse: relative height ratio: 0.3≤H r <0.6; Area expansion ratio: 1.2≤A r ≤2.0; interlayer void ratio: 0.2≤ρ g <0.4; Component density distribution: ρ component Layered distribution; component size distribution index: 0.4≤S d <0.7;

[0097] Destruction index of fragmentation and accumulation type collapse: relative height ratio: H r <0.3; Area expansion ratio: A r >2.0; interlayer void ratio: ρ g <0.2; Component density distribution: ρ component Irregular distribution (its distribution entropy is calculated to be close to random distribution characteristics); component size distribution index: S d <0.4.

[0098] In an optional implementation provided by an embodiment of the present invention, step S104 further includes a mixed determination method of the collapse morphology type, including:

[0099] (1) When the ruins model shows a variety of collapse morphological characteristics in different areas, a regional discrimination method is adopted:

[0100] a. Divide the characteristic areas;

[0101] b. Perform morphological discrimination respectively;

[0102] c. Determine the primary and secondary collapse patterns.

[0103] (2) Rules for determining mixed forms:

[0104] a. When a certain morphological feature accounts for more than 60%, it is determined to be the dominant morphology;

[0105] b. When the proportions of various morphological features are close, a combined morphological description is used;

[0106] c. Determine the priority of rescue strategies based on the dominant form.

[0107] Specifically, in the embodiment of the present invention, the calculation formula of the living space evaluation index includes:

[0108]

[0109] Wherein, SSI is the living space assessment index, and Respectively represent the weight coefficients of relative height ratio and area expansion ratio in living space assessment, and satisfy + =1,0< , <1, calculated using the equal weight method;

[0110] The calculation formula of the rescue channel complexity index includes:

[0111]

[0112] Among them, RCI is the rescue channel complexity index, and They represent the weight coefficients of component density distribution, component size distribution and interlayer void ratio in the complexity analysis of rescue channels, and satisfy , 0< <1, determined by equal weight method;

[0113] The calculation formula of the comprehensive rescue difficulty index includes:

[0114]

[0115] Wherein, DRI is the comprehensive rescue difficulty index, and are the weight coefficients of the survival space evaluation index and the rescue channel complexity index, and satisfy =1,0< , <1, determined by equal weight method.

[0116] In an optional implementation provided by an embodiment of the present invention, the rescue difficulty level in step S110 includes: DRI<0.3 is a low difficulty area; 0.3≤DRI<0.6 is a medium difficulty area; 0.6≤DRI<0.8 is a high difficulty area; DRI≥0.8 is an extremely high difficulty area.

[0117] Specifically, in the embodiment of the present invention, the calculation formula for estimating the rescue time includes:

[0118] T = T0 × (1 + k × DRI)

[0119] Among them, T is the estimated rescue time, T0 is the benchmark rescue time, which depends on the rescue team and equipment configuration, k is the rescue difficulty correction coefficient related to the collapse shape type, and DRI is the comprehensive rescue difficulty index.

[0120] In an optional implementation manner provided by an embodiment of the present invention, the rescue difficulty correction coefficients corresponding to different collapse form types are as follows:

[0121] Inclined collapse: k=1.2;

[0122] Sandwich type collapse: k=1.5;

[0123] Destruction accumulation type collapse: k=2.0.

[0124] In an optional implementation provided by an embodiment of the present invention, a method for determining the reference rescue time T0 is as follows:

[0125] Light rescue equipment: T0 = 2 hours;

[0126] Medium rescue equipment: T0 = 1.5 hours;

[0127] Heavy rescue equipment: T0 = 1 hour.

[0128] Preferably, the method provided by the embodiment of the present invention further includes correcting the estimated rescue time and dynamically correcting the remaining rescue time.

[0129] Specifically, the estimated rescue time is revised, including:

[0130] T actual =T×α

[0131] α=α1×α2×α3

[0132] In the formula, α is the time extension coefficient, α1 is the component scale influence coefficient, α2 is the space restriction influence coefficient, α3 is the rescue channel influence coefficient, T actual This is the estimated rescue time after correction;

[0133] For example, the value ranges of various influence coefficients include:

[0134] (1) Component scale influence coefficient α1:

[0135] Small components (<0.5m³): 1.0;

[0136] Medium-sized components (0.5-2m³): 1.3;

[0137] Large components (>2m³): 1.6;

[0138] (2) Space restriction influence coefficient α2:

[0139] Spacious space (>1m): 1.0;

[0140] Confined space (0.5-1m): 1.4;

[0141] Extreme space (<0.5m): 1.8;

[0142] (3) Rescue channel influence coefficient α3:

[0143] Direct channel: 1.0;

[0144] Tortuous passage: 1.3;

[0145] Multiple obstacles:1.6.

[0146] Specifically, the remaining rescue time is dynamically revised, including:

[0147] T revised =T remaining / β

[0148] β = (V actual / V plan )×100%

[0149] Among them, β is the rescue progress evaluation index, T revised T is the corrected remaining rescue time, remaining is the original estimated remaining time, V actual is the actual rescue speed, V plan To plan rescue speed.

[0150] In an optional implementation provided by the embodiment of the present invention, it also includes implementing progress exception processing based on the rescue progress evaluation index. Specifically, it includes:

[0151] When β<0.6, the emergency plan is activated;

[0152] When 0.6≤β<0.8, rescue resources are increased;

[0153] When β≥0.8, maintain the original plan.

[0154] Preferably, the method provided by the embodiment of the present invention further includes: determining the rescue priority based on the estimated rescue time; including:

[0155] P i =w i ×(1 / T i )

[0156] Among them, P i is the priority of the i-th rescue point, w i is the life feature weight of the i-th rescue point, T i is the estimated rescue time of the i-th rescue point.

[0157] Preferably, the method provided by the embodiment of the present invention also includes multi-point rescue time optimization. Specifically, it includes:

[0158] (1) Resource allocation strategy:

[0159] Emergency level: 60% rescue force;

[0160] Emergency level: 30% rescue force;

[0161] Conventional level: 10% rescue force.

[0162] (2) Time optimization goal: min(ΣT i ), constraints:

[0163] The total rescue force does not exceed the existing resources;

[0164] Ensure that the shortest rescue time point is implemented first;

[0165] Consider the distance constraints between rescue points.

[0166] As can be seen from the above description, the embodiment of the present invention provides a method for assessing the difficulty of rescuing injured persons after an earthquake based on the collapse form of a building. The method can be implemented by an electronic device. The method first simulates the collapse of a building by acquiring the building structure parameter information, constructs a three-dimensional ruins model and extracts the collapse characteristics. The model can reflect the density distribution, void ratio and component characteristics of the ruins; then, based on the ruins model, geometric and spatial feature parameters are extracted, and the collapse form is qualitatively classified (such as inclined type, interlayer type, fragmentation accumulation type, etc.), and quantitatively evaluated in combination with the feature parameters to calculate the index value of each form; on this basis, the survival space assessment index (SSI), the rescue channel complexity index (RCI) and the comprehensive rescue difficulty index (DRI) are further calculated, and rescue priority recommendations are generated according to the DRI value to provide a scientific basis for rescue work; finally, the difficulty level of the rescue area is divided according to the comprehensive rescue difficulty index, the estimated rescue time is calculated in combination with the difficulty level, and the rescue plan is dynamically adjusted to optimize resource allocation. Through the above steps, the method realizes the scientific quantification and evaluation of the post-earthquake ruins form and rescue difficulty, and provides important support for accurate and efficient rescue priority division and resource optimization allocation.

[0167] Embodiment 2

[0168] The embodiment of the present invention further illustrates the implementation process of the method provided by the present invention by taking a practical application example.

[0169] Taking a certain area as an example, there are 8 buildings in the area. By acquiring satellite images, the basic outlines and locations of the 8 buildings in the area are identified. Through information collection and machine learning methods, the basic building information such as the structural type, construction year, number of floors, and building height of these buildings is determined.

[0170] Extract the geometric dimensions, material properties and component connection relationships of the collapsed building and establish a "simulated building model to be collapsed".

[0171] By loading the earthquake data, a three-dimensional digital model reflecting the density distribution and void ratio inside the ruins was simulated. Figure 2 As shown in the figure, these models clearly show the spatial configuration and internal structural characteristics of the building after collapse. The overall shape, component fragmentation and spatial distribution characteristics of each building ruin were obtained through analysis.

[0172] In the feature parameter extraction stage, the present invention calculates the relative height ratio H of each building ruin. r , Area expansion ratio A r , interlayer void ratio ρ g , component density distribution ρ component and component size distribution index S d According to key indicators such as Figure 3The collapse form classification standard shown in the figure qualitatively classifies the collapse forms of the eight buildings, of which the inclined type accounts for 12.5% ​​(1 building), the sandwich type accounts for 75% (6 buildings), and the fragmentation and accumulation type accounts for 12.5% ​​(1 building). The classification results provide an important basis for the subsequent rescue difficulty assessment.

[0173] The survival space assessment index (SSI) and rescue channel complexity index (RCI) of each building are calculated. Through the comprehensive analysis of these two indicators, the comprehensive rescue difficulty index (DRI) of each building is obtained, such as Figure 4 The statistical results show that among the 8 buildings, there is 1 building with low difficulty (DRI < 0.4), 0 buildings with medium difficulty (0.4 ≤ DRI < 0.7), 3 buildings with high difficulty (0.7 ≤ DRI < 0.9), and 4 buildings with extremely high difficulty (DRI ≥ 0.9).

[0174] According to the results of the rescue difficulty assessment, the rescue work for the injured was planned and prioritized in different areas. For the injured in one mezzanine-type collapse (low difficulty), light rescue equipment was deployed, and the average rescue time for each injured person was estimated to be 2.3 hours; for the injured in three mezzanine-type collapses (high difficulty), two mezzanine-type collapses (extremely high difficulty), one inclined collapse (extremely high difficulty) and one fragmented accumulation collapse (extremely high difficulty), heavy rescue equipment was deployed, and the average rescue time for each injured person was estimated to be 2.2, 2.5, 2.2 and 3.0 hours respectively.

[0175] In summary, the present invention has established a complete post-earthquake casualty rescue difficulty assessment system through building collapse morphology analysis, survival space assessment and rescue channel complexity analysis, which solves the subjective problem of relying on experience judgment in the traditional rescue process. At the same time, the rescue resource allocation is optimized by difficulty grading, and a differentiated rescue strategy is established, which significantly improves the rescue efficiency. This precise resource allocation method based on difficulty level not only avoids the waste of rescue resources, but also ensures that key difficult areas can obtain sufficient rescue force support. It helps to implement rescue operations efficiently and accurately, which is very necessary to enhance the city's earthquake emergency medical rescue capabilities.

[0176] Embodiment 3

[0177] Figure 5 FIG. 1 is a schematic diagram of a post-earthquake casualty rescue difficulty assessment system based on building collapse morphology according to an embodiment of the present invention. Figure 5 As shown, the system includes: a ruins model generation module 10, a collapse shape analysis module 20, a post-earthquake casualty rescue difficulty assessment module 30 and a rescue priority and time optimization module 40.

[0178] Specifically, the ruins model generation module 10 is used to generate a post-earthquake ruins model of the target earthquake zone based on the geometric and mechanical properties of the building structures in the target earthquake zone and the component distribution of the ruins after the building collapses.

[0179] The collapse morphology analysis module 20 is used to extract the geometric and spatial features of the post-earthquake ruins model, and classify the collapse morphology types of the post-earthquake ruins model based on the geometric and spatial features; the collapse morphology types include inclined collapse, sandwich collapse and fragmentation accumulation collapse.

[0180] The post-earthquake casualty rescue difficulty assessment module 30 is used to calculate the survival space assessment index and rescue channel complexity index of the post-earthquake ruins model based on geometric and spatial features; based on the survival space assessment index and the rescue channel complexity index, calculate the comprehensive rescue difficulty index of the post-earthquake ruins model.

[0181] The rescue priority and time optimization module 40 is used to determine the rescue difficulty level of different areas in the post-earthquake ruins model based on the comprehensive rescue difficulty index; and to determine the estimated rescue time of the post-earthquake ruins model based on the comprehensive rescue difficulty index and the collapse morphology type.

[0182] Specifically, Figure 5 As shown, the ruins model generation module 10 includes a building structure parameter acquisition unit 11, a model construction unit 12 and a collapse feature extraction unit 13.

[0183] Specifically, the building structure parameter acquisition unit 11 is used to extract the geometric shape, material properties and component connection relationship of the destroyed building, and establish a "simulated building model to be collapsed";

[0184] The model building unit 12 is used to simulate the whole process of building collapse by loading earthquake motion, and generate a three-dimensional digital model reflecting the internal density distribution and void ratio of the ruins based on the voxelization method and the nonlinear behavior of the components;

[0185] The collapse feature extraction unit 13 is used to obtain the overall shape, component fragmentation degree and spatial distribution characteristics of the ruins.

[0186] Specifically, Figure 5 As shown, the collapse morphology analysis module 20 includes a geometric feature extraction unit 21 , a collapse morphology qualitative classification unit 22 and a collapse morphology quantitative evaluation unit 23 .

[0187] Specifically, the geometric feature extraction unit 21 is used to extract the geometric and spatial features of the post-earthquake ruins model, including the relative height ratio H r , Area expansion ratio A r , interlayer void ratio ρ g , component density distribution ρ component and component size distribution index S d ;

[0188] The collapse morphology qualitative classification unit 22 is used to qualitatively classify the collapse morphology type of the post-earthquake ruins model into inclined collapse, sandwich collapse and fragmentation accumulation collapse based on the extracted geometric and spatial features;

[0189] The collapse morphology quantitative evaluation unit 23 is used to quantitatively classify the collapse morphology types of the post-earthquake ruins model into inclined collapse, sandwich collapse and fragmentation accumulation collapse based on geometric and spatial characteristics and component distribution characteristics.

[0190] Specifically, Figure 5 As shown, the post-earthquake casualty rescue difficulty assessment module 30 includes a living space assessment unit 31, a rescue channel complexity assessment unit 32 and a comprehensive rescue difficulty assessment unit 33.

[0191] Specifically, the living space assessment unit 31 is used to calculate the living space assessment index (SSI) according to the inter-layer void ratio and component distribution of the ruins model;

[0192] A rescue channel complexity evaluation unit 32 is used to calculate a rescue channel complexity index (RCI) based on the connectivity, density distribution and path length of the internal component network of the ruins;

[0193] The comprehensive rescue difficulty evaluation unit 33 is used to calculate a comprehensive rescue difficulty index (DRI) based on the SSI and the RCI.

[0194] Specifically, the rescue priority and time optimization module 40 is also used to correct the estimated rescue time and dynamically correct the remaining rescue time; and, is used to determine the rescue priority based on the estimated rescue time.

[0195] The present invention further provides an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method provided in the embodiment of the present invention when executing the computer program.

[0196] An embodiment of the present invention further provides a computer-readable storage medium, which stores computer instructions. When the computer instructions are executed by a processor, the method provided by the embodiment of the present invention is implemented.

[0197] It should be understood that the memory in the embodiments of the present invention may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable ROM (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of random access memory (RAM) are available, such as static RAM (SRAM), dynamic random access memory (DRAM), synchronous DRAM (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link DRAM (SLDRAM), and direct rambus RAM (DR RAM).

[0198] The above embodiments can be implemented in whole or in part by software, hardware (such as circuits), firmware or any other combination. When implemented by software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present invention is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center by wired (such as infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (for example, a floppy disk, a hard disk, a tape), an optical medium (for example, a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0199] It should be understood that in various embodiments of the present invention, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0200] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0201] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described equipment, devices and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0202] In the several embodiments provided by the present invention, it should be understood that the disclosed devices, apparatuses and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0203] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0204] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0205] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, and other media that can store program codes.

[0206] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A method for assessing the difficulty of rescuing injured persons after an earthquake based on the form of building collapse, characterized in that: The method comprises: Based on the geometric and mechanical properties of the building structures in the target earthquake zone and the component distribution of the ruins after the building collapses, a post-earthquake ruins model of the target earthquake zone is generated; Extracting geometric and spatial features of the post-earthquake ruins model, and classifying the collapse form types of the post-earthquake ruins model based on the geometric and spatial features; the collapse form types include inclined collapse, sandwich collapse and fragmentation accumulation collapse; Based on the geometric and spatial characteristics, calculating the survival space evaluation index and the rescue channel complexity index of the post-earthquake ruins model; Calculating a comprehensive rescue difficulty index of the post-earthquake ruins model based on the living space evaluation index and the rescue channel complexity index; Based on the comprehensive rescue difficulty index, determining the rescue difficulty levels of different areas in the post-earthquake ruins model; Based on the comprehensive rescue difficulty index and the collapse form type, an estimated rescue time of the post-earthquake ruins model is determined.

2. The method according to claim 1, characterized in that: Based on the geometric and mechanical properties of the building structures in the target earthquake zone and the component distribution of the ruins after the building collapses, a post-earthquake ruins model of the target earthquake zone is generated, including: Based on the geometric and mechanical characteristics of the building structure in the target earthquake zone, a simulated building model to be collapsed is established; The earthquake motion is applied to the simulated building model to be collapsed, the whole process of building collapse is reproduced based on the explicit time integration method, and a post-earthquake ruins model reflecting the collapse morphology is generated based on the voxelization method and the nonlinear behavior of the components.

3. The method according to claim 1, characterized in that: The geometric and spatial characteristics of the post-earthquake ruins model include: relative height ratio, area expansion ratio, interlayer void ratio, component density distribution and component size distribution index; extracting the geometric and spatial characteristics of the post-earthquake ruins model includes: Based on the height of the original building model before collapse and the height of the ruins model after collapse, the relative height ratio is calculated, including: ； In the formula, H r is the relative height ratio, is the maximum height of the ruins model after collapse, is the height of the original building model before collapse; The area expansion ratio is calculated based on the projection area of ​​the original building model before the collapse and the projection area of ​​the ruins after the collapse, including: ； In the formula, A r is the area expansion ratio, is the projected area of ​​the ruins after collapse, It is the projection area of ​​the original building model before collapse; Calculating the interlayer void ratio based on the three-dimensional model characteristic data of the post-earthquake ruins model includes: ； In the formula, ρ g is the interlayer void ratio, V component is the component volume, V region is the volume of the main building after collapse; Calculating the component density distribution based on the number of components in the unit volume of the post-earthquake ruins model includes: ； In the formula, is the component density distribution, is the number of components; is the volume of collapsed ruins; Calculating the component size distribution index based on the size characteristics of the building components in the post-earthquake ruins model includes: ； In the formula, is the component size distribution index , is the size of the i-th type component, is the number frequency of the i-th type component.

4. The method according to claim 3, characterized in that: The collapse form types of the post-earthquake ruins model are divided based on the geometric and spatial characteristics, including: Determining index of tilt type collapse: relative height ratio: H r ≥0.6; Area expansion ratio: A r ≤1.5; interlayer void ratio: ρ g ≥0.4; Component density distribution: ρ component The directional distribution deviation exceeds the preset deviation threshold; component size distribution index: S d ≥0.7; Identification index of sandwich type collapse: relative height ratio: 0.3≤H r <0.6; Area expansion ratio: 1.2≤A r ≤2.0; interlayer void ratio: 0.2≤ρ g <0.4; Component density distribution: ρ component Layered distribution; component size distribution index: 0.4≤S d <0.7; Destruction index of fragmentation and accumulation type collapse: relative height ratio: H r <0.3; Area expansion ratio: A r >2.0; interlayer void ratio: ρ g <0.2; Component density distribution: ρ component Irregular distribution; component size distribution index: S d <0.

4.

5. The method according to claim 3, characterized in that: The calculation formula of the living space evaluation index includes: ； Wherein, SSI is the living space assessment index, and Respectively represent the weight coefficients of relative height ratio and area expansion ratio in living space assessment, and satisfy + =1,0< , <1; The calculation formula of the rescue channel complexity index includes: ； Wherein, RCI is the rescue channel complexity index, and They represent the weight coefficients of component density distribution, component size distribution and interlayer void ratio in the complexity analysis of rescue channels, and satisfy , 0< <1; The calculation formula of the comprehensive rescue difficulty index includes: ； Wherein, DRI is the comprehensive rescue difficulty index, and are the weight coefficients of the survival space evaluation index and the rescue channel complexity index, respectively, and satisfy =1,0< , <1.

6. The method according to claim 1, characterized in that: The calculation formula for the estimated rescue time includes: T = T0 × (1 + k × DRI) Among them, T is the estimated rescue time, T0 is the benchmark rescue time, k is the rescue difficulty correction coefficient related to the collapse shape type, and DRI is the comprehensive rescue difficulty index.

7. The method according to claim 6, characterized in that: The method further includes revising the estimated rescue time and dynamically revising the remaining rescue time; including: T actual =T×α α=α1×α2×α3 In the formula, α is the time extension coefficient, α1 is the component scale influence coefficient, α2 is the space restriction influence coefficient, α3 is the rescue channel influence coefficient, T actual This is the estimated rescue time after correction; T revised =T remaining / β β=(V actual / V plan )×100% Among them, β is the rescue progress evaluation index, T revised is the corrected remaining rescue time, T remaining is the original estimated remaining time, V actual is the actual rescue speed, V plan To plan rescue speed.

8. The method according to claim 1, characterized in that: The method further includes: determining a rescue priority based on the estimated rescue time; including: P i =w i ×(1 / T i ) Among them, P i is the priority of the i-th rescue point, w i is the life feature weight of the i-th rescue point, T i is the estimated rescue time of the i-th rescue point.

9. A post-earthquake casualty rescue difficulty assessment system based on building collapse morphology, characterized in that: include: The module includes the ruins model generation module, the collapse morphology analysis module, the post-earthquake casualty rescue difficulty assessment module, and the rescue priority and time optimization module. The ruins model generation module is used to generate a post-earthquake ruins model of the target earthquake zone based on the geometric and mechanical properties of the building structures in the target earthquake zone and the component distribution of the ruins after the building collapses; The collapse morphology analysis module is used to extract the geometric and spatial features of the post-earthquake ruins model, and classify the collapse morphology types of the post-earthquake ruins model based on the geometric and spatial features; the collapse morphology types include inclined collapse, sandwich collapse and fragmentation accumulation collapse; The post-earthquake casualty rescue difficulty assessment module is used to calculate the survival space assessment index and the rescue channel complexity index of the post-earthquake ruins model based on the geometric and spatial features; based on the survival space assessment index and the rescue channel complexity index, calculate the comprehensive rescue difficulty index of the post-earthquake ruins model; The rescue priority and time optimization module is used to determine the rescue difficulty levels of different areas in the post-earthquake ruins model based on the comprehensive rescue difficulty index; Based on the comprehensive rescue difficulty index and the collapse form type, an estimated rescue time of the post-earthquake ruins model is determined.

10. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method according to any one of claims 1 to 8 when executing the computer program.

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