Construction method and system of engineering building visual model based on BIM technology

Abstract

The invention relates to the technical field of data processing, in particular to an engineering building visualization model construction method and system based on the BIM technology, and the method comprises the steps: constructing a target three-dimensional model through historical engineering building data; dividing the target three-dimensional model into a plurality of detection nodes through a preset structure, and determining a collision type of each detection node; determining the collision severity and the position key degree of each detection node by using the collision type; and determining a processing priority of each detection node by using the collision severity and the position key degree, and further performing building engineering repair processing according to the processing priority and the target three-dimensional model. According to the method, rapid and accurate analysis of hard collision is realized, repair processing is carried out according to the processing priority, and the collision detection efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a method and system for constructing an engineering building visualization model based on BIM technology. Background Art

[0002] BIM-based 3D model construction methods and systems cover the entire process from design to construction and from construction to operation and maintenance, greatly improving the accuracy, efficiency, and collaboration of construction projects. Clash detection, a core function in BIM, refers to the use of software tools to automatically identify and report physical conflicts or overlaps between model elements during building design, construction, and operation and maintenance. Clash detection not only reduces problems during construction but also helps design teams optimize models, improving design quality and construction efficiency.

[0003] At present, the problem of structural "collision" is inevitable in the process of BIM-based modeling of engineering buildings. Traditional collision detection methods have accuracy problems when detecting large-scale building models, resulting in false positives or missed negatives in collision detection results, affecting the efficiency and quality of the construction of engineering building three-dimensional models, affecting the overall quality or design integrity of subsequent projects, and posing a safety hazard. Summary of the Invention

[0004] To address the technical problem that existing traditional collision detection methods have accuracy issues when detecting large-scale building models, resulting in false positives or missed negatives in collision detection results, the present invention aims to provide a method and system for constructing a visual model of an engineering building based on BIM technology. This method uses an octree structure to partition the BIM three-dimensional model and determine the possible collision type for each node. Based on the collision severity and location criticality of the corresponding structure in a hard collision, the corresponding risk treatment coefficient is determined to determine the treatment priority of different collision structures, which is conducive to improving work efficiency and enhancing the quality of constructing a three-dimensional building model.

[0005] The technical solution adopted is as follows: a method for constructing an engineering building visualization model based on BIM technology is provided, including: constructing a target three-dimensional model using historical engineering building data; dividing the target three-dimensional model into multiple detection nodes through a preset structure, and determining the collision type of each detection node; using the collision type, determining the collision severity and position criticality of each detection node; using the collision severity and position criticality, determining the processing priority of each detection node, and then performing repair processing on the construction project based on the processing priority and the target three-dimensional model.

[0006] In one embodiment of the present invention, the use of historical engineering construction data to construct a target three-dimensional model includes: obtaining historical engineering construction data corresponding to the construction project, wherein the historical engineering construction data at least includes the geometric shape information, material information, spatial structure information and functional division information of the construction project; using the geometric shape information, the material information, the spatial structure information and the functional division information to construct the target three-dimensional model corresponding to the construction project through a preset drawing method.

[0007] In one embodiment of the present invention, the target three-dimensional model is divided into multiple detection nodes by a preset structure, and the collision type of each detection node is determined, including: obtaining a first spatial structure of the target three-dimensional model; dividing the first spatial structure into multiple second spatial structures by using a preset structure, wherein the second spatial structures are identical to each other and each second spatial structure represents a detection node; obtaining the overlap between any two detection nodes, and determining the collision type between the two detection nodes by using the overlap.

[0008] In one embodiment of the present invention, it also includes: in response to the second spatial structure including multiple building units, each of the second spatial structures is divided into multiple third spatial structures using a preset structure, so that the number of building units included in each of the third spatial structures is less than a preset number threshold, wherein the building units are independent building structures.

[0009] In one embodiment of the present invention, obtaining the degree of overlap between any two detection nodes and determining the type of collision between the two detection nodes using the degree of overlap includes: obtaining a first building unit in any one of the detection nodes, obtaining a second building unit in another detection node, and obtaining the Euclidean distance between the two detection nodes; determining the morphological similarity between the first building unit and the second building unit using the first building unit and the second building unit; determining the degree of overlap between the two detection nodes using the Euclidean distance and the morphological similarity; obtaining the first fractal dimension and the second fractal dimension of the first building unit and the second building unit respectively, and determining the average fractal dimension using the first fractal dimension and the second fractal dimension; and determining the type of collision between the two detection nodes using the average fractal dimension and the degree of overlap.

[0010] In one embodiment of the present invention, the method further includes: in response to the Euclidean distance being less than a preset distance threshold, determining that the collision type between the two detection nodes is a hard collision by using the average fractal dimension and the overlap.

[0011] In one embodiment of the present invention, the use of the collision type to determine the collision severity and position criticality of each detection node includes: obtaining the spatial intrusion degree of the current collision position, and obtaining the confidence level of the current collision position; using the spatial intrusion degree and the confidence level to determine the collision severity of the current collision position of the detection node; obtaining the relative vertical height of the current collision position in the target three-dimensional model, and obtaining the distance proximity between the current collision position and the core area of the target three-dimensional model; using a preset model height value, the relative vertical height and the distance proximity to determine the position criticality of the current collision position of the detection node.

[0012] In one embodiment of the present invention, obtaining the spatial intrusion degree of the current collision position includes: in response to the collision type being a hard collision, obtaining the first volume of the third building unit of the current collision position, and obtaining the second volume of the fourth building unit of the current collision position, and obtaining the third volume of the overlap between the third building unit and the fourth building unit; determining a first volume value using the first volume and the third volume, and determining a second volume value using the second volume and the third volume; and determining the spatial intrusion degree of the current collision position using the first volume value and the second volume value.

[0013] In one embodiment of the present invention, the method of determining the position criticality of the current collision position of the detection node by using the preset model height value, the relative vertical height and the distance proximity includes: determining the distance proximity between the current collision position and the core area by using the preset model height value, the relative vertical height and the proximity; obtaining the fourth volume of the current detection node where the current collision position is located, and obtaining the fifth volume of the third building unit and the fourth building unit where the current collision position collides, and obtaining the sixth volume of the previous-level detection node where the current collision position is located; and determining the position criticality of the current collision position of the detection node by using the fourth volume, the fifth volume, the sixth volume and the distance proximity.

[0014] To solve the above technical problems, another technical solution adopted in this application is: a construction visualization model construction system for engineering buildings based on BIM technology, including: a construction module, which uses historical engineering construction data to construct a target three-dimensional model; a first determination module, which divides the target three-dimensional model into multiple detection nodes through a preset structure, and determines the collision type of each detection node; a second determination module, which uses the collision type to determine the collision severity and position criticality of each detection node; a third determination module, which uses the collision severity and position criticality to determine the processing priority of each detection node, and then performs repair processing on the construction project based on the processing priority and the target three-dimensional model.

[0015] The beneficial effects of the present invention are as follows: a method for constructing an engineering building visualization model based on BIM technology is provided, comprising: constructing a target three-dimensional model using historical engineering building data; dividing the target three-dimensional model into multiple detection nodes through a preset structure, and determining the collision type of each detection node; using the collision type, determining the collision severity and position criticality of each detection node; using the collision severity and the position criticality, determining the processing priority of each detection node, and then repairing the construction project based on the processing priority and the target three-dimensional model; that is, the present invention divides the target three-dimensional model of the construction project into multiple detection nodes through a preset structure, and determines the collision type of each detection node, and then obtains the collision severity and position criticality of the building structure in the detection node, and then determines the processing priority of each collision position, which is conducive to improving work efficiency and improving the quality of constructing the three-dimensional model of the building. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art descriptions. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0017] Figure 1 This is a flow chart of a method for constructing an engineering building visualization model based on BIM technology provided by the present invention;

[0018] Figure 2 This is a structural diagram of the engineering building visualization model construction system based on BIM technology provided by the present invention. DETAILED DESCRIPTION

[0019] To further illustrate the technical means and effectiveness of the present invention in achieving its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, describes in detail the specific implementation, structure, features, and effectiveness of a method and system for constructing a visual model of an engineering building based on BIM technology. In the following description, references to different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.

[0020] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0021] The following describes in detail a method and system for constructing a visual model of an engineering building based on BIM technology provided by the present invention in conjunction with the accompanying drawings.

[0022] See also Figure 1 , which shows a flow chart of the method for constructing an engineering building visualization model based on BIM technology provided by the present invention.

[0023] like Figure 1 As shown in the figure, the method for constructing an engineering building visualization model based on BIM technology includes the following steps:

[0024] S10. Use historical engineering and construction data to construct a target three-dimensional model.

[0025] Among them, engineering construction data refers to the geometric shape information, material information, spatial structure information and functional division information of buildings in construction projects, among which the geometric shape information includes the size and shape of the building, the material information includes the material of the building, the spatial structure information includes the spatial structure of the building, and the functional division information includes the functional division of each building; the three-dimensional model refers to a model that presents engineering construction data in the form of electronic data through drawing.

[0026] Specifically, historical engineering building data that requires three-dimensional model construction is obtained, and the geometric shape information, material information, spatial structure information and functional division information of the buildings in the historical building projects are used to construct a model in the form of electronic data, thereby determining the target three-dimensional model corresponding to the historical engineering building data.

[0027] In some embodiments, a BIM (Building Information Modeling) model may be used as the target three-dimensional model. The BIM model, also known as the Building Information Model, is a new tool in architecture, engineering, and civil engineering.

[0028] S20 , dividing the target three-dimensional model into a plurality of detection nodes through a preset structure, and determining a collision type of each detection node.

[0029] Among them, the preset structure refers to the structure for dividing the target three-dimensional model; the detection node refers to the representation of the subspace structure obtained after the target three-dimensional model is divided according to the preset structure, that is, each subspace structure obtained by the division is used to represent a detection node; the collision type refers to the type of collision between building units in the detection node, such as hard collision and soft collision. A hard collision refers to a collision with overlap or actual interference, and a soft collision refers to a collision with a distance that is too close, affecting installation or operation, but without actual contact. A building unit refers to the smallest independent building structure, which can also be called a building element.

[0030] Specifically, a suitable preset structure is selected, and then the spatial structure of the target three-dimensional model is divided into multiple sub-space structures of the same size through the preset structure, and each sub-space structure is represented by a corresponding detection node; then the building units contained in each detection node are obtained, and it is determined whether the building units in the detection node collide, that is, the collision type between the building units is determined.

[0031] In some embodiments, the preset structure may be an octree structure, that is, the target three-dimensional model is divided by the octree structure, and each divided subspace serves as a detection node.

[0032] S30 : In response to the collision type of the detection node being a hard collision, determine the collision severity and position criticality of each detection node of the hard collision.

[0033] Among them, the severity of the collision refers to the degree of overlap or interference between building units in the detection node, which is positively correlated; that is, the higher the degree of overlap, the more severe the collision severity; or the higher the degree of interference, the more severe the collision severity; the position criticality refers to the distance between the collision position where the collision occurs and the core of the three-dimensional model of the building, which is negatively correlated; for example, the greater the distance, the smaller the position criticality, and the smaller the distance, the greater the position criticality.

[0034] Specifically, after determining that the collision type of the detection node is a hard collision, in response to the collision type of the detection node being a hard collision, the degree of overlap or interference between the building units in the detection node is obtained, and the degree of overlap or interference is used to determine the severity of the collision between the building units, that is, determine the severity of the collision of each detection node; and obtain the collision position where the collision occurs and the core position of the three-dimensional model of the building, and then use the distance between the collision position and the core position to determine the position criticality of the collision position where the collision occurs, that is, the position criticality of the detection node where the hard collision occurs.

[0035] S40: Determine the processing priority of each detection node by using the collision severity and the location criticality, and then perform repair processing on the building project of the target three-dimensional model according to the processing priority.

[0036] The processing priority refers to the order in which the detection nodes need to be processed.

[0037] Specifically, after obtaining the collision severity and position criticality of each detection node, vector calculation or matrix norm calculation is performed using the collision severity and position criticality, and the processing priority of each detection node is determined based on the calculation results; then, based on the processing priority, the construction projects of the target three-dimensional model are repaired one by one from large to small, and the final three-dimensional model is determined.

[0038] In this embodiment, the target three-dimensional model constructed by historical engineering construction data is divided into multiple detection nodes, and then the collision type of each detection node is determined, and the collision severity and position criticality of the detection node with a hard collision type are obtained, and then the processing priority of each detection node is determined, thereby achieving rapid and accurate analysis of hard collisions, and performing repair processing according to the processing priority, thereby improving the efficiency of collision detection.

[0039] In some embodiments, S10 constructs a target three-dimensional model using historical engineering and construction data, which may include the following operations:

[0040] First, historical engineering building data corresponding to the construction project is obtained, wherein the historical engineering building data at least includes geometric shape information, material information, spatial structure information and functional division information of the construction project.

[0041] Among them, construction projects refer to construction projects that are in the process of design, construction, or operation and maintenance.

[0042] Specifically, for construction projects that are under design, construction, or operation and maintenance, all existing building units, geometric shape information, material information, spatial structure information, and functional division information are obtained.

[0043] Then, using geometric shape information, material information, spatial structure information and functional division information, a target three-dimensional model corresponding to the construction project is constructed through a preset drawing method.

[0044] The preset drawing method may be an electronic drawing method, that is, drawing corresponding electronic data, such as a BIM (Building Information Modeling) model.

[0045] Specifically, the BIM (Building Information Modeling) model is used to draw the geometric shape information, material information, spatial structure information and functional division information of all building units in the construction project to obtain the target three-dimensional model corresponding to the construction project.

[0046] In this embodiment, the target three-dimensional model is constructed using historical engineering construction data, which can accurately depict the current structure of the construction project and display it in the form of electronic data to facilitate collision identification and analysis, saving the time required for field investigations, and helping to improve the efficiency of analysis and collision detection.

[0047] In some embodiments, S20 divides the target three-dimensional model into a plurality of detection nodes using a preset structure and determines the collision type of each detection node, which may include the following operations:

[0048] First, a first spatial structure of the target three-dimensional model is obtained.

[0049] Among them, the first spatial structure refers to the spatial structure displayed after the target three-dimensional model of the construction project is constructed.

[0050] Specifically, a large cube or sphere is determined using the target three-dimensional model. This embodiment is described as a cube, that is, the cube can contain the target three-dimensional model, and the determined cube is used as the first spatial structure of the target three-dimensional model.

[0051] Next, the first spatial structure is divided into a plurality of second spatial structures using a preset structure, wherein the second spatial structures are identical to each other, and each second spatial structure represents a detection node.

[0052] The second spatial structure refers to a sub-space structure formed by dividing the first spatial structure.

[0053] Specifically, a suitable preset structure is selected, and then the preset structure is used to divide the first spatial structure corresponding to the target three-dimensional model into multiple identical second spatial structures; for example, the preset structure is explained using the octree structure as an example, and then the octree structure is used to divide the first spatial structure corresponding to the target three-dimensional model into eight identical second spatial structures.

[0054] Then, the overlap degree between any two detection nodes is obtained, and the collision type between the two detection nodes is determined using the overlap degree.

[0055] Among them, the overlap degree refers to the degree of overlap of building units within different detection nodes; the collision type refers to the type of collision between building units in the detection node, such as hard collision and soft collision. A hard collision refers to a collision with overlap or actual interference, that is, a collision occurs; a soft collision refers to a collision where the distance is too close, affecting installation or operation, but there is no actual contact.

[0056] Specifically, after obtaining the eight identical second spatial structures divided by the first spatial structure, each second spatial structure is used as a detection node, and the building units within each detection node are obtained, and then the degree of overlap of the corresponding building units between different detection nodes is determined, and then the collision type between different detection nodes is determined based on the size of the overlap.

[0057] Furthermore, the following operations may be included.

[0058] In response to the second spatial structure including multiple building units, each second spatial structure is divided into multiple third spatial structures using a preset structure, so that the number of building units included in each third spatial structure is less than a preset number threshold, wherein the building units are independent building structures.

[0059] In order to more accurately characterize the building unit, the second spatial structure can be further divided.

[0060] Specifically, for each second space structure, it can be divided into multiple third space structures according to a preset structure; for example, according to an octree structure, each second space structure is divided into eight third space structures of the same size, so that the number of building units in each divided sub-space structure is less than a preset number threshold, for example, less than 2, that is, the number of building units in each divided sub-space structure is 1 or 0.

[0061] In some embodiments, if the number of building units in the third spatial structure is greater than 1, it can be further divided until the number of building units in each sub-space structure is 1 or 0.

[0062] In this embodiment, the divided second spatial structure is used as a detection node to determine whether there is overlap among the building units within different second spatial structures. The collision type can then be effectively distinguished based on the degree of overlap, providing a basis for subsequent operations.

[0063] In some embodiments, obtaining the overlap between any two detection nodes and determining the collision type between the two detection nodes using the overlap may further include the following operations.

[0064] First, a first building unit in any detection node is obtained, and a second building unit in another detection node is obtained, and the Euclidean distance between the two detection nodes is obtained.

[0065] Among them, the first building unit refers to the building unit contained in the current detection node, which can be 1 or 0; the second building unit refers to the building unit contained in another detection node, which can be 1 or 0; it can be understood that the detection node corresponding to 0 building units is not processed, that is, the detection node containing building units is subsequently processed.

[0066] Specifically, detection nodes that do not contain building units are not processed. For detection nodes that contain building units, the first building unit of the current detection node is obtained, and the second building unit in another building node is obtained, and then the Euclidean distance between the two detection nodes is obtained, for example, the distance between the center positions of the two detection nodes is obtained.

[0067] Next, the first building unit and the second building unit are used to determine the morphological similarity between the first building unit and the second building unit.

[0068] Among them, morphological similarity refers to the degree of similarity between the structures of two building units. The greater the morphological similarity, the more likely it is that overlap will occur.

[0069] Specifically, a first form of a first building unit is obtained, and a second form of a second building unit is obtained. The first form and the second form are compared to determine the form similarity between the first building unit and the second building unit.

[0070] It can be understood that the first form is the spatial structural morphology of the first building unit. When the target three-dimensional model is constructed using historical engineering construction data, the spatial structural morphology of each building unit has been clarified, and the spatial structural morphology of the first building unit has been obtained when the first building unit in the current detection node is obtained. The second form is the spatial structural morphology of the second building unit. When the second building unit in another detection node is obtained, the spatial structural morphology of the second building unit has been obtained. The spatial structural morphology of the building units contained in the target three-dimensional model is simply split into the forms of the building units in each detection node; the morphological similarity, that is, the first form and the second form are compared, and the degree of similarity obtained by the comparison is used as the morphological similarity.

[0071] Then, the overlap between two detection nodes is determined using Euclidean distance and morphological similarity.

[0072] Specifically, after obtaining the Euclidean distance and the morphological similarity, the overlap between two detection nodes is calculated.

[0073] The first spatial structure is set as the root node, the divided second spatial structure or the third spatial structure is a child node, and the previous node of the current child node can be the parent node.

[0074] The overlap is calculated as follows:

[0075]

[0076] Among them, Q i,j A represents the degree of overlap between the building units in child node i and child node j; i With A j Represents the building units in child node i and child node j respectively; L(i,j) is the Euclidean distance between child node i and child node j in three-dimensional space. i ∩A j It represents the morphological similarity between the building units in child nodes i and j. The greater the similarity, the more likely it is that overlapping features will occur. At the same time, combined with the distance between the two child nodes, since overlap only occurs in adjacent child nodes, the smaller L(i,j), the greater the overlap.

[0077] Next, the first fractal dimension and the second fractal dimension of the first building unit and the second building unit are obtained respectively, and the average fractal dimension is determined by using the first fractal dimension and the second fractal dimension.

[0078] Fractal dimension refers to a non-integer dimension used to describe shapes whose complexity lies between traditional dimensions (such as 1D, 2D, and 3D). In traditional Euclidean geometry, a straight line or curve is 1D, a plane or sphere is 2D, and a shape with length, width, and height is 3D.

[0079] Specifically, the first building unit and the second building unit in the current detection node and another detection node are obtained, and then the first fractal dimension of the first building unit is obtained, and the second fractal dimension of the second building unit is obtained. The average value is calculated using the first fractal dimension and the second fractal dimension, and the obtained average value is used as the average fractal dimension between the first building unit and the second building unit.

[0080] Since the larger the fractal dimension, the more complex and irregular the structure of the corresponding object, the larger the average fractal dimension of the two sub-node building monomers, the more irregular the corresponding shape, and the more likely they are overlapping elements, that is, overlap occurs.

[0081] Then, the fractal dimension and overlap are used to determine the collision type between two detection nodes.

[0082] Specifically, after obtaining the fractal dimension and the overlap, the probability of collision between two detection nodes is calculated, and then the corresponding collision type is determined.

[0083] For example, if two adjacent subnodes contain the same building unit type, resulting in a large overlap, we can analyze the regularity of the building unit's shape to further differentiate them. Generally, building units (such as pipes and walls) have relatively regular shapes, while overlapping units are relatively irregular.

[0084] Then, the probability of collision between building units in two detection nodes is calculated as follows:

[0085]

[0086] Where Z is the probability of a hard collision between building units within two detection nodes of this building structure, that is, the confidence level. norm is the norm function used to calculate the norm of a vector or matrix; Q i,j is the degree of overlap between the building elements in child node i and child node j. i With D j are the first fractal dimension and the second fractal dimension of the building monomer in child node i and child node j respectively. Since the larger the fractal dimension, the more complex and irregular the structure of the object, the average fractal dimension of the building monomers of the two child nodes is The larger the value, the more irregular the shape, and the more likely it is an overlapping element. i,j , then Z i,j The larger the value, the more likely a hard collision will occur.

[0087] You can also normalize the result to the range [0,1], here select Z i,j The building elements in the sub-node combination corresponding to ≥0.9 are overlapping hard collision building structures, and are marked in the model by setting different colors.

[0088] Furthermore, the following operations may be included.

[0089] In response to the Euclidean distance being less than a preset distance threshold, the fractal dimension and the overlap are used to determine that the collision type between the two detection nodes is a hard collision.

[0090] The preset distance threshold may be set according to actual conditions, such as a distance that does not affect installation or operation.

[0091] Specifically, if the Euclidean distance between two detection nodes is less than a preset distance threshold, it means that the distance between the building units within the two detection nodes is too close, which will affect the installation or operation. Then, through the aforementioned method, the fractal dimension and overlap are used to determine the collision type between the two detection nodes as a hard collision; if it affects the installation or operation and there is no actual contact, it can be determined as a soft operation; for example, if the distance between the pipe and the beam is too small, although there is no collision, it may affect future installation.

[0092] Since soft collisions cannot be analyzed based on the relative position of building structures and need to be considered in conjunction with their function, they are not considered here. Hard collisions are generally prioritized over soft collisions, prioritizing the identification of possible hard collisions within a subspace. Generally, if a hard collision occurs, physical overlap between different building units is necessary. However, when dividing subspaces, each subspace is guaranteed to have a separate building unit. Therefore, overlapping building units, due to their integrity, will exist in both subspaces simultaneously, creating a "non-separate" effect. Therefore, the similarity of building units in different subspaces can be compared to distinguish them.

[0093] In this embodiment, by analyzing the overlap between different detection nodes and determining the collision type between two detection nodes, the corresponding collision type can be obtained effectively and accurately, which is conducive to improving detection efficiency.

[0094] In some embodiments, in response to the collision type of the detection node being a hard collision, S30 determines the collision severity and position criticality of each detection node of the hard collision, which may include the following operations.

[0095] First, in response to detecting that the collision type of the node is a hard collision, the spatial intrusion degree of the current collision position is obtained, and the confidence level of the current collision position is obtained.

[0096] Among them, the spatial intrusion degree refers to the volume representation of the overlapping part occupying the volume of the two building units, that is, the larger the volume of the overlapping part occupies the volume of the two building units, the greater the spatial intrusion degree; the confidence level represents the morphological characteristics of the building unit at the current collision position, that is, the possibility of a hard collision between the building units within the two detection nodes.

[0097] Specifically, when the collision type of the detection node is determined to be a hard collision, the volume of the overlapping part and the volume of the two building units currently colliding are obtained, and the volume of the overlapping part and the volume of the two building units are compared to determine the spatial intrusion degree of the current collision position.

[0098] Furthermore, obtaining the spatial intrusion degree of the current collision position may include the following operations.

[0099] First, in response to the collision type being a hard collision, the first volume of the third building unit at the current collision position is obtained, the second volume of the fourth building unit at the current collision position is obtained, and the third volume overlapping between the third building unit and the fourth building unit is obtained.

[0100] Next, a first volume value is determined using the first volume and the third volume, and a second volume value is determined using the second volume and the third volume.

[0101] Then, the spatial intrusion degree of the current collision position is determined using the first volume value and the second volume value.

[0102] For example, set the first volume of the third building unit to V a , the second volume of the fourth building unit is V b The third overlapping volume between the third building unit and the fourth building unit is V c .

[0103] The calculation of spatial intrusion is as follows:

[0104]

[0105] Where S is the spatial intrusion degree of the current collision position. a With V b are the volumes of the two building units that produce hard collision in this subspace, that is, the first volume of the third building unit is V a , the second volume of the fourth building unit is V b , V c The volume of the overlapping part of the two building units, that is, the third volume of the overlap between the third building unit and the fourth building unit is V c Therefore, if the volume of the overlapping part occupies the larger volume of the two building units, that is, The larger it is, the greater the corresponding spatial intrusion.

[0106] Then, the collision severity of the current collision position of the detection node is determined using the spatial intrusion degree and confidence.

[0107] Specifically, after obtaining the spatial intrusion degree and the confidence level, the collision severity of the current collision position of the detection node can be directly calculated and determined.

[0108] The crash severity is calculated as follows:

[0109] E x =S x ×Z x

[0110] Among them, E x Represents the severity of the collision that produces a hard collision position x. x is the spatial intrusion degree of the hard collision position x, Z x is the confidence level of the collision position x, i.e., the possibility of a hard collision of a building unit. x The morphological characteristics of the building elements at the collision location are also characterized. Therefore, if the spatial intrusion of the building unit at the hard collision location x is greater and the shape is more irregular, the corresponding collision severity will be greater.

[0111] At this point, the severity of the impact has been determined for each collision location. The location of the collision is also crucial for risk assessment and repair. If the collision occurs in the core area of the building or in load-bearing components (such as columns and beams), the impact will be more severe. Alternatively, if the collision occurs in a hard-to-reach area (such as internal piping in a high-rise building or underground), the cost of repair will increase. Therefore, the next step is to analyze the criticality of different collision locations.

[0112] Next, the relative vertical height of the current collision position in the target three-dimensional model is obtained, and the degree of proximity between the current collision position and the core area of the target three-dimensional model is obtained.

[0113] The distance proximity refers to the distance between the current collision position and the core area of the target three-dimensional model. The smaller the value, the closer the collision position is to the nearest core area, and the greater the position criticality.

[0114] Specifically, the position information of the current collision position in the target three-dimensional model is obtained, as well as the spatial structure of the target three-dimensional model, and then the relative vertical height of the current collision position in the target three-dimensional model is determined, as well as the degree of proximity between the current collision position and the core area of the target three-dimensional model.

[0115] In some embodiments, determining the position criticality of the current collision position of the detection node using a preset model height value, a relative vertical height, and a distance proximity may include the following operations.

[0116] First, the distance proximity between the current collision location and the core area is determined using the preset model height value, relative vertical height, and proximity.

[0117] The distance proximity is calculated as follows:

[0118]

[0119] Among them, Y x K is the distance between the current collision position x and the core area. n Represents the core area closest to the current collision position x, H x is the relative vertical height of the current collision position x in the model, H m This is the median height of the target 3D model. Therefore, L(x,K n ) represents the proximity between the current collision position and the core area. The smaller the value, the closer the collision position is to the nearest core area, and the greater the position criticality. x -H m| represents the difference between the height of the current collision position and the median building height. Since the farther away from the median height, the more likely the current collision position is to be in the top pipe or foundation structure, the larger the value, the more critical the corresponding position.

[0120] Then, the position criticality of the current collision position of the detection node is determined using the preset model height value, the relative vertical height and the distance proximity.

[0121] The size of the free space around the current collision location also determines the difficulty of repair. The greater the repair difficulty, the more critical the collision location is. Here, the location criticality is calculated by combining the proximity of the current collision location to the core and the size of the surrounding free space.

[0122] Next, the fourth volume of the current detection node where the current collision position is located is obtained, as well as the fifth volume of the third building unit and the fourth building unit that collided with the current collision position, and the sixth volume of the previous level detection node where the current collision position is located is obtained.

[0123] Then, the position criticality of the current collision position of the detection node is determined using the fourth volume, the fifth volume, the sixth volume, and the proximity.

[0124] For example, set the fourth volume of the current detection node to V x The fifth volume of the third building unit and the fourth building unit that collided at the current collision position is V ab , the sixth volume of the previous level detection node where the current collision position is located is V r .

[0125] Then, the position criticality is calculated as follows:

[0126]

[0127] Among them, P x is the position criticality of the current collision position x. Vx is the volume of the subspace where the current collision position x is located, that is, the fourth volume of the current detection node is V x ; V ab is the actual volume of the two building units that produce a hard collision, that is, the fifth volume of the third building unit and the fourth building unit that collide at the current collision position is V ab ; V r is the spatial volume of the parent node where the current collision position x is located, that is, the sixth volume of the previous level detection node where the current collision position is located is V r .Y x The distance between the current collision position x and the core area.

[0128] therefore, Represents the size of the free space around the current collision position x. Since the model space is divided into multiple subspaces by the octree, the ratio of the volume occupied by the non-building monomer in the subspace to the space occupied by the corresponding parent node can be used to obtain the free space around the current collision position x. To reflect the free space. The smaller the free space, the The smaller it is, the more complex the structure around this location is, the more critical the location is, and combined with its proximity to the core Y x Then the position criticality P x The larger the value is, the more critical the current collision position x is, and vice versa.

[0129] In this embodiment, the corresponding collision severity and location criticality are obtained for any current collision location. When repairing, the more severe the collision and the more critical the location, the greater the risk. Therefore, the higher the risk, the faster the repair or treatment will be performed, increasing its priority, thereby improving the overall construction efficiency and quality of the project.

[0130] In some embodiments, the collision severity and location criticality are used to determine the processing priority of each detection node, and then the construction project of the target three-dimensional model is repaired according to the processing priority.

[0131] Specifically, the processing priority is calculated as follows:

[0132] γ x =norm(E x ×P x )

[0133] Among them, γ x The processing priority of the current collision position x. E x is the collision severity of the current collision position x, P x is the position criticality of the current collision location x. Therefore, combining these two factors, a more severe collision and a more critical location will result in a higher priority for repair. Finally, the result is normalized to the range [0, 1].

[0134] It is understandable that if there are multiple collision locations with the same processing priority, their spatial intrusion degrees S will continue to be compared and sorted according to the size of the spatial intrusion degree. The larger the spatial intrusion degree, the higher the processing priority, ensuring that the most critical collision problem is solved first.

[0135] In this embodiment, hard collisions that may occur in the BIM 3D model of a construction project are precisely analyzed and repaired based on priority, improving collision detection efficiency. Soft collisions, on the other hand, are prioritized for handling compared to hard collisions, as they primarily affect the building's functionality. Designers can analyze the actual functional conflicts between building elements and determine the corresponding repair priorities. By rationally arranging workflows and collaborative mechanisms, the design and construction teams can efficiently resolve these collision issues, ensuring the smooth construction and subsequent operation of the building.

[0136] The present invention also provides an engineering building visualization model construction system based on BIM technology.

[0137] See also Figure 2 , Figure 2 It is a structural diagram of the engineering building visualization model construction system based on BIM technology provided by the present invention. The engineering building visualization model construction system based on BIM technology can execute the steps in the engineering building visualization model construction method based on BIM technology. The engineering building visualization model construction system 300 based on BIM technology includes: a construction module 310, which constructs a target three-dimensional model using historical engineering building data; a first determination module 320, which divides the target three-dimensional model into multiple detection nodes through a preset structure, and determines the collision type of each detection node; a second determination module 330, which determines the collision severity and position criticality of each detection node of the hard collision in response to the collision type of the detection node being a hard collision; a third determination module 340, which uses the collision severity and position criticality to determine the processing priority of each detection node, and then repairs the construction project of the target three-dimensional model according to the processing priority.

[0138] It should be noted that the order in which the embodiments of the present invention are described above is for illustrative purposes only and does not necessarily represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or sequential order shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0139] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments.

Claims

1. A method for constructing an engineering building visualization model based on BIM technology, characterized in that: The method for constructing an engineering building visualization model based on BIM technology includes: Use historical engineering and construction data to build a target 3D model; Dividing the target three-dimensional model into a plurality of detection nodes through a preset structure, and determining a collision type of each detection node; In response to the collision type of the detection node being a hard collision, determining a collision severity and a position criticality of each of the detection nodes involved in the hard collision; The processing priority of each detection node is determined by using the collision severity and the position criticality, and then the construction project of the target three-dimensional model is repaired according to the processing priority.

2. The method for constructing an engineering building visualization model based on BIM technology according to claim 1, characterized in that: The method of constructing a target three-dimensional model using historical engineering and construction data includes: Acquiring historical engineering building data corresponding to the construction project, wherein the historical engineering building data at least includes geometric shape information, material information, spatial structure information, and functional division information of the construction project; The target three-dimensional model corresponding to the construction project is constructed by using the geometric shape information, the material information, the spatial structure information and the functional division information through a preset drawing method.

3. The method for constructing an engineering building visualization model based on BIM technology according to claim 1, characterized in that: The step of dividing the target three-dimensional model into a plurality of detection nodes by a preset structure and determining the collision type of each detection node includes: Acquiring a first spatial structure of a target three-dimensional model; Dividing the first spatial structure into a plurality of second spatial structures using a preset structure, wherein the second spatial structures are identical to each other and each second spatial structure represents a detection node; The overlap degree between any two detection nodes is obtained, and the collision type between the two detection nodes is determined using the overlap degree.

4. The method for constructing an engineering building visualization model based on BIM technology according to claim 3 is characterized in that: Also includes: In response to the second spatial structure including multiple building units, each of the second spatial structures is divided into multiple third spatial structures using a preset structure, so that the number of building units contained in each of the third spatial structures is less than a preset number threshold, wherein the building units are independent building structures.

5. The method for constructing an engineering building visualization model based on BIM technology according to claim 3, characterized in that: The obtaining of the overlap between any two detection nodes and determining the collision type between the two detection nodes using the overlap includes: Obtaining a first building unit in any one of the detection nodes, obtaining a second building unit in another of the detection nodes, and obtaining a Euclidean distance between the two detection nodes; Determining a morphological similarity between the first building unit and the second building unit using the first building unit and the second building unit; Determining the degree of overlap between two detection nodes using the Euclidean distance and the morphological similarity; Obtaining a first fractal dimension and a second fractal dimension of the first building unit and the second building unit respectively, and determining an average fractal dimension using the first fractal dimension and the second fractal dimension; The collision type between two detection nodes is determined by using the average fractal dimension and the overlap degree.

6. The method for constructing an engineering building visualization model based on BIM technology according to claim 5, characterized in that: Also includes: In response to the Euclidean distance being less than a preset distance threshold, the collision type between the two detection nodes is determined to be a hard collision by using the average fractal dimension and the overlap.

7. The method for constructing an engineering building visualization model based on BIM technology according to claim 1, characterized in that: In response to the collision type of the detection node being a hard collision, determining the collision severity and position criticality of each detection node of the hard collision includes: In response to the collision type of the detection node being a hard collision, obtaining a spatial intrusion degree of a current collision position and obtaining a confidence level of the current collision position; Determining a collision severity of a current collision position of the detection node using the spatial intrusion degree and the confidence level; Obtaining a relative vertical height of the current collision position in the target three-dimensional model, and obtaining a degree of proximity between the current collision position and a core area of the target three-dimensional model; The position criticality of the current collision position of the detection node is determined using the preset model height value, the relative vertical height and the distance proximity.

8. The method for constructing an engineering building visualization model based on BIM technology according to claim 7, characterized in that: The obtaining of the spatial intrusion degree of the current collision position includes: In response to the collision type being a hard collision, obtaining a first volume of a third building unit at the current collision position, obtaining a second volume of a fourth building unit at the current collision position, and obtaining a third volume of overlap between the third building unit and the fourth building unit; determining a first volume value using the first volume and the third volume, and determining a second volume value using the second volume and the third volume; The spatial intrusion degree of the current collision position is determined using the first volume value and the second volume value.

9. The method for constructing an engineering building visualization model based on BIM technology according to claim 7, characterized in that: The determining the position criticality of the current collision position of the detection node by using the preset model height value, the relative vertical height, and the distance proximity includes: Determining the proximity between the current collision position and the core area using a preset model height value, the relative vertical height, and the proximity; Obtaining the fourth volume of the current detection node where the current collision position is located, obtaining the fifth volumes of the third and fourth building units that collide with the current collision position, and obtaining the sixth volume of the previous-level detection node where the current collision position is located; The position criticality of the current collision position of the detection node is determined by using the fourth volume, the fifth volume, the sixth volume, and the distance proximity.

10. A BIM-based engineering building visualization model construction system, characterized by: include: Construction module, which uses historical engineering and construction data to build a target 3D model; a first determination module, which divides the target three-dimensional model into a plurality of detection nodes through a preset structure and determines a collision type of each detection node; a second determining module, in response to the collision type of the detection node being a hard collision, determining a collision severity and a position criticality of each of the detection nodes; The third determination module determines the processing priority of each detection node using the collision severity and the position criticality, and then performs repair processing on the construction project based on the processing priority and the target three-dimensional model.

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