CN117035323A - Method and system for scheduling and distributing fire-fighting resources in building based on BIM data - Google Patents

Method and system for scheduling and distributing fire-fighting resources in building based on BIM data Download PDF

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CN117035323A
CN117035323A CN202311019758.5A CN202311019758A CN117035323A CN 117035323 A CN117035323 A CN 117035323A CN 202311019758 A CN202311019758 A CN 202311019758A CN 117035323 A CN117035323 A CN 117035323A
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辛业洪
郑永康
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Shenzhen Jiarui Construction Information Technology Co ltd
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Abstract

The invention relates to the technical field of digital information, and discloses a method and a system for scheduling and distributing fire-fighting resources in a building based on BIM data, wherein the method comprises the following steps: performing data fusion on BIM data and sensor data to obtain multidimensional fusion data; constructing a three-dimensional building model of the target building according to the multidimensional fusion data, and performing fire simulation on the three-dimensional building model to obtain a fire data image; extracting fire factor characteristics of the fire data image, generating an evacuation path of the target building according to the fire factor characteristics, and performing fire-fighting resource allocation according to the evacuation path to obtain a fire-fighting resource allocation vector of the evacuation path; calculating a resource allocation score of the fire-fighting resource allocation vector; when the resource allocation score is larger than a preset resource allocation threshold, a fire-fighting resource scheduling strategy is generated according to the fire-fighting resource allocation vector, and fire-fighting resources are allocated according to the fire-fighting resource scheduling strategy. The invention can improve the accuracy of fire-fighting resource scheduling and distribution in the building.

Description

Method and system for scheduling and distributing fire-fighting resources in building based on BIM data
Technical Field
The invention relates to the technical field of digital information, in particular to a method and a system for scheduling and distributing fire-fighting resources in a building based on BIM data.
Background
In recent years, with the continuous acceleration of the urban process, the structure of urban buildings is increasingly complex, the fire risks in the buildings threaten personnel safety and property safety, and once the fire conditions occur in the buildings, the fire resources are difficult to dispatch and deal with based on the complex internal structures of the buildings, so that the fire resources are required to be finely managed to accurately dispatch and distribute the fire resources.
The existing building fire-fighting resource scheduling technology is to preset the fixed position of fire-fighting equipment so as to cope with the situation of fire. In practical application, the information such as the spatial structure, equipment distribution and the like in the building may be changed, and only fire-fighting resource allocation at a fixed position is considered, so that the building information may be insufficiently known, and the accuracy in the process of scheduling and allocating fire-fighting resources in the building is low.
Disclosure of Invention
The invention provides a method and a system for scheduling and distributing fire-fighting resources in a building based on BIM data, and mainly aims to solve the problem of accuracy in scheduling and distributing fire-fighting resources in the building.
In order to achieve the above purpose, the method for scheduling and distributing fire-fighting resources in a building based on BIM data provided by the invention comprises the following steps:
s1, acquiring BIM data and sensor data of a target building, and carrying out data fusion on the BIM data and the sensor data by using a preset multidimensional data fusion algorithm to obtain multidimensional fusion data;
s2, constructing a three-dimensional building model of the target building according to the multidimensional fusion data, and performing fire simulation on the three-dimensional building model through a pre-constructed building fire numerical model to obtain a fire data image;
s3, extracting fire factor characteristics of the fire data image through a preset dual vision algorithm, generating an evacuation path of the target building according to the fire factor characteristics, and performing fire-fighting resource allocation according to the evacuation path by utilizing a preset resource allocation algorithm to obtain a fire-fighting resource allocation vector of the evacuation path;
s4, calculating a resource allocation score of the fire-fighting resource allocation vector by using a preset resource allocation evaluation algorithm, and returning to the step of performing fire-fighting resource allocation according to the evacuation path by using the preset resource allocation algorithm until the resource allocation score is greater than the preset resource allocation threshold when the resource allocation score is smaller than or equal to the preset resource allocation threshold, wherein the step of calculating the resource allocation score of the fire-fighting resource allocation vector by using the preset resource allocation evaluation algorithm comprises the following steps:
S41, determining the resource allocation weight of the fire-fighting resources in the fire-fighting resource allocation vector through a preset analytic hierarchy process;
s42, calculating a resource allocation score of the fire fighting resource allocation vector according to the resource allocation weight by using the resource allocation evaluation algorithm, wherein the resource allocation evaluation algorithm is as follows:
wherein S is the resource allocation score, p u,v The v vector value fire extinguishing probability in the vector is allocated to the fire control resource in the u-th discrete path point,for the allocation quantity of the v vector value in the fire-fighting resource allocation vector in the u-th discrete path point at the t moment, y u,v For the allocation constraint value of the V vector value in the fire-fighting resource allocation vector in the U-th discrete path point, mod is a remainder function, U is the number of the discrete path points, V is the vector dimension of the fire-fighting resource allocation vector, W u,v The resource allocation weight of the v vector value in the firefighting resource allocation vector in the u-th discrete path point is calculated;
and S5, when the resource allocation score is larger than a preset resource allocation threshold, generating a fire-fighting resource scheduling strategy according to the fire-fighting resource allocation vector, and allocating fire-fighting resources according to the fire-fighting resource scheduling strategy.
Optionally, the performing data fusion on the BIM data and the sensor data by using a preset multidimensional data fusion algorithm to obtain multidimensional fusion data includes:
Extracting building data factors in the BIM data, and generating a building data matrix of the BIM data according to the building data factors;
extracting sensing data factors in the sensor data according to a preset time interval, and generating a sensing data matrix of the sensor data according to the sensing data factors;
and carrying out data fusion on the building data matrix and the sensing data matrix by using the multi-dimensional data fusion algorithm to obtain multi-dimensional fusion data, wherein the multi-dimensional data fusion algorithm is as follows:
wherein R is the multidimensional fusion data, A n For the nth building data factor, B in the building data matrix 1t For the first sensor data in the sensor data matrix at time t, C 2t For the second sensor data in the sensor data matrix at time t, N nt Is the nth sensor data in the sensor data matrix at time t.
Optionally, the constructing a three-dimensional building model of the target building according to the multidimensional fusion data includes:
extracting building geometric attributes, spatial attributes and information attributes from the multidimensional fusion data;
generating the geometric shape of the target building according to the building geometric attribute;
Performing spatial correlation on the geometric shapes according to the spatial attributes to obtain target building geometric shapes;
and adding the information attribute and the sensor data in the multidimensional fusion data to the target building geometric shape to obtain a three-dimensional building model of the target building.
Optionally, before the fire simulation is performed on the three-dimensional building model through the pre-constructed building fire numerical model to obtain the fire data image, the method further comprises:
acquiring physical parameters of building components and physical parameters of fire sources in the three-dimensional building model;
constructing the building fire numerical model according to the building member physical parameters and the fire source physical parameters, wherein the building fire numerical model is as follows:
wherein T represents the temperature in the fire source physical parameter, T represents the fire source combustion time in the fire source physical parameter, alpha represents the thermal diffusion coefficient,representing Laplacian, representing the second spatial derivative of temperature, E representing the concentration of a substance in the physical parameter of the fire source, F representing the chemical reaction rate term, Q representing the energy density of radiation transfer, δ representing the divergence operator, κ representing the thermal conductivity of the object in the physical parameter of the building element, ε representing the surface emissivity of the object in the physical parameter of the building element, σ representing the Stefan-Boltzmann constant, T 0 Indicating the ambient temperature.
Optionally, the performing fire simulation on the three-dimensional building model through a pre-constructed building fire numerical model to obtain a fire data image includes:
dividing fire areas of the three-dimensional building model to obtain three-dimensional building fire areas;
performing analog parameter conversion on the three-dimensional building fire disaster area to obtain three-dimensional building fire disaster conversion parameters;
performing fire simulation on the three-dimensional building fire conversion parameters through the building fire numerical model to obtain fire simulation parameters;
and generating a fire disaster data image according to the fire disaster simulation parameters and the preset fire disaster simulation time.
Optionally, the extracting the fire factor feature of the fire data image through a preset dual vision algorithm includes:
extracting a combustion area in the fire data image by using the dual vision algorithm;
performing morphological operation on the combustion area to obtain an enhanced combustion area;
coding the region color in the enhanced combustion region to obtain a combustion color code;
and determining fire factor characteristics of the fire data image according to the combustion color codes.
Optionally, the generating the evacuation path of the target building according to the fire factor characteristics includes:
Determining a fire position and a fire environment of the target building according to the fire factor characteristics;
calculating the real-time pheromone concentration of the ignition position according to the preset initial pheromone concentration by using a preset pheromone concentration algorithm, wherein the pheromone concentration algorithm is as follows:
wherein τ ij (s+1) is the real-time pheromone concentration, deltaτ, of the ignition position (i, j) at time s+1 ij (s) is the initial pheromone concentration of the ignition position (i, j) at the time s ij (s) is the real-time pheromone concentration of the ignition position (i, j) at the time of s+1, e is a constant, ρ min The method is characterized in that the method comprises the steps that the method is characterized in that the method is that the minimum value of a pheromone volatilization factor, max is a maximum function, log is a logarithmic function, and N is the total updating time of the pheromone concentration;
extracting an environmental influence factor in the ignition environment, and selecting an ignition position with the highest real-time pheromone concentration as a target path position according to the environmental influence factor;
generating an evacuation path of the target building according to the target path position and the preset fire exit attribute by the following shortest path algorithm:
wherein L is the evacuation path, min is a minimum function, c is the attribute of trapped personnel, f is the fire exit attribute, ω is a real-time environmental weight parameter, and L is a real-time evacuation path.
Optionally, the performing fire-fighting resource allocation according to the evacuation path by using a preset resource allocation algorithm to obtain a fire-fighting resource allocation vector of the evacuation path includes:
performing path point dispersion on the evacuation path to obtain a dispersion path point;
fire-fighting resource allocation is carried out on the discrete path points according to fire characteristics of the discrete path points by using the resource allocation algorithm, so as to obtain discrete fire-fighting resource allocation vectors of the discrete path points, wherein the resource allocation algorithm is as follows:
{φ u }→{ζ u ,η u ,Ω u }
wherein phi is a Zeta is the fire feature of the u-th discrete waypoint a Assigning quantity, eta to firefighter at the u-th discrete waypoint a Allocating quantity omega to fire-fighting equipment of the u-th discrete path point a Assigning a quantity to the fire equipment category of the u-th discrete waypoint;
and generating the fire-fighting resource allocation vector of the evacuation path according to the discrete fire-fighting resource allocation vector of the discrete path point.
Optionally, the generating a fire resource scheduling policy according to the fire resource allocation vector includes:
determining a resource scheduling priority according to the number of resources in the fire-fighting resource allocation vector;
determining a key scheduling area of the target building according to the resource scheduling priority;
And generating a fire-fighting resource scheduling strategy according to the key scheduling area and the fire-fighting resource allocation vector one by one.
In order to solve the above problems, the present invention further provides a fire-fighting resource scheduling and distributing system in a building based on BIM data, the system comprising:
the data fusion module is used for acquiring BIM data and sensor data of a target building, and carrying out data fusion on the BIM data and the sensor data by utilizing a preset multidimensional data fusion algorithm to obtain multidimensional fusion data;
the fire data image generation module is used for constructing a three-dimensional building model of the target building according to the multidimensional fusion data, and carrying out fire simulation on the three-dimensional building model through a pre-constructed building fire numerical model to obtain a fire data image;
the fire control resource allocation vector generation module is used for extracting fire factor characteristics of the fire data image through a preset dual vision algorithm, generating an evacuation path of the target building according to the fire factor characteristics, and performing fire control resource allocation according to the evacuation path by utilizing the preset resource allocation algorithm to obtain a fire control resource allocation vector of the evacuation path;
The resource allocation score calculation module is used for calculating the resource allocation score of the fire-fighting resource allocation vector by using a preset resource allocation evaluation algorithm, and returning to the step of performing fire-fighting resource allocation by using the preset resource allocation algorithm according to the evacuation path when the resource allocation score is smaller than or equal to a preset resource allocation threshold until the resource allocation score is larger than the preset resource allocation threshold;
and the fire-fighting resource allocation module is used for generating a fire-fighting resource scheduling strategy according to the fire-fighting resource allocation vector when the resource allocation score is larger than a preset resource allocation threshold value, and allocating fire-fighting resources according to the fire-fighting resource scheduling strategy.
According to the embodiment of the invention, the BIM data and the sensor data are subjected to data fusion to obtain multidimensional fusion data, so that the overall understanding and sensing capability of a target building are improved; constructing a three-dimensional building model of a target building according to the multidimensional fusion data, and performing fire simulation on the three-dimensional building model based on the building fire numerical model, so that the method is beneficial to evaluating the severity of building fire and providing important information for firefighters, thereby making a more accurate emergency plan and evacuation scheme; extracting fire factor characteristics of the fire data image, generating an evacuation path according to the fire factor characteristics, and performing fire-fighting resource allocation based on the evacuation path, so that the efficiency and effect of building fire-fighting safety management are improved; the resource allocation score of the fire-fighting resource allocation vector is calculated, so that the quality of the fire-fighting resource allocation scheme can be evaluated; and generating a fire-fighting resource scheduling strategy based on the resource allocation score, and realizing the allocation of fire-fighting resources according to the fire-fighting resource scheduling strategy so as to ensure the timely response and the whole coverage of the resources. Therefore, the method and the system for scheduling and distributing the fire-fighting resources in the building based on BIM data can solve the problem of lower accuracy in scheduling and distributing the fire-fighting resources in the building.
Drawings
FIG. 1 is a flow chart of a method for scheduling and distributing fire resources in a building based on BIM data according to an embodiment of the present application;
FIG. 2 is a flow chart of data fusion according to an embodiment of the present application;
FIG. 3 is a flow chart of extracting fire factor features according to an embodiment of the present application;
fig. 4 is a functional block diagram of a fire-fighting resource scheduling and distributing system in a building based on BIM data according to an embodiment of the present application.
The achievement of the objects, functional features and advantages of the present application will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
Detailed Description
It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.
The embodiment of the application provides a method for dispatching and distributing fire-fighting resources in a building based on BIM data. The execution main body of the in-building fire control resource scheduling and distributing method based on BIM data comprises at least one of electronic equipment, such as a server side, a terminal and the like, which can be configured to execute the method provided by the embodiment of the application. In other words, the in-building fire resource scheduling and distributing method based on BIM data can be executed by software or hardware installed in a terminal device or a server device, wherein the software can be a blockchain platform. The service end includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, and the like. The server may be an independent server, or may be a cloud server that provides cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (Content Delivery Network, CDN), and basic cloud computing services such as big data and artificial intelligence platforms.
Referring to fig. 1, a flow chart of a method for scheduling and allocating fire resources in a building based on BIM data according to an embodiment of the present invention is shown. In this embodiment, the method for scheduling and allocating fire resources in a building based on BIM data includes:
s1, BIM data and sensor data of a target building are obtained, and the BIM data and the sensor data are subjected to data fusion by using a preset multidimensional data fusion algorithm to obtain multidimensional fusion data.
In the embodiment of the invention, the BIM data is various information generated, collected and stored in the BIM (Building Information Modeling, digital model-based building information management) process, including building geometric data, building component attributes, material information and equipment information; the sensor data includes measured data for various environmental parameters such as temperature, humidity, smoke concentration, gas, light, etc.
In detail, the BIM data and the sensor data may be acquired from a storage area where the BIM data and the sensor data of the target building are stored in advance, including but not limited to a database, a blockchain, etc., by a computer sentence having a data grabbing function (e.g., java sentence, python sentence, etc.).
Further, in order to improve the integrity and accuracy of the data, a plurality of data sources can be fused to obtain more comprehensive and accurate information, so that the overall understanding and perception capability of the target building can be improved.
In the embodiment of the invention, the multidimensional fusion data integrates data from different sources into a comprehensive data set so as to acquire more comprehensive and accurate information.
In the embodiment of the present invention, referring to fig. 2, the data fusion of the BIM data and the sensor data by using a preset multidimensional data fusion algorithm to obtain multidimensional fusion data includes:
s21, extracting building data factors in the BIM data, and generating a building data matrix of the BIM data according to the building data factors;
s22, extracting sensing data factors in the sensor data according to a preset time interval, and generating a sensing data matrix of the sensor data according to the sensing data factors;
s23, carrying out data fusion on the building data matrix and the sensing data matrix by using the multi-dimensional data fusion algorithm to obtain multi-dimensional fusion data, wherein the multi-dimensional data fusion algorithm is as follows:
Wherein R is the multidimensional fusion data, A n For the nth building data factor, B in the building data matrix 1t For the first sensor data in the sensor data matrix at time t, C 2t For the second sensor data in the sensor data matrix at time t, N nt Is the nth sensor data in the sensor data matrix at time t.
In detail, the building data factor refers to geometric data, construction attribute, material attribute and equipment information of a target building, and further generates a building data matrix of BIM data according to the attribute quantity in the building data factor; similarly, the sensing data factor refers to data generated by a sensor in a target building, such as temperature, humidity, smoke concentration, gas, illumination, and the like, so as to generate a sensing data matrix of the sensor data according to the attribute quantity in the sensing data factor, wherein the building data factor and the sensing data factor in the BIM data can be extracted through a computer sentence (Python sentence).
Specifically, the building data matrix is [ A ] 1 ,A 2 ,…,A n ]The sensing data matrix isUnifying the matrix dimension of the building data matrix and the matrix dimension of the sensing data matrix, and performing matrix splicing on the building data matrix and the sensing data matrix to obtain multidimensional fusion data, wherein each line in the sensing data matrix represents that any sensor collects data at different moments, for example, a first line represents temperature data of a temperature sensor at different moments, and a second line represents smoke concentration data of a smoke concentration sensor at different moments.
Further, in order to provide more specific and visual reference and decision support for fire-fighting resource allocation, a three-dimensional building model needs to be constructed, which provides more comprehensive and accurate building information and environmental parameters, thereby enhancing decision support capability.
And S2, constructing a three-dimensional building model of the target building according to the multidimensional fusion data, and performing fire simulation on the three-dimensional building model through a pre-constructed building fire numerical model to obtain a fire data image.
In the embodiment of the invention, the three-dimensional building model is constructed by multi-dimensional fusion data, presents the appearance, structure and environmental characteristics of the building, and can be used for visualization, analysis and decision support.
In an embodiment of the present invention, the constructing a three-dimensional building model of the target building according to the multidimensional fusion data includes:
extracting building geometric attributes, spatial attributes and information attributes from the multidimensional fusion data;
generating the geometric shape of the target building according to the building geometric attribute;
performing spatial correlation on the geometric shapes according to the spatial attributes to obtain target building geometric shapes;
And adding the information attribute and the sensor data in the multidimensional fusion data to the target building geometric shape to obtain a three-dimensional building model of the target building.
In detail, the building data matrix in the multidimensional fusion data comprises building geometric attributes, spatial attributes and information attributes of a target building, wherein the geometric attributes comprise the outline of the building, the positions of walls, windows and doors, the height of the building, the elevation, the roof shape, the floor and the like; the space attribute comprises plane graph and three-dimensional coordinate information of the building, and space attribute information such as space position relation of the building, temperature, humidity, illumination and the like in the building is extracted; the information attributes include basic information of the building, use of the building, type of the building, security level, etc., wherein the building geometric attributes, spatial attributes, and information attributes can be extracted from the storage area in which the multidimensional fusion data is stored in advance by computer sentence.
Specifically, the appearance geometric shape of the target building is generated according to the building geometric attributes through preset three-dimensional building model software, and then the appearance geometric shape is spatially associated according to the spatial position relation in the spatial attributes, so that the overall geometric shape of the target building is obtained, and the information data of the target building, the sensor data in the multidimensional fusion data and other building attributes are supplemented to the target building geometric shape, so that the three-dimensional building model of the target building is obtained.
Further, in order to simulate the development of fire, the propagation of smoke, the heat radiation and the like when a fire disaster occurs in a building based on the three-dimensional building model, the method is beneficial to evaluating the severity of the fire disaster of the building, and provides important information for firefighters, so that a more accurate emergency plan and evacuation scheme are formulated, and a building fire disaster numerical model needs to be constructed.
In an embodiment of the present invention, the building fire numerical model is a model that uses computer simulation and calculation techniques to describe and predict the course of a building fire. Based on physical principle and mathematical model, it simulates and analyzes the development and spreading process of fire by establishing a series of equations and calculation methods.
In the embodiment of the invention, before the fire simulation is performed on the three-dimensional building model through the pre-constructed building fire numerical model to obtain the fire data image, the method further comprises the following steps:
acquiring physical parameters of building components and physical parameters of fire sources in the three-dimensional building model;
constructing the building fire numerical model according to the building member physical parameters and the fire source physical parameters, wherein the building fire numerical model is as follows:
wherein T represents the temperature in the fire source physical parameter, T represents the fire source combustion time in the fire source physical parameter, alpha represents the thermal diffusion coefficient, Representing Laplacian, representing the second spatial derivative of temperature, E representing the concentration of a substance in the physical parameter of the fire source, F representing the chemical reaction rate term, Q representing the energy density of radiation transfer, δ representing the divergence operator, κ representing the thermal conductivity of the object in the physical parameter of the building element, ε representing the surface emissivity of the object in the physical parameter of the building element, σ representing the Stefan-Boltzmann constant, T 0 Indicating the ambient temperature.
In detail, the physical parameters of the building component include physical parameters such as the size, shape and position of the component, the density of the component material, the heat conductivity coefficient, the heat capacity, the heat conductivity coefficient, the light transmittance coefficient and the like; the physical parameters of the fire source comprise the physical parameters of the temperature, the size, the shape, the duration, the burning rate of burning substances, the flame propagation speed, the release rate of burning generated substances and the like of the fire source, wherein the physical parameters of building construction can be obtained through experimental measurement or engineering practice experience, and the physical parameters of the fire source can be obtained through the actual condition of fire and the burning experimental result.
Specifically, the building fire numerical model includes a heat conduction equationMass conservation equation->Energy conservation equation->The distribution change condition of the internal temperature of the building member in space and time can be obtained by solving a heat conduction equation, and a mass conservation equation describes the conservation relation of the mass of each component in the flue gas. The energy conservation equation describes the conservation relationship of smoke flow and temperature in building elements, taking into account the generation and consumption of combustion substances, and the migration and conversion of other components in the smoke. It takes into account heat conduction, convection and radiative heat transfer, among other factors. The distribution, concentration and change condition of the combustion substances can be obtained through a heat conduction equation, a mass conservation equation and an energy conservation equation, so that the fire disaster process can be better understood and proper measures can be taken.
Further, the fire simulation is carried out on the target building through the building fire numerical model, so that prediction of fire development and smoke propagation and evaluation of parameters such as combustion substance distribution, temperature and pressure can be provided. Therefore, the behavior of the fire can be better understood, and the development trend and the potential danger area of the fire can be predicted, so that the establishment of fire countermeasures and escape plans can be facilitated.
In the embodiment of the invention, the fire data image comprises a smoke propagation image, a temperature image, a smoke transparency image and a smoke removal path image, wherein the smoke propagation image refers to an image for displaying smoke or gas propagation through fire numerical simulation or on-site actual measurement data. These images typically show the smoke or gas concentration distribution in a color coded manner; the temperature image may show temperature changes at different locations in the area affected by the fire source or fire, typically using color coding to reflect the temperature gradient, such as by thermodynamic diagrams or iridescent diagrams; the smoke transparency image shows the transparency distribution of smoke or gas to visible light. The transparency image is typically color coded to represent the concentration or density of smoke to visualize the effect of smoke on visibility; the smoke evacuation path image shows the path that smoke propagates within a building or in a large space. Smoke evacuation path images are typically presented by dividing a building or space into different areas and drawing paths for smoke propagation and delivery.
In the embodiment of the present invention, the performing fire simulation on the three-dimensional building model through a pre-constructed building fire numerical model to obtain a fire data image includes:
dividing fire areas of the three-dimensional building model to obtain three-dimensional building fire areas;
performing analog parameter conversion on the three-dimensional building fire disaster area to obtain three-dimensional building fire disaster conversion parameters;
performing fire simulation on the three-dimensional building fire conversion parameters through the building fire numerical model to obtain fire simulation parameters;
and generating a fire disaster data image according to the fire disaster simulation parameters and the preset fire disaster simulation time.
In detail, different areas of the three-dimensional building model are divided, so that different three-dimensional building fire areas for fire simulation can be obtained, and further, fire parameters of the areas of the three-dimensional building fire areas for fire simulation are converted into three-dimensional building fire conversion parameters for fire simulation, so that the three-dimensional building fire conversion parameters are subjected to parameter assignment on the building fire numerical model, and fire simulation parameters are obtained, wherein the fire simulation parameters comprise fire source positions, sizes, burning rates and burning temperatures; the three-dimensional building fire conversion parameters comprise parameters such as heat conductivity, combustion rate, combustion heat release rate, smoke generation rate and the like of the material.
Specifically, according to the position, the size, the burning rate and the burning temperature of the fire source in the fire simulation parameters, and within a preset fire simulation time, a smoke propagation image, a temperature image, a smoke transparency image and a smoke removal path image can be generated, so that a fire data image is obtained.
Further, in order to more accurately grasp the characteristics, extent and smoke propagation of a fire, it is necessary to extract fire factor characteristics in a fire data image.
S3, extracting fire factor characteristics of the fire data image through a preset dual vision algorithm, generating an evacuation path of the target building according to the fire factor characteristics, and performing fire-fighting resource allocation according to the evacuation path by utilizing a preset resource allocation algorithm to obtain a fire-fighting resource allocation vector of the evacuation path.
In the embodiment of the invention, the fire factor characteristics comprise the position of a combustion area, the combustion intensity, the combustion temperature, the combustion range and the smoke density, and the quantitative or qualitative information about the fire factor in the fire data image can be provided based on the fire factor characteristics. The fire factor characteristics can be used for knowing the characteristics, the degree and the smoke propagation condition of the fire, so that the fire analysis and emergency response work is further promoted.
In an embodiment of the present invention, referring to fig. 3, the extracting the fire factor feature of the fire data image by a preset dual vision algorithm includes:
s31, extracting a combustion area in the fire data image by using the dual vision algorithm;
s32, performing morphological operation on the combustion area to obtain an enhanced combustion area;
s33, coding the region colors in the enhanced combustion region to obtain combustion color codes;
s34, determining fire factor characteristics of the fire data image according to the combustion color codes.
In detail, the dual vision algorithm can more accurately identify the combustion region in the fire data image, and then the dual vision algorithm includes an image processing algorithm and a temperature distribution image, i.e., the flame region and the smoke region in the combustion region are extracted using an image processing technique such as edge detection, color segmentation, etc., the contour and the region of the combustion object are extracted through a target detection or image segmentation algorithm, and the temperature peak is extracted through color coding in the temperature distribution image, thereby obtaining a more accurate combustion region, and morphological operations such as expansion, corrosion, etc., are applied to enhance and de-noise the flame and smoke region in the extracted combustion region, so as to obtain an enhanced combustion region.
In particular, the enhanced combustion region is color coded, i.e., a color gradient may be used to indicate the intensity or temperature change of the combustion. A chromatographic range may be defined, for example from yellow to red, from a region representing low or weaker combustion to a region of high or stronger combustion. By using different proportions of colors in the combustion zone, different degrees of combustion can be represented, and by encoding the zone colors of the combustion zone, the nature and intensity of combustion can be visually displayed, helping an observer understand the condition and extent of a fire event.
Further, by detecting the combustion color coded region, the location and shape of the combustion region in the fire data image can be determined, which can help determine the location of the flame and the extent of the fire; by burning the brightness or saturation of the color coding, the burning intensity of different areas in the fire data image can be determined, and brighter or more saturated colors may represent stronger burning; the range and the form of the combustion area in the fire data image can be determined by detecting the area, the circumference or the boundary of the combustion color coding area, so that the scale of the fire and the diffusion range of the smoke can be evaluated; if combustion color coding is also related to smoke density, smoke concentration or density can be estimated by the brightness or color density of the color, a lighter or darker color may represent a higher smoke density; if the combustion color coding is temperature dependent, the temperature of the combustion region may be estimated by a color map or color temperature of the color, and a warmer tone color may represent a higher combustion temperature. Therefore, the fire factor characteristics can be obtained, and further the fire characteristics, the degree and the smoke propagation condition can be known according to the fire factor characteristics, so that the fire analysis and emergency response work can be further promoted.
In the embodiment of the invention, the evacuation path refers to a path through which people can safely evacuate from a building or a place in case of fire or other emergency.
In an embodiment of the present invention, the generating the evacuation path of the target building according to the fire factor feature includes:
determining a fire position and a fire environment of the target building according to the fire factor characteristics;
calculating the real-time pheromone concentration of the ignition position according to the preset initial pheromone concentration by using a preset pheromone concentration algorithm, wherein the pheromone concentration algorithm is as follows:
wherein τ ij (s+1) is the real-time pheromone concentration, deltaτ, of the ignition position (i, j) at time s+1 ij (s) is the initial pheromone concentration of the ignition position (i, j) at the time s ij (s) is the real-time pheromone concentration of the ignition position (i, j) at the time of s+1, e is a constant, ρ min The method is characterized in that the method comprises the steps that the method is characterized in that the method is that the minimum value of a pheromone volatilization factor, max is a maximum function, log is a logarithmic function, and N is the total updating time of the pheromone concentration;
extracting an environmental influence factor in the ignition environment, and selecting an ignition position with the highest real-time pheromone concentration as a target path position according to the environmental influence factor;
Generating an evacuation path of the target building according to the target path position and the preset fire exit attribute by the following shortest path algorithm:
L min ＝min(L(ω c,f l c,f ))
wherein L is the evacuation path, min is a minimum function, c is the attribute of trapped personnel, f is the fire exit attribute, ω is a real-time environmental weight parameter, and L is a real-time evacuation path.
In detail, determining the ignition position and the ignition environment of a target building according to the position, the combustion intensity, the combustion temperature, the combustion range and the smoke density of a combustion area in the fire factor characteristics, setting an initial pheromone concentration for each ignition position, continuously updating the pheromone concentration of the ignition position based on the initial pheromone concentration to obtain the real-time pheromone concentration of the ignition position, and selecting a path according to the height of the pheromone concentration, wherein the higher the pheromone concentration is, the more critical area is the ignition position, wherein a pheromone volatilization factor rho in a pheromone concentration algorithm is the most direct factor influencing the calculation performance and the convergence rate of the overall pheromone concentration, and if the value of rho is too large, the calculation performance of the overall pheromone concentration is weakened; if the value of ρ is too small, the calculation convergence speed of the overall pheromone concentration becomes slow, so that it is necessary to reduce the value of ρ, and the calculation performance of the pheromone concentration is improved.
Specifically, the environmental impact factor refers to the intensity and smoke concentration of a combustion area of a fire location in a fire environment, the intensity and smoke concentration of the fire area are ordered from big to small, the fire location with the highest pheromone concentration is further determined as a target path location, and an optimal evacuation path is selected from a plurality of selected target path locations and fire exit attributes, wherein the fire exit attributes refer to fire scene entrances and exits, in order to effectively avoid the positions of fire points and obstacles, trapped people are found from the nearest starting point of a rescue person at the moment, and the found trapped people are evacuated from the nearest exit at the moment, so that an effective and shortest distance can be found, and reasonable planning of the fire-extinguishing rescue evacuation path is realized.
Further, after the optimal evacuation path is selected, effective allocation of fire-fighting resources is needed to be realized based on the evacuation path, so that efficiency and effect of building fire-fighting safety management are improved.
In the embodiment of the invention, the fire-fighting resource allocation vector refers to a resource allocation vector formed after the number of fire fighters, fire-fighting equipment and fire-fighting equipment types are allocated based on the evacuation path.
In the embodiment of the present invention, the fire-fighting resource allocation is performed according to the evacuation path by using a preset resource allocation algorithm to obtain a fire-fighting resource allocation vector of the evacuation path, including:
performing path point dispersion on the evacuation path to obtain a dispersion path point;
fire-fighting resource allocation is carried out on the discrete path points according to fire characteristics of the discrete path points by using the resource allocation algorithm, so as to obtain discrete fire-fighting resource allocation vectors of the discrete path points, wherein the resource allocation algorithm is as follows:
{φ u }→{ζ u ,η u ,Ω u }
wherein phi is a Zeta is the fire feature of the u-th discrete waypoint a Assigning quantity, eta to firefighter at the u-th discrete waypoint a Allocating quantity omega to fire-fighting equipment of the u-th discrete path point a Assigning a quantity to the fire equipment category of the u-th discrete waypoint;
and generating the fire-fighting resource allocation vector of the evacuation path according to the discrete fire-fighting resource allocation vector of the discrete path point.
In detail, dispersing path points in an evacuation path according to a target path position, namely, carrying out path segmentation on the evacuation path to obtain discrete path points, carrying out path planning, path analysis, navigation and other operations more easily by dispersing the evacuation path into the path points, calculating fire resources of the discrete path points one by one based on fire characteristics around the path points in each discrete path point, namely, preferentially distributing fire extinguishers in a region with stronger combustion according to the intensity of a combustion region on the discrete path points; according to the position and the combustion characteristics of the path points, fire hydrant resources are preferentially allocated; if a large amount of smoke or toxic gas is released at a discrete path point, environmental control equipment can be distributed near that point; rescue teams are assigned to areas that may require more assistance and support based on the fire characteristics of the discrete waypoints. These areas may be where the intensity of combustion is high, exit is blocked or personnel density is high; according to the position of the discrete path points and fire characteristics, indication marks are installed on the paths and lighting equipment is provided to help personnel find the correct evacuation paths and ensure the visibility and safety on the way.
Specifically, according to fire characteristics of the surrounding environment of each discrete path point, such as the intensity and the smoke concentration of the combustion area, the higher the light degree of the combustion area and the higher the smoke concentration, the more firefighters, the fire-fighting equipment and the fire-fighting equipment types are allocated, and the firefighters, the fire-fighting equipment and the fire-fighting equipment types can be allocated in a self-defined mode according to the intensity and the smoke concentration of the combustion area. And further, collecting the discrete fire-fighting resource allocation vectors of all the discrete path points as the fire-fighting resource allocation vectors of the evacuation path.
Further, in order to evaluate the allocation effect of the fire-fighting resource allocation vector, an optimal resource allocation scheme is found, the utilization efficiency of fire-fighting resources is improved to the greatest extent, the optimal allocation of the resources is ensured, and the allocation evaluation of the fire-fighting resource allocation vector is required.
And S4, calculating the resource allocation score of the fire-fighting resource allocation vector by using a preset resource allocation evaluation algorithm, and returning to the step of performing fire-fighting resource allocation according to the evacuation path by using the preset resource allocation algorithm when the resource allocation score is smaller than or equal to a preset resource allocation threshold until the resource allocation score is larger than the preset resource allocation threshold.
In the embodiment of the invention, the resource allocation score is a value calculated by a preset resource allocation evaluation algorithm and is used for evaluating the quality of a fire-fighting resource allocation scheme.
In the embodiment of the present invention, the calculating the resource allocation score of the fire-fighting resource allocation vector by using a preset resource allocation evaluation algorithm includes:
determining the resource allocation weight of the fire resources in the fire resource allocation vector by a preset analytic hierarchy process;
calculating a resource allocation score of the fire fighting resource allocation vector according to the resource allocation weight by using the resource allocation evaluation algorithm, wherein the resource allocation evaluation algorithm is as follows:
wherein S is the resource allocation score, p u,v The v vector value fire extinguishing probability in the vector is allocated to the fire control resource in the u-th discrete path point,for the allocation quantity of the v vector value in the fire-fighting resource allocation vector in the u-th discrete path point at the t moment, y u,v For the allocation constraint value of the V vector value in the fire-fighting resource allocation vector in the U-th discrete path point, mod is a remainder function, U is the number of the discrete path points, V is the vector dimension of the fire-fighting resource allocation vector, W u,v And (3) distributing weights for the resources of the v vector value in the firefighting resource distribution vector in the u-th discrete path point.
In detail, the analytic hierarchy process is a commonly used decision analysis process for determining weights among different factors, such as a criterion layer can be determined according to the number of people, the number of equipment and the training level; and further constructing a hierarchical structure, wherein the personnel number can be subdivided into the number of firefighters, the number of teams and the like, so as to construct a judgment matrix, evaluate the pairwise comparison between the criterion layer and the sub-criterion layer, calculate the feature vector of each factor according to the judgment matrix, and the feature vector represents the weight of each factor, thereby determining the resource allocation weight of the firefighting resources in the firefighting resource allocation vector, and evaluate the firefighting resource allocation quality in the firefighting resource allocation vector according to the resource allocation weight.
Specifically, p in the resource allocation evaluation algorithm u,v Refers to fire fighters in fire-fighting resource allocation vectorsThe number of the personnel, the number of the fire-fighting equipment and the number of the fire-fighting equipment types are used for self-defining and evaluating the fire-extinguishing probability of the fire-extinguishing position, and the number of the fire-fighting personnel, the number of the fire-fighting equipment and the number of the fire-fighting equipment types in each fire-extinguishing position are constrained to save fire-fighting cost, so that the resource allocation score of the whole fire-fighting resource allocation vector in the evacuation path is obtained, and therefore, the resource allocation score of the fire-fighting resource allocation vector can be calculated according to the resource allocation weight and the actual number of the resources and is used for evaluating the allocation condition of the resources. Wherein, a feasible fire-fighting resource allocation vector at the moment t can be found, and the fire-fighting resource allocation vector is Then all fire-fighting resource allocation amounts to +.>And comparing all the fire-fighting resource allocation quantity with the resource allocation constraint value, thereby ensuring the effectiveness of fire extinguishment.
Further, when the resource allocation score is smaller than or equal to a preset resource allocation threshold, returning to the step of allocating fire-fighting resources according to the evacuation path by using a preset resource allocation algorithm, allocating fire-fighting resources again to obtain an updated fire-fighting resource allocation vector, and re-calculating the fire-fighting resource allocation score of the updated fire-fighting resource allocation vector until the resource allocation score is larger than the preset resource allocation threshold.
And S5, when the resource allocation score is larger than a preset resource allocation threshold, generating a fire-fighting resource scheduling strategy according to the fire-fighting resource allocation vector, and allocating fire-fighting resources according to the fire-fighting resource scheduling strategy.
In the embodiment of the invention, when the resource allocation score is larger than the preset resource allocation threshold, the fire-fighting resource allocation vector can meet the fire-fighting resource scheduling of the target building, and the fire condition of the target building can be efficiently and accurately processed based on the fire-fighting resource allocation vector. And further, a fire-fighting resource scheduling strategy can be generated according to the fire-fighting resource allocation vector, wherein the fire-fighting resource scheduling strategy aims at optimizing and coordinating allocation and application of fire-fighting resources so as to cope with fire and other emergency situations.
In the embodiment of the present invention, the generating a fire-fighting resource scheduling policy according to the fire-fighting resource allocation vector includes:
determining a resource scheduling priority according to the number of resources in the fire-fighting resource allocation vector;
determining a key scheduling area of the target building according to the resource scheduling priority;
and generating a fire-fighting resource scheduling strategy according to the key scheduling area and the fire-fighting resource allocation vector one by one.
In detail, the fire resources are scheduled according to priorities of fire and emergency. The high priority situation will obtain more resources and support to ensure that the most critical areas are responded in time and supported effectively, therefore, the resource scheduling priority can be determined according to the number of resources in the fire-fighting resource allocation vector, and the area with the high resource scheduling priority is determined as the critical scheduling area, and fire-fighting power and materials are scheduled according to the spreading area and the spreading speed of the fire. The resources are concentrated in the area with the fastest fire spread, highest personnel density or the greatest hazard degree so as to effectively control the fire and protect personnel safety.
Specifically, a fire-fighting resource scheduling strategy can be generated according to the fire-fighting resource allocation vector corresponding to each key scheduling area, and fire-fighting forces and materials from different sources, including fire-fighting teams, fire-fighting vehicles, fire hydrants, fire extinguishers and the like, can be utilized to perform coordinated scheduling according to requirements and actual conditions so as to provide support and guarantee to the greatest extent.
Further, the fire-fighting resource allocation of the target building can be realized according to the fire-fighting resource allocation vector of each building area in the target building, so that reasonable allocation and optimal utilization of the fire-fighting resource are ensured, and the life and property safety of personnel is protected to the greatest extent.
In the embodiment of the present invention, the allocating the fire fighting resources according to the fire fighting resource scheduling policy includes:
extracting fire-fighting resource allocation vectors corresponding to key scheduling areas in the fire-fighting resource scheduling strategy one by one;
and distributing fire-fighting resources according to the fire-fighting resource distribution quantity in the fire-fighting resource distribution vector.
In detail, fire-fighting resource allocation vectors corresponding to key scheduling areas in the fire-fighting resource scheduling strategy are extracted one by one, and then the allocation of fire-fighting resources in each scheduling area is realized according to the allocation quantity of fire-fighting personnel, the allocation quantity of fire-fighting equipment and the allocation quantity of fire-fighting equipment types in the fire-fighting resource allocation vectors.
Further, fire-fighting power and materials are distributed to a preset area and a route point according to a fire-fighting resource distribution scheme specified in a fire-fighting resource scheduling strategy, so that timely response and full coverage of resources are ensured.
According to the embodiment of the invention, the BIM data and the sensor data are subjected to data fusion to obtain multidimensional fusion data, so that the overall understanding and sensing capability of a target building are improved; constructing a three-dimensional building model of a target building according to the multidimensional fusion data, and performing fire simulation on the three-dimensional building model based on the building fire numerical model, so that the method is beneficial to evaluating the severity of building fire and providing important information for firefighters, thereby making a more accurate emergency plan and evacuation scheme; extracting fire factor characteristics of the fire data image, generating an evacuation path according to the fire factor characteristics, and performing fire-fighting resource allocation based on the evacuation path, so that the efficiency and effect of building fire-fighting safety management are improved; the resource allocation score of the fire-fighting resource allocation vector is calculated, so that the quality of the fire-fighting resource allocation scheme can be evaluated; and generating a fire-fighting resource scheduling strategy based on the resource allocation score, and realizing the allocation of fire-fighting resources according to the fire-fighting resource scheduling strategy so as to ensure the timely response and the whole coverage of the resources. Therefore, the method and the system for scheduling and distributing the fire-fighting resources in the building based on BIM data can solve the problem of lower accuracy in scheduling and distributing the fire-fighting resources in the building.
Fig. 4 is a functional block diagram of a fire-fighting resource scheduling and distributing system in a building based on BIM data according to an embodiment of the present invention.
The in-building fire-fighting resource scheduling and distributing system 100 based on BIM data can be installed in electronic equipment. Depending on the functions implemented, the in-building fire resource scheduling and distributing system 100 based on BIM data may include a data fusion module 101, a fire data image generation module 102, a fire resource allocation vector generation module 103, a resource allocation score calculation module 104, and a fire resource allocation module 105. The module of the invention, which may also be referred to as a unit, refers to a series of computer program segments, which are stored in the memory of the electronic device, capable of being executed by the processor of the electronic device and of performing a fixed function.
In the present embodiment, the functions concerning the respective modules/units are as follows:
the data fusion module 101 is configured to obtain BIM data and sensor data of a target building, and perform data fusion on the BIM data and the sensor data by using a preset multidimensional data fusion algorithm to obtain multidimensional fusion data;
the fire data image generating module 102 is configured to construct a three-dimensional building model of the target building according to the multidimensional fusion data, and perform fire simulation on the three-dimensional building model through a pre-constructed building fire numerical model to obtain a fire data image;
The fire-fighting resource allocation vector generation module 103 is configured to extract fire factor characteristics of the fire data image through a preset dual vision algorithm, generate an evacuation path of the target building according to the fire factor characteristics, and perform fire-fighting resource allocation according to the evacuation path by using a preset resource allocation algorithm to obtain a fire-fighting resource allocation vector of the evacuation path;
the resource allocation score calculating module 104 is configured to calculate a resource allocation score of the fire fighting resource allocation vector by using a preset resource allocation evaluation algorithm, and return to the step of performing fire fighting resource allocation according to the evacuation path by using the preset resource allocation algorithm when the resource allocation score is less than or equal to a preset resource allocation threshold until the resource allocation score is greater than the preset resource allocation threshold;
the fire-fighting resource allocation module 105 is configured to generate a fire-fighting resource scheduling policy according to the fire-fighting resource allocation vector when the resource allocation score is greater than a preset resource allocation threshold, and allocate fire-fighting resources according to the fire-fighting resource scheduling policy.
In detail, each module in the in-building fire-fighting resource scheduling and distributing system 100 based on the BIM data in the embodiment of the present invention adopts the same technical means as the in-building fire-fighting resource scheduling and distributing method based on the BIM data described in fig. 1 to 3, and can generate the same technical effects, which are not described herein.
In the several embodiments provided by the present invention, it should be understood that the disclosed systems and methods may be implemented in other ways. For example, the system embodiments described above are merely illustrative, e.g., the division of the modules is merely a logical function division, and other manners of division may be implemented in practice.
The modules described as separate components may or may not be physically separate, and components shown as modules may or may not be physical units, may be located in one place, or may be distributed over multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional module in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units can be realized in a form of hardware or a form of hardware and a form of software functional modules.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof.
The present embodiments are, therefore, to be considered in all respects as illustrative and not restrictive, the scope of the application being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference signs in the claims shall not be construed as limiting the claim concerned.
The embodiment of the application can acquire and process the related data based on the artificial intelligence technology. Among these, artificial intelligence (Artificial Intelligence, AI) is the theory, method, technique and application system that uses a digital computer or a digital computer-controlled machine to simulate, extend and extend human intelligence, sense the environment, acquire knowledge and use knowledge to obtain optimal results.
Furthermore, it is evident that the word "comprising" does not exclude other elements or steps, and that the singular does not exclude a plurality. Multiple units or systems as set forth in the system claims may also be implemented by means of one unit or system in software or hardware. The terms first, second, etc. are used to denote a name, but not any particular order.
Finally, it should be noted that the above-mentioned embodiments are merely for illustrating the technical solution of the present application and not for limiting the same, and although the present application has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications and equivalents may be made to the technical solution of the present application without departing from the spirit and scope of the technical solution of the present application.

Claims (10)

1. The method for scheduling and distributing fire-fighting resources in a building based on BIM data is characterized by comprising the following steps:
s1, acquiring BIM data and sensor data of a target building, and carrying out data fusion on the BIM data and the sensor data by using a preset multidimensional data fusion algorithm to obtain multidimensional fusion data;
s2, constructing a three-dimensional building model of the target building according to the multidimensional fusion data, and performing fire simulation on the three-dimensional building model through a pre-constructed building fire numerical model to obtain a fire data image;
s3, extracting fire factor characteristics of the fire data image through a preset dual vision algorithm, generating an evacuation path of the target building according to the fire factor characteristics, and performing fire-fighting resource allocation according to the evacuation path by utilizing a preset resource allocation algorithm to obtain a fire-fighting resource allocation vector of the evacuation path;
s4, calculating a resource allocation score of the fire-fighting resource allocation vector by using a preset resource allocation evaluation algorithm, and returning to the step of performing fire-fighting resource allocation according to the evacuation path by using the preset resource allocation algorithm until the resource allocation score is greater than the preset resource allocation threshold when the resource allocation score is smaller than or equal to the preset resource allocation threshold, wherein the step of calculating the resource allocation score of the fire-fighting resource allocation vector by using the preset resource allocation evaluation algorithm comprises the following steps:
S41, determining the resource allocation weight of the fire-fighting resources in the fire-fighting resource allocation vector through a preset analytic hierarchy process;
s42, calculating a resource allocation score of the fire fighting resource allocation vector according to the resource allocation weight by using the resource allocation evaluation algorithm, wherein the resource allocation evaluation algorithm is as follows:
wherein S is the resource allocation score, p u,v The v vector value fire extinguishing probability in the vector is allocated to the fire control resource in the u-th discrete path point,for the allocation quantity of the v vector value in the fire-fighting resource allocation vector in the u-th discrete path point at the t moment, y u,v A distribution constraint value of a v vector value in a fire-fighting resource distribution vector in a u-th discrete path point, mod is a remainder function,u is the number of discrete path points, V is the vector dimension of the fire-fighting resource allocation vector, W u,v The resource allocation weight of the v vector value in the firefighting resource allocation vector in the u-th discrete path point is calculated;
and S5, when the resource allocation score is larger than a preset resource allocation threshold, generating a fire-fighting resource scheduling strategy according to the fire-fighting resource allocation vector, and allocating fire-fighting resources according to the fire-fighting resource scheduling strategy.
2. The method for scheduling and distributing fire resources in a building based on BIM data according to claim 1, wherein the step of performing data fusion on the BIM data and the sensor data by using a preset multidimensional data fusion algorithm to obtain multidimensional fusion data includes:
Extracting building data factors in the BIM data, and generating a building data matrix of the BIM data according to the building data factors;
extracting sensing data factors in the sensor data according to a preset time interval, and generating a sensing data matrix of the sensor data according to the sensing data factors;
and carrying out data fusion on the building data matrix and the sensing data matrix by using the multi-dimensional data fusion algorithm to obtain multi-dimensional fusion data, wherein the multi-dimensional data fusion algorithm is as follows:
wherein R is the multidimensional fusion data, A n For the nth building data factor, B in the building data matrix 1t For the first sensor data in the sensor data matrix at time t, C 2t For the second sensor data in the sensor data matrix at time t, N nt Is the nth sensor data in the sensor data matrix at time t.
3. The method for scheduling and distributing fire resources in a building based on BIM data according to claim 1, wherein the constructing a three-dimensional building model of the target building according to the multi-dimensional fusion data includes:
extracting building geometric attributes, spatial attributes and information attributes from the multidimensional fusion data;
Generating the geometric shape of the target building according to the building geometric attribute;
performing spatial correlation on the geometric shapes according to the spatial attributes to obtain target building geometric shapes;
and adding the information attribute and the sensor data in the multidimensional fusion data to the target building geometric shape to obtain a three-dimensional building model of the target building.
4. The method for scheduling and distributing fire resources in a building based on BIM data according to claim 1, wherein before the fire simulation is performed on the three-dimensional building model through the pre-constructed building fire numerical model, the method further comprises:
acquiring physical parameters of building components and physical parameters of fire sources in the three-dimensional building model;
constructing the building fire numerical model according to the building member physical parameters and the fire source physical parameters, wherein the building fire numerical model is as follows:
wherein T represents the temperature in the fire source physical parameter, T represents the fire source combustion time in the fire source physical parameter, alpha represents the thermal diffusion coefficient,represents the Laplace operator, represents the second spatial derivative of temperature, E represents the concentration of a substance in the physical parameter of the fire source, F represents the chemical reaction rate term, Q represents the energy density of radiation transfer, delta represents a divergence operator, kappa represents the thermal conductivity of an object in the physical parameter of the building element, epsilon represents the surface emissivity of the object in the physical parameter of the building element, sigma represents a Stefan-Boltzmann constant, T 0 Indicating the ambient temperature.
5. The method for scheduling and distributing fire resources in a building based on BIM data according to claim 4, wherein the performing fire simulation on the three-dimensional building model through a pre-constructed building fire numerical model to obtain a fire data image includes:
dividing fire areas of the three-dimensional building model to obtain three-dimensional building fire areas;
performing analog parameter conversion on the three-dimensional building fire disaster area to obtain three-dimensional building fire disaster conversion parameters;
performing fire simulation on the three-dimensional building fire conversion parameters through the building fire numerical model to obtain fire simulation parameters;
and generating a fire disaster data image according to the fire disaster simulation parameters and the preset fire disaster simulation time.
6. The method for scheduling and distributing fire resources in a building based on BIM data according to claim 1, wherein the extracting the fire factor characteristics of the fire data image through a preset dual vision algorithm includes:
Extracting a combustion area in the fire data image by using the dual vision algorithm;
performing morphological operation on the combustion area to obtain an enhanced combustion area;
coding the region color in the enhanced combustion region to obtain a combustion color code;
and determining fire factor characteristics of the fire data image according to the combustion color codes.
7. The method for scheduling and distributing fire resources in a building based on BIM data according to claim 1, wherein the generating the evacuation path of the target building according to the fire factor characteristics includes:
determining a fire position and a fire environment of the target building according to the fire factor characteristics;
calculating the real-time pheromone concentration of the ignition position according to the preset initial pheromone concentration by using a preset pheromone concentration algorithm, wherein the pheromone concentration algorithm is as follows:
wherein τ ij (s+1) is the real-time pheromone concentration, deltaτ, of the ignition position (i, j) at time s+1 ij (s) is the initial pheromone concentration of the ignition position (i, j) at the time s ij (s) is the real-time pheromone concentration of the ignition position (i, j) at the time of s+1, e is a constant, ρ min The method is characterized in that the method comprises the steps that the method is characterized in that the method is that the minimum value of a pheromone volatilization factor, max is a maximum function, log is a logarithmic function, and N is the total updating time of the pheromone concentration;
extracting an environmental influence factor in the ignition environment, and selecting an ignition position with the highest real-time pheromone concentration as a target path position according to the environmental influence factor;
generating an evacuation path of the target building according to the target path position and the preset fire exit attribute by the following shortest path algorithm:
L min ＝min(L(ω c,f l c,f ))
wherein L is the evacuation path, min is a minimum function, c is the attribute of trapped personnel, f is the fire exit attribute, ω is a real-time environmental weight parameter, and L is a real-time evacuation path.
8. The method for scheduling and allocating fire resources in a building based on BIM data according to claim 1, wherein the performing fire resources allocation according to the evacuation path using a preset resource allocation algorithm to obtain a fire resources allocation vector of the evacuation path includes:
performing path point dispersion on the evacuation path to obtain a dispersion path point;
fire-fighting resource allocation is carried out on the discrete path points according to fire characteristics of the discrete path points by using the resource allocation algorithm, so as to obtain discrete fire-fighting resource allocation vectors of the discrete path points, wherein the resource allocation algorithm is as follows:
{φ u }→{ζ u ,η u ,Ω u }
Wherein phi is a Zeta is the fire feature of the u-th discrete waypoint a Assigning quantity, eta to firefighter at the u-th discrete waypoint a Allocating quantity omega to fire-fighting equipment of the u-th discrete path point a Assigning a quantity to the fire equipment category of the u-th discrete waypoint;
and generating the fire-fighting resource allocation vector of the evacuation path according to the discrete fire-fighting resource allocation vector of the discrete path point.
9. The method for scheduling and allocating fire resources in a building based on BIM data according to claim 1, wherein the generating a fire resource scheduling policy according to the fire resource allocation vector includes:
determining a resource scheduling priority according to the number of resources in the fire-fighting resource allocation vector;
determining a key scheduling area of the target building according to the resource scheduling priority;
and generating a fire-fighting resource scheduling strategy according to the key scheduling area and the fire-fighting resource allocation vector one by one.
10. An in-building fire resource scheduling and distributing system based on BIM data, the system comprising:
the data fusion module is used for acquiring BIM data and sensor data of a target building, and carrying out data fusion on the BIM data and the sensor data by utilizing a preset multidimensional data fusion algorithm to obtain multidimensional fusion data;
The fire data image generation module is used for constructing a three-dimensional building model of the target building according to the multidimensional fusion data, and carrying out fire simulation on the three-dimensional building model through a pre-constructed building fire numerical model to obtain a fire data image;
the fire control resource allocation vector generation module is used for extracting fire factor characteristics of the fire data image through a preset dual vision algorithm, generating an evacuation path of the target building according to the fire factor characteristics, and performing fire control resource allocation according to the evacuation path by utilizing the preset resource allocation algorithm to obtain a fire control resource allocation vector of the evacuation path;
the resource allocation score calculation module is used for calculating the resource allocation score of the fire-fighting resource allocation vector by using a preset resource allocation evaluation algorithm, and returning to the step of performing fire-fighting resource allocation by using the preset resource allocation algorithm according to the evacuation path when the resource allocation score is smaller than or equal to a preset resource allocation threshold until the resource allocation score is larger than the preset resource allocation threshold;
and the fire-fighting resource allocation module is used for generating a fire-fighting resource scheduling strategy according to the fire-fighting resource allocation vector when the resource allocation score is larger than a preset resource allocation threshold value, and allocating fire-fighting resources according to the fire-fighting resource scheduling strategy.
CN202311019758.5A 2023-08-14 2023-08-14 Method and system for scheduling and distributing fire-fighting resources in building based on BIM data Pending CN117035323A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117495311A (en) * 2023-12-15 2024-02-02 浙大启真未来城市科技(杭州)有限公司 Regional fire safety physical examination method

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117495311A (en) * 2023-12-15 2024-02-02 浙大启真未来城市科技(杭州)有限公司 Regional fire safety physical examination method
CN117495311B (en) * 2023-12-15 2024-03-29 浙大启真未来城市科技(杭州)有限公司 Regional fire safety physical examination method

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