Building data processing method and system based on multiple building codes

Abstract

The present invention provides a method and system for processing building data based on multiple building specifications, which relates to the technical field of data processing and comprises: decomposing a first building image based on building image data of a first building to obtain a plurality of building blocks, and adding corresponding building specification labels according to the attributes of the building blocks; acquiring a multi-directional layer structure of the corresponding building block based on a second building image of each building block, and determining the layer structure information of each directional layer structure, wherein the layer structure information at least includes the material type and thickness; a multi-building specification processing model calculates and processes the material type and thickness based on a pre-trained processing algorithm to obtain corresponding thermal analysis data, and obtains a thermal analysis result of each building block based on the building specification label; and performing data display processing on the thermal analysis data and the thermal analysis result based on the building image data to obtain a thermal analysis display result.

Description

Technical Field

[0001] The present invention relates to data processing technology, and in particular to a method and system for processing building data based on multiple building codes. Background Art

[0002] In order to improve the energy efficiency and structural safety of buildings, the construction industry has gradually introduced a variety of building codes and standards. These codes cover all aspects of construction, from structural design to material selection, to energy efficiency assessment and environmental impact. By standardizing building data, it is possible to optimize building design, standardize the construction process, and manage the entire life cycle of buildings.

[0003] Existing building data processing methods mainly rely on manual annotation and single-dimensional analysis, which leads to a variety of problems. First, manual annotation is time-consuming and labor-intensive, and is prone to subjective errors, making it difficult to ensure the consistency and accuracy of data processing. Second, single-dimensional analysis methods cannot fully consider the multi-dimensional characteristics of buildings, especially the comprehensive analysis of building energy efficiency and structural safety, and are difficult to adapt to different types of buildings and changing building code requirements.

[0004] Therefore, how to combine the automated analysis of architectural images to conduct a comprehensive analysis of architectural data and improve the accuracy and efficiency of data processing has become a problem that needs to be solved. Summary of the invention

[0005] The embodiment of the present invention provides a method and system for processing building data based on multiple building codes, which can combine the automated analysis of building images to conduct a comprehensive analysis of building data and improve the accuracy and efficiency of data processing.

[0006] A first aspect of an embodiment of the present invention provides a method for processing building data based on multiple building codes, comprising:

[0007] Decomposing the first building image based on the building image data of the first building to obtain a plurality of building blocks, and adding corresponding building code labels according to the attributes of the building blocks;

[0008] Acquire the multi-dimensional layer structure of the corresponding building block based on the second building image of each building block, and determine the layer structure information of each directional layer structure, wherein the layer structure information at least includes material type and thickness;

[0009] The multi-building code processing model calculates and processes the material type and thickness based on the pre-trained processing algorithm to obtain the corresponding thermal analysis data, and obtains the thermal analysis results of each building block based on the building code label;

[0010] The thermal analysis data and thermal analysis results are processed based on the building image data to obtain the thermal analysis display results.

[0011] Optionally, in a possible implementation manner of the first aspect, the decomposing the first building image based on the building image data of the first building to obtain a plurality of building blocks, and adding corresponding building specification labels according to attributes of the building blocks, includes:

[0012] The building image data includes a three-dimensional first building image and a plane image corresponding to the first building image, wherein the plane image has layer structure information of the building;

[0013] Compare and divide based on the coordinate information of each pixel point in the first building image to obtain a plurality of building blocks, wherein the building blocks include independent building blocks and combined building blocks;

[0014] A corresponding building code label is generated according to the attributes of the building block and stored corresponding to the corresponding building block, wherein the attributes at least include residential attributes, commercial attributes and public attributes.

[0015] Optionally, in a possible implementation manner of the first aspect, the comparing and dividing based on the coordinate information of each pixel point in the first building image to obtain a plurality of building blocks, wherein the building blocks include independent building blocks and combined building blocks, includes:

[0016] Acquire the three-dimensional coordinate information of each pixel point in the first building image, and determine all the pixel points whose Z-axis coordinate values ​​are greater than the preset Z-axis coordinate value to obtain a set of pixel points to be selected;

[0017] Determine all pixel points with the same X-axis coordinate value and the maximum Z-axis coordinate value in the set of pixel points to be selected, and obtain the set of pixel points to be compared;

[0018] Based on the adjacent relationship of all the pixels to be compared in the set of pixels to be compared, statistical processing is performed on the corresponding pixels to be compared to obtain the building block;

[0019] If it is determined that the management end actively divides the building blocks, the manually divided building blocks are obtained based on the division of the building blocks by the management end.

[0020] Optionally, in a possible implementation manner of the first aspect, the step of obtaining a building block by statistically processing corresponding pixels to be compared based on the neighbor relationship of all pixels to be compared in the set of pixels to be compared includes:

[0021] Determine all pixels directly adjacent to the pixel set to be compared or all pixels indirectly adjacent to other pixel sets to be compared, and obtain a corresponding block pixel set;

[0022] Acquire a first top view of a first building image;

[0023] Extracting the maximum Z-axis coordinate value of the same X-axis coordinate value and the same Y-axis coordinate value of the pixel points in each block pixel point set, and selecting the pixel points, so as to perform block division in the first top view to obtain the building block corresponding to each block pixel point set;

[0024] The building blocks are classified based on their adjacent relationships to obtain independent building blocks and combined building blocks.

[0025] Optionally, in a possible implementation manner of the first aspect, classifying the building blocks based on the adjacent relationship of the building blocks to obtain independent building blocks and combined building blocks includes:

[0026] Extracting the outline of each building block in the first top view to obtain corresponding outline information, wherein the outline information includes an X-axis coordinate value and a Y-axis coordinate value of a pixel point;

[0027] If it is determined that the X-axis coordinate value and the same Y-axis coordinate value of any building block and all other building blocks are greater than the preset value, the corresponding building block is determined to be an independent building block and an independent label is added;

[0028] If the difference between the X-axis coordinate value and the same Y-axis coordinate value of any two building blocks is less than or equal to a preset value, the two building blocks are judged to be combined building blocks and a combined label is added.

[0029] Optionally, in a possible implementation manner of the first aspect, acquiring the multi-directional layer structure of the corresponding building block based on the second building image of each building block, and determining the layer structure information of each directional layer structure, wherein the layer structure information at least includes material type and thickness, comprises:

[0030] Acquire a second building image for each building block in the first building image, wherein the second building image is a three-dimensional image of the corresponding building block;

[0031] Determine the walls, top surfaces and ground surfaces in different directions in the three-dimensional image, obtain multi-directional layer structures corresponding to the walls, top surfaces and ground surfaces respectively, and determine the layer structure information of each directional layer structure;

[0032] The corresponding layer structure information is counted and the corresponding wall surface, top surface or ground surface is marked and stored to obtain the corresponding layer structure storage information.

[0033] Optionally, in a possible implementation manner of the first aspect, determining walls, top surfaces, and ground surfaces in different orientations in the three-dimensional image, and acquiring multi-orientation layer structures corresponding to the walls, top surfaces, and ground surfaces, respectively, and determining layer structure information of each orientation layer structure includes:

[0034] If the building block is determined to be an independent building block, all faces of the building block are determined to be independent faces, the layer structure information of each independent face is obtained and an independent face label is added;

[0035] If the building block is judged to be a combined building block, then it is determined that there are non-independent faces in the building block, and the faces corresponding to the combined building blocks are compared to obtain fully combined faces and / or semi-combined faces, the layer structure information of each independent face is obtained and an independent face label is added, and the layer structure information of each fully combined face or semi-combined face is obtained and a fully combined label or a semi-combined label is added.

[0036] Optionally, in a possible implementation of the first aspect, comparing the surfaces corresponding to the combined building blocks to obtain the fully combined surface and / or the semi-combined surface includes:

[0037] Obtaining a three-dimensional outline of each building block in the first building image, and if it is determined that a distance value between any edge of the three-dimensional outline of the building block and any edge of the three-dimensional outline of another building block is less than or equal to an edge distance value, taking the corresponding two edges as a first comparison edge and a second comparison edge;

[0038] Acquire an orientation relationship between the first comparison edge and the second comparison edge, wherein the orientation relationship at least includes a vertical relationship and a horizontal relationship;

[0039] Determine the first comparison face and the second comparison face corresponding to the first comparison side and the second comparison side respectively based on the orientation relationship, and if it is determined that the first comparison face and the second comparison face completely overlap, take the first comparison face and the second comparison face as the full combination face;

[0040] If it is determined that the first comparison surface and the second comparison surface do not completely overlap, the first comparison surface and the second comparison surface are regarded as semi-combined surfaces.

[0041] Optionally, in a possible implementation of the first aspect, the multi-building code processing model calculates and processes material types and thicknesses based on a pre-trained processing algorithm to obtain corresponding thermal analysis data, and obtains thermal analysis results for each building block based on the building code label, including:

[0042] Obtain the independent surface of the building block and the corresponding layer structure information and input it into the multi-building code processing model, calculate and process the material type and thickness according to the pre-trained processing algorithm, and obtain the corresponding independent surface thermal analysis information;

[0043] If it is determined that the non-independent surface has a full combination label, the full combination surface thermal analysis information stored in the full combination extraction library is obtained, and the corresponding full combination surface thermal analysis information is stored correspondingly to the corresponding non-independent surface;

[0044] If it is determined that a non-independent surface has a full combination label, and the corresponding full combination surface thermal analysis information is not stored in the full combination extraction library, the material type and thickness are calculated and processed according to the pre-trained processing algorithm to obtain the corresponding full combination surface thermal analysis information and store it in the full combination extraction library.

[0045] Optionally, in a possible implementation of the first aspect, the method further includes:

[0046] If it is determined that a non-independent surface has a semi-combination label, and the layer structure information of multiple non-independent surfaces is the same, the thermal analysis information of the semi-combination surface stored in the semi-combination extraction library is obtained, and the corresponding thermal analysis information of the semi-combination surface is stored correspondingly to the corresponding non-independent surface;

[0047] If it is determined that a non-independent surface has a semi-combination label, and the corresponding semi-combination surface thermal analysis information is not stored in the semi-combination extraction library, and the layer structure information of the non-independent surface is the same, the material type and thickness are calculated and processed according to the pre-trained processing algorithm to obtain the corresponding semi-combination surface thermal analysis information and store it in the semi-combination extraction library;

[0048] If it is determined that a non-independent surface has a semi-combination label and the layer structure information of multiple non-independent surfaces is different, the material type and thickness are calculated and processed according to a pre-trained processing algorithm to obtain the corresponding semi-combination surface thermal analysis information.

[0049] Optionally, in a possible implementation of the first aspect, performing data display processing on the thermal analysis data and the thermal analysis results based on the building image data to obtain the thermal analysis display results includes:

[0050] Get the center point of each face of each building block to establish the corresponding selected coordinate point;

[0051] Comparing the thermal analysis information of each surface with the preset thermal analysis information to obtain a thermal analysis result, wherein the thermal analysis result is qualified or unqualified;

[0052] The thermal analysis information, thermal analysis results and corresponding faces are stored correspondingly, and the thermal analysis display results are obtained by calculation based on the thermal analysis algorithm.

[0053] Optionally, in a possible implementation manner of the first aspect, storing the thermal analysis information, the thermal analysis results and the corresponding faces in correspondence, and calculating based on the thermal analysis algorithm to obtain the thermal analysis display results, includes:

[0054] Count the number of first faces of all unqualified faces and the total number of faces of all faces, count the number of first blocks of building blocks with unqualified faces and the total number of blocks of all building blocks;

[0055] Performing a quantity dimension calculation based on the first number of surfaces, the total number of surfaces, the first number of blocks, and the total number of blocks to obtain a quantity coefficient;

[0056] Counting the first area of ​​the unqualified surface and the total area of ​​all surfaces, and calculating the area coefficient based on the first area and the total area;

[0057] Calculating the thermal information difference between the thermal analysis information of each unqualified surface and the preset thermal analysis information, and determining the corresponding thermal information coefficient based on the thermal information difference, so that different thermal information difference intervals have different thermal information coefficients;

[0058] Based on the quantity coefficient, area coefficient and thermal information coefficient, the thermal analysis anomaly coefficient of the thermal analysis display result is obtained.

[0059] Optionally, in a possible implementation manner of the first aspect, obtaining the thermal analysis anomaly coefficient of the thermal analysis display result based on the quantity coefficient, the area coefficient, and the thermal information coefficient includes:

[0060] The thermal analysis anomaly coefficient is calculated by the following formula,

[0061] ;

[0062] in, is the thermal analysis anomaly coefficient, is the number of the first side, is the total number of faces, Face weight, is the number of the first block, is the total number of blocks, is the block weight, is the quantity weight, For the The sub-area of ​​the non-conforming surface, is the upper limit of the unqualified surface, For all faces The sub-area of ​​a face, is the upper limit of all faces, is the area weight, For the The thermal information coefficient of the unqualified surface is is the upper limit of the thermal information coefficient of the calculated unqualified surface, is the normalized value, is the thermal coefficient weight.

[0063] A processing module, configured to decompose the first building image based on the building image data of the first building to obtain a plurality of building blocks, and add corresponding building specification labels according to the attributes of the building blocks;

[0064] A determination module, configured to obtain a multi-dimensional layer structure of the corresponding building block based on the second building image of each building block, and determine layer structure information of each dimensional layer structure, wherein the layer structure information at least includes a material type and a thickness;

[0065] A calculation module, used for the multi-building code processing model to calculate and process the material type and thickness based on a pre-trained processing algorithm to obtain corresponding thermal analysis data, and to obtain thermal analysis results for each building block based on the building code label;

[0066] The display module is used to perform data display processing on the thermal analysis data and thermal analysis results based on the building image data to obtain the thermal analysis display results.

[0067] Technical effects of the present invention:

[0068] 1. Automated architectural image data processing

[0069] The present invention obtains architectural image data of a first building, including a three-dimensional image and a corresponding plane image, and automatically decomposes and processes the image data to generate a plurality of architectural blocks. Then, according to the attributes of the architectural blocks, corresponding architectural specification labels are automatically added. This process not only reduces manual intervention and improves the efficiency and accuracy of data processing, but also can convert architectural image data into architectural blocks with specification labels, thereby facilitating subsequent architectural data management and application. Through this automated processing, it is possible to effectively cope with complex architectural structures and improve the consistency and standardization of data processing.

[0070] 2. Acquisition and analysis of multi-dimensional layer structure information

[0071] Based on the three-dimensional image of each building block, the present invention obtains multi-dimensional layer structure information of walls, top surfaces and ground surfaces in different directions, and determines the layer structure information of each direction layer structure, including material type and thickness. This process extracts the multi-dimensional layer structure information of the building by analyzing the two-dimensional and three-dimensional image data of the building in detail, providing rich and accurate data support for subsequent thermal analysis and data processing. Through the systematic processing of this information, a comprehensive evaluation of building materials and structures can be achieved, thereby improving the scientificity and rationality of building design and maintenance.

[0072] 3. Comprehensive thermal analysis and visualization

[0073] The present invention uses a pre-trained processing algorithm and a multi-building specification processing model to calculate the material type and thickness, obtain the corresponding thermal analysis data, and obtain the thermal analysis results of each building block based on the building specification label. By calculating the thermal analysis information of each surface and block and comparing it with the preset standard, the thermal analysis results and display information are generated. This process not only realizes the accurate evaluation of building energy efficiency, but also provides intuitive visual display results, which is convenient for further analysis and decision-making. Through comprehensive thermal analysis and visual display, thermal performance problems in buildings can be quickly identified, and scientific solutions can be provided, thereby improving the energy efficiency and sustainability of buildings. Through the building data processing method based on multiple building specifications of the present invention, not only the automatic processing of building image data and the standardized labeling of building blocks are realized, but also a comprehensive building thermal performance evaluation is provided through the acquisition and analysis of multi-dimensional layer structure information. In particular, through comprehensive thermal analysis and visual display, strong technical support is provided for building energy efficiency improvement and structural safety assessment. This method not only improves the efficiency and accuracy of data processing, but also enhances the visualization effect of the results, providing a scientific basis for modern building design and management. BRIEF DESCRIPTION OF THE DRAWINGS

[0074] Figure 1 It is a flowchart of a method for processing building data based on multiple building codes provided by an embodiment of the present invention;

[0075] Figure 2 It is a schematic diagram of a building image processing provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0076] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0077] See also Figure 1 , is a flow chart of a method for processing building data based on multiple building codes provided by an embodiment of the present invention, comprising:

[0078] S1, based on the architectural image data of the first building, decompose the first architectural image to obtain a plurality of architectural blocks, and add corresponding architectural specification labels according to the attributes of the architectural blocks.

[0079] This solution first obtains the architectural image data of the first building (including a three-dimensional image and a corresponding plane image). Then, these image data are decomposed and processed to generate multiple building blocks. Finally, according to the attributes of each building block, the corresponding building specification label is added. Through the above process, the decomposition of the architectural image data and the addition of specification labels to the building blocks can be automatically realized. This method can effectively convert the architectural image data into building blocks with specification labels, thereby facilitating the subsequent architectural data management and application.

[0080] In some embodiments, the decomposing the first building image based on the building image data of the first building to obtain a plurality of building blocks, and adding corresponding building code labels according to the attributes of the building blocks, includes:

[0081] S11, the building image data includes a three-dimensional first building image and a plane image corresponding to the first building image, wherein the plane image has layer structure information of the building.

[0082] This solution will obtain the architectural image data of the first building, including a three-dimensional architectural image and a corresponding plane image. The three-dimensional image is used to describe the overall three-dimensional structure of the building, which can be a three-dimensional virtual model, and the plane image has the layer structure information of the building, which can be the view information of the six faces of the building. This step involves obtaining the three-dimensional and two-dimensional image data of the building by scanning, shooting or other means for subsequent processing.

[0083] It should be noted that the first building mentioned above may be a building complex, such as a residential area, a commercial area, etc. The first building may include multiple building blocks, and a building block corresponds to, for example, one building, or several buildings, and there will be a step of automatically determining the building blocks later.

[0084] It can be understood that a three-dimensional image can represent a specific building structure, while a two-dimensional image data can analyze the structure of each surface of the building.

[0085] S12, performing comparison and division based on the coordinate information of each pixel point in the first building image to obtain a plurality of building blocks, wherein the building blocks include independent building blocks and combined building blocks.

[0086] See also Figure 2 In this scheme, building blocks include independent building blocks and combined building blocks. Independent building blocks refer to parts with independent structures and functions, such as a single building; while combined building blocks are composed of multiple independent building blocks, such as a single building (such as a residential building) and another single building (such as a commercial building). This step requires the use of image processing and spatial analysis technology to divide the building image into different blocks.

[0087] S13, generating corresponding building code labels according to the attributes of the building blocks and storing them in correspondence with the corresponding building blocks, wherein the attributes at least include residential attributes, commercial attributes and public attributes.

[0088] The attributes in this scheme include at least residential attributes, commercial attributes and public attributes. Residential attribute labels are used to mark building blocks that are mainly used for living, such as residences, dormitories, etc.; commercial attribute labels are used to mark building blocks that are mainly used for commercial purposes, such as office buildings, shopping malls, etc.; public attribute labels are used to mark building blocks that are mainly used for public services, such as hospitals, schools, etc. This step ensures that the function and purpose of each block are accurately identified. Through the above steps, the building image data can be effectively decomposed and processed, and the corresponding building specification labels can be added according to the attributes of the building blocks, so as to facilitate the subsequent building data management and application. This method is of great significance for urban planning, building management and the development of intelligent building systems.

[0089] The comparison and division based on the coordinate information of each pixel point in the first building image is performed to obtain a plurality of building blocks, wherein the building blocks include independent building blocks and combined building blocks, including:

[0090] S121, obtaining the three-dimensional coordinate information of each pixel point in the first building image, and determining all the pixel points whose Z-axis coordinate values ​​are greater than a preset Z-axis coordinate value to obtain a set of pixel points to be selected.

[0091] This solution needs to obtain the three-dimensional coordinate information of each pixel from the first building image. Usually, building images can be obtained by laser scanning, drone photogrammetry, etc., and each pixel contains three coordinate values ​​of X, Y, and Z. In order to filter out the valid parts of the building, we set a preset Z-axis coordinate value (such as the height of the ground), and then determine all pixels whose Z-axis coordinate values ​​are greater than the preset value to form a set of pixels to be selected. The purpose of this step is to remove the ground and other low non-building parts, obtain the buildings that need to be analyzed, and improve the accuracy of subsequent processing.

[0092] S122, determining all pixel points in the set of pixel points to be selected that have the same X-axis coordinate value and the same Y-axis coordinate value and the maximum Z-axis coordinate value, to obtain a set of pixel points to be compared.

[0093] This solution can further screen out representative pixels based on the set of pixels to be selected. Specifically, for all pixels with the same X-axis coordinate value and the same Y-axis coordinate value in the set of pixels to be selected, we only retain the pixel with the largest Z-axis coordinate value. In this way, a more concise set of pixels can be obtained, which is called the set of pixels to be compared. It can be understood that the set of pixels to be compared represents the set of pixels on the roof of the building. The purpose of this step is to extract the highest point of the building so that the subsequent block division is more accurate.

[0094] S123, based on the neighbor relationship of all the pixels to be compared in the set of pixels to be compared, statistically process the corresponding pixels to be compared to obtain a building block.

[0095] This solution divides building blocks based on the neighboring relationship of all pixels in the set of pixels to be compared. Interconnected pixels can be grouped to identify independent building blocks and combined building blocks. The purpose of this step is to divide the building image into different blocks corresponding to the actual building structure. Through the above steps, automated processing reduces manual intervention and improves the efficiency of image processing.

[0096] S124: If it is determined that the management end actively divides the building blocks, manually divided building blocks are obtained based on the division of the building blocks by the management end.

[0097] Finally, this solution allows the management end to manually divide the building blocks. In some cases, the automatic division results may not fully meet the actual needs, or need further refinement. Based on the preliminary results of the automatic division, the management end can manually adjust and modify through the user interface to obtain the final divided building blocks. This step increases the flexibility of the operation and makes the division results more accurate and in line with actual needs.

[0098] In the above embodiment, based on the neighbor relationship of all the pixels to be compared in the set of pixels to be compared, statistical processing is performed on the corresponding pixels to be compared to obtain the building block, including:

[0099] Determine all the pixels that are directly adjacent to the pixel set to be compared or indirectly adjacent to other pixels to be compared, and obtain the corresponding block pixel set. It can be understood that in this step, we need to determine which pixels are directly adjacent, or indirectly adjacent through other pixels. Specifically: Directly adjacent: pixel A and pixel B are adjacent to each other in the 8-neighborhood (i.e., up, down, left, right, and four diagonal directions). Indirectly adjacent: pixel A and pixel B are not directly adjacent, but can be connected through other intermediate pixels C, D, etc. In the above manner, interconnected pixels can be combined into a block pixel set.

[0100] Obtaining a first top view of the first building image: It is understandable that this solution needs to obtain a first top view of the first building image and perform analysis in combination with the first top view.

[0101] Extract the maximum Z-axis coordinate value of the same X-axis coordinate value and the same Y-axis coordinate value of the pixels in each block pixel point set, and select the pixels to perform block division in the first upper view to obtain the building block corresponding to each block pixel point set. In the upper view, for each block pixel point set, extract the X-axis coordinate value and Y-axis coordinate value of all the pixels therein, and filter these pixels. For pixels with the same X-axis coordinate value and the same Y-axis coordinate value, we can select one of the pixels (usually the one with the largest Z-axis coordinate value) as the representative pixel point of that position. Through such screening, a simplified block pixel point set can be obtained in the upper view. Using the simplified block pixel point set, block division can be performed in the first upper view. Each block pixel point set corresponds to a building block, and there is usually a clear distance between different blocks.

[0102] Based on the adjacent relationship of the building blocks, the building blocks are classified into independent building blocks and combined building blocks. Finally, we classify the building blocks based on the adjacent relationship after division: Independent building blocks: These blocks are not adjacent to other blocks, or even if they are adjacent, they are not combined together. Combined building blocks: These blocks have a close adjacent relationship with each other and can be regarded as a whole building structure.

[0103] The method of classifying the building blocks based on the adjacent relationship of the building blocks to obtain independent building blocks and combined building blocks includes:

[0104] The outline of each building block in the first upper view is extracted to obtain corresponding outline information, wherein the outline information includes the X-axis coordinate value and the corresponding Y-axis coordinate value of the pixel point. In this solution, the outline of each building block is identified from the upper view using image processing technology (such as edge detection algorithm). The coordinate values ​​of the pixel points of the identified outline are recorded, and these coordinate values ​​include the X-axis coordinate value and the corresponding Y-axis coordinate value.

[0105] If it is determined that the X-axis coordinate value and the same Y-axis coordinate value of any building block and all other building blocks are greater than the preset value, the corresponding building block is judged to be an independent building block and an independent label is added. It can be understood that the specific steps for determining whether a building block is an independent building block are as follows: Contour information comparison: Check the contour information of each building block in turn and compare it with the contour information of all other building blocks. Distance judgment: Calculate the distance difference between the contour points of the building block and all other building blocks. If the difference between the X-axis coordinate value and the corresponding Y-axis coordinate value of the building block and all other building blocks is greater than the preset threshold, the building block is considered to be independent. Label addition: If the independence condition is met, add an independent label to the building block.

[0106] If it is determined that the difference between the X-axis coordinate value and the same Y-axis coordinate value of any two building blocks is less than or equal to a preset value, the two building blocks are determined to be combined building blocks and a combined label is added. It can be understood that the specific steps for determining whether two building blocks are combined building blocks are as follows: Contour information comparison: Check the contour information of each two building blocks in turn and compare the contour information of the two building blocks. Distance judgment: Calculate the distance difference between the contour points of the two building blocks. If the difference between the X-axis coordinate value and the corresponding Y-axis coordinate value of the two building blocks is less than or equal to a preset threshold, the two building blocks are considered to be combined. Label addition: If the combination condition is met, a combined label is added to the two building blocks respectively.

[0107] S2, acquiring the multi-directional layer structure of the corresponding building block based on the second building image of each building block, and determining the layer structure information of each directional layer structure, wherein the layer structure information at least includes material type and thickness.

[0108] The purpose of this step is to obtain the layer structure information in different directions by analyzing the three-dimensional image of the building block, so as to conduct data analysis on the building by combining the layer structure information in different directions.

[0109] In some embodiments, the step of acquiring the multi-dimensional layer structure of the corresponding building block based on the second building image of each building block and determining the layer structure information of each dimensional layer structure, wherein the layer structure information includes at least the material type and thickness, includes:

[0110] S21, obtaining a second building image for each building block in the first building image, where the second building image is a three-dimensional image of the corresponding building block.

[0111] For each building block identified in the first building image (usually a two-dimensional top view or plan view), a corresponding second building image is obtained. The second building image is a three-dimensional image of the building block, which can provide multi-directional viewing angles.

[0112] S22, determining walls, top surfaces and ground surfaces in different orientations in the three-dimensional image, and obtaining multi-orientation layer structures corresponding to the walls, top surfaces and ground surfaces respectively, and determining layer structure information of each orientation layer structure.

[0113] In the second building image, architectural elements of different orientations are identified and segmented, including walls, tops, and ground. Wall recognition can identify the portion of the three-dimensional image that is perpendicular to the ground and mark it as a wall. Top recognition can identify the portion of the three-dimensional image that is horizontal and above the building and mark it as a top. Ground recognition can identify the portion of the three-dimensional image that is horizontal and below the building and mark it as the ground. Orientation layer structure acquisition: For each identified wall, top, and ground, obtain its corresponding multi-orientation layer structure information. This information includes but is not limited to material type and thickness. Among them, the material type can be determined by analyzing the texture, color, and other characteristics of the image to determine the type of building material used. The material thickness can be determined by three-dimensional measurement or inference to determine the thickness of each layer of material, or it can be obtained by obtaining the preset thickness data of the second building image.

[0114] S23, the corresponding layer structure information is counted and the corresponding wall surface, top surface or ground surface is marked and stored to obtain the corresponding layer structure storage information.

[0115] This solution marks the acquired layer structure information on the corresponding wall, top and ground. For example, the layer structure information of a wall can be marked as "material A, thickness 10cm". The marked layer structure information is stored to form a structured data set. This data set can include detailed layer structure information of each building block to facilitate subsequent query and analysis. The storage information can be in a table, database or other suitable data structure for easy management and access. The specific stored information should include building block identification, orientation (wall / top / ground), material type and thickness, etc. In the above way, the automated marking and information storage process can be realized to improve work efficiency and reduce manual intervention and errors.

[0116] The step of determining the walls, top surfaces and ground surfaces in different directions in the three-dimensional image, obtaining multi-directional layer structures corresponding to the walls, top surfaces and ground surfaces respectively, and determining the layer structure information of each directional layer structure includes:

[0117] S221: If the building block is determined to be an independent building block, all faces of the building block are determined to be independent faces, layer structure information of each independent face is obtained, and an independent face label is added.

[0118] If the building block is determined to be an independent building block, this solution will identify independent faces and mark all faces of the building block (including walls, tops and ground) as independent faces. For each independent face (wall, top, ground), obtain its layer structure information, including material type and thickness. Add an independent face label to each independent face.

[0119] S222, if the building block is judged to be a combined building block, then determine whether there are non-independent faces in the building block, compare the faces corresponding to the combined building blocks to obtain fully combined faces and / or semi-combined faces, obtain the layer construction information of each independent face and add an independent face label, obtain the layer construction information of each fully combined face or semi-combined face and add a fully combined label or a semi-combined label.

[0120] If the building block is determined to be a composite building block, the face of the building block is distinguished by comparison to see whether it is a fully composite face or a semi-composite face. Fully composite face: the entire face is shared with the adjacent building block. Semi-composite face: part of the face is shared with the adjacent building block. Independent face: a face that is not shared with other building blocks. For each independent face, obtain its layer construction information and add an independent face label. For each fully composite face or semi-composite face, obtain its layer construction information. Fully composite face label: add a fully composite label to the fully composite face. Semi-composite face label: add a semi-composite label to the semi-composite face. For example, suppose there is a composite building block, two of the four walls are shared with other building blocks, one is a fully composite face, one is a semi-composite face, and the remaining two are independent faces. The top face and the ground face are both independent faces.

[0121] In the above embodiment, the steps of comparing the surfaces corresponding to the combined building blocks to obtain the fully combined surface and / or the semi-combined surface include:

[0122] The three-dimensional outline of each building block in the first building image is obtained. If it is determined that the distance value between any edge of the three-dimensional outline of the building block and any edge of the three-dimensional outline of other building blocks is less than or equal to the edge distance value, the corresponding two edges are used as the first comparison edge and the second comparison edge.

[0123] For each building block, obtain its three-dimensional contour in the first building image (such as a two-dimensional top view or plan view). Determine the distance value between any edge of the three-dimensional contour of the building block and any edge of the three-dimensional contour of other building blocks. Margin comparison: Calculate the distance value between any edge of the building block and any edge of other building blocks. Distance calculation: Use Euclidean distance or other appropriate distance measurement methods to calculate the distance between edges. Distance threshold: Define an edge distance value (threshold), such as 1 meter, to determine whether it belongs to a neighboring edge. If it is determined that the distance between the three-dimensional contour edge of a building block and the three-dimensional contour edge of other building blocks is less than or equal to the edge distance value, it is identified as a matching edge. The corresponding two edges are used as the first comparison edge and the second comparison edge.

[0124] An orientation relationship between the first comparison edge and the second comparison edge is obtained, where the orientation relationship at least includes a vertical relationship and a horizontal relationship.

[0125] This scheme identifies the orientation relationship between the first comparison side and the second comparison side. If the two sides are perpendicular to each other, the orientation relationship is a vertical relationship. If the two sides are parallel, the orientation relationship is a horizontal relationship.

[0126] The first comparison surface and the second comparison surface respectively corresponding to the first comparison side and the second comparison side are determined based on the orientation relationship. If it is determined that the first comparison surface and the second comparison surface completely overlap, the first comparison surface and the second comparison surface are taken as full combination surfaces.

[0127] If it is determined that the first comparison surface and the second comparison surface do not completely overlap, the first comparison surface and the second comparison surface are regarded as semi-combined surfaces.

[0128] This scheme will compare the overlap between the first comparison surface and the second comparison surface. If the two surfaces completely overlap, then the two surfaces are considered to completely overlap. If the two surfaces overlap in some parts but are not completely consistent, then the two surfaces are considered to not completely overlap.

[0129] S3, the multi-building code processing model calculates and processes the material type and thickness based on the pre-trained processing algorithm to obtain the corresponding thermal analysis data, and obtains the thermal analysis results of each building block based on the building code label.

[0130] The purpose of this solution is to calculate and obtain thermal analysis data of building blocks through pre-trained algorithms and models combined with building code labels. The pre-trained algorithm can be the calculation of the heat transfer coefficient in the following table, or other existing algorithms for thermal analysis in the prior art. This solution does not elaborate on it, nor does it limit it.

[0131]

[0132] In some embodiments, the multi-building code processing model calculates and processes the material type and thickness based on a pre-trained processing algorithm to obtain corresponding thermal analysis data, and obtains thermal analysis results for each building block based on the building code label, including:

[0133] S31, obtaining the independent surface of the building block and the corresponding layer structure information and inputting them into the multi-building code processing model, calculating and processing the material type and thickness according to the pre-trained processing algorithm, and obtaining the corresponding independent surface thermal analysis information.

[0134] Among them, the multi-building code processing model is a pre-trained machine learning model that can calculate thermal analysis data based on the input building materials and construction information. The geometric information and layer construction information of the independent surface are input into the model. Based on the input layer construction information, the model calculates and outputs the thermal analysis information of each independent surface. Finally, the thermal analysis information of the corresponding independent surface is obtained.

[0135] S32, if it is determined that the non-independent surface has a full combination label, obtain the full combination surface thermal analysis information stored in the full combination extraction library, and store the corresponding full combination surface thermal analysis information corresponding to the corresponding non-independent surface.

[0136] It can be understood that if a non-independent surface has a full combination label, it means that it is a surface shared by the building. If the thermal analysis information of one of the non-independent surfaces has been calculated before, there is no need to recalculate it. It can be directly obtained from the thermal analysis information of the full combination surface stored in the full combination extraction library, and the corresponding thermal analysis information of the full combination surface is stored corresponding to the corresponding non-independent surface.

[0137] S33, if it is determined that a non-independent surface has a full combination label, and the corresponding full combination surface thermal analysis information is not stored in the full combination extraction library, the material type and thickness are calculated and processed according to the pre-trained processing algorithm to obtain the corresponding full combination surface thermal analysis information and store it in the full combination extraction library.

[0138] If a non-independent surface has a full combination label, but there is no corresponding data in the full combination extraction library, the following processing is performed. Use the model to calculate the corresponding full combination surface thermal analysis information based on the material type and thickness information. Obtain new full combination surface thermal analysis information.

[0139] Based on the above embodiment, it also includes:

[0140] If it is determined that a non-independent surface has a semi-combination label and the layer structure information of multiple non-independent surfaces is the same, the thermal analysis information of the semi-combination surface stored in the semi-combination extraction library is obtained, and the corresponding semi-combination surface thermal analysis information is stored correspondingly to the corresponding non-independent surface.

[0141] The system first detects whether the non-independent surface is marked as a semi-combined label. The semi-combined label indicates that the surface shares certain characteristics or processing requirements with other surfaces. Determine whether the layer structure information of multiple non-independent surfaces is the same. If the layer structure information (such as material type, thickness, etc.) of multiple non-independent surfaces is the same. Obtain the stored thermal analysis information of the semi-combined surface: extract the corresponding thermal analysis information of the semi-combined surface from the semi-combined extraction library. Store the obtained thermal analysis information corresponding to the corresponding non-independent surface. In this way, repeated calculations are avoided and processing efficiency is improved.

[0142] If it is determined that a non-independent surface has a semi-combination label, the corresponding semi-combination surface thermal analysis information is not stored in the semi-combination extraction library, and the layer structure information of the non-independent surface is the same, the material type and thickness are calculated and processed according to the pre-trained processing algorithm to obtain the corresponding semi-combination surface thermal analysis information and store it in the semi-combination extraction library.

[0143] Check whether there is corresponding thermal analysis information in the semi-combination extraction library. If there is no corresponding information, calculate and process the material type and thickness according to the pre-trained processing algorithm to obtain the corresponding thermal analysis information. Store the calculated thermal analysis information in the semi-combination extraction library for subsequent use. New thermal analysis information is obtained through calculation and stored and updated in time to maintain the dynamic and real-time nature of the library content.

[0144] If it is determined that a non-independent surface has a semi-combination label and the layer structure information of multiple non-independent surfaces is different, the material type and thickness are calculated and processed according to a pre-trained processing algorithm to obtain the corresponding semi-combination surface thermal analysis information.

[0145] It is understandable that if the layer structure information is different, the material type and thickness are calculated and processed according to the pre-trained processing algorithm to obtain the corresponding semi-combination surface thermal analysis information.

[0146] S4, performing data display processing on the thermal analysis data and thermal analysis results based on the building image data to obtain the thermal analysis display results.

[0147] This step can extract the center point of each face from the building image data, accurately store and compare thermal analysis information, and then generate comprehensive thermal analysis display results. This process not only improves the accuracy and efficiency of thermal analysis processing, but also enhances the visual display effect of the results, facilitating further analysis and decision-making.

[0148] In some embodiments, the thermal analysis data and thermal analysis results are processed based on the building image data to obtain the thermal analysis display results, including:

[0149] S41, obtaining the center point of each face of each building block to establish a corresponding selected coordinate point.

[0150] Among them, for faces with simple geometric shapes, the center point can be obtained by calculating the geometric center. For complex shapes, image processing technology (such as the centroid algorithm) may be used to determine the center point, or a value is obtained by the top coordinate value and the bottom coordinate value, and then a value is obtained by the leftmost coordinate value and the rightmost coordinate value, and the two values ​​are combined into one coordinate, namely the center point. These selected coordinate points are used for positioning and association operations in subsequent data storage and display processing. Extract each face of each building block from the building image data. Calculate the center point of each face. Establish the center point as the selected coordinate point and record it.

[0151] S42, comparing the thermal analysis information of each surface with preset thermal analysis information to obtain a thermal analysis result, wherein the thermal analysis result is qualified or unqualified.

[0152] This solution compares the actual thermal analysis information of each surface with the preset standard information, such as temperature distribution, heat flux density, etc. According to the preset standard, it is judged whether the thermal analysis information of the surface is within the qualified range. The comparison result can generate a flag (such as qualified, unqualified) for storage.

[0153] S43, storing the thermal analysis information, thermal analysis results and corresponding faces in correspondence, and calculating based on the thermal analysis algorithm to obtain the thermal analysis display results.

[0154] The thermal analysis information and comparison results of each surface are stored corresponding to the selected coordinate points. Based on the stored information, a pre-designed thermal analysis algorithm is used for further calculation. Based on the calculation results of the thermal analysis algorithm, a visual thermal analysis display result is generated, which may include a pass / fail mark diagram, etc.

[0155] The storing of the thermal analysis information, the thermal analysis results and the corresponding faces, and the calculation based on the thermal analysis algorithm to obtain the thermal analysis display results, include:

[0156] S431, counting the number of first faces of all unqualified faces and the total number of faces of all faces, counting the number of first blocks of building blocks with unqualified faces and the total number of blocks of all building blocks.

[0157] This solution will count the number of all unqualified faces. The number of unqualified faces is based on the comparison results in step S42, and all faces marked as unqualified are screened out. The total number of faces is the sum of the number of faces of all building blocks in the building image data. Count the number of building blocks with unqualified faces. This part counts the number of building blocks that have at least one face marked as unqualified. The total number of blocks is the sum of all building blocks in the building image data.

[0158] S432: Perform quantity dimension calculation based on the first number of surfaces, the total number of surfaces, the first number of blocks, and the total number of blocks to obtain a quantity coefficient.

[0159] This solution calculates the coefficient of the quantity dimension, called the quantity coefficient. Through this coefficient, the ratio of the number of unqualified surfaces to the total number of surfaces and the number of unqualified blocks to the total number of blocks in the building can be quantified.

[0160] S433, counting the first area of ​​the unqualified surface and the total area of ​​all surfaces, and calculating the area coefficient based on the first area and the total area.

[0161] At the same time, this solution will count the total area of ​​the unqualified faces (first area) and the total area of ​​all faces. The coefficient of the area dimension is calculated, called the area coefficient. Through this coefficient, the proportion of the area of ​​the unqualified faces to the total area can be quantified.

[0162] S434, calculating the thermal information difference between the thermal analysis information of each unqualified surface and the preset thermal analysis information, and determining the corresponding thermal information coefficient based on the thermal information difference, and different thermal information difference intervals have different thermal information coefficients.

[0163] The difference between the thermal analysis information of each unqualified surface and the preset thermal analysis information is calculated, which is called the thermal information difference. In this way, the difference in thermal performance between each unqualified surface and the standard can be evaluated. The corresponding thermal information coefficient is determined based on the thermal information difference. Different thermal information difference intervals are assigned different thermal information coefficients. For example: if the difference is between 0-5 degrees, the thermal information coefficient is 1. If the difference is between 5-10 degrees, the thermal information coefficient is 2. If the difference exceeds 10 degrees, the thermal information coefficient is 3.

[0164] S435, obtaining a thermal analysis anomaly coefficient of the thermal analysis display result based on the quantity coefficient, the area coefficient, and the thermal information coefficient.

[0165] The thermal analysis anomaly coefficient is a comprehensive coefficient that is used to quantify the degree of abnormality in the thermal performance of the entire building and can be intuitively reflected in the display results.

[0166] In some embodiments, the thermal analysis anomaly coefficient of the thermal analysis display result obtained based on the quantity coefficient, area coefficient, and thermal information coefficient includes:

[0167] The thermal analysis anomaly coefficient is calculated by the following formula,

[0168] ;

[0169] in, is the thermal analysis anomaly coefficient, is the number of the first side, is the total number of faces, Face weight, is the number of the first block, is the total number of blocks, is the block weight, is the quantity weight, For the The sub-area of ​​the non-conforming surface, is the upper limit of the unqualified surface, For all faces The sub-area of ​​a face, is the upper limit of all faces, is the area weight, For the The thermal information coefficient of the unqualified surface is is the upper limit of the thermal information coefficient of the calculated unqualified surface, is the normalized value, is the thermal coefficient weight. In the above formula, Represents the quantity coefficient, where the face weight and block weight can be pre-set. represents the area coefficient, represents the thermal information coefficient; finally, the thermal analysis anomaly coefficient is obtained by combining the quantity coefficient weight, area weight and thermal coefficient weight. Among them, the quantity coefficient weight, area weight and thermal coefficient weight can be pre-set. In this way, the system can effectively integrate multiple indicators of the building structure to quantify and display the degree of abnormality of thermal performance. This thermal analysis anomaly coefficient not only provides a comprehensive perspective, but also helps identify and prioritize the areas that need the most attention.

[0170] The embodiment of the present invention further provides a building data processing system based on multiple building codes, comprising:

[0171] A processing module, configured to decompose the first building image based on the building image data of the first building to obtain a plurality of building blocks, and add corresponding building specification labels according to the attributes of the building blocks;

[0172] A determination module, configured to obtain a multi-dimensional layer structure of the corresponding building block based on the second building image of each building block, and determine layer structure information of each dimensional layer structure, wherein the layer structure information at least includes a material type and a thickness;

[0173] A calculation module, used for the multi-building code processing model to calculate and process the material type and thickness based on a pre-trained processing algorithm to obtain corresponding thermal analysis data, and to obtain thermal analysis results for each building block based on the building code label;

[0174] The display module is used to perform data display processing on the thermal analysis data and thermal analysis results based on the building image data to obtain the thermal analysis display results.

[0175] The present invention also provides a storage medium, in which a computer program is stored. When the computer program is executed by a processor, it is used to implement the methods provided by the various embodiments described above.

[0176] Among them, the storage medium can be a computer storage medium or a communication medium. The communication medium includes any medium that facilitates the transmission of a computer program from one place to another. The computer storage medium can be any available medium that can be accessed by a general-purpose or special-purpose computer. For example, the storage medium is coupled to the processor so that the processor can read information from the storage medium and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and the storage medium can be located in an application-specific integrated circuit (Application Specific Integrated Circuits, referred to as: ASIC). In addition, the ASIC can be located in a user device. Of course, the processor and the storage medium can also exist in a communication device as discrete components. The storage medium can be a read-only memory (ROM), a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, and an optical data storage device, etc.

[0177] The present invention also provides a program product, which includes an execution instruction, which is stored in a storage medium. At least one processor of a device can read the execution instruction from the storage medium, and at least one processor executes the execution instruction so that the device implements the methods provided in the above various embodiments.

[0178] In the above-mentioned terminal or server embodiments, it should be understood that the processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), etc. A general-purpose processor may be a microprocessor or any conventional processor. The steps of the method disclosed in the present invention may be directly implemented as being executed by a hardware processor, or may be executed by a combination of hardware and software modules in the processor.

[0179] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein by equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for processing building data based on multiple building codes, characterized in that: include: Decomposing the first building image based on the building image data of the first building to obtain a plurality of building blocks, and adding corresponding building code labels according to the attributes of the building blocks; Acquire the multi-dimensional layer structure of the corresponding building block based on the second building image of each building block, and determine the layer structure information of each directional layer structure, wherein the layer structure information includes at least material type and thickness; The multi-building code processing model calculates and processes the material type and thickness based on the pre-trained processing algorithm to obtain the corresponding thermal analysis data, and obtains the thermal analysis results of each building block based on the building code label; Perform data processing on thermal analysis data and thermal analysis results based on building image data to obtain thermal analysis display results; The step of decomposing the first building image based on the building image data of the first building to obtain a plurality of building blocks, and adding corresponding building specification labels according to the attributes of the building blocks, comprises: The building image data includes a three-dimensional first building image and a plane image corresponding to the first building image, wherein the plane image has layer structure information of the building; Compare and divide based on the coordinate information of each pixel point in the first building image to obtain a plurality of building blocks, wherein the building blocks include independent building blocks and combined building blocks; Generate a corresponding building code label according to the attributes of the building block and store it in correspondence with the corresponding building block, wherein the attributes include at least residential attributes, commercial attributes and public attributes; The comparison and division based on the coordinate information of each pixel point in the first building image is performed to obtain a plurality of building blocks, wherein the building blocks include independent building blocks and combined building blocks, including: Acquire the three-dimensional coordinate information of each pixel point in the first building image, and determine all the pixel points whose Z-axis coordinate values ​​are greater than the preset Z-axis coordinate value to obtain a set of pixel points to be selected; Determine all pixel points with the same X-axis coordinate value and the maximum Z-axis coordinate value in the set of pixel points to be selected, and obtain the set of pixel points to be compared; Based on the adjacent relationship of all the pixels to be compared in the set of pixels to be compared, statistical processing is performed on the corresponding pixels to be compared to obtain the building block; If it is determined that the management end actively divides the building blocks, then manually divided building blocks are obtained based on the division of the building blocks by the management end; The method of acquiring the multi-directional layer structure of the corresponding building block based on the second building image of each building block and determining the layer structure information of each directional layer structure, wherein the layer structure information at least includes the material type and thickness, comprises: Acquire a second building image for each building block in the first building image, wherein the second building image is a three-dimensional image of the corresponding building block; Determine the walls, top surfaces and ground surfaces in different directions in the three-dimensional image, obtain multi-directional layer structures corresponding to the walls, top surfaces and ground surfaces respectively, and determine the layer structure information of each directional layer structure; Counting the corresponding layer structure information, marking and storing the corresponding wall surface, top surface or ground surface, and obtaining the corresponding layer structure storage information; The determining of walls, top surfaces and ground surfaces in different orientations in the three-dimensional image, and obtaining multi-orientation layer structures corresponding to the walls, top surfaces and ground surfaces respectively and determining layer structure information of each orientation layer structure includes: If the building block is determined to be an independent building block, all faces of the building block are determined to be independent faces, the layer structure information of each independent face is obtained and an independent face label is added; If the building block is determined to be a combined building block, it is determined that there are non-independent faces in the building block, and faces corresponding to the combined building blocks are compared to obtain fully combined faces and / or semi-combined faces, and the layer structure information of each independent face is obtained and an independent face label is added, and the layer structure information of each fully combined face or semi-combined face is obtained and a fully combined label or semi-combined label is added; The multi-building code processing model calculates and processes the material type and thickness based on a pre-trained processing algorithm to obtain corresponding thermal analysis data, and obtains thermal analysis results for each building block based on the building code label, including: Obtain the independent surface of the building block and the corresponding layer structure information and input it into the multi-building code processing model, calculate and process the material type and thickness according to the pre-trained processing algorithm, and obtain the corresponding independent surface thermal analysis information; If it is determined that the non-independent surface has a full combination label, the full combination surface thermal analysis information stored in the full combination extraction library is obtained, and the corresponding full combination surface thermal analysis information is stored correspondingly to the corresponding non-independent surface; If it is determined that a non-independent surface has a full combination label, and the corresponding full combination surface thermal analysis information is not stored in the full combination extraction library, the material type and thickness are calculated and processed according to the pre-trained processing algorithm to obtain the corresponding full combination surface thermal analysis information and store it in the full combination extraction library; Also includes: If it is determined that a non-independent surface has a semi-combination label, and the layer structure information of multiple non-independent surfaces is the same, the thermal analysis information of the semi-combination surface stored in the semi-combination extraction library is obtained, and the corresponding thermal analysis information of the semi-combination surface is stored correspondingly to the corresponding non-independent surface; If it is determined that a non-independent surface has a semi-combination label, and the corresponding semi-combination surface thermal analysis information is not stored in the semi-combination extraction library, and the layer structure information of the non-independent surface is the same, the material type and thickness are calculated and processed according to the pre-trained processing algorithm to obtain the corresponding semi-combination surface thermal analysis information and store it in the semi-combination extraction library; If it is determined that a non-independent surface has a semi-combined label and the layer structure information of multiple non-independent surfaces is different, the material type and thickness are calculated and processed according to the pre-trained processing algorithm to obtain the corresponding semi-combined surface thermal analysis information; The thermal analysis data and thermal analysis results are processed based on the building image data to obtain the thermal analysis display results, including: Get the center point of each face of each building block to establish the corresponding selected coordinate point; Comparing the thermal analysis information of each surface with the preset thermal analysis information to obtain a thermal analysis result, wherein the thermal analysis result is qualified or unqualified; The thermal analysis information, thermal analysis results and corresponding faces are stored correspondingly, and the thermal analysis display results are obtained by calculation based on the thermal analysis algorithm.

2. The method for processing building data based on multiple building codes according to claim 1, characterized in that: The method of obtaining a building block by statistically processing the corresponding pixels to be compared based on the neighbor relationship of all the pixels to be compared in the set of pixels to be compared includes: Determine all pixels directly adjacent to the pixel set to be compared or all pixels indirectly adjacent to other pixel sets to be compared, and obtain a corresponding block pixel set; Acquire a first top view of a first building image; Extracting the maximum Z-axis coordinate value of the same X-axis coordinate value and the same Y-axis coordinate value of the pixel points in each block pixel point set, and selecting the pixel points, so as to perform block division in the first top view to obtain the building block corresponding to each block pixel point set; The building blocks are classified based on their adjacent relationships to obtain independent building blocks and combined building blocks.

3. The method for processing building data based on multiple building codes according to claim 2, characterized in that: The method of classifying the building blocks based on the adjacent relationship of the building blocks to obtain independent building blocks and combined building blocks includes: Extracting the outline of each building block in the first top view to obtain corresponding outline information, wherein the outline information includes an X-axis coordinate value and a Y-axis coordinate value of a pixel point; If it is determined that the X-axis coordinate value and the same Y-axis coordinate value of any building block and all other building blocks are greater than the preset value, the corresponding building block is determined to be an independent building block and an independent label is added; If the difference between the X-axis coordinate value and the same Y-axis coordinate value of any two building blocks is less than or equal to a preset value, the two building blocks are judged to be combined building blocks and a combined label is added.

4. The method for processing building data based on multiple building codes according to claim 1, characterized in that: The step of comparing the surfaces corresponding to the combined building blocks to obtain the full combined surface and / or the half combined surface includes: Obtaining a three-dimensional outline of each building block in the first building image, and if it is determined that a distance value between any edge of the three-dimensional outline of the building block and any edge of the three-dimensional outline of other building blocks is less than or equal to an edge distance value, taking the corresponding two edges as a first comparison edge and a second comparison edge; Acquire an orientation relationship between the first comparison edge and the second comparison edge, wherein the orientation relationship at least includes a vertical relationship and a horizontal relationship; Determine the first comparison face and the second comparison face corresponding to the first comparison side and the second comparison side respectively based on the orientation relationship, and if it is determined that the first comparison face and the second comparison face completely overlap, take the first comparison face and the second comparison face as the full combination face; If it is determined that the first comparison surface and the second comparison surface do not completely overlap, the first comparison surface and the second comparison surface are regarded as semi-combined surfaces.

5. The method for processing building data based on multiple building codes according to claim 1, characterized in that: The thermal analysis information, thermal analysis results and corresponding faces are stored correspondingly, and the thermal analysis display results are obtained by calculation based on the thermal analysis algorithm, including: Count the number of first faces of all unqualified faces and the total number of faces of all faces, count the number of first blocks of building blocks with unqualified faces and the total number of blocks of all building blocks; Performing a quantity dimension calculation based on the first number of surfaces, the total number of surfaces, the first number of blocks, and the total number of blocks to obtain a quantity coefficient; Counting the first area of ​​the unqualified surface and the total area of ​​all surfaces, and calculating the area coefficient based on the first area and the total area; Calculating the thermal information difference between the thermal analysis information of each unqualified surface and the preset thermal analysis information, and determining the corresponding thermal information coefficient based on the thermal information difference, so that different thermal information difference intervals have different thermal information coefficients; Based on the quantity coefficient, area coefficient and thermal information coefficient, the thermal analysis anomaly coefficient of the thermal analysis display result is obtained.

6. The method for processing building data based on multiple building codes according to claim 5, characterized in that: The thermal analysis anomaly coefficient of the thermal analysis display result obtained based on the quantity coefficient, area coefficient, and thermal information coefficient includes: The thermal analysis anomaly coefficient is calculated by the following formula, ， in, is the thermal analysis anomaly coefficient, is the number of the first side, is the total number of faces, Face weight, is the number of the first block, is the total number of blocks, is the block weight, is the quantity weight, For the The sub-area of ​​the non-conforming surface, is the upper limit of the unqualified surface, For all faces The sub-area of ​​a face, is the upper limit of all faces, is the area weight, For the The thermal information coefficient of the unqualified surface is is the upper limit of the thermal information coefficient of the calculated unqualified surface, is the normalized value, is the thermal coefficient weight.

7. A building data processing system based on multiple building specifications according to the building data processing method based on multiple building specifications according to any one of claims 1 to 6, characterized in that: include: A processing module, configured to decompose the first building image based on the building image data of the first building to obtain a plurality of building blocks, and add corresponding building specification labels according to the attributes of the building blocks; A determination module, configured to obtain a multi-dimensional layer structure of the corresponding building block based on the second building image of each building block, and determine layer structure information of each dimensional layer structure, wherein the layer structure information at least includes a material type and a thickness; A calculation module, used for the multi-building code processing model to calculate and process the material type and thickness based on a pre-trained processing algorithm to obtain corresponding thermal analysis data, and to obtain thermal analysis results for each building block based on the building code label; A display module is used to perform data processing on thermal analysis data and thermal analysis results based on building image data to obtain thermal analysis display results; The step of decomposing the first building image based on the building image data of the first building to obtain a plurality of building blocks, and adding corresponding building specification labels according to the attributes of the building blocks, comprises: The building image data includes a three-dimensional first building image and a plane image corresponding to the first building image, wherein the plane image has layer structure information of the building; Compare and divide based on the coordinate information of each pixel point in the first building image to obtain a plurality of building blocks, wherein the building blocks include independent building blocks and combined building blocks; Generate a corresponding building code label according to the attributes of the building block and store it in correspondence with the corresponding building block, wherein the attributes include at least residential attributes, commercial attributes and public attributes; The comparison and division based on the coordinate information of each pixel point in the first building image is performed to obtain a plurality of building blocks, wherein the building blocks include independent building blocks and combined building blocks, including: Acquire the three-dimensional coordinate information of each pixel point in the first building image, and determine all the pixel points whose Z-axis coordinate values ​​are greater than the preset Z-axis coordinate value to obtain a set of pixel points to be selected; Determine all pixel points with the same X-axis coordinate value and the maximum Z-axis coordinate value in the set of pixel points to be selected, and obtain the set of pixel points to be compared; Based on the adjacent relationship of all the pixels to be compared in the set of pixels to be compared, statistical processing is performed on the corresponding pixels to be compared to obtain the building block; If it is determined that the management end actively divides the building blocks, the manually divided building blocks are obtained based on the division of the building blocks by the management end.

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