A method for rapid modeling

Abstract

The application relates to the field of building CAD data modeling and the technical field of building model storage cloud database, and particularly relates to a rapid modeling method; the method is based on computer-aided design technology, CAD construction drawings are used as a data source for modeling, a wall equivalent line algorithm based on priority is introduced to extract walls in a building, a space distance guide algorithm is introduced to reconstruct indoor space relations, parameterized modeling is carried out based on the indoor space relations and the existing walls, and the building modeling of the CAD data obtained in advance is stored in an Oracle database and can be called in time when needed; the method improves a preprocessing step of CAD data, automatically extracts useful data of CAD, removes redundant data, and significantly improves the speed of traditional CAD modeling.

Description

Technical Field

[0001] This invention relates to the fields of building CAD data modeling, CAD secondary development, and building model storage cloud database technology, specifically to a rapid modeling method. Background Technology

[0002] With the development of smart cities, the demand for 3D building models is increasing, especially for sophisticated 3D models, which are the core and foundation of smart city construction. However, existing modeling technologies have certain shortcomings. First, the labor costs are high: 1. Building modeling requires extensive professional knowledge and skills, demanding significant time and effort from architects. 2. Second, model quality is difficult to control: The quality of building models is affected by the architect's individual skills, precision, and professional knowledge. These factors can influence the reliability and accuracy of the building model, leading to variations in model quality that can impact subsequent construction processes and even the entire construction project. 3. Missing micro-details: During the building modeling process, micro-details are sometimes overlooked, potentially affecting the building's usability. 4. Most importantly, high hardware requirements: Large building models require high-end computers and specialized software. The high cost of this software and hardware may limit its application to small companies or individual architects, increasing modeling costs. Summary of the Invention

[0003] The purpose of this invention is to address the shortcomings of existing technologies by proposing the use of CAD data for modeling. The invention optimizes the data preprocessing steps before CAD modeling, removing redundant data in advance and significantly improving the speed of CAD modeling. Furthermore, due to the inherent accuracy of CAD data, the accuracy of the resulting model is also guaranteed to a certain extent. The parametric method used for modeling offers advantages such as high process repeatability and strong process adaptability, saving costs and time for enterprises. The Boolean difference method used for spatial extraction also possesses the aforementioned advantages. Finally, this invention proposes converting the final building model into binary data using gltf-jar and storing it in the BLOB field of an Oracle database, and then reconverting it to the required format using an OpenGL image database when needed.

[0004] To achieve the above objectives, the present invention is implemented through the following technical solution: a rapid modeling method, the method being as follows:

[0005] Step 1: Obtain the as-built CAD data of the building;

[0006] Step 2: Extract the building's external boundary lines in CAD to obtain the building's external wall layer;

[0007] Step 3: Based on the building exterior wall layer obtained in Step 2, perform an isoequivalence line algorithm based on wall priority to sequentially traverse the building's internal boundary lines and obtain the building wall data. The building wall data includes wall layers that equate doors and windows to walls. Then, stretch the building wall data to obtain the building model outline.

[0008] Step 4: Apply a navigable interior space extraction algorithm to the building exterior wall layer obtained in Step 2 to obtain the building's interior space relationships. The building's interior space relationships include building opening nodes, door nodes, and window nodes. Then extract building opening symbols, door symbols, and window symbols. Based on the building symbols, filter and check the nodes to obtain the specific interior space relationships. Interior spaces are divided into simple interior spaces and complex interior spaces. For simple interior spaces, Boolean subtraction can be used directly, while complex interior spaces require further processing before using Boolean subtraction. When extracting the specific relationships of interior spaces, a navigable space extraction algorithm is introduced. Boolean difference operation is used to subtract the polygons of all building components from the polygons determined by the building exterior wall layer, which makes the extracted interior space more visible and avoids some complex interior situations.

[0009] Step 5: Based on the specific indoor spatial relationships obtained in Step 4, reconstruct the indoor relationships of the building model outline obtained in Step 3 to obtain a more complete building model outline. Then, identify and parameterize the building components, perform parametric modeling, and obtain a detailed building model. The building model components include stairs, floor slabs, doors and windows. Parametric modeling mainly involves parameterizing some repetitive building components to optimize the modeling speed.

[0010] Step Six: Store the detailed building model in the database for future use.

[0011] Preferably, in step three, based on the building's external wall layer obtained in step two, an isoequivalence line algorithm based on wall priority is performed to sequentially traverse the building's internal boundary lines to obtain the building's wall data; the specific steps are as follows:

[0012] The relationship between walls and doors / windows in a building is categorized into five types: A1 central opening, A2 full-face opening, A3 edge opening, A4 corner opening, and A5 combined opening. These five types of walls are processed using equivalent lines. For the A5 combined opening, a priority concept is introduced, with the final priority being A1, A2, A3, and A4 for equivalent line processing. If both A1 and A3 exist within A5, A5 is directly processed using the A1 equivalent line method. This process continues, extending two equivalent parallel lines with the same thickness and elevation as the wall at both ends of the opening, thus obtaining the building wall data.

[0013] Preferably, the process of stretching the building wall data in step three to obtain the building model outline is as follows:

[0014] The obtained building wall data is stretched based on the wall's own elevation information to obtain the building model outline.

[0015] Preferably, the step four involves applying a navigable interior space extraction algorithm to the building exterior wall layer obtained in step two to obtain a building interior space relationship model. The specific steps are as follows:

[0016] Visibility analysis is performed on the building exterior wall layer obtained in step two to identify nodes with high spatial visibility values. Based on these nodes, navigable indoor spaces are extracted using the following formula: IVM(G,L)={P i (x i ,y i ,RI,D100)},i=1,...n, where P is the sampling point for visibility analysis; G represents the global visibility of the point; L represents the local visibility of the point; RID is the unique identifier for each individual indoor space, i.e., room or corridor; x,y represent the x and y coordinates of the visibility sampling point in the Cartesian coordinate system; i represents the number of nodes; the nodes include door nodes, window nodes, and cross-floor opening nodes inside the building.

[0017] Preferably, in step four, building void symbols, door symbols, and window symbols are extracted. Based on these building symbols, nodes are screened and investigated to obtain specific interior spatial relationships. The specific steps are as follows:

[0018] First, identify hole symbols, door symbols, and window symbols on the building exterior wall layer obtained in step two. Then, extract the polygons composed of multi-line segments of the above three symbols and compare them with the obtained building interior space relationship to determine whether they contain hole nodes, door nodes, and window nodes. If the polygon position information coincides with the node, it means that the node is a correct node; otherwise, it is an incorrect node, and the incorrect node is deleted. Traverse all nodes to obtain the spatial equivalent polygons of the correct nodes, such as the equivalent polygons of cross-floor interior space, door space, and window space, and the incorrect nodes. Then, merge the equivalent polygons of cross-floor interior space with the interior space nodes of the lower floor, that is, the floor slab does not exist at this point, and modify the attribute of this point to a staircase or elevator shaft according to the hole symbol. Perform a Boolean difference operation on the door space equivalent polygons, window space equivalent polygons, and the building model outline obtained in step three to leave door and window model holes on the building model outline.

[0019] Preferably, in step five, the architectural model outline obtained in step three is reconstructed based on the specific interior spatial relationships obtained in step four to obtain a more complete architectural model outline. Then, the architectural components are identified and parameterized, and parametric modeling is performed to obtain a detailed building model. The specific steps are as follows:

[0020] By performing a Boolean difference operation between the equivalent polygon of the cross-floor interior space and the floor slab of the same floor, a floor slab with holes is obtained, which is the real floor slab structure. Finally, the interior relationships are reconstructed by inserting the real floor slab into the building wall model obtained above to obtain a more complete building model outline. Based on the complete building model outline, the building components are parameterized and parametric modeling is performed.

[0021] Preferably, step six involves storing the detailed architectural model in a database for future use. The specific steps are as follows:

[0022] Detailed building models are first stored in a cloud database, then in an Oracle database. The model files are converted into binary files and stored in the BLOB field to obtain a building model database. When needed, the models are converted back into Glt format using the OpenGL graphics processing library for use.

[0023] The present invention has the following beneficial effects: (1) This method is based on computer-aided design (CAD) technology and uses CAD construction drawings as the data source for modeling; then, by introducing a priority-based wall equivalence line algorithm, the walls in the building are extracted; then, a navigable space extraction algorithm is introduced to reconstruct the indoor space relationship; then, parametric modeling is performed based on the indoor space relationship and the existing walls; the building model that can obtain CAD data in advance is stored in an Oracle database and can be called up in time when needed; the data preprocessing steps before CAD modeling have been optimized, redundant data has been removed in advance, and useful data from CAD has been automatically extracted, which significantly improves the speed of traditional CAD modeling; moreover, the parametric method used for modeling has the advantages of high process repeatability and strong process adaptability, which saves costs and time for enterprises.

[0024] (2) Existing wall extraction algorithms are greatly affected by noise and have low accuracy. The method of this invention introduces the concept of priority and takes high-priority walls as the primary search targets, avoiding wasting time on unnecessary walls and improving efficiency and accuracy. The indoor navigable space extraction algorithm extracts complex indoor relationships into visual nodes, which improves visibility when processing indoor spatial relationships and indirectly improves the speed and accuracy of indoor spatial relationship processing. The combination of the two algorithms also optimizes the shortcomings of traditional modeling algorithms, which are complex, difficult to implement and time-consuming. Attached Figure Description

[0025] Figure 1 The flowchart is a method for rapid modeling according to the present invention;

[0026] Figure 2 This is a schematic diagram of wall classification and equivalent walls in this invention;

[0027] Figure 3 The traditional interior relationship diagram is used, while the present invention extracts the interior spatial relationship into building opening nodes, door nodes and window nodes, thus simplifying the interior spatial relationship;

[0028] Figure 4 This is a schematic diagram of the building model in this invention. Detailed Implementation

[0029] The present invention will be further described below with reference to embodiments, but these embodiments are not intended to limit the scope of the invention.

[0030] like Figure 1 As shown, a rapid modeling method is described below:

[0031] Step 1: Obtain the as-built CAD data of the building.

[0032] Step 2: Extract the building's external boundary lines in CAD to obtain the building's external wall layer.

[0033] Step 3: Based on the building exterior wall layer obtained in Step 2, perform an isoequivalence line algorithm based on wall priority to sequentially traverse the building's internal boundary lines and obtain the building wall data. The building wall data includes wall layers that equate doors and windows to walls. Then, stretch the building wall data to obtain the building model outline.

[0034] Because the wall lines are interrupted by doors and windows, in order to obtain a complete wall, it is necessary to construct equivalent wall lines to replace the doors and windows. The specific steps are as follows:

[0035] The relationship between walls and doors / windows in buildings is categorized into five types: A1 Central opening, A2 Full-wall opening, A3 Edge opening, A4 Corner opening, and A5 Combined opening; A1 Central opening location relationship: The opening is sandwiched between two walls located on a straight line, such as... Figure 2 As shown in (a); the positional relationship of the opening on A2: the opening is sandwiched between two parallel but not straight walls, as shown in (a). Figure 2 As shown in (b); the positional relationship of the opening at the edge of A3: the opening is sandwiched between two walls that are perpendicular to each other and one wall has a projection onto the other wall, as shown in (b). Figure 2 (c) Middle; A4 Corner Opening Position Relationship: The opening is sandwiched between two mutually perpendicular wall sections that do not project onto each other, such as... Figure 2(d) shows the positional relationship of the A5 combined opening: walls that simultaneously satisfy multiple conditions mentioned above, such as... Figure 2 (e) Simultaneously satisfying the positional relationships of A1 and A3; to quickly extract the wall, the above positional relationships are processed as follows: The positional relationship of A1 is the most common in real life. The way to create the wall equivalence line is to stretch the walls on both sides, and the result is... Figure 2 (f); To create the equivalent lines for wall A2, you first need to find the center point of the opening enclosure, and then create two equivalent lines perpendicular to the two wall segments, at a distance of half the wall thickness from the center point, located on either side of the center point. Figure 2 As shown in (g); creating the A3 wall equivalence line is much simpler, just extend it perpendicularly until it intersects, and the result is... Figure 2 (h); The equivalent line for wall A4 is the same as that for A3, but it requires extending both ends of the wall until they intersect, resulting in... Figure 2 (i); For the A5 wall equivalence line, we need to introduce the concept of priority. The final absolute priority is A1, A2, A3, A4. That is, when the above relationships exist simultaneously, the relationship with the higher priority is processed first. For example, if A5 has both A1 and A3 relationships, then A5 can be directly processed using the A1 equivalence line method, and the final result is... Figure 1 As shown in (j); by analogy, two equivalent parallel lines with the same thickness and elevation as the wall extend from the walls at both ends of the opening, thus obtaining the building wall data;

[0036] The obtained building wall data is stretched based on the wall's own elevation information to obtain the building model outline.

[0037] Step 4: Apply a navigable interior space extraction algorithm to the building exterior wall layer obtained in Step 2 to obtain the building's interior space relationships. These relationships include building opening nodes, door nodes, and window nodes. Then, extract the building opening symbols, door symbols, and window symbols. Based on these building symbols, filter and examine the nodes to obtain the specific interior space relationships. The specific steps are as follows:

[0038] Visibility analysis is performed on the building exterior wall layer obtained in step two to identify nodes with high spatial visibility values. Based on these nodes, navigable indoor spaces are extracted using the following formula: IVM(G,L)={P i (x i ,y i,RI,D100)},i=1,...n, where P is the sampling point for visibility analysis; G represents the global visibility of the point; L represents the local visibility of the point; RID is the unique identifier for each individual indoor space, i.e., room or corridor; x,y represent the x and y coordinates of the visibility sampling point in the Cartesian coordinate system; i represents the number of nodes; the nodes include door nodes, window nodes, and cross-floor opening nodes inside the building;

[0039] First, identify hole symbols, door symbols, and window symbols on the building exterior wall layer obtained in step two. Then, extract the polygons composed of multi-line segments of the above three symbols and compare them with the obtained building interior space relationship to determine whether they contain hole nodes, door nodes, and window nodes. If the polygon position information coincides with the node, it means that the node is a correct node; otherwise, it is an incorrect node, and the incorrect node is deleted. Traverse all nodes to obtain the spatial equivalent polygons of the correct nodes, such as the equivalent polygons of cross-floor interior space, door space, and window space, and the incorrect nodes. Then, merge the equivalent polygons of cross-floor interior space with the interior space nodes of the lower floor, that is, the floor slab does not exist at this point, and modify the attribute of this point to a staircase or elevator shaft according to the hole symbol. Perform a Boolean difference operation on the door space equivalent polygons, window space equivalent polygons, and the building model outline obtained in step three to leave door and window model holes on the building model outline.

[0040] Step 5: Based on the specific interior spatial relationships obtained in Step 4, reconstruct the interior relationships of the building model outline obtained in Step 3 to obtain a more complete building model outline. Then, identify and parameterize the building components, perform parametric modeling, and obtain a detailed building model. The building model components include stairs, floors, doors, and windows.

[0041] The specific steps are as follows: Perform a Boolean difference operation between the equivalent polygon of the multi-story interior space and the floor slab of the same floor to obtain the perforated floor slab, i.e., the actual floor slab structure. Finally, reconstruct the interior relationships by inserting the actual floor slab into the building wall model obtained above, resulting in a more complete building model outline. Based on the complete building model outline, parameterize the building components and perform parametric modeling. After obtaining the model of a single-story building using the above method, repeat the above operations to obtain the model of the entire building or the model of multiple buildings, such as... Figure 4 As shown.

[0042] Step Six: Store the detailed building model in the database for future use;

[0043] The specific steps are as follows: First, store the detailed building model in the cloud database, then store it in the Oracle database. Convert the model file into a binary file and store it under the BLOB field to obtain the building model database. When needed, use the OpenGL graphics processing library to convert the model back into Glt format for use.

[0044] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. However, the above description is merely a specific embodiment of the present invention, and the technical features of the present invention are not limited thereto. Any other embodiments derived by those skilled in the art without departing from the technical solution of the present invention should be covered within the patent scope of the present invention.

Claims

1. A method for rapid modeling, characterized in that, The method is as follows: Step 1: Obtain the as-built CAD data of the building; Step 2: Extract the building's external boundary lines in CAD to obtain the building's external wall layer; Step 3: Based on the building exterior wall layer obtained in Step 2, perform an isoequivalence line algorithm based on wall priority to sequentially traverse the building's internal boundary lines and obtain the building wall data. The building wall data includes wall layers that equate doors and windows to walls. Then, stretch the building wall data to obtain the building model outline. Step 4: Apply a navigable interior space extraction algorithm to the building exterior wall layer obtained in Step 2 to obtain the building interior space relationship. The building interior space relationship includes building void nodes, door nodes, and window nodes. Then extract building void symbols, door symbols, and window symbols. Based on the building symbols, filter and investigate the nodes to obtain the specific interior space relationship. Step 5: Based on the specific interior spatial relationships obtained in Step 4, reconstruct the interior relationships of the building model outline obtained in Step 3 to obtain a more complete building model outline. Then, identify and parameterize the building components, perform parametric modeling, and obtain a detailed building model. The building model components include stairs, floors, doors, and windows. Step Six: Store the detailed building model in the database for future use.

2. The rapid modeling method according to claim 1, characterized in that, Step 3 involves performing an isoequivalence line algorithm based on wall priority on the building's external wall layer obtained in Step 2 to sequentially traverse the building's internal boundary lines and obtain the building's wall data. The specific steps are as follows: The relationship between walls and doors / windows in a building is categorized into five types: A1 central opening, A2 full-face opening, A3 edge opening, A4 corner opening, and A5 combined opening. These five types of walls are processed using equivalent lines. For the A5 combined opening, a priority concept is introduced, with the final priority being A1, A2, A3, and A4 for equivalent line processing. If both A1 and A3 exist within A5, A5 is directly processed using the A1 equivalent line method. This process continues, extending two equivalent parallel lines with the same thickness and elevation as the wall at both ends of the opening, thus obtaining the building wall data.

3. The rapid modeling method according to claim 2, characterized in that, The steps for stretching the building wall data to obtain the building model outline in step three are as follows: stretch the obtained building wall data according to the wall's own elevation information to obtain the building model outline.

4. The rapid modeling method according to claim 1, characterized in that, Step four describes the application of a navigable interior space extraction algorithm to the building exterior wall layer obtained in step two to obtain a building interior space relationship model. The specific steps are as follows: Visibility analysis is performed on the building exterior wall layer obtained in step two to identify nodes with high spatial visibility values. Based on these nodes, navigable indoor spaces are extracted using the following formula: IVM(G,L)={P i (x i ,y i ,RID,100)},i=1,...n, where P is the sampling point for visibility analysis; G represents the global visibility of the point; L represents the local visibility of the point; RID is the unique identifier for each individual indoor space, i.e., room or corridor; x,y represent the x and y coordinates of the visibility sampling point in the Cartesian coordinate system; i represents the number of nodes; the nodes include door nodes, window nodes, and cross-floor opening nodes inside the building.

5. The rapid modeling method according to claim 4, characterized in that, Step four involves extracting building void symbols, door symbols, and window symbols. Based on these building symbols, nodes are filtered and examined to obtain specific interior spatial relationships. The specific steps are as follows: First, identify hole symbols, door symbols, and window symbols on the building exterior wall layer obtained in step two. Then, extract the polygons composed of multi-line segments of the above three symbols and compare them with the obtained building interior space relationship to determine whether they contain hole nodes, door nodes, and window nodes. If the polygon position information coincides with the node, it means that the node is a correct node; otherwise, it is an incorrect node, and the incorrect node is deleted. Traverse all nodes to obtain the spatial equivalent polygons of the correct nodes, such as the equivalent polygons of cross-floor interior space, door space, and window space, and the incorrect nodes. Then, merge the equivalent polygons of cross-floor interior space with the interior space nodes of the lower floor, that is, the floor slab does not exist at this point, and modify the attribute of this point to a staircase or elevator shaft according to the hole symbol. Perform a Boolean difference operation on the door space equivalent polygons, window space equivalent polygons, and the building model outline obtained in step three to leave door and window model holes on the building model outline.

6. The rapid modeling method according to claim 5, characterized in that, Step five involves reconstructing the interior relationships of the architectural model outline obtained in step three based on the specific interior spatial relationships obtained in step four, resulting in a more refined architectural model outline. Then, architectural components are identified and parameterized, and parametric modeling is performed to obtain a detailed building model. The specific steps are as follows: By performing a Boolean difference operation between the equivalent polygon of the cross-floor interior space and the floor slab of the same floor, a floor slab with holes is obtained, which is the real floor slab structure. Finally, the interior relationships are reconstructed by inserting the real floor slab into the building wall model obtained above to obtain a more complete building model outline. Based on the complete building model outline, the building components are parameterized and parametric modeling is performed.

7. The rapid modeling method according to claim 1, characterized in that, Step six involves storing the detailed architectural model in the database for future use. The specific steps are as follows: Detailed building models are first stored in a cloud database, then in an Oracle database. The model files are converted into binary files and stored in the BLOB field to obtain a building model database. When needed, the models are converted back into Glt format using the OpenGL graphics processing library for use.

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