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

Abstract

The application relates to the technical field of data processing, in particular to a building engineering visual model construction method and system based on BIM technology, which comprises the following steps: constructing a target three-dimensional model by using historical building engineering data; dividing the target three-dimensional model into multiple detection nodes by a preset structure, and determining the collision type of each detection node; determining the collision severity and position key degree of each detection node by using the collision type; determining the processing priority of each detection node by using the collision severity and the position key degree, and then performing repair processing on the building engineering according to the processing priority and the target three-dimensional model. That is, the application realizes rapid and accurate analysis of hard collision, and performs repair processing according to the processing priority, thereby improving the collision detection efficiency.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data processing, in particular to a construction visualization model construction method and system based on BIM technology. BACKGROUND

[0002] The BIM-based three-dimensional model construction method and system cover the whole process from design to construction and from construction to operation, greatly improving the precision, efficiency and collaboration level of construction projects. Collision detection is a core function in BIM, which refers to automatically identifying and reporting physical conflicts or overlaps between elements in the model during the design, construction and operation of buildings. Collision detection not only reduces problems in the construction process, but also helps the design team optimize the model and improve design quality and construction efficiency.

[0003] Currently, the modeling process of engineering construction based on BIM inevitably produces structural "collision" problems, and the traditional collision detection method has precision problems when detecting large-scale building models, resulting in false positives or false negatives in the collision detection results, affecting the efficiency and quality of the construction of three-dimensional models, affecting the overall quality or design integrity of subsequent projects, and posing a safety hazard. SUMMARY

[0004] In order to solve the technical problem that the existing general collision detection method has precision problems when detecting large-scale building models, resulting in false positives or false negatives in the collision detection results, the purpose of the present application is to provide a construction visualization model construction method and system based on BIM technology, which divides the BIM three-dimensional model by octree structure and determines the possible collision type of each node. Based on the collision severity and location criticality of the corresponding structure in hard collision, the risk processing coefficient of the corresponding structure is determined to determine the processing priority of different collision structures, which is beneficial to improve work efficiency and improve the quality of constructing three-dimensional models of buildings.

[0005] The technical solution adopted is as follows: a construction visualization model construction method based on BIM technology is provided, comprising: constructing a target three-dimensional model using historical engineering construction data; 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; using the collision type, determining the collision severity and location criticality of each detection node; using the collision severity and location criticality, determining the processing priority of each detection node, and then repairing the construction according to the processing priority and the target three-dimensional model.

[0006] In an embodiment of the present application, the constructing the target three-dimensional model by using the historical engineering construction data comprises: obtaining historical engineering construction data corresponding to the construction project, wherein the historical engineering construction data at least comprises geometric shape information, material information, spatial structure information and functional division information of the construction project; and constructing the target three-dimensional model corresponding to the construction project by using the geometric shape information, the material information, the spatial structure information and the functional division information through a preset drawing mode.

[0007] In an embodiment of the present application, the dividing the target three-dimensional model into a plurality of detection nodes by using the preset structure and determining the collision type of each detection node comprises: obtaining a first spatial structure of the target three-dimensional model; dividing the first spatial structure into a plurality of second spatial structures by using the preset structure, wherein the second spatial structures are identical and each second spatial structure represents a detection node; obtaining an overlap degree between any two detection nodes and determining the collision type between the two detection nodes by using the overlap degree.

[0008] In an embodiment of the present application, further comprising: in response to the second spatial structure comprising a plurality of building monomers, dividing each second spatial structure into a plurality of third spatial structures by using the preset structure, so that the number of building monomers contained in each third spatial structure is less than a preset number threshold, wherein the building monomer is an independent building structure.

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

[0010] In an embodiment of the present application, further comprising: in response to the Euclidean distance being less than a preset distance threshold, determining the collision type between the two detection nodes as hard collision by using the average fractal dimension and the overlap degree.

[0011] In an embodiment of the present application, the determining the collision severity and the position criticality of each detection node according to the collision type comprises: obtaining a spatial invasion degree of the current collision position, and obtaining a confidence degree of the current collision position; determining the collision severity of the current collision position of the detection node according to the spatial invasion degree and the confidence degree; obtaining a relative vertical height of the current collision position in the target three-dimensional model, and obtaining a distance proximity between the current collision position and a core region of the target three-dimensional model; and determining the position criticality of the current collision position of the detection node according to a preset model height value, the relative vertical height and the distance proximity.

[0012] In an embodiment of the present application, the obtaining the spatial invasion degree of the current collision position comprises: in response to the collision type being a hard collision, obtaining a first volume of a third building unit of the current collision position, obtaining a second volume of a first building unit of the current collision position, and obtaining a third volume of overlap between the third building unit and the first building unit; determining a first volume value according to the first volume and the third volume, and determining a second volume value according to the second volume and the third volume; and determining the spatial invasion degree of the current collision position according to the first volume value and the second volume value.

[0013] In an embodiment of the present application, the determining the position criticality of the current collision position of the detection node according to the preset model height value, the relative vertical height and the distance proximity comprises: determining the distance proximity between the current collision position and the core region according to the preset model height value, the relative vertical height and the distance proximity; obtaining a fourth volume of a current detection node where the current collision position is located, obtaining a fifth volume of a third building unit and a first building unit where the current collision position collides, and obtaining a sixth volume of a previous detection node where the current collision position is located; and determining the position criticality of the current collision position of the detection node according to the fourth volume, the fifth volume, the sixth volume and the distance proximity.

[0014] To solve the above technical problems, another technical solution adopted by the present application is: a building engineering visual model construction system based on BIM technology, comprising: a construction module, which constructs a target three-dimensional model by using historical building engineering data; a first determination module, which divides the target three-dimensional model into a plurality of detection nodes by a preset structure and determines the collision type of each detection node; a second determination module, which determines the collision severity and position criticality of each detection node by using the collision type; and a third determination module, which determines the processing priority of each detection node by using the collision severity and the position criticality, and then performs repair processing on the building engineering according to the processing priority and the target three-dimensional model.

[0015] The present application has the following advantages: a building engineering visual model construction method based on BIM technology is provided, which comprises: constructing a target three-dimensional model by using historical building engineering data; 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; determining the collision severity and position criticality of each detection node by using the collision type; determining the processing priority of each detection node by using the collision severity and the position criticality, and then performing repair processing on the building engineering according to the processing priority and the target three-dimensional model; that is, the present application divides the target three-dimensional model of the building engineering into a plurality of detection nodes by a preset structure, determines the collision type of each detection node, then obtains the collision severity and position criticality of the building structure in the detection node, and finally determines the processing priority of each collision position, which is beneficial to improving work efficiency and the quality of constructing the three-dimensional model of the building. BRIEF DESCRIPTION OF DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, and the advantages thereof, a brief introduction will be given to the drawings needed in the embodiments or prior art description. Obviously, the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained without creative labor based on these drawings.

[0017] Figure 1 is a flowchart of the building engineering visual model construction method based on BIM technology provided by the present application;

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

[0019] In order to further clarify the technical means and effects taken by the present application to achieve the predetermined inventive objectives, the following describes in detail the specific implementation, structure, features and effects of the BIM technology-based engineering building visual model construction method and system according to the present application, in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures or characteristics in one or more embodiments can be combined in any suitable form.

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

[0021] The specific scheme of the BIM technology-based engineering building visual model construction method and system provided by the present application is described in detail below in combination with the accompanying drawings.

[0022] Please refer to Figure 1 , which shows the flowchart of the BIM technology-based engineering building visual model construction method provided by the present application.

[0023] As Figure 1 shown, the BIM technology-based engineering building visual model construction method includes the following steps:

[0024] S10, constructing a target three-dimensional model by using historical engineering building data.

[0025] Among them, the engineering building data refers to the geometric shape information, material information, spatial structure information and functional division information of the building in the construction project, wherein 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 the engineering building data in electronic data form by drawing.

[0026] Specifically, the historical engineering building data that needs to be constructed into a three-dimensional model is obtained, and the geometric shape information, material information, spatial structure information and functional division information of the building in the historical building project are used to depict in electronic data form by constructing a model, so as to determine the target three-dimensional model corresponding to the historical engineering building data.

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

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

[0029] The preset structure refers to a structure for dividing the target three-dimensional model; the detection node refers to a representation of a subspace structure obtained after the target three-dimensional model is divided according to the preset structure, i.e. each subspace structure obtained after division is used to represent a detection node; the collision type refers to a type of collision between building monomers in the detection node and building monomers, such as hard collision and soft collision, the hard collision refers to a collision with overlap or actual interference, the soft collision refers to a collision with too close distance, affecting installation or operation, but without actual contact, and the building monomer refers to the smallest building structure that exists independently, which can also be referred to as 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 a plurality of subspace structures of the same size by the preset structure, and each subspace structure represents a corresponding detection node; then the building monomers contained in each detection node are obtained, and it is determined whether the building monomers in the detection node collide, i.e. the collision type between the building monomers and the building monomers is determined.

[0031] In some embodiments, the preset structure can be an octree structure, i.e. the target three-dimensional model is divided by the octree structure, and each subspace obtained by division is a detection node.

[0032] S30, in response to the collision type of the detection node being hard collision, determining the collision severity and the position criticality of each detection node of the hard collision.

[0033] The collision severity refers to the overlap degree or interference degree between the building monomers in the detection node and the building monomers, which is positively correlated; i.e. the higher the overlap degree, the more serious the collision severity; or the higher the interference degree, the more serious the collision severity; the position criticality refers to the distance between the collision position where the collision occurs and the core of the building three-dimensional model, 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 it is determined that the collision type of the detection node is hard collision, in response to the collision type of the detection node being hard collision, the overlap degree or interference degree between the building monomers in the detection node and the building monomers is obtained, and the overlap degree or interference degree is used to determine the collision severity between the building monomers and the building monomers, i.e. the collision severity of each detection node is determined; and the collision position where the collision occurs and the core position of the building three-dimensional model are obtained, and then the distance between the collision position and the core position is used to determine the position criticality of the collision position where the collision occurs, i.e. the position criticality of the detection node where the hard collision occurs.

[0035] S40, determining a processing priority of each detection node by using the collision severity and the position criticality, and then repairing the construction project of the target three-dimensional model according to the processing priority.

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

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

[0038] In this embodiment, by dividing the target three-dimensional model constructed by the historical engineering construction data into multiple detection nodes, the collision type of each detection node is determined, and the collision severity and the position criticality of the detection node with hard collision are obtained, and then the processing priority of each detection node is determined, so that the fast and accurate analysis of hard collision is realized, and the collision detection efficiency is improved by repairing according to the processing priority.

[0039] In some embodiments, S10 of constructing the target three-dimensional model by using the historical engineering construction data can include the following operations:

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

[0041] The construction project refers to a building project in design, in construction or in operation.

[0042] Specifically, for the building project in design, in construction or in operation, all existing building monomers, geometric shape information, material information, spatial structure information and function division information are obtained.

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

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

[0045] Specifically, by using a BIM (Building Information Modeling) model, geometric shape information, material information, spatial structure information and function division information of all building units in the construction project are drawn to obtain a target three-dimensional model corresponding to the construction project.

[0046] In this embodiment, the target three-dimensional model is constructed by using historical engineering building data, so that the current structure of the construction project can be accurately depicted and displayed in the form of electronic data, so as to facilitate collision identification and analysis, save time required for on-site investigation, and improve analysis efficiency and collision detection efficiency.

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

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

[0049] The first spatial structure refers to a spatial structure displayed after the construction project is constructed into the target three-dimensional model.

[0050] Specifically, a large cube or sphere is determined by using the target three-dimensional model, and the cube is described in this embodiment, 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] Then, the first spatial structure is divided into a plurality of second spatial structures by using a preset structure, wherein the second spatial structures are the same, and each second spatial structure represents a detection node.

[0052] The second spatial structure refers to a sub-spatial structure after the first spatial structure is divided.

[0053] Specifically, a suitable preset structure is selected, and then the first spatial structure corresponding to the target three-dimensional model is divided into a plurality of identical second spatial structures by using the preset structure; for example, the preset structure is described by taking an octree structure as an example, and then the first spatial structure corresponding to the target three-dimensional model is divided into eight identical second spatial structures by using the octree structure.

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

[0055] Among them, overlap refers to the degree of overlap between individual buildings within different detection nodes; collision type refers to the type of collision between individual buildings in the detection node, such as hard collision and soft collision. Hard collision refers to a collision that involves overlap or actual interference, i.e., a collision has occurred; 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 individual buildings within each detection node are obtained. Then, the degree of overlap between the corresponding individual buildings between different detection nodes is determined, and the collision type between different detection nodes is determined based on the degree of overlap.

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

[0058] In response to the fact that the second spatial structure includes 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 contained in each third spatial structure is less than a preset number threshold, wherein the building unit is an independent building structure.

[0059] In order to more accurately represent individual buildings, the second spatial structure can be further divided.

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

[0062] In this embodiment, the divided second space structure is used as a detection node, which can clearly identify whether there is overlap between the individual buildings inside the different second space structures. Based on the degree of overlap, the collision type can be effectively distinguished, providing a basis for subsequent operations.

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

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

[0065] 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 the building unit of 0 is not processed, that is, the detection node containing the building unit is processed subsequently.

[0066] Specifically, the detection node without containing the building unit is not processed, and for the detection node containing the building unit, the first building unit of the current detection node is acquired, and the second building unit in another building node is acquired, and then the Euclidean distance between the two detection nodes is acquired, for example, the distance between the center positions of the two detection nodes is acquired.

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

[0068] The shape similarity refers to the similarity between the structures of the two building units, and the greater the shape similarity, the more likely the overlap occurs.

[0069] Specifically, the first shape of the first building unit is acquired, and the second shape of the second building unit is acquired, and the first shape and the second shape are compared to determine the shape similarity between the first building unit and the second building unit.

[0070] It can be understood that the first shape is the spatial structure morphology of the first building unit, and the spatial structure morphology of each building unit has been determined when the target three-dimensional model is constructed using historical engineering building data, and the spatial structure morphology of the first building unit has been acquired when the first building unit in the current detection node is acquired. The second shape is the spatial structure morphology of the second building unit, and the spatial structure morphology of the second building unit has been acquired when the second building unit in another detection node is acquired, only the spatial structure morphology of the building unit contained in the target three-dimensional model is split into the shape of the building unit in each detection node; the shape similarity is that the first shape and the second shape are compared, and the same degree obtained by comparison is taken as the shape similarity.

[0071] Then, the Euclidean distance and the shape similarity are used to determine the overlap degree between the two detection nodes.

[0072] Specifically, after the Euclidean distance and the shape similarity are acquired, the overlap degree between the two detection nodes is calculated.

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

[0074] The overlap degree is calculated as follows:

[0075]

[0076] wherein Q i,j represents the overlap degree of the building units in the child node i and the child node j; A i and A j respectively represent the building units in the child node i and the child node j; L(i, j) is the Euclidean distance of the child node i and the child node j in the three-dimensional space. Therefore, A i ∩A j represents the shape similarity of the building units in the child node i and the child node j. The greater the similarity, the more likely the overlap feature is generated. In combination with the distance of the two child nodes, since the overlap only occurs in adjacent child nodes, the smaller the L(i, j) is, the greater the overlap degree is.

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

[0078] The fractal dimension refers to a non-integer dimension, which is used to describe the shape with complexity between the traditional dimensions (such as 1D, 2D, 3D). In traditional Euclidean geometry, a straight line or a curve is 1D, a plane or a 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 by using the first fractal dimension and the second fractal dimension, and the obtained average value is taken as the average fractal dimension between the first building unit and the second building unit.

[0080] Since a greater fractal dimension corresponds to a more complex and irregular structure of an object, the greater the average fractal dimension of the two child node building units is, the more irregular the shape is, and the more likely it is to be an overlapping element, that is, overlap occurs.

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

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

[0083] For example, the types of the building elements in the two adjacent sub-nodes are the same, resulting in a still large overlap degree, and thus the regularity of the morphology of the building elements can be analyzed for further differentiation. General building elements (such as pipes and walls) present a relatively regular morphology, while the overlapping elements are relatively more irregular.

[0084] Therefore, the possibility of collision between the building elements in the two detection nodes is calculated as follows:

[0085]

[0086] wherein Z is the possibility of hard collision between the building elements in the two detection nodes of the building structure, i.e., the confidence. norm is a norm function for calculating the norm of a vector or matrix; Q i,j is the overlap degree of the building elements in the sub-node i and the sub-node j. D i and D j are the first fractal dimension and the second fractal dimension of the building elements in the sub-node i and the sub-node j, respectively. Since a larger fractal dimension corresponds to a more complex and irregular structure of an object, a larger average fractal dimension of the building elements in the two sub-nodes corresponds to a more irregular morphology and a higher possibility of being an overlapping element. In combination with the overlap degree Q i,j , Z i,j is larger, which corresponds to a higher possibility of hard collision.

[0087] The result can also be normalized to the range of [0, 1], and in this case, Z i,j ≥ 0.9 corresponds to the building elements in the sub-node combination being an overlapping hard collision building structure, and the building elements are marked in the model by setting different colors.

[0088] Further, the following operations can also be included.

[0089] In response to the Euclidean distance being less than the preset distance threshold, the type of collision between the two detection nodes is determined to be hard collision by using the fractal dimension and the overlap degree.

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

[0091] Specifically, when the Euclidean distance between the two detection nodes is less than the preset distance threshold, it indicates that the distance between the building elements in the two detection nodes is too close, which affects installation or operation, and thus the type of collision between the two detection nodes is determined to be hard collision by using the fractal dimension and the overlap degree in the foregoing manner; and the soft operation can be determined when the installation or operation is affected and there is no actual contact. For example, the distance between the pipe and the beam is too small, although there is no collision, but it may affect future installation.

[0092] Since soft collision cannot be analyzed according to the relative position of the building structure, the function thereof is not considered herein, and the processing priority of hard collision is generally higher than that of soft collision, the hard collision possibly generated in the sub-space is determined first. Generally, if hard collision is generated, there is physical overlap of different building monomers, and when the sub-space is divided, it is ensured that each sub-space has a separate building monomer, so that the overlapping building monomers exist in two sub-spaces due to their integrity, thus generating a "non-separate" effect, and therefore the similarity of the building monomers in different sub-spaces can be compared to distinguish them.

[0093] In the embodiment, the collision type between two detection nodes is determined by analyzing the overlap degree between different detection nodes, so that the corresponding collision type can be effectively and accurately obtained, which is beneficial to improving the detection efficiency.

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

[0095] First, in response to the collision type of the detection node being hard collision, the spatial invasion degree of the current collision position is obtained, and the confidence degree of the current collision position is obtained.

[0096] The spatial invasion degree refers to the volume of the overlapping part occupying the volume of the two building monomers, that is, the greater the volume of the overlapping part occupying the volume of the two building monomers, the greater the spatial invasion degree; the confidence degree represents the morphological characteristics of the building monomer at the current collision position, that is, the possibility of hard collision between the building monomers in the two detection nodes.

[0097] Specifically, when the collision type of the detection node is determined as hard collision, the volume of the overlapping part is obtained, and the volume of the two building monomers at the current collision is obtained, and the volume of the overlapping part and the volume of the two building monomers are compared to determine the spatial invasion degree of the current collision position.

[0098] Further, obtaining the spatial invasion degree of the current collision position can include the following operations.

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

[0100] Then, the first volume value is determined by using the first volume and the third volume, and the second volume value is determined by using the second volume and the third volume.

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

[0102] For example, the first volume of the third building element is set as V a , the second volume of the first building element is set as V b , and the third volume of the overlap between the third building element and the first building element is set as V c .

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

[0104]

[0105] wherein S represents the spatial intrusion degree of the current collision position. V a and V b are the volumes of the two building elements in the subspace that cause the hard collision, i.e., the first volume of the third building element is V a , the second volume of the first building element is V b , and V c is the volume of the overlap between the two building elements, i.e., the third volume of the overlap between the third building element and the first building element is V c . Therefore, the greater the volume of the overlap occupies the volumes of the two building elements, i.e. , the greater the corresponding spatial intrusion degree.

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

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

[0108] The calculation of the collision severity is as follows:

[0109] E x =S x ×Z x

[0110] wherein E x represents the collision severity of the hard collision position x. S x is the spatial intrusion degree of the hard collision position x, and Z x is the confidence of the collision position x, i.e., the possibility of the hard collision of the building element. Since Z x also represents the morphological characteristics of the collision position building element, if the spatial intrusion degree of the building element of the hard collision position x is greater and the morphology is more irregular, the corresponding collision severity is greater.

[0111] So far, the collision degree of different collision positions has been determined, and the position of the collision is also very important for risk assessment and repair processing. If the collision occurs in the core area of the building and the load-bearing member (such as column, beam, etc.), the influence is more serious, or the collision occurs in a difficult-to-access place (such as the internal pipeline of a high-rise building or underground), which increases the repair processing cost. Therefore, the position criticality of different collisions needs to be analyzed next.

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

[0113] Wherein, the distance proximity refers to the distance between the current collision position and the core area of the target three-dimensional model, and the smaller the value corresponds to the closer the collision position 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, and the spatial structure of the target three-dimensional model is obtained, and then the relative vertical height of the current collision position in the target three-dimensional model is determined, and the distance proximity between the current collision position and the core area of the target three-dimensional model is determined.

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

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

[0117] The distance proximity is calculated as follows:

[0118]

[0119] Wherein, Y x is the distance proximity between the current collision position x and the core area. K n represents the nearest core area to the current collision position x, H x is the relative vertical height of the current collision position x in the model, H m is the height median of the target three-dimensional model. Therefore, L(x, K n ) represents the proximity of the current collision position to the core area, and the smaller the value corresponds to the closer the collision position to the nearest core area, and the greater the position criticality. At the same time, |H x -H m| represents the difference between the height of the current collision position and the median building height, and the farther away from the median height, the more likely the current collision position is at the top of the pipeline or the foundation structure position, so the greater the value, the more critical the position.

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

[0121] The size of the empty space around the current collision position also determines the difficulty of repair, and the greater the repair difficulty, the more critical the corresponding collision position, and the proximity of the current collision position to the core and the size of the empty space around it are combined to calculate the position criticality.

[0122] Next, the fourth volume of the current detection node where the current collision position is located is obtained, and the fifth volume of the third building and the first building where the current collision position collides is obtained, and the sixth volume of the upper 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 by using the fourth volume, the fifth volume, the sixth volume and the proximity.

[0124] For example, the fourth volume of the current detection node is set to V x , the fifth volume of the third building and the first building where the current collision position collides is V ab , and the sixth volume of the upper detection node where the current collision position is located is V r .

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

[0126]

[0127] Where 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, i.e. the fourth volume of the current detection node is V x ; V ab is the actual volume of the two building units that produce hard collision, i.e. the fifth volume of the third building and the first building where the current collision position collides is V ab ; V r is the space volume of the parent node where the current collision position x is located, i.e. the sixth volume of the upper detection node where the current collision position is located is V r . Y x is the distance proximity of the current collision position x to the core area.

[0128] Therefore, This represents the size of the free space around the current collision position x. Since the model space is divided into multiple subspaces using an octree, it can be represented by the ratio of the volume occupied by non-building units in the subspace to the volume occupied by their corresponding parent nodes. This reflects the amount of empty space. The smaller the empty space, the better. The smaller the value, the more complex the surrounding structure and the more critical the location, combined with its proximity to the core, Y. x So, what is the positional importance P? x The larger the value, the more critical the current collision position x is, and vice versa.

[0129] In this embodiment, the severity and criticality of the collision are determined for any given current collision location. Therefore, during repair work, locations with more severe and critical collisions pose a greater risk. These higher-risk locations are repaired or addressed as quickly as possible, increasing their priority and thus improving the overall construction efficiency and quality of the project.

[0130] In some embodiments, the processing priority of each detection node is determined by the severity of the collision and the criticality of its location, and then the architectural engineering of the target 3D 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] Where, γ x The processing priority for the current collision position x. E x P represents the collision severity at the current collision location x. x Let x be the location criticality of the current collision position. Therefore, considering both factors, the more severe the collision and the more critical the location, the higher the priority of the repair process. Finally, the result is normalized to the range [0,1].

[0134] Understandably, if multiple collision locations have the same processing priority, their spatial intrusion degree S is compared, and they are 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 problems are resolved first.

[0135] In this embodiment, the hard collision that may occur in the BIM three-dimensional model of the construction project is accurately analyzed and repaired according to the priority, and the collision detection efficiency is improved. At the same time, for the soft collision, since its main influence is the function of the building, the priority of the processing is lower than that of the hard collision, and the relevant design personnel can analyze the function conflict effect between the actual building elements to determine the corresponding repair priority. Through reasonable arrangement of the work flow and the cooperation mechanism, the design and construction team can efficiently solve these collision problems, and ensure the smooth construction and later operation of the building.

[0136] The application further provides a BIM technology-based engineering building visual model construction system.

[0137] Please refer to Figure 2 , Figure 2 is a structural schematic diagram of the BIM technology-based engineering building visual model construction system provided by the application. The BIM technology-based engineering building visual model construction system can execute the steps in the above-mentioned BIM technology-based engineering building visual model construction method. The BIM technology-based engineering building visual model construction system 300 comprises: a construction module 310, which constructs a target three-dimensional model by using historical engineering building data; a first determination module 320, which divides the target three-dimensional model into a plurality of detection nodes by a preset structure, and determines the collision type of each detection node; a second determination module 330, which, in response to the collision type of the detection node being hard collision, determines the collision severity and the position criticality of each detection node of the hard collision; a third determination module 340, which determines the processing priority of each detection node by using the collision severity and the position criticality, and then performs repair processing on the construction project of the target three-dimensional model according to the processing priority.

[0138] It should be noted that the above-mentioned sequence of the embodiments of the application is only for description, and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multi-task processing and parallel processing are also possible or can be advantageous.

[0139] Each embodiment in the specification is described in a progressive manner, and the same or similar parts between each embodiment can be referred to each other, and each embodiment mainly describes the difference from other embodiments.

Claims

1. A method for constructing a visual model of an engineering building based on BIM technology, characterized in that, The BIM technology-based engineering building visualization model construction method comprises: Utilize historical engineering building data to construct a target three-dimensional model; Divide the target three-dimensional model into a plurality of detection nodes through a preset structure, and determine the collision type of each detection node; In response to the collision type of the detection node being hard collision, determine the collision severity and position criticality of each detection node of the hard collision; Utilize the collision severity and the position criticality to determine the processing priority of each detection node, and then perform repair processing on the building engineering of the target three-dimensional model according to the processing priority; In response to the collision type of the detection node being hard collision, determine the collision severity and position criticality of each detection node of the hard collision, comprising: In response to the collision type of the detection node being hard collision, obtain the spatial invasion degree of the current collision position, and obtain the confidence degree of the current collision position; Utilize the spatial invasion degree and the confidence degree to determine the collision severity of the current collision position of the detection node; Obtain the relative vertical height of the current collision position in the target three-dimensional model, and obtain the distance proximity between the current collision position and the core area of the target three-dimensional model; Utilize the 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; The spatial invasion degree of the current collision position is obtained, comprising: In response to the collision type being hard collision, obtain the first volume of the third building monomer at the current collision position, and obtain the second volume of the first building monomer at the current collision position, and obtain the third volume overlapping between the third building monomer and the first building monomer; Utilize the first volume and the third volume to determine the first volume value, and utilize the second volume and the third volume to determine the second volume value; Utilize the first volume value and the second volume value to determine the spatial invasion degree of the current collision position.

2. The BIM technology-based engineering construction visual model construction method according to claim 1, characterized in that, The target three-dimensional model is constructed by utilizing historical engineering building data, comprising: Obtain the historical engineering building data corresponding to the building engineering, wherein the historical engineering building data at least includes the geometric shape information, material information, spatial structure information, and function division information of the building engineering; Utilize the geometric shape information, the material information, the spatial structure information, and the function division information to construct the target three-dimensional model corresponding to the building engineering through a preset drawing method. 3.The BIM-based engineering building visualization model construction method of claim 1, wherein, The target three-dimensional model is divided into a plurality of detection nodes through a preset structure, and the collision type of each detection node is determined, comprising: Obtain the first spatial structure of the target three-dimensional model; Divide the first spatial structure into a plurality of second spatial structures through a preset structure, wherein the second spatial structures are the same, and each second spatial structure represents a detection node; Obtain the overlapping degree between any two detection nodes, and utilize the overlapping degree to determine the collision type between the two detection nodes. 4.The BIM-based engineering building visualization model construction method of claim 3, wherein, Further comprising: In response to the second spatial structure including a plurality of building units, each of the second spatial structure is divided into a plurality of third spatial structures by a preset structure, so that the number of building units contained in each third spatial structure is less than a preset number threshold, wherein the building unit is an independent building structure. 5.The BIM-based engineering building visualization model construction method of claim 3, wherein, The acquisition of the overlap between any two detection nodes and the determination of the collision type between the two detection nodes by using the overlap include: Acquire the first building unit in any one of the detection nodes, and acquire the second building unit in another detection node, and acquire the Euclidean distance between the two detection nodes; Determine the shape similarity between the first building unit and the second building unit by using the first building unit and the second building unit; Determine the overlap between the two detection nodes by using the Euclidean distance and the shape similarity; Acquire the first fractal dimension and the second fractal dimension of the first building unit and the second building unit respectively, and determine the average fractal dimension by using the first fractal dimension and the second fractal dimension; Determine the collision type between the two detection nodes by using the average fractal dimension and the overlap. 6.The BIM-based engineering building visualization model construction method of claim 5, wherein, Further comprising: In response to the Euclidean distance being less than a preset distance threshold, further determine the collision type between the two detection nodes by using the average fractal dimension and the overlap as hard collision. 7.The BIM-based engineering building visualization model construction method of claim 1, wherein, The determination of the position key degree 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: Determine 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; Acquire the fourth volume of the current detection node where the current collision position is located, and acquire the fifth volume of the third building unit and the fourth building unit where the current collision position collides, and acquire the sixth volume of the upper level detection node where the current collision position is located; Determine the position key degree of the current collision position of the detection node by using the fourth volume, the fifth volume, the sixth volume and the distance proximity.

8. A BIM technology-based engineering construction visual model construction system, characterized by, A system for implementing the steps of the BIM technology-based engineering building visualization model construction method according to any one of claims 1-7, and the system specifically comprises: A construction module for constructing a target three-dimensional model by using historical engineering building data; A first determination module for 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; A second determination module for determining the collision severity and the position key degree of each detection node in response to the collision type of the detection node being hard collision; A third determination module for determining the processing priority of each detection node by using the collision severity and the position key degree, and further performing repair processing on the building engineering according to the processing priority and the target three-dimensional model.

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