CN115861569A - Three-dimensional reconstruction method based on digital image acquisition in existing building green reconstruction - Google Patents
Three-dimensional reconstruction method based on digital image acquisition in existing building green reconstruction Download PDFInfo
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Abstract
The invention discloses a three-dimensional reconstruction method based on digital image acquisition in the green reconstruction of the existing building, which belongs to the technical field of building informatization and comprises the following steps: establishing a technical framework of field measurement for different types of buildings to be mapped, and measuring data of three aspects of geometry, color and disease; aiming at the applicability of different algorithms in different types of existing buildings, an image-based existing building three-dimensional reconstruction technology is established; the BIM is combined with the GIS to express and manage the measurement results in three levels of building components, geographic environment and time evolution; the method aims at carbon emission, thermal comfort and cost effectiveness, and establishes the greening transformation technology integration coupling wind, light and thermal environments. The invention can provide data base and convenience for green reconstruction of the existing building more accurately on the aspects of data acquisition and management.
Description
Technical Field
The invention belongs to the technical field of building informatization, and particularly relates to a three-dimensional reconstruction method based on digital image acquisition in green reconstruction of an existing building.
Background
Surveying and mapping are the foundation for green reconstruction of the existing buildings. The applicability of surveying and mapping techniques is particularly important in the face of different existing building types. The application of laser scanning technology in recent years has brought new technical paths to existing building surveying and mapping. However, the use of the technology is limited by the existing buildings and the surrounding environment, and laser drawing is difficult to use in mountain buildings and high-rise buildings.
Three-dimensional reconstruction based on images brings expansion of measurement range (from a building monomer to the surrounding environment) and increase of measurement dimension (from geometry to color and diseases), which are very important for existing building modification and later evaluation, but the two-dimensional drawing commonly used at present cannot effectively express and manage the measurement results. Moreover, the research of the three-dimensional reconstruction technology based on the image in China mostly comes from the fields of civil engineering, surveying and mapping, computers and the like. Although these fields of research also target buildings, they are not directed to existing building green renovation information.
For example, how to make the precision of the technology meet the requirements of surveying and mapping of existing buildings of different types and under sites, how to effectively express and manage the results of three-dimensional reconstruction, and how to establish a corresponding technical framework according to the characteristics of the existing buildings of different types.
Disclosure of Invention
Aiming at the defects or the improvement requirements of the prior art, the invention provides an architecturally-dominated three-dimensional reconstruction method based on digital image acquisition, which can more accurately provide data base and convenience for the green reconstruction of the existing building on the aspects of data acquisition and management.
In order to achieve the aim, the invention provides a three-dimensional reconstruction method based on digital image acquisition in the existing building green reconstruction, which comprises the following steps:
s1: establishing a technical framework of field measurement for different types of buildings to be mapped, and measuring data of three aspects of geometry, color and diseases;
s2: aiming at the applicability of different algorithms in different types of existing buildings, an image-based existing building three-dimensional reconstruction technology is established;
s3: BIM is combined with GIS to express and manage measurement results in three levels of building components, geographic environment and time evolution;
s4: the method aims at carbon emission, thermal comfort and cost effectiveness, and establishes the greening transformation technology integration coupling wind, light and thermal environments.
In some alternative embodiments, step S1 comprises:
s11: acquiring a color image of a building to be mapped through a camera sensor, acquiring a thermal infrared image of the building to be mapped through a thermal infrared imager, and confirming a recessive disease in a wall body through abnormal temperature distribution;
s12: determining the shooting distance, the image coincidence rate and the image acquisition number for measuring the building to be mapped;
s13: and carrying out color correction on the color image by adopting a multi-scale Retinex algorithm with color recovery to obtain a corrected color image.
In some alternative embodiments, step S12 comprises: by
Determining a shooting distance, wherein s x Representative camera sensingDimension of device, p x Representing a pixel, f represents a focal length;
by
Determining the area of overlap of adjacent images by>
And determining the image acquisition quantity N, wherein B represents tolerance, R represents the radius of a circumscribed circle of the building surface, and L is the visible length of the building in a world coordinate system.
More preferably, the step S1 may collect image information at different times, so as to observe the building variation trend, and obtain the physical performance of the building to be measured more intuitively.
In some alternative embodiments, step S2 comprises:
generating feature identification and matching of a color image, generating sparse point cloud through a measured ground control point, generating dense point cloud from the sparse point cloud, generating a grid surface from the dense point cloud, forming texture mapping by combining a thermal infrared image to obtain a final GIS model, creating a BIM model based on point cloud data subjected to the texture mapping, and constructing a three-dimensional point cloud slice outline to automatically generate a BIM entity model by using a visual programming platform combined function node.
In some alternative embodiments, step S2 comprises:
s21: importing positioning data by using Bentley ContextCapture, ensuring the data interoperability of coordinate system data and a GIS solution, processing a color image by using Descriptes, converting a raster image into a vector engineering drawing, and associating the color image with vector information;
s22: enhancing, segmenting and classifying dense point clouds by using Bentley Pointools, combining with an engineering model, detecting conflicts from the dense point clouds, detecting conflicts between real-world data and suggested designs, and generating a GIS model which can be updated to the latest in real time by synchronizing with an original data source;
s23: and establishing a BIM model based on the point cloud data after texture mapping, and constructing a dense point cloud slice outline to automatically generate a BIM building model by using a visual programming platform combined function node.
In some alternative embodiments, step S22 comprises:
s221: the image change causes point cloud change, dense point clouds in the same area are compared, any increase and decrease in the image change is identified, a difference tool is used for detecting and changing the dense point clouds, the dense point clouds and an original image data source are synchronized through monitoring, and a generated model can be updated to be the latest in real time;
s222: the point layer technology is used for editing a large data set of dense point clouds, a point cloud model is operated, cleaned or subdivided, the point clouds are divided into various layers, simplification and noise reduction are achieved, the purposes of point cloud isolation editing, attribute region and the like are achieved, the change point clouds monitored in the S221 can be independently edited through isolation editing, and the modeling time is shortened. Attribute distinction can obtain a construction level point cloud with unique attribute, and a data basis is provided for subsequent BIM modeling;
s223: and manipulating the real grid, the extensible model and hundreds of millions of triangular tiles, importing, decorating and exporting grids in a plurality of formats, generating accurate geographic reference three-dimensional models in various GIS formats, and utilizing PCL to realize texture mapping to obtain a final GIS environment model.
In some alternative embodiments, step S23 comprises:
s231: calculating the surface area S of an enclosing box of the dense point cloud, and calculating the average surface density alpha of the dense point cloud according to the quantity N of the dense point cloud;
s232: point cloud slicing, wherein in order to ensure the model appearance to be accurate, point cloud density alpha is set as a slicing threshold, x is input as a slicing number parameter, and a point set on a slicing plane is calculated;
s233: projecting the point sets on the tangent plane, intersecting the two adjacent point sets to the tangent plane, and fitting discrete points to obtain x tangent plane boundary profiles;
s234: lofting and fusing adjacent contour boundaries to form a segmented solid model;
s235: and combining the segmented entity models, and giving corresponding material, structure and disease information to the building members through manual data processing to obtain the BIM.
In some alternative embodiments, step S3 comprises:
s31: the method comprises the steps that a portable BIM importing mechanism provided by Supermap GIS software is utilized to realize interaction of a GIS environment model and a BIM building model, and a high-precision three-dimensional model with micro building semantic information and macro geographic environment information is obtained;
s32: establishing an external reference for the building to be surveyed and drawn, unifying high-precision three-dimensional models at different times before and after the building to a coordinate system, and obtaining the change trend of the existing building in the same time period;
the invisible building diseases invisible to naked eyes and the existing surveying and mapping means can be visually obtained by observing the change trend, a basis is provided for subsequent reconstruction, the service life and the change of the building which is not reconstructed can be simulated according to the change rule, and whether reconstruction is performed or not is selected according to the formula.
S33: analyzing by adopting a CFD-DEM coupling simulation method, comprehensively considering the influence of topographic factors on the basis of the traditional finite element simulation analysis, performing multi-technology platform linkage simulation, and performing simulation analysis on the wind, light and heat real environment of the obtained high-precision three-dimensional model to obtain a building wind speed and temperature cloud map to be drawn;
s34: and (4) importing the high-precision three-dimensional model into energy consumption measuring and calculating software to measure and calculate the carbon emission and the greenhouse gas emission.
In some alternative embodiments, step S4 comprises:
s41: carrying out primary transformation based on a BIM building model, and importing a transformation result into finite element simulation software to carry out wind, light and heat environment simulation to obtain a transformed building wind speed and temperature cloud picture;
s42: performing primary transformation based on a BIM building model, and importing transformation results into energy consumption measuring and calculating software to obtain carbon emission and greenhouse gas emission;
s43: the transformed building wind speed temperature cloud picture is compared with a building wind speed temperature cloud picture to be drawn, and parameters of the enclosure structure are continuously modified according to a comparison result;
s44: the carbon emission and the greenhouse gas emission obtained in the step S42 are compared with the carbon emission and the greenhouse gas emission of the building to be painted in the step S34, cost increment calculation is carried out according to the comparison result, and green reconstruction cost and reconstruction benefit are calculated;
s45: the above steps are repeated until the most preferred green retrofit protocol is obtained.
In general, compared with the prior art, the above technical solution contemplated by the present invention can achieve the following beneficial effects:
the dimensionality of building surveying and mapping is expanded to color and hidden diseases, the information and geometric information can be integrated into a three-dimensional model together for quantitative presentation through three-dimensional reconstruction based on images, and the data type of building surveying and mapping is greatly expanded. The method expresses and manages and measures achievements in three levels of building components, geographic environment and time evolution, is used for disease analysis, safety monitoring, structure simulation and the like of buildings, and provides more accurate and systematic data support for green modification of the existing buildings.
Drawings
Fig. 1 is a flowchart of a three-dimensional reconstruction method based on digital image acquisition according to an embodiment of the present invention;
FIG. 2 is an image acquisition framework for existing buildings according to an embodiment of the present invention;
fig. 3 is a schematic diagram of a modeling flow provided by an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. In addition, the technical features involved in the embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.
As shown in fig. 1, the present embodiment provides a three-dimensional reconstruction method based on digital image acquisition in green reconstruction of an existing building: and taking the buildings of different types as objects, and finally obtaining a database of the buildings from digital image acquisition through a high-precision three-dimensional model. In the process, a digital image of the existing building is obtained through semi-automatic image acquisition; converting non-quantitative local information (images with shooting inclination angles and lens distortion) into quantitative global information (a three-dimensional model) through an automatic digital image-based three-dimensional reconstruction algorithm; and through manual data processing, the model is endowed with building semantic information (corresponding information such as materials, structures and diseases are endowed on the level of building members) and geographic registration so as to meet the follow-up application of safety monitoring, structural simulation and the like based on the actual state of the building. The method comprises the following specific steps:
s1: aiming at different types of existing buildings, a technical framework of field measurement is established, so that data in the aspects of geometry, color and disease are accurately measured;
in step S1, measuring methods for different types of building characteristics are designed. In the prior numerous existing building transformation and building-oriented mapping, the three-dimensional data of the wall surface is far from being obtained, and the color and the hidden diseases (such as wall hollowing) are important bases for technical intervention. Aiming at different types of building characteristics and advantages and disadvantages of surveying and mapping modes, the surveying and mapping mode applicable to common buildings is summarized, and in the early stage of surveying and mapping, a proper surveying and mapping tool and a surveying and mapping mode are selected according to the building characteristics, as shown in FIG. 2, the method specifically comprises the following steps:
s11: for three-dimensional reconstruction, the laser scanner needs to be matched with an external camera. This is because the current built-in cameras of laser scanners typically have 8-bit color depth, which can only distinguish 256 colors. However, the combination of laser scanning with an external camera is currently difficult to use on a large scale due to cost and portability reasons. The passive optical sensor used for digital image acquisition has better sensitivity to light and heat: at present, the single lens reflex camera has 24-bit color depth and can distinguish more than 1600 colors; the thermal infrared imager can find the recessive diseases in the wall body through abnormal temperature distribution. (color depth is the number of bits used in computer science to store a 1-pixel color.if the color depth is n, a superposition of 2n colors can be distinguished.
S12: measurement accuracy and modeling integrity are considered, and measurement accuracy can be reduced due to excessive image acquisition; but insufficient image acquisition may lead to an incomplete three-dimensional reconstruction. In order to ensure the accuracy and the integrity of modeling and avoid resource waste of a large number of collected pictures, the standardized calculation of measurement parameters of a building to be mapped before shooting is necessary, and according to the image modeling principle, the parameters to be determined comprise shooting distance, image coincidence rate and image collection quantity, wherein the image coincidence rate and the image collection quantity are calculated based on a visual range.
The parameters are obtained based on the relation among a world coordinate system, a pixel coordinate system and an image coordinate system, and the specific calculation formula is as follows:
shooting distance:
wherein s is x Representing the camera sensor size, p x Representing a pixel and f representing a focal length.
The calculation formula of the image acquisition quantity N and the image coincidence rate is as follows:
S13: for the green reconstruction of existing buildings and blocks, the measurement accuracy of colors is very important. At present, commission International de L' Eclairage (CIE) stipulates a standard color measurement method, defines a plurality of standard light sources and recommends standard measurement geometric conditions. But in actual measurement, it is difficult to achieve standard light sources and standard geometries. In order to avoid image color differences, color correction is required. The traditional solution is to put a 24-color card in the photo, extract a color template by taking the card as a reference in the post-processing, and endow the rest images with the same illumination condition. But this method is relatively labor intensive. The invention adopts a multi-scale Retinex algorithm with color recovery, namely a dodging algorithm based on an illumination and reflectivity model. The light is homogenized first and then corrected. The specific operation is to input Retinex algorithm by matlab programming, calculate a color correction factor before multi-scale operation, import the image to be corrected and automatically correct. Many researches on the Retinex algorithm for color correction have been made, and will not be described herein.
S2: aiming at the applicability of different algorithms in different types of existing buildings, a technical process of three-dimensional reconstruction of the existing buildings based on images is established;
in a specific step (such as image recognition), the accuracy of the correlation algorithm (such as ASFIT, SIFT, SURF) is compared in the transverse direction (such as by comparing the number of homonymous points that are correctly matched with each other or with a point cloud model obtained by laser scanning). Other links involved in algorithm evaluation are: image processing, sparse point cloud generation, dense point cloud generation, mesh surface generation, texture mapping, BIM model generation from the point cloud, and the like.
In image-based three-dimensional reconstruction, the current commercial software cannot intervene in a modeling process once image acquisition is completed due to the opaqueness of an operation process; open source software provided in the field of computer vision provides the possibility of optimizing modeling precision and integrity in each link of the modeling process, and can quantitatively evaluate important algorithms of each link of three-dimensional reconstruction according to the characteristics of different types of buildings in the aspects of layout, appearance, materials, texture and the like, as shown in fig. 3, the method specifically comprises the following steps:
s21: in the image processing stage, various types of positioning data such as GPS marks, positioning points and the like are introduced by using Bentley ContextCapture, and the data interoperability of coordinate system data and a GIS solution is ensured. Processing the raster image using Desscartes, converting the raster image to a vector engineering drawing, processing the mixed workflow by vectorizing the old document using raster and vector editing, cleaning, and processing tools. The image size and scale are set using the output scale, scale and position, associating the image with vector information so that it can be accurately reused at a later time.
S22: and (3) enhancing, segmenting and classifying point clouds by using Bentley Pointools, combining with an engineering model, detecting conflicts from the point clouds, and detecting conflicts between real world data and suggested designs. The method comprises the following specific steps:
s221, distinguishing point clouds;
two point clouds in the same region are compared and any increase or decrease that occurs in the data is identified. Changes can be detected using a difference tool and monitored over time. By synchronizing with the original data source, the generative model can be updated to the latest in real time. This is valuable in having a global, up-to-date, and comprehensive representation of all data and for using various display modes and performing analysis.
S222: editing the point cloud;
a large dataset of point clouds is edited using a point layer technique. Moving dots between layers isolates the area to be edited in detail. The point cloud model is operated, cleaned or subdivided so as to be convenient for cleaning and enriching the point cloud model, so that the point cloud model is easier to recycle, and the modeling time is shortened.
S223: mesh mapping and texture mapping;
real-world grids and extensible models are manipulated with hundreds of millions of triangular tiles. Importing, decorating, and exporting a mesh of a plurality of formats. Accurate geo-referenced three-dimensional models in various GIS formats are generated, including true orthographic imagery and new Cesium 3D Tiles. And (3) converting the image in the step (S1) into texture materials by utilizing PCL, realizing texture mapping and obtaining a final GIS model.
S23: the method comprises the steps of establishing a BIM model based on point cloud data, constructing a node chain of a three-dimensional point cloud slice outline and automatically generating a BIM entity model by using a visual programming platform combined function node, reconstructing the three-dimensional point cloud through the step S22, screening and classifying the point cloud to obtain a component-level point cloud with unique attributes, exporting a coordinate point format with three-dimensional semantics, and importing the component-level point cloud into Dynamo. The specific modeling process is as follows:
s231: calculating the surface area of the point cloud bounding box, and calculating the average surface density of the point cloud according to the number of the point clouds; calculating the feature vector and the feature value of the point cloud can be directly realized by C + + programming, can also be realized by using a PCL point cloud library, or can be realized by using a numpy function of Python;
s232: point cloud slices, inputting x as a slice number parameter, and obtaining a point set threshold value on a tangent plane;
s233: projecting two adjacent point sets to a tangent plane for intersection, and fitting discrete points to obtain x tangent plane boundary profiles;
s234: lofting and fusing adjacent contour boundaries to form a segmented solid model;
s235: and (3) combining the segmented entities, and giving the entity model building semantic information (giving corresponding information such as materials, structures, diseases and the like on the level of building components) through manual data processing.
S3: BIM is combined with GIS to express and manage measurement results on three levels of building components, geographic environment and time evolution, and scientific data support is provided for research and management of evaluation after the existing green building is modified;
in step S3, wind environment, light environment and heat environment of the existing building and site are measured and calculated by using finite element software simulation based on the measurement and conversion result of BIM/GIS. And measuring the energy consumption of the original building by using the design builder, and calculating the greenhouse gas emission amount. And (3) expressing 1) a building form, a building shape and a site environment by combining BIM and GIS. 2) Building color and material. 3) Building invisible diseases. And the existing various physical environments, energy consumption and carbon emission of the building are calculated based on the analysis of the building results. Step S3 includes the following steps:
s31: by utilizing a portable BIM importing mechanism provided by Supermap GIS software, interaction of a GIS environment model and a BIM building model is realized, and a high-precision three-dimensional model result with micro building semantic information (information such as materials, structures, diseases and the like) and macro geographic environment information is obtained.
S32: and establishing an external reference (through a total station or a GPS) for the measured building, unifying the measurement results of different times to a coordinate system, obtaining the change trend (such as floor settlement, structural displacement, wall cracking, cuticle peeling, peripheral vegetation change and the like) of the building in the time period, and providing scientific data for safety monitoring and technical intervention.
S33: the CFD-DEM coupling simulation method is adopted for analysis, the influence of terrain factors is considered, multi-technology platforms are subjected to linkage simulation, the obtained model result is subjected to simulation analysis of wind, light and heat real environments, the wind speed and temperature cloud pictures of the existing building are obtained, and the comparison parameters are provided for the follow-up modification of the green building reconstruction enclosure structure. The current finite element commercial software can be compatible with various models, can carry out error-free data transmission with the subsequent ANSYS meshing software, and can read almost all file formats output by mainstream CAD software.
S34: and (4) introducing the model result into energy consumption measuring and calculating software, and measuring and calculating the carbon emission and the greenhouse gas emission.
S4: the method aims at carbon emission, thermal comfort and cost effectiveness, and establishes the greening transformation technology integration coupling wind, light and thermal environments. The single target sensitivity of various types, structures, systems and equipment strategies of typical buildings is quantified in a multi-technology platform linkage simulation mode. And (4) redesigning and reconstructing the data result based on the step S3, measuring and calculating various simulated calculation data differences before and after reconstruction based on a mode of reconstructing and reusing multi-platform linkage simulation, and repeating continuously until a reasonable reconstruction mode is explored to assist in later-stage reconstruction decision making, wherein the method specifically comprises the following steps:
s41: performing primary transformation on the BIM model obtained in the step S2, and importing the result into finite element simulation software to perform wind, light and heat environment simulation to obtain a transformed building wind speed and temperature cloud picture;
s42: performing primary transformation based on the BIM obtained in the step S2, and importing the results into energy consumption measuring and calculating software to obtain data such as carbon emission, greenhouse gas emission and the like;
s43: comparing the data obtained in the step S41 with the existing building wind speed and temperature cloud chart obtained in the step S3, and continuously modifying the parameters of the enclosure structure according to the comparison result;
s44: comparing the data obtained in the step S42 with the existing building carbon emission and greenhouse gas emission in the step S3, calculating cost increment according to the comparison result, and calculating green modification cost and modification benefit;
s45: the above steps are repeated until the most preferred green retrofit protocol is obtained.
In the step S1, a digital image of an existing building is obtained through semi-automatic image acquisition; faithfully reflecting building color information, geometric information, disease information and surrounding environment information.
In step S2, by processing the point cloud data, an accurate geo-referenced three-dimensional model in a GIS format is quickly generated, including a point cloud, a broken line, a grating digital elevation model, and an existing triangulated irregular network. By synchronizing with the original data source, the scalable environmental model can be updated to the latest in real time.
Further, automatic BIM modeling based on real data is realized by screening, segmenting, slicing and projecting point cloud data, obtaining construction-level point cloud with unique attributes, inputting Dynamo, and constructing a node chain.
In step S3, through the intermediary between the measurement and the application and the GPS positioning information input in the image processing stage of step S2, the BIM and the GIS are combined to completely express the measurement result on the micro-scale (building component) and the macro-scale (geographical environment), respectively.
And (4) obtaining the recessive disease and the service life of the building to be measured by observing the change trend of the model based on the measurement and transformation result of the BIM/GIS.
And (3) simulating and measuring the wind environment, the light environment and the thermal environment of the existing building and site by using finite element software. And (4) measuring and calculating the energy consumption of the original building by using energy consumption measuring and calculating software, and calculating the emission of greenhouse gases.
In step S4, the energy consumption calculation result obtained by the modified building model is compared with the data in step S3, and continuous improvement is designed until the most reasonable modification mode is explored to assist the later modification decision.
In conclusion, by means of the technical scheme, the dimensionality of building surveying and mapping can be expanded to color and hidden diseases, the information can be integrated into a three-dimensional model together with geometric information for quantitative presentation through three-dimensional reconstruction based on images, and the data type of building surveying and mapping is greatly expanded. The method expresses and manages and measures achievements in three levels of building components, geographic environment and time evolution, is used for disease analysis, safety monitoring, structure simulation and the like of buildings, and provides more accurate and systematic data support for green modification of the existing buildings.
It should be noted that, according to the implementation requirement, each step/component described in the present application can be divided into more steps/components, and two or more steps/components or partial operations of the steps/components can be combined into new steps/components to achieve the purpose of the present invention.
It will be understood by those skilled in the art that the foregoing is only a preferred embodiment of the present invention, and is not intended to limit the invention, and that any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (9)
1. A three-dimensional reconstruction method based on digital image acquisition in existing building green reconstruction is characterized by comprising the following steps:
s1: establishing a technical framework of field measurement for different types of buildings to be mapped, and measuring data of three aspects of geometry, color and diseases;
s2: aiming at the applicability of different algorithms in different types of existing buildings, an image-based existing building three-dimensional reconstruction technology is established;
s3: the BIM is combined with the GIS to express and manage the measurement results in three levels of building components, geographic environment and time evolution;
s4: the method aims at carbon emission, thermal comfort and cost effectiveness, and establishes the greening transformation technology integration coupling wind, light and thermal environments.
2. The method according to claim 1, wherein step S1 comprises:
s11: acquiring a color image of a building to be mapped through a camera sensor, acquiring a thermal infrared image of the building to be mapped through a thermal infrared imager, and confirming a recessive disease in a wall body through abnormal temperature distribution;
s12: determining the shooting distance, the image coincidence rate and the image acquisition quantity for measuring the building to be mapped;
s13: and carrying out color correction on the color image by adopting a multi-scale Retinex algorithm with color recovery to obtain a corrected color image.
3. The method according to claim 2, wherein step S12 comprises: by
Determining a shooting distance, wherein s x Representing the camera sensor size, p x Representing a pixel, f representing a focal length;
by
Determining the overlapping area of adjacent images by>
And determining the number N of image acquisition, wherein B represents tolerance, R represents the radius of a circumscribed circle of the surface of the building, and L is the visible length of the building in a world coordinate system.
4. The method according to claim 1, wherein step S2 comprises:
generating feature identification and matching of a color image, generating sparse point cloud through a measured ground control point, generating dense point cloud from the sparse point cloud, generating a grid surface from the dense point cloud, forming texture mapping by combining a thermal infrared image to obtain a final GIS model, creating a BIM model based on point cloud data subjected to the texture mapping, and constructing a three-dimensional point cloud slice outline to automatically generate a BIM entity model by using a visual programming platform combined function node.
5. The method according to claim 4, wherein step S2 comprises:
s21: importing positioning data by using Bentley ContextCapture, ensuring data interoperability of coordinate system data and a GIS solution, processing a color image by using Descriptes, converting a raster image into a vector engineering drawing, vectorizing an old document by using editing, cleaning and processing tools of the raster and a vector, processing a mixed workflow, setting image size and scale by using an output scale, scale and positioning, and associating the color image with vector information;
s22: enhancing, segmenting and classifying dense point clouds by using Bentley Pointools, combining with an engineering model, detecting conflicts from the dense point clouds, detecting conflicts between real world data and a proposed design, and synchronizing with an original data source to obtain a GIS model which can be updated to the latest in real time;
s23: and establishing a BIM model based on the point cloud data after texture mapping, and constructing a point cloud slice outline to automatically generate the BIM building model by using a visual programming platform combined function node.
6. The method of claim 5, wherein step S22 comprises:
s221: comparing dense point clouds in the same area, identifying any increase and decrease, detecting and changing by using a difference tool, monitoring at any time, and realizing synchronization of the dense point clouds and an original image data source through monitoring;
s222: editing a large data set of the dense point cloud by using a point layer technology, operating, cleaning or subdividing the dense point cloud, dividing the dense point cloud into various layers, and realizing isolation editing and attribute distinguishing of the dense point cloud, wherein the isolation editing independently edits the monitored change point cloud, and the attribute distinguishing obtains a construction-level point cloud with unique attributes;
s223: and manipulating the real grid, the extensible model and hundreds of millions of triangular tiles, importing, decorating and exporting grids in a plurality of formats, generating accurate geographic reference three-dimensional models in various GIS formats, and utilizing PCL to realize texture mapping to obtain a final GIS environment model.
7. The method according to claim 6, wherein step S23 comprises:
s231: calculating the surface area S of an enclosing box of the dense point cloud, and calculating the average surface density alpha of the dense point cloud according to the quantity N of the dense point cloud;
s232: point cloud slicing, wherein point cloud density alpha is set as a slicing threshold value, x is input as a slicing number parameter, and a point set on a tangent plane is calculated;
s233: for the point set on the tangent plane, projecting two adjacent point sets to the tangent plane for intersection, and fitting discrete points to obtain x tangent plane boundary profiles;
s234: lofting and fusing adjacent contour boundaries to form a segmented solid model;
s235: and combining the segmented entity models, and giving corresponding material, structure and disease information to the building members through manual data processing to obtain the BIM.
8. The method of claim 7, wherein step S3 comprises:
s31: the method comprises the steps that a portable BIM importing mechanism provided by Supermap GIS software is utilized to realize interaction of a GIS environment model and a BIM building model, and a high-precision three-dimensional model with micro building semantic information and macro geographic environment information is obtained;
s32: establishing an external reference for the building to be surveyed, unifying high-precision three-dimensional models at different times before and after the building to a coordinate system, and obtaining the change trend of the building in the same time period;
s33: analyzing by adopting a CFD-DEM coupling simulation method, considering the influence of topographic factors, performing multi-technology platform linkage simulation, and performing simulation analysis on the obtained high-precision three-dimensional model in wind, light and heat real environments to obtain a building wind speed and temperature cloud map to be drawn;
s34: and (4) importing the high-precision three-dimensional model into energy consumption measuring and calculating software to measure and calculate the carbon emission and the greenhouse gas emission.
9. The method of claim 8, wherein step S4 comprises:
s41: carrying out primary transformation based on a BIM building model, and importing a transformation result into finite element simulation software to carry out wind, light and heat environment simulation to obtain a transformed building wind speed and temperature cloud picture;
s42: performing primary transformation based on a BIM building model, and importing transformation results into energy consumption measuring and calculating software to obtain carbon emission and greenhouse gas emission;
s43: the transformed building wind speed temperature cloud picture is compared with a building wind speed temperature cloud picture to be drawn, and parameters of the enclosure structure are continuously modified according to a comparison result;
s44: the carbon emission and the greenhouse gas emission obtained in the step S42 are compared with the carbon emission and the greenhouse gas emission of the building to be painted in the step S34, cost increment calculation is carried out according to the comparison result, and green reconstruction cost and reconstruction benefit are calculated;
s45: the above steps are repeated until the most preferred green retrofit protocol is obtained.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN116805351A (en) * | 2023-06-14 | 2023-09-26 | 壹品慧数字科技(上海)有限公司 | Intelligent building management system and method based on Internet of things |
| CN116844068A (en) * | 2023-09-01 | 2023-10-03 | 山东省地质矿产勘查开发局第五地质大队（山东省第五地质矿产勘查院） | Building mapping method, system, computer equipment and storage medium |
| CN117635374A (en) * | 2023-12-15 | 2024-03-01 | 北京大学深圳研究生院 | Urban village housing film area improvement comprehensive evaluation system |
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN116805351A (en) * | 2023-06-14 | 2023-09-26 | 壹品慧数字科技(上海)有限公司 | Intelligent building management system and method based on Internet of things |
| CN116844068A (en) * | 2023-09-01 | 2023-10-03 | 山东省地质矿产勘查开发局第五地质大队（山东省第五地质矿产勘查院） | Building mapping method, system, computer equipment and storage medium |
| CN116844068B (en) * | 2023-09-01 | 2023-12-26 | 山东省地质矿产勘查开发局第五地质大队（山东省第五地质矿产勘查院） | Building mapping method, system, computer equipment and storage medium |
| CN117635374A (en) * | 2023-12-15 | 2024-03-01 | 北京大学深圳研究生院 | Urban village housing film area improvement comprehensive evaluation system |
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