Method and System for Evaluating the Difficulty of Rescuing Earthquake Victims Based on the Collapse Pattern of Buildings

Abstract

The present invention discloses a method and system for evaluating the rescue difficulty of post-earthquake wounded persons based on the building collapse form, which relates to the technical field of post-earthquake rescue, and includes: extracting the geometric form and attribute information of damaged buildings based on the earthquake damage analysis of the target earthquake area, and establishing a to-be-collapsed simulation building model; loading ground motion on the to-be-collapsed simulation building model, and generating a post-earthquake rubble model reflecting the collapse form based on the explicit time integration method; extracting the geometric and spatial features of the post-earthquake rubble model, and classifying the collapse form types of the post-earthquake rubble model; calculating the comprehensive rescue difficulty index of the post-earthquake rubble model based on the survival space evaluation index and the rescue passage complexity index; determining the rescue difficulty levels of different regions in the post-earthquake rubble model based on the comprehensive rescue difficulty index; and determining the estimated rescue time of the post-earthquake rubble model based on the comprehensive rescue difficulty index and the collapse form type. The present invention alleviates the technical problem that the post-earthquake rubble in the prior art is difficult to quantitatively evaluate.

Description

Technical Field

[0001] The present invention relates to the technical field of post-earthquake rescue, and particularly to a method and system for evaluating the rescue difficulty of post-earthquake wounded based on the building collapse form. Background Art

[0002] Earthquake disasters are one of the most serious natural disasters, which often result in a large number of building collapses and casualties. The ruins formed after the building collapses not only directly threaten the lives of survivors, but also block the rescue channels, delay rescue operations, and further exacerbate the losses. The core goal of post-earthquake rescue work is to quickly evaluate the survival space of the wounded inside the ruins and the feasibility of the rescue channels, formulate a scientific rescue priority, and save lives to the greatest extent. However, due to the complex and changeable form of the ruins, the existing rescue difficulty evaluation 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 its impact on rescue is of great significance for improving the post-earthquake rescue efficiency and optimizing resource allocation.

[0003] In recent years, certain progress has been made in the research on the morphology of post-earthquake building ruins (Shuochen Shan. Research on the seismic collapse mode and the structural characteristics of the ruins of typical bottom-frame masonry structures [D]. Heilongjiang: Institute of Engineering Mechanics, China Earthquake Administration, 2015; Nan Wang, Shugen Ma, Bin Li, et al. Simultaneous localization and mapping for the internal earthquake damage morphology [J]. Chinese Science Bulletin, 2013(S2): 104-111; Pollino M, Cappucci S, Giordano L, et al. Assessing earthquake-induced urban rubble by means of multiplatform remotely sensed data [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 2016 Kumamoto, Japan, earthquake from Lidar data [J]. Nat. Hazards Earth Syst. Sci, 2017, 18: 65; Yu Wang. Research on building multi-scale earthquake damage identification and assessment enhanced by geometric constraint deep learning [D]. Gansu: Lanzhou University, 2023). However, these studies mainly focus on the detection and classification of collapsed buildings, and there is a lack of analysis on the geometric features, survival space, and complexity of rescue channels inside the ruins. In addition, existing methods mostly rely on experience to qualitatively classify the morphology of the ruins, lacking a systematic quantitative evaluation standard. There is a lack of a unified analysis method for the geometric features and component distribution characteristics of different collapse types (such as inclined type, sandwich type, fragmented accumulation type), making it difficult to accurately describe the complexity of the ruins. Summary of the Invention

[0004] To solve the above technical problems existing in the prior art, an embodiment of the present invention provides a method and system for evaluating the rescue difficulty of earthquake victims based on the building collapse morphology. The technical solution is as follows:

[0005] On the one hand, a method for evaluating the rescue difficulty of earthquake victims based on the building collapse form is provided, including: generating a post-earthquake debris model of the target earthquake area based on the geometric and mechanical characteristics of the building structure in the target earthquake area and the component distribution of the debris after the building collapses; extracting the geometric and spatial characteristics of the post-earthquake debris model, and dividing the collapse form types of the post-earthquake debris model based on the geometric and spatial characteristics; the collapse form types include inclined collapse, sandwich collapse, and fragmented accumulation collapse; calculating the survival space evaluation index and the rescue passage complexity index of the post-earthquake debris model based on the geometric and spatial characteristics; calculating the comprehensive rescue difficulty index of the post-earthquake debris model based on the survival space evaluation index and the rescue passage complexity index; determining the rescue difficulty levels of different regions in the post-earthquake debris model based on the comprehensive rescue difficulty index; and determining the estimated rescue time of the post-earthquake debris model based on the comprehensive rescue difficulty index and the collapse form type.

[0006] Further, generating the post-earthquake debris model of the target earthquake area based on the geometric and mechanical characteristics of the building structure in the target earthquake area and the component distribution of the debris after the building collapses includes: establishing a building model to be collapsed and simulated based on the geometric and mechanical characteristics of the building structure in the target earthquake area; loading ground motion on the building model to be collapsed and simulated, reproducing the whole process of building collapse based on the explicit time integration method, and generating a post-earthquake debris model reflecting the collapse form based on the voxelization method and the nonlinear behavior of components.

[0007] Further, the geometric and spatial characteristics of the post-earthquake debris 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 debris model includes: calculating the relative height ratio based on the height of the original building model before collapse and the height of the post-earthquake debris model after collapse, including:

[0008]

[0009] wherein, H r is the relative height ratio, is the maximum height of the post-earthquake debris model after collapse, is the height of the original building model before collapse; calculating the area expansion ratio based on the projected area of the original building model before collapse and the projected area of the post-earthquake debris, including:

[0010]

[0011] wherein, A r is the area expansion ratio, is the projected area of the post-earthquake debris after collapse, is the projected area of the original building model before collapse; based on the three-dimensional model feature data of the post-earthquake ruins model, calculating the inter-story void ratio, including:

[0012]

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

[0014]

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

[0016]

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

[0018] Further, based on the geometric and spatial characteristics, classifying the collapse form types of the post-earthquake ruins model, including: Discriminant indexes for inclined collapse: Relative height ratio: H r ≥0.6; Area expansion ratio: A r ≤1.5; Inter-story void ratio: ρ g ≥0.4; Component density distribution: ρ component has a significant directional distribution characteristic (the directional distribution deviation exceeds the preset deviation threshold); Component size distribution index: S d ≥0.7; Discriminant indexes for sandwich-type collapse: Relative height ratio: 0.3 ≤ H r <0.6; Area expansion ratio: 1.2 ≤ A r ≤2.0; Inter-story void ratio: 0.2 ≤ ρ g <0.4; Component density distribution: ρ component shows a layered distribution; Component size distribution index: 0.4 ≤ S d <0.7; Discriminant indexes for fragmented accumulation-type collapse: Relative height ratio: H r <0.3; Area expansion ratio: A r >2.0; Inter-story void ratio: ρ g< 0.2; Component density distribution: ρ component Show an irregular distribution (the calculated distribution entropy value is close to the characteristics of random distribution); Component size distribution index: S d < 0.4.

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

[0020]

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

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

[0023]

[0024] Wherein, RCI is the rescue passage complexity index, and respectively represent the weight coefficients of the component density distribution, the component size distribution, and the interlayer void ratio in the rescue passage complexity analysis, 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 respectively the weight coefficients of the survival space evaluation index and the rescue passage complexity index, and satisfy = 1, 0 < , < 1.

[0028] Furthermore, the calculation formula of the estimated rescue time includes:

[0029] T = T 0 × (1 + k × DRI)

[0030] Wherein, T is the estimated rescue time, T 0 is the benchmark rescue time, k is the rescue difficulty correction coefficient related to the collapse form type, and DRI is the comprehensive rescue difficulty index.

[0031] Further, the method further includes correcting the estimated rescue time and dynamically correcting the remaining rescue time, including:

[0032] T actual = T × α

[0033] α = α 1 × α 2 × α 3

[0034] In the formula, α is the time extension coefficient, α 1 is the component scale influence coefficient, α 2 is the space limitation influence coefficient, α 3 is the rescue passage influence coefficient, T actual is the corrected estimated rescue time;

[0035] T revised = T remaining / β

[0036] β = (V actual / V plan ) × 100%

[0037] where β is the rescue progress evaluation index, T revised is the remaining rescue time after correction, T remaining is the original estimated remaining time, V actual is the actual rescue speed, V plan is the planned rescue speed.

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

[0039] P i = w i × (1 / T i )

[0040] where P i is the priority of the i-th rescue point, w i is the life characteristic 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 the building collapse form is also provided, including: a ruins model generation module, a collapse form 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 area based on the geometric and mechanical characteristics of the building structure in the target earthquake area and the component distribution of the ruins after the building collapses; the collapse form analysis module is used to extract the geometric and spatial characteristics of the post-earthquake ruins model and divide the collapse form types of the post-earthquake ruins model based on the geometric and spatial characteristics; the collapse form 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 passage complexity index of the post-earthquake ruins model based on the geometric and spatial characteristics; and calculate the comprehensive rescue difficulty index of the post-earthquake ruins model based on the survival space assessment index and the rescue passage complexity index; the rescue priority and time optimization module is used to determine the rescue difficulty levels of different regions in the post-earthquake ruins model based on the comprehensive rescue difficulty index; and determine the estimated rescue time of the post-earthquake ruins model based on the comprehensive rescue difficulty index and the collapse form type.

[0042] On the other hand, an electronic device is also provided, including: a memory, a processor, and a computer program stored on the memory and executable on the processor, and when the processor executes the computer program, the method provided in the embodiment of the present invention is implemented.

[0043] The present invention provides a method and system for assessing the rescue difficulty of post-earthquake casualties based on the building collapse form, which can extract and quantify the geometric features and component distribution features of the ruins, consider the geometric features, component distribution features and collapse form classification of the ruins, scientifically evaluate the survival space and the complexity of the rescue passage, and generate a comprehensive rescue difficulty assessment index and rescue priority suggestions, thereby effectively improving the post-earthquake rescue efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present invention, and those of ordinary skill in the art can obtain other drawings without creative efforts based on these drawings.

[0045] Figure 1 It is a flowchart of a method for assessing the rescue difficulty of post-earthquake casualties based on the building collapse form provided by an embodiment of the present invention;

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

[0047] Figure 3 Schematic diagram of the collapse form type provided by the embodiment of the present invention;

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

[0049] Figure 5 Schematic diagram of a post-earthquake casualty rescue difficulty assessment system based on building collapse forms provided by the embodiment of the present invention. Detailed implementation manners

[0050] The following describes the technical solutions in the present invention with reference to the accompanying drawings.

[0051] In the embodiments of the present invention, words such as "exemplarily" and "for example" are used to represent examples, illustrations or explanations. Any embodiment or design solution described as "example" in the present invention should not be construed as being more preferred or having more advantages than other embodiments or design solutions. Exactly speaking, the use of the word "example" is intended to present concepts in a specific way. In addition, in the embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one of the two.

[0052] To make the technical problems, technical solutions and advantages to be solved by the present invention clearer, the following will be described in detail with reference to the accompanying drawings and specific embodiments.

[0053] Embodiment 1

[0054] Figure 1 It is a flowchart of a method for assessing the post-earthquake casualty rescue difficulty based on building collapse forms provided by the embodiment of the present invention. As Figure 1 shown, the method specifically includes the following steps:

[0055] Step S102, generate a post-earthquake debris model of the target earthquake area based on the geometric and mechanical characteristics of the building structure in the target earthquake area and the component distribution of the debris after the building collapses.

[0056] Step S104, extract the geometric and spatial characteristics of the post-earthquake debris model, and divide the collapse form types of the post-earthquake debris model based on the geometric and spatial characteristics; the collapse form types include inclined collapse, sandwich collapse, and fragmented accumulation collapse.

[0057] Step S106, calculate the survival space assessment index and the rescue passage complexity index of the post-earthquake debris model based on the geometric and spatial characteristics.

[0058] Step S108, calculate the comprehensive rescue difficulty index of the post-earthquake debris model based on the survival space assessment index and the rescue passage complexity index.

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

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

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

[0062] Step S1021: Establish a building model to be collapsed and simulated based on the geometric and mechanical characteristics of the building structure in the target earthquake area.

[0063] Step S1022: Apply ground motion to the building model to be collapsed and simulated, reproduce the whole process of building collapse based on the explicit time integration method, and generate a post-earthquake ruins model reflecting the collapse form based on the voxelization method and the nonlinear behavior of components.

[0064] In an optional implementation manner provided by the 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, extracting the geometric and spatial characteristics of the post-earthquake ruins model includes:

[0065] Calculating the relative height ratio based on the height of the original building model before collapse and the height of the post-earthquake ruins model, including:

[0066]

[0067] where H r is the relative height ratio, is the maximum height of the post-earthquake ruins model, is the height of the original building model before collapse;

[0068] Calculating the area expansion ratio based on the projected area of the original building model before collapse and the projected area of the post-earthquake ruins, including:

[0069]

[0070] where A r is the area expansion ratio, is the projected area of the post-earthquake ruins, is the projected area of the original building model before collapse;

[0071] Calculating the interlayer void ratio based on the three-dimensional model feature data of the post-earthquake ruins model, including:

[0072]

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

[0074] Based on the number of components per unit volume in the post-earthquake rubble model, calculate the component density distribution, including:

[0075]

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

[0077] Based on the dimensional characteristics of the building components in the post-earthquake rubble model, calculate the component size distribution index, including:

[0078]

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

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

[0081] In an alternative implementation provided by the embodiments of the present invention, the qualitative classification of the collapse form types includes:

[0082] (1) Overall configuration characteristics:

[0083] Inclined collapse: The building remains somewhat intact and tilts or collapses as a whole;

[0084] Interlayer collapse: The floor spacing is significantly reduced and stacked in a "pancake" shape;

[0085] Fragmented accumulation collapse: The building is completely broken and loses its original shape;

[0086] (2) Local damage characteristics:

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

[0088] Interlayer collapse: A stacked state with a very small spacing is formed between the floors;

[0089] Fragmented accumulation collapse: The components are severely damaged and form irregular fragments;

[0090] (3) Spatial distribution characteristics:

[0091] Inclined collapse: overall inclination or displacement, with part of the geometric configuration remaining;

[0092] Interlayer collapse: obvious compression in the vertical direction and less change in the horizontal direction;

[0093] Fragmented accumulation collapse: random accumulation state, with chaotic spatial distribution.

[0094] In an alternative implementation provided by the embodiments of the present invention, the quantitative classification indicators for the collapse form types are as follows:

[0095] Discrimination indicators for 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 Having a significant directional distribution characteristic (the directional distribution deviation exceeds the preset deviation threshold); component size distribution index: S d ≥0.7;

[0096] Discrimination indicators for interlayer 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 Showing a layered distribution; component size distribution index: 0.4 ≤ S d <0.7;

[0097] Discrimination indicators for fragmented accumulation 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 Showing a random distribution (after calculation, its distribution entropy value is close to the random distribution characteristic); component size distribution index: S d <0.4.

[0098] In an alternative implementation provided by the embodiments of the present invention, step S104 further includes a mixed discrimination method for the collapse form type, including:

[0099] (1) When the ruins model shows multiple collapse form characteristics in different regions, adopt a sub-region discrimination method:

[0100] a. Divide the characteristic regions;

[0101] b. Conduct form discrimination separately;

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

[0103] (2)Discrimination rules for mixed forms:

[0104] a. When the proportion of a certain morphological feature exceeds 60%, it is determined as the dominant form;

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

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

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

[0108]

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

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

[0111]

[0112] Wherein, RCI is the rescue passage complexity index, and respectively represent the weight coefficients of the component density distribution, the component size distribution, and the interlayer void ratio in the rescue passage complexity analysis, and satisfy , 0 < < 1, and is determined by the 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 respectively the weight coefficients of the living space evaluation index and the rescue passage complexity index, and satisfy = 1, 0 < , < 1, and is determined by the equal weight method.

[0116] In an alternative embodiment provided by the embodiments of the present invention, the rescue difficulty levels in step S110 include: 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 embodiments of the present invention, the calculation formula for estimating the rescue time includes:

[0118] T = T 0 ×(1 + k × DRI)

[0119] where T is the estimated rescue time, T 0 is the benchmark rescue time, which depends on the rescue team and equipment configuration, k is the rescue difficulty correction coefficient related to the type of collapse form, and DRI is the comprehensive rescue difficulty index.

[0120] In an alternative embodiment provided by the embodiments of the present invention, the rescue difficulty correction coefficients corresponding to different types of collapse forms are as follows:

[0121] Inclined collapse: k = 1.2;

[0122] Interlayer collapse: k = 1.5;

[0123] Fragmented accumulation collapse: k = 2.0.

[0124] In an alternative embodiment provided by the embodiments of the present invention, the method for determining the benchmark rescue time T 0 is as follows:

[0125] Light rescue equipment: T 0 = 2 hours;

[0126] Medium rescue equipment: T 0 = 1.5 hours;

[0127] Heavy rescue equipment: T 0 = 1 hour.

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

[0129] Specifically, correcting the estimated rescue time includes:

[0130] T actual = T × α

[0131] α = α 1 × α 2 × α 3

[0132] Where α is the time extension coefficient, α 1 is the component scale influence coefficient, α 2 is the space constraint influence coefficient, α 3 is the rescue passage influence coefficient, T actual is the estimated rescue time after correction;

[0133] For example, the value ranges of each influence coefficient include:

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

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

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

[0137] Large components (>2m³): 1.6;

[0138] (2) Space constraint influence coefficient α 2 :

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

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

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

[0142] (3) Rescue passage influence coefficient α 3 :

[0143] Direct passage: 1.0;

[0144] Winding passage: 1.3;

[0145] Multiple obstacles: 1.6.

[0146] Specifically, the dynamic correction of the remaining rescue time includes:

[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 is the remaining rescue time after correction, T remaining is the original estimated remaining time, V actual is the actual rescue speed, V plan is the planned rescue speed.

[0150] In an alternative implementation provided by the embodiments of the present invention, it further includes implementing progress anomaly handling based on rescue progress evaluation metrics. Specifically, it includes:

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

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

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

[0154] Preferably, the method provided by the embodiments 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] Where P i is the priority of the i-th rescue point, w i is the life characteristic weight of the i-th rescue point, and T i is the estimated rescue time of the i-th rescue point.

[0157] Preferably, the method provided by the embodiments of the present invention further includes optimizing the multi-point rescue time. Specifically, it includes:

[0158] (1) Resource allocation strategy:

[0159] Extra urgent level: 60% of the rescue force;

[0160] Urgent level: 30% of the rescue force;

[0161] Regular level: 10% of the rescue force.

[0162] (2) Time optimization objective: min(ΣT i ), constraint conditions:

[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 constraint between rescue points.

[0166] As described above, the embodiment of the present invention provides a method for evaluating the rescue difficulty of earthquake victims based on the building collapse form. This method can be implemented by an electronic device. First, the method performs building earthquake collapse simulation by obtaining building structure parameter information, constructs a three-dimensional ruins model, and extracts collapse features. This model can reflect the density distribution, porosity, and component characteristics of the ruins. Subsequently, geometric and spatial feature parameters are extracted based on the ruins model, the collapse form is qualitatively classified (such as inclined type, sandwich type, fragmented accumulation type, etc.), and quantitative evaluation is carried out in combination with the feature parameters to calculate the index values of each form. On this basis, the survival space evaluation index (SSI), the rescue passage complexity index (RCI), and the comprehensive rescue difficulty index (DRI) are further calculated, and rescue priority suggestions 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, this 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 with an actual application example.

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

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

[0171] Seismic motion data is loaded to simulate and generate a three-dimensional digital model that reflects the density distribution and porosity inside the ruins. As Figure 2 shown, these models clearly show the spatial configuration and internal structural characteristics after the building collapses. Through analysis, the overall form, component fragmentation degree, and spatial distribution characteristics of the ruins of each building are obtained.

[0172] In the feature parameter extraction link, the present invention calculates the relative height ratio H r 、area expansion ratio A r 、interlayer porosity ρ g 、component density distribution ρ component and component size distribution index S d and other key indicators for each building ruins. According to Figure 3According to the collapse pattern classification criteria shown, the collapse patterns of 8 buildings were qualitatively classified. Among them, the inclined type accounted for 12.5% (1 building), the sandwich type accounted for 75% (6 buildings), and the fragmented accumulation type accounted for 12.5% (1 building). This classification result provides an important basis for the subsequent assessment of rescue difficulty.

[0173] Calculate the survival space assessment index (SSI) and the rescue passage complexity index (RCI) for each building. Through the comprehensive analysis of these two indicators, the comprehensive rescue difficulty index (DRI) of each building was obtained, as Figure 4 shown. 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 rescue difficulty assessment results, the wounded rescue work was planned in zones and prioritized. For the wounded in 1 building with a sandwich - type collapse (low difficulty), light rescue equipment was configured, and the estimated average rescue time for each wounded was 2.3 hours; for the wounded in 3 buildings with a sandwich - type collapse (high difficulty), 2 buildings with a sandwich - type collapse (extremely high difficulty), 1 building with an inclined - type collapse (extremely high difficulty), and 1 building with a fragmented accumulation - type collapse (extremely high difficulty), heavy rescue equipment was deployed, and the estimated average rescue time for each wounded was 2.2, 2.5, 2.2, and 3.0 hours respectively.

[0175] In summary, through the analysis of building collapse patterns, survival space assessment, and rescue passage complexity analysis, the present invention has established a complete post - earthquake wounded rescue difficulty assessment system, solving the subjectivity problem of relying on experience judgment in the traditional rescue process. At the same time, by optimizing the allocation of rescue resources according to the difficulty level and establishing a differentiated rescue strategy, the rescue efficiency has been significantly improved. This precise resource allocation method based on the difficulty level not only avoids the waste of rescue resources but also ensures that key and difficult areas can obtain sufficient rescue force support. It helps to implement rescue operations efficiently and accurately, which is very necessary for enhancing the urban earthquake emergency medical rescue ability.

[0176] Embodiment III

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

[0178] Specifically, the post-earthquake ruins model generation module 10 is used to generate a post-earthquake ruins model of the target earthquake area based on the geometric and mechanical characteristics of the building structures in the target earthquake area and the distribution of components in the ruins after the buildings collapse.

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

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

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

[0182] Specifically, as Figure 5 shown, the post-earthquake 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 form, material properties, and component connection relationships of the damaged buildings and establish a "building model to be simulated for collapse".

[0184] The model construction unit 12 is used to simulate the whole process of building collapse by loading ground motions, and generate a three-dimensional digital model reflecting the internal density distribution and porosity of the ruins based on the voxel method and the nonlinear behavior of components.

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

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

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

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

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

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

[0191] Specifically, the survival space assessment unit 31 is used to calculate the survival space assessment index (SSI) according to the interlayer void ratio and component distribution of the debris model;

[0192] The rescue passage complexity assessment unit 32 is used to calculate the rescue passage complexity index (RCI) based on the connectivity, density distribution, and path length of the component network inside the debris;

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

[0194] Specifically, the rescue priority and time optimization module 40 is further 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 also provides an electronic device, including: a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor implements the method provided by the embodiments of the present invention when executing the computer program.

[0196] The embodiments of the present invention also provide a computer-readable storage medium, where the computer-readable storage medium stores computer instructions, and the computer instructions implement the method provided by the embodiments of the present invention when executed by a processor.

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

[0198] The above embodiments can be implemented in whole or in part by software, hardware (such as circuits), firmware, or any combination thereof. When implemented using 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 processes or functions described in the embodiments of the present invention are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another. 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.) means. 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 collections of available media. The available media can be magnetic media (such as floppy disks, hard disks, magnetic tapes), optical media (such as DVDs), or semiconductor media. The semiconductor media can be a solid-state drive.

[0199] It should be understood that in various embodiments of the present invention, the order numbers of the above processes do not imply the order of execution. The order of execution of each process should be determined by its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.

[0200] Those of ordinary skill in the art can realize that the units and algorithm steps of the examples described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present invention.

[0201] Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working processes of the devices, apparatuses, and units described above can refer to the corresponding processes in the foregoing method embodiments and will not be described herein again.

[0202] In 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 merely illustrative. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods. For example, 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 displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces. The indirect couplings or communication connections of the devices or units can be in electrical, mechanical, or other forms.

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

[0204] In addition, in each embodiment of the present invention, the functional units can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in 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 such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs that can store program codes.

[0206] As described above, the above are only the specific implementation manners of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention can easily think of changes or substitutions, which should all be covered by the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to 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; Determining an estimated rescue time of the post-earthquake ruins model based on the comprehensive rescue difficulty index and the collapse form type; 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.

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 collapse form types of the post-earthquake ruins model are divided based on the geometric and spatial characteristics, including: Indicators for judging 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 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; Discrimination index of fragmentation 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.

4. The method according to claim 1, characterized in that: The calculation formula of the living space evaluation index includes: ； in, SSI is the living space evaluation index, and Respectively represent the weight coefficients of relative height ratio and area expansion ratio in living space assessment, and satisfy , ; The calculation formula of the rescue channel complexity index includes: ； in, 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 , ; The calculation formula of the comprehensive rescue difficulty index includes: ； in, 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 , .

5. The method according to claim 1, characterized in that: The calculation formula for the estimated rescue time includes: T = T 0 ×(1+ k × DRI ) in, T is the estimated rescue time, T 0 is the benchmark rescue time, k is the rescue difficulty correction factor related to the collapse type, DRI It is the comprehensive rescue difficulty index.

6. The method according to claim 5, characterized in that: The method further includes revising the estimated rescue time and dynamically revising the remaining rescue time; include: T actual = T × α α = α 1 × α 2 × α 3 In the formula, α is the time extension factor, α 1 is the component scale influence coefficient, α 2 is the spatial restriction influence coefficient, α 3 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% in, β As an indicator for evaluating the progress of rescue, T revised The remaining rescue time after correction. T remaining is the original estimated remaining time, V actual is the actual rescue speed, V plan To plan rescue speed.

7. 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 ) in, P i For the i Rescue point priority, w i For the i The life feature weight of each rescue point, T i For the i The estimated rescue time for each rescue point.

8. 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 level of different areas in the post-earthquake ruins model based on the comprehensive rescue difficulty index; and determine the estimated rescue time of the post-earthquake ruins model based on the comprehensive rescue difficulty index and the collapse morphology type; 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.

9. 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 7 when executing the computer program.

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