A building design method based on BIM

Abstract

The application is applied to the field of architectural design, and particularly relates to a building design method based on BIM, which comprises the following steps: determining a scanning complex reference value according to an obstacle coverage coincidence degree and a shielding distribution concentration index, and determining a scene partition mode according to a component correlation influence reference value and the scanning complex reference value; when partitioning based on a target of interest, determining the target of interest according to a reference interest degree, and determining an acquisition mode of a sub-region as sub-region construction based on a segmentation parameter or the target of interest based on a distribution state of the target of interest; determining a change request category according to a request range coverage and a target of interest proportion, and determining to adjust an update frequency or adjust a user change authority duration when the update frequency is adjusted according to a high wave request proportion. The application improves the efficiency of building design.

Description

Technical Field

[0001] This invention is applied to the field of architectural design, and in particular relates to a BIM-based architectural design method. Background Technology

[0002] With the gradual development of BIM (Building Information Modeling), the long-standing problems of information silos and collaborative work have been gradually solved. However, when faced with complex architectural designs, the actual construction process often results in architectural errors that deviate from the architectural design requirements and modifications to the architectural model. Frequent model changes can lead to design conflicts and thus affect the overall efficiency of architectural design. Therefore, how to reduce the occurrence of design conflicts to improve management efficiency is a problem of great concern to those skilled in the art.

[0003] Chinese Patent Publication No. CN116628800B discloses a BIM-based architectural design system, including: an information acquisition module, a modeling module, and a BIM design module. The information acquisition module is used to acquire depth images of the interior space of the building to be decorated. The modeling module is used to build a three-dimensional model of the interior space based on the depth images. The BIM design module is used to display the three-dimensional model in BIM software and to receive design instructions input by designers, modify the three-dimensional model according to the design instructions, and obtain a BIM design scheme. It can be seen that the above technical solution proposes to take multiple photos of structurally complex areas to obtain higher-precision modeling results, which is conducive to improving the efficiency of architectural decoration design. However, the following problems exist: in the process of architectural design involving multiple people and complex dynamics, the modification and alteration of the BIM model is prone to conflict with the actual construction scene, which can easily lead to low efficiency in solving problems and thus affect the design efficiency. Summary of the Invention

[0004] To address this, the present invention provides a BIM-based architectural design method to overcome the problem that existing technologies cannot meet dynamic modification requests in actual design, and are prone to low efficiency in dealing with complex and frequent modification needs, thus affecting design efficiency.

[0005] To achieve the above objectives, the present invention provides a BIM-based architectural design method, comprising: The scanning complexity reference value is determined based on the obstacle coverage overlap and the occlusion distribution concentration index, and the scene partitioning method (uniform partitioning or target partitioning) is determined based on the component association influence reference value and the scanning complexity reference value. In the target partition, the target of interest is determined based on the reference attention, and the method of obtaining the sub-region is determined based on the distribution status of the target of interest, which is to construct the sub-region based on the segmentation parameters or the target of interest. The change request is classified as a high-impact request or a normal request based on the coverage of the request scope and the proportion of the target of concern. The update frequency is adjusted or the duration of user permission change is adjusted based on the proportion of high-impact requests.

[0006] Furthermore, for target areas where the component association influence reference value is greater than the preset component association influence reference value or the scanning complexity reference value is greater than the preset scanning complexity reference value, the scene partitioning method is determined as the target partitioning.

[0007] Furthermore, the target partition includes: Detect the reference attention level of each target building, and record the target buildings with a reference attention level greater than the preset reference attention level as targets of attention; If the target of interest is a clustered distribution, then the first segmentation parameter is used to segment the first type of region, and the second segmentation parameter is used to segment the second type of region to obtain several sub-regions. If the target of interest is discretely distributed, then several sub-regions are constructed based on the target of interest.

[0008] Furthermore, for target areas where the component association influence reference value is less than or equal to the preset component association influence reference value and the scanning complexity reference value is less than or equal to the preset scanning complexity reference value, the scene partitioning method is determined to be uniform partitioning, and several sub-regions are obtained through uniform partitioning.

[0009] Furthermore, the complex reference values ​​for scanning are determined based on the overlap of obstacle coverage and the concentration index of occlusion distribution; The scanning complexity reference value is positively correlated with the overlap of obstacle coverage and the concentration index of occlusion distribution.

[0010] Furthermore, change requests with a scope coverage greater than the preset request scope coverage or a proportion of targets of interest greater than the preset proportion of targets of interest are denoted as high-impact requests. Change requests with a scope coverage less than or equal to the preset scope coverage and a target proportion less than or equal to the preset target proportion are categorized as ordinary requests.

[0011] Furthermore, based on the condition that the proportion of high-volume requests is less than the preset proportion of high-volume requests, the update frequency is adjusted for the area range corresponding to the high-volume requests.

[0012] Furthermore, based on the condition that the proportion of high-impact requests is greater than or equal to the preset proportion of high-impact requests, the duration for changing user permissions is adjusted.

[0013] Furthermore, when adjusting the update frequency for the area range corresponding to the high wave and the request, the update frequency is adjusted according to the parameter-driven difference. The update frequency is positively correlated with the parameter-driven variability.

[0014] Furthermore, when adjusting the duration of user permission changes, the duration of user permission changes is adjusted according to the joint coefficient of the associated components; The adjustment range of the user permission change duration is positively correlated with the joint coefficient of the associated components.

[0015] Compared with the prior art, the beneficial effects of the present invention are as follows: the present invention determines the scene partitioning method of the target area by using component association influence reference value and scanning complexity reference value. The component association influence reference value reflects the degree of association between each target building in the target area and other target buildings in the architectural design, and the scanning complexity reference value reflects the complexity of the actual building model obtained by scanning the target area. Then, when the component association influence reference value is greater than the preset component association influence reference value or the scanning complexity reference value is greater than the preset scanning complexity reference value, the target area is partitioned based on the target of interest, which further improves the flexibility of the scene partitioning method and makes the selection of the scene partitioning method more in line with the actual situation of the target area.

[0016] Furthermore, this invention reflects the number of times the target building has been modified or changed during the architectural design process based on the reference attention level. When the reference attention level is greater than the preset reference attention level, the focus target is identified and the distribution status of the focus target is analyzed. Thus, different sub-region division methods are adopted according to the different distribution status of the focus targets in the target area, avoiding the inability of a single sub-region division method to adapt to diverse regional situations, which would make the division effect difficult to support subsequent change request analysis.

[0017] Furthermore, this invention determines the scanning complexity reference value by using obstacle coverage overlap degree and occlusion distribution concentration index. The obstacle coverage overlap degree reflects the severity of the occlusion of the target building by obstacles, and the occlusion distribution concentration index reflects the distribution of obstacles affecting the scanning within the target area. This enables the determination of the scanning complexity reference value and provides data support for the subsequent determination of the scene zoning method of the target area.

[0018] Furthermore, this invention determines the category of change requests by using the request scope coverage and the proportion of the target of interest. The request scope coverage reflects the proportion of the sub-region to be modified in the change request to the target region, and the proportion of the target of interest reflects the proportion of the target of interest in the sub-region covered by the change request. This allows for precise classification of change request categories and provides accurate data support for subsequent adjustment methods. Attached Figure Description

[0019] Figure 1 This is a schematic diagram of the BIM-based architectural design method of the present invention; Figure 2This is a flowchart illustrating the method for determining scene partitioning based on component association influence reference values ​​and scanning complexity reference values ​​according to the present invention. Figure 3 This is a flowchart illustrating how the adjustment method is determined based on the proportion of high wave and request in this invention. Detailed Implementation

[0020] To make the objectives and advantages of the present invention clearer, the present invention will be further described below with reference to embodiments; it should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention.

[0021] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0022] Please see Figures 1 to 3 As shown, this invention provides a BIM-based architectural design method, including: The scanning complexity reference value is determined based on the obstacle coverage overlap and the occlusion distribution concentration index, and the scene partitioning method (uniform partitioning or target partitioning) is determined based on the component association influence reference value and the scanning complexity reference value. In the target partition, the target of interest is determined based on the reference attention, and the method of obtaining the sub-region is determined based on the distribution status of the target of interest, which is to construct the sub-region based on the segmentation parameters or the target of interest. The change request is classified as a high-impact request or a normal request based on the coverage of the request scope and the proportion of the target of concern. The update frequency is adjusted or the duration of user permission change is adjusted based on the proportion of high-impact requests.

[0023] This invention applies to a management platform for architectural design. The target area is the actual building area corresponding to the BIM model, and the target building is the building within the target area. During the design process of the BIM model in the target area, if the user needs to modify the BIM model according to the actual building conditions and change requests, a change request can be sent to the management platform. The content of the change request includes, but is not limited to, the area and spatial location of the target building in the BIM model that needs to be modified. Obstacles are devices or personnel located between the scanner and the target building during the scanning process.

[0024] This invention features a cyclical phase analysis cycle, with each phase analysis cycle lasting 48 hours. Users can adjust the duration of the phase analysis cycle according to their actual needs. The shorter the duration of the phase analysis cycle, the higher the frequency of data collection and the higher the analysis accuracy. The higher the user's requirements for analysis accuracy, the shorter the duration of the phase analysis cycle.

[0025] Specifically, the complex reference values ​​for scanning are determined based on the overlap of obstacle coverage and the concentration index of occlusion distribution; The scanning complexity reference value is positively correlated with the overlap of obstacle coverage and the concentration index of occlusion distribution.

[0026] The scanning complexity reference value = obstacle coverage overlap / preset obstacle coverage overlap + occlusion distribution concentration index / occlusion distribution concentration index. Obstacle coverage overlap = total maximum width of obstacle projections / perimeter of the smallest rectangle that can contain all obstacles. Occlusion distribution concentration index = number of obstacle projections / number of obstacles. The number of obstacle projections is the number of projections detected by the scanner during scanning. The total maximum width of obstacle projections is the sum of the widths of the smallest rectangles that can contain all obstacle projections.

[0027] In this embodiment of the invention, the preset obstacle coverage overlap value is 0.08. It can be understood that the obstacle coverage overlap reflects the severity of the obstruction of the target building by the obstacle. The higher the obstacle coverage overlap, the greater the impact of the obstacle during scanning, and the more difficult it is to obtain accurate scanning results. The more sensitive the managers are to the difficulty of obtaining accurate scanning results, the lower the preset obstacle coverage overlap value will be.

[0028] In this embodiment of the invention, the preset occlusion distribution concentration index is set to 0.5. It can be understood that the occlusion distribution concentration index reflects the distribution of obstacles in the target area that affect scanning. The larger the occlusion distribution index, the lower the degree of concentration of the obstacles, the higher the difficulty of scanning the target area, and the more sensitive the managers are to the difficulty of scanning the target area. Therefore, the preset occlusion distribution concentration index is set to a lower value.

[0029] Specifically, for target areas where the component association influence reference value is greater than the preset component association influence reference value or the scan complexity reference value is greater than the preset scan complexity reference value, the scene partitioning method is determined as the target partitioning.

[0030] The component association impact reference value is the average value of the component association impact reference sub-values ​​of each target building in the target area. For a single target building, the adjustable parameters corresponding to the target building are detected, and the definition formulas of other parameters besides the adjustable parameter are traversed. The number of times the adjustable parameter is referenced by other formulas is recorded as the component association impact reference sub-value. The scanning complexity reference value = obstacle coverage overlap / preset obstacle coverage overlap + occlusion distribution concentration index / preset occlusion distribution concentration index.

[0031] In this embodiment of the invention, the preset component association influence reference value is 6. It can be understood that the component association influence reference value reflects the degree of association between each target building in the target area and other target buildings in the architectural design. The larger the component association influence reference value, the higher the degree of association between target buildings, the higher the difficulty of analyzing the target area, and the more sensitive the managers are to the difficulty of analyzing the target area. Therefore, the preset component association influence reference value is lower.

[0032] In this embodiment of the invention, the preset scanning complexity reference value is 1.6. It can be understood that the scanning complexity reference value reflects the complexity of the target area to determine the target building model. The higher the scanning complexity reference value, the greater the impact of the distribution of obstacles on the scanning process, the higher the difficulty of scanning the target building, and the higher the difficulty of obtaining the target building model. The more sensitive the managers are to the difficulty of obtaining the target building model, the lower the preset scanning complexity reference value.

[0033] Specifically, the target partition includes: Detect the reference attention level of each target building, and record the target buildings with a reference attention level greater than the preset reference attention level as targets of attention; If the distribution of the target of interest is clustered, then the first segmentation parameter is used to segment the first type of region, and the second segmentation parameter is used to segment the second type of region to obtain several sub-regions. If the distribution of the target of interest is discrete, then several sub-regions are constructed based on the target of interest.

[0034] If the density of the target of interest is greater than the preset density of the target of interest, the target of interest is in a clustered distribution state; if the density of the target of interest is less than or equal to the preset density of the target of interest, the target of interest is in a discrete distribution state.

[0035] For a single target of interest, the reference attention level is the number of times the target of interest receives change requests. The density of the target of interest = the area of ​​the target of interest / the area of ​​the target region. The area of ​​the target of interest is the area of ​​a rectangle that can contain all targets of interest. The area corresponding to the rectangle is recorded as a type I region, and the target regions other than the type I regions are recorded as type II regions.

[0036] The first type of region is uniformly divided into several sub-regions, the number of which is the integer obtained by rounding up the first segmentation parameter, which is the average value of the reference sub-values ​​of the component influence of each target of interest. The second type of region is uniformly divided into several sub-regions, the number of which is the integer obtained by rounding up the second segmentation parameter, which is the reciprocal of the geometric complexity reference value of the second type of region. The geometric complexity reference value = number of grid faces in the second type of region / number of grid faces in the target region. The number of grid faces in the second type of region is the number of grids in the grid model exported from the BIM model corresponding to the second type of region, and the number of grid faces in the target region is the number of grids in the grid model exported from the BIM model.

[0037] When the target of interest is discretely distributed, for a single target of interest, based on the location of the target of interest, the complete target buildings within the adjacent distance of the target of interest are recorded as a sub-region, and the adjacent distance is the minimum distance between the target of interest and other targets of interest.

[0038] In this embodiment of the invention, the preset reference attention value is 15. It can be understood that the reference attention value reflects the changes in the target building during the architectural design process. The higher the reference attention value, the more times the target building is modified, the higher the probability of subsequent modifications to the target, and the higher the probability that the target building will affect the modified content when analyzing the target area. Therefore, the attention value of the target building is higher. The higher the sensitivity of managers to the attention value of the target building, the lower the preset reference attention value.

[0039] Specifically, for target areas where the component association influence reference value is less than or equal to the preset component association influence reference value and the scanning complexity reference value is less than or equal to the preset scanning complexity reference value, the scene partitioning method is determined to be uniform partitioning, and several sub-regions are obtained through uniform partitioning.

[0040] In uniform partitioning, the target area is evenly divided into several sub-regions. Administrators can adjust the number of partitions according to their own needs. The larger the number of partitions, the smaller the volume of the sub-regions and the lower the difficulty of analyzing the sub-regions. The higher the user's sensitivity to the difficulty of sub-region analysis, the higher the value of the number of partitions. In this embodiment of the invention, the number of partitions is 20.

[0041] Specifically, change requests with a scope coverage greater than the preset request scope coverage or a proportion of targets of interest greater than the preset proportion of targets of interest are denoted as high-impact requests. Change requests with a scope coverage less than or equal to the preset scope coverage and a target proportion less than or equal to the preset target proportion are categorized as ordinary requests.

[0042] Request scope coverage = area of ​​the sub-region corresponding to the change request / area of ​​the target region. For a single change request, the percentage of targets of concern = number of targets of concern modified in the change request / number of target buildings modified in the change request.

[0043] In this embodiment of the invention, the preset request range coverage value is 0.05. It can be understood that the request range coverage reflects the coverage of the area that needs to be changed in the change request. The higher the request range coverage, the larger the area of ​​the sub-area that needs to be changed in the change request, and the more difficult it is to complete the change request. The more sensitive the managers are to the difficulty of completing the change request, the lower the preset request range coverage value.

[0044] In this embodiment of the invention, the preset target proportion is 0.3. It can be understood that the target proportion reflects the proportion of targets of concern in the modification content corresponding to the change request. The larger the target proportion, the greater the impact of the target on the process of realizing the content corresponding to the change request, and the higher the difficulty of realizing the change request. The more sensitive the managers are to the difficulty of realizing the change request, the lower the preset target proportion.

[0045] Specifically, based on the condition that the proportion of high-volume requests is less than the preset proportion of high-volume requests, the adjustment method is determined to be to adjust the update frequency for the area range corresponding to the high-volume requests.

[0046] Specifically, based on the condition that the proportion of high-impact requests is greater than or equal to the preset proportion of high-impact requests, the adjustment method is determined to be to adjust the duration of user permission changes.

[0047] For a single phase analysis period, the percentage of high-impact requests = number of high-impact requests / number of change requests.

[0048] In this embodiment of the invention, the preset high-impact request ratio is 0.3. It can be understood that the high-impact request ratio reflects the ratio of the number of high-impact requests to change requests. The higher the high-impact request ratio, the larger the proportion of high-impact requests, and the higher the design difficulty of the analysis cycle of this stage. The more sensitive the managers are to the design difficulty of the stage analysis cycle, the lower the preset high-impact request ratio.

[0049] Specifically, when adjusting the update frequency for the area corresponding to the high wave and the request, the update frequency is adjusted according to the parameter-driven difference. The update frequency is positively correlated with the parameter-driven variability.

[0050] For a single high-sweep request, the parameter-driven variability is determined by detecting the target buildings modified in the high-sweep request and recording the variance of the number of parameters modified for each target building as the parameter-driven variability.

[0051] For a single stage analysis cycle, the update frequency = baseline frequency × (parameter-driven difference / preset parameter-driven difference). In this embodiment of the invention, the update frequency is an integer rounded up, the baseline frequency is 5 times per cycle, and the preset parameter-driven difference is 4.

[0052] The preset parameter-driven difference value can be understood as reflecting the degree of difference in modifications made to each target building by the high-impact request. The larger the parameter-driven difference value, the greater the difference in the degree of modification between each target building. This means that the modification fluctuation of each target building within the area corresponding to the high-impact request is larger, which makes it more difficult to analyze the modification progress in that area. The more sensitive the managers are to the difficulty of analyzing the modification progress, the lower the preset parameter-driven difference value should be.

[0053] Specifically, when adjusting the duration of user permission changes, the duration of user permission changes is adjusted according to the joint coefficient of the associated components; The adjustment range of the user permission change duration is positively correlated with the joint coefficient of the associated components.

[0054] For the area range corresponding to the change request, the method for confirming the joint coefficient of associated components is to confirm all parameters that need to be modified within the area range, detect the number of parameters driven by the automated script among the parameters that need to be modified, and the joint coefficient of associated components = 1 - the number of parameters driven by the automated script / the number of parameters that need to be modified.

[0055] User permission change duration = base duration + adjustment duration × associated component joint coefficient. In this embodiment of the invention, the base duration is 3 hours and the adjustment duration is 1 hour. It can be understood that the administrator can adjust the base duration and adjustment duration according to actual needs. The longer the base duration and adjustment duration, the longer the user permission change duration.

[0056] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of the present invention.

Claims

1. A BIM-based architectural design method, characterized in that, include: The scanning complexity reference value is determined based on the obstacle coverage overlap and the occlusion distribution concentration index, and the scene partitioning method (uniform partitioning or target partitioning) is determined based on the component association influence reference value and the scanning complexity reference value. In the target partition, the target of interest is determined based on the reference attention, and the method of obtaining the sub-region is determined based on the distribution status of the target of interest, which is to construct the sub-region based on the segmentation parameters or the target of interest. The change request is classified as a high-impact request or a normal request based on the coverage of the request scope and the proportion of the target of concern. The update frequency is adjusted or the duration of user permission change is adjusted based on the proportion of high-impact requests.

2. The BIM-based architectural design method according to claim 1, characterized in that, For target areas where the component association impact reference value is greater than the preset component association impact reference value or the scan complexity reference value is greater than the preset scan complexity reference value, the scene partitioning method is determined as the target partitioning.

3. The BIM-based architectural design method according to claim 2, characterized in that, The target partition includes: Detect the reference attention level of each target building, and record the target buildings with a reference attention level greater than the preset reference attention level as targets of attention; If the target of interest is a clustered distribution, then the first segmentation parameter is used to segment the first type of region, and the second segmentation parameter is used to segment the second type of region to obtain several sub-regions. If the target of interest is discretely distributed, then several sub-regions are constructed based on the target of interest.

4. The BIM-based architectural design method according to claim 1, characterized in that, For target areas where the component association influence reference value is less than or equal to the preset component association influence reference value and the scanning complexity reference value is less than or equal to the preset scanning complexity reference value, the scene partitioning method is determined to be uniform partitioning, and several sub-regions are obtained through uniform partitioning.

5. The BIM-based architectural design method according to claim 2, characterized in that, The complex reference values ​​for scanning are determined based on the overlap of obstacle coverage and the concentration index of occlusion distribution. The scanning complexity reference value is positively correlated with the overlap of obstacle coverage and the concentration index of occlusion distribution.

6. The BIM-based architectural design method according to claim 2 or 4, characterized in that, Change requests with a scope coverage greater than the preset request scope coverage or a proportion of targets of interest greater than the preset proportion of targets of interest are denoted as high-impact requests. Change requests with a scope coverage less than or equal to the preset scope coverage and a target proportion less than or equal to the preset target proportion are categorized as ordinary requests.

7. The BIM-based architectural design method according to claim 6, characterized in that, Based on the condition that the proportion of high-volume requests is less than the preset proportion of high-volume requests, the update frequency is adjusted for the area range corresponding to the high-volume requests.

8. The BIM-based architectural design method according to claim 6, characterized in that, Based on the condition that the proportion of high-impact requests is greater than or equal to the preset proportion of high-impact requests, the duration for changing user permissions is adjusted.

9. The BIM-based architectural design method according to claim 7, characterized in that, When adjusting the update frequency for the area range corresponding to the high wave and the request, the update frequency is adjusted according to the parameter-driven difference. The adjustment range of the update frequency is positively correlated with the parameter-driven variability.

10. The BIM-based architectural design method according to claim 8, characterized in that, When adjusting the duration of user permission changes, the duration of user permission changes is adjusted according to the joint coefficient of the associated components; The adjustment range of the user permission change duration is positively correlated with the joint coefficient of the associated components.

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