CN111340100B - Similarity calculation method of BIM model - Google Patents
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Abstract
The invention provides a similarity calculation method and device of a BIM model, wherein the method comprises the following steps: extracting information of each component in the two BIM models, and acquiring an association relationship between the components in the two BIM models; constructing an adjacency graph model of the two BIM models according to the information of each component in the two BIM models and the association relation between the components; and calculating the edit distance between the adjacent graph models of the two BIM models based on the graph edit distance algorithm, and calculating the similarity between the two BIM models according to the edit distance. According to the method, similarity calculation is carried out on the BIM model from the component level, the influence of the association relation of the components and the information of the components on the BIM model is fully considered, the calculation of the similarity of the BIM model is more accurate, and the BIM retrieval result based on the similarity of the BIM model is more accurate.
Description
Technical Field
The invention belongs to the technical field of BIM model retrieval, and particularly relates to a similarity calculation method of a BIM model.
Background
BIM (Building Information Modeling, building information model) is an important business carrier throughout the life cycle of a building, from design to construction to management, based on models, so a large number of different versions of BIM models are generated at different stages. At present, more and more BIM shared resource libraries, such as BIM product websites, BIM shared communities and the like, are built at home and abroad. How to find the BIM model that best meets the business requirements from various model libraries is a broad need.
At present, the method comprises the steps of manually searching, primarily screening through basic information such as naming, building time, service stage and the like of the model, then opening the screened models one by one for manual reading, and finally finding out the BIM model which meets the requirements most. The required models are obtained from a huge model library, so that a great deal of time and labor are required, and the workload is huge. Therefore, how to quickly search the BIM model, so that the user can quickly obtain the required model has become a problem to be solved.
In performing automatic BIM retrieval, it is necessary to calculate the similarity of the BIM models. At present, certain researches are carried out on BIM model similarity calculation at home and abroad, and two main research methods exist. One is to track information changes of the model, and the main methods include shape distribution-based comparison, point-based convergence comparison, skeleton-based comparison and geometric comparison, which are mainly aimed at different versions of the same BIM model, and are to track information changes between different versions. The second type is based on the similarity obtained by the model structure, and the research on BIM model similarity at home and abroad is mainly obtained by analyzing the structure of the model. The basic method is to measure the similarity between building models by analyzing the room and the connectivity between rooms. For example, studies analyze the functions of rooms and connectivity between rooms, and categorize models according to these two characteristics; still other studies analyze the functionality of the room, the importance of the room, and connectivity, and categorize models based on these three characteristics.
However, with the development of the building industry, the design sense of the building is stronger, and the functions, connectivity and the like of the room cannot embody the characteristics of the building model with the design sense. Therefore, the similarity of the BIM model calculated by the existing method is inaccurate, so that the search result is inaccurate, and the requirement of people for obtaining the similar model cannot be met.
Disclosure of Invention
In order to solve the problem that the similarity of the BIM model calculated by the prior art is inaccurate or at least partially solve the problem, the embodiment of the invention provides a similarity calculation method of the BIM model.
According to a first aspect of an embodiment of the present invention, there is provided a similarity calculation method for a BIM model, including:
extracting information of each component in any BIM model to be matched in a target BIM model and a pre-built BIM model library, and acquiring an association relationship between components in the target BIM model and an association relationship between components in the BIM model to be matched;
constructing an adjacency graph model of the target BIM model according to the information of each component in the target BIM model and the association relation between the components; constructing an adjacency graph model of the BIM model to be matched according to the information of each component in the BIM model to be matched and the association relation between the components;
And calculating the editing distance between the adjacent graph model of the target BIM model and the adjacent graph model of the BIM model to be matched based on a graph editing distance algorithm, and calculating the similarity between the target BIM model and the BIM model to be matched according to the editing distance.
Specifically, the information of the component includes semantic information and original geometric information of the component;
correspondingly, the step of obtaining the association relationship between the components in the target BIM model and the association relationship between the components in the BIM model to be matched comprises the following steps:
constructing an OBB bounding box of each component according to the original geometric information of each component in the target BIM model and the BIM model to be matched;
judging whether OBB bounding boxes of any two components in the target BIM model collide, if so, obtaining that the any two components intersect, wherein an association relationship exists between the any two components;
judging whether the OBB bounding boxes of any two components in the BIM model to be matched collide, if so, obtaining that the any two components intersect, wherein an association relationship exists between the any two components.
Specifically, the step of constructing an OBB bounding box of each component according to the original geometric information of each component in the target BIM model and the BIM model to be matched includes:
Extracting triangular mesh vertexes of each component in the target BIM model and the BIM model to be matched according to the original geometric information of each component in the target BIM model and the BIM model to be matched;
according to the original coordinates of the triangular mesh vertexes of each component, obtaining feature vectors corresponding to each component based on a principal component analysis method, and taking the feature vectors corresponding to each component as the direction axis of the OBB bounding box of each component;
acquiring the center of the OBB bounding box of each member according to the direction axis of the OBB bounding box of each member;
and acquiring the OBB bounding box of each component according to the direction axis and the center of the OBB bounding box of each component.
Specifically, the step of constructing an OBB bounding box of each component according to the original geometric information of each component in the target BIM model and the BIM model to be matched includes:
for any two components in the target BIM model, moving one component in the any two components by a preset displacement amount according to a plurality of preset directions;
constructing an OBB bounding box of the moving member in each preset direction according to the geometric information of the moving member in the two members after the moving member moves;
And constructing an OBB bounding box of the other member according to the original geometric information of the other member in the two arbitrary members.
Specifically, judging whether the OBB bounding boxes of any two components in the target BIM model collide, if so, obtaining that the any two components intersect includes:
judging whether the OBB bounding box of the moving component in each preset direction collides with the OBB bounding box of the other component or not based on a separation axis law;
and if the OBB bounding box of the member in at least one preset direction collides with the OBB bounding box of the other member, knowing that any two members intersect.
Specifically, the step of constructing the adjacency graph model of the target BIM model according to the information of each component in the target BIM model and the association relation between the components comprises the following steps:
taking a component in the target BIM model as a vertex of an adjacency graph model of the target BIM model, and taking the type of the component as a mark of the vertex;
connecting the vertexes corresponding to the components with the association relationship to construct the edge of the adjacency graph model;
and assigning an index to each vertex, and taking the index as the vertex number of the vertex.
Specifically, the step of calculating the edit distance between the adjacency graph model of the target BIM model and the adjacency graph model of the BIM model to be matched based on the graph edit distance algorithm includes:
obtaining mapping between the vertexes of the adjacent graph model of the target BIM model and the vertexes of the adjacent graph model of the BIM model to be matched based on a vertex mapping method;
forming a mapping between the edges of the adjacent graph model of the target BIM model and the edges of the adjacent graph model of the BIM model to be matched according to the mapping between the vertexes;
according to the mapping between the edges of the adjacent graph models of the target BIM model and the BIM model to be matched, respectively acquiring editing paths of the target BIM model and the BIM model to be matched based on a tree searching process;
calculating the maximum editing distance between the target BIM model and the BIM model to be matched, and calculating the minimum editing distance between the target BIM model and the BIM model to be matched according to the editing paths of the target BIM model and the BIM model to be matched.
Specifically, the step of forming a mapping between edges of the adjacency graph model of the target BIM model and edges of the adjacency graph model of the BIM model to be matched according to the mapping between the vertices includes:
If the number of vertexes in the adjacent graph models of the target BIM model is different from the number of vertexes of the adjacent graph models of the BIM model to be matched, selecting an adjacent graph model with a smaller number of vertexes from the adjacent graph models of the target BIM model and the BIM model to be matched;
introducing virtual vertexes into the selected adjacency graph model; the number of the virtual vertexes is equal to the difference between the number of vertexes of the adjacent graph models of the BIM model to be matched and the target BIM model;
a mapping between the selected virtual vertex-introduced adjacency graph model and the unselected adjacency graph model is obtained.
Specifically, the similarity between the target BIM model and the BIM model to be matched is calculated according to the editing distance by the following formula:
wherein G represents an adjacent graph model with a smaller number of vertices in the adjacent graph models of the target BIM model and the BIM model to be matched, G ' represents an adjacent graph model with a larger number of vertices in the adjacent graph models of the target BIM model and the BIM model to be matched, G is an adjacent graph model with a smaller number of vertices after virtual vertices are introduced into the adjacent graph model, sim (G, G ') is a similarity between G and G ', sed (G, G ') represents a minimum edit distance between G and G ', V ' represents a total number of vertices in G ', E ' represents a total number of edges in G ', and E ' represents a total number of edges in G '.
According to a second aspect of the embodiment of the present invention, there is provided a similarity calculation apparatus for a BIM model, including:
the acquisition module is used for extracting information of each component in any BIM model to be matched in a target BIM model and a pre-constructed BIM model library, and acquiring the association relationship between the components in the target BIM model and the association relationship between the components in the BIM model to be matched;
the building module is used for building an adjacency graph model of the target BIM model according to the information of each component in the target BIM model and the association relation between the components; constructing an adjacency graph model of the BIM model to be matched according to the information of each component in the BIM model to be matched and the association relation between the components;
the calculating module is used for calculating the editing distance between the adjacent graph model of the target BIM model and the adjacent graph model of the BIM model to be matched based on a graph editing distance algorithm, and calculating the similarity between the target BIM model and the BIM model to be matched according to the editing distance.
According to a third aspect of embodiments of the present invention, there is also provided an electronic device including a memory, a processor and a computer program stored on the memory and executable on the processor, the processor invoking the program instructions to be able to perform a similarity calculation method of a BIM model provided by any of the various possible implementations of the first aspect.
According to a fourth aspect of embodiments of the present invention, there is also provided a non-transitory computer-readable storage medium storing computer instructions that cause the computer to perform a similarity calculation method of a BIM model provided by any of the various possible implementations of the first aspect.
The embodiment of the invention provides a similarity calculation method of BIM models, which comprises the steps of constructing an adjacent graph model of the BIM models by extracting information of components in the BIM models and incidence relations between the components, converting similarity calculation of the BIM models into similarity between adjacent graph models of the BIM models, determining similarity between two BIM models by calculating editing distances between the adjacent graph models, carrying out similarity calculation on the BIM models from component levels, fully considering the incidence relations of the components and influence of the information of the components on the BIM models, calculating the similarity of the BIM models more accurately, and enabling BIM retrieval results based on the similarity of the BIM models to be more accurate.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions of the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic overall flow chart of a similarity calculation method of a BIM model according to an embodiment of the invention;
fig. 2 is a schematic diagram of an OBB bounding box construction flow in the similarity calculation method of the BIM model according to the embodiment of the present invention;
fig. 3 is a schematic diagram of OBB bounding box collision detection in the similarity calculation method of the BIM model according to the embodiment of the present invention;
fig. 4 is a schematic diagram of improved OBB bounding box collision detection in the similarity calculation method of the BIM model according to the embodiment of the present invention;
FIG. 5 is a schematic diagram of the overall structure of a similarity calculation device of BIM model according to the embodiment of the invention;
fig. 6 is a schematic diagram of an overall structure of an electronic device according to an embodiment of the present invention.
Detailed Description
In order to more clearly illustrate the embodiments of the present invention or the technical solutions of the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.
In one embodiment of the present invention, a similarity calculation method of a BIM model is provided, and fig. 1 is a schematic overall flow chart of the similarity calculation method of the BIM model provided in the embodiment of the present invention, where the method includes: s101, extracting information of each component in any BIM model to be matched in a target BIM model and a pre-constructed BIM model library, and acquiring an association relationship between components in the target BIM model and an association relationship between components in the BIM model to be matched;
The target BIM model refers to a BIM model to be retrieved, and the BIM model to be matched refers to a BIM model waiting to be matched with the target BIM model in a BIM model library. The IFC (Industry Foundation Classes, industrial basic class) file contains the information of the semantics, geometry, connection relation among building elements and the like of the elements in the BIM model, and at present, the product support of software developers at home and abroad is shared and exchanged with BIM data through an IFC standard format. The IFC standard IFC2x3 includes 600 entities (entities) and 300 enumeration, selection, etc. classes, and also includes semantic connection relationships between various building components. Therefore, the implementation can take the IFC file as a source file of the target BIM model and the BIM model to be matched, and extract information of components in the target BIM model and the BIM model to be matched, such as geometric information and semantic information of the components. The association relationship between the components can be directly obtained from the target BIM model and the IFC file of the BIM model to be matched.
S102, constructing an adjacency graph model of the target BIM model according to the information of each component in the target BIM model and the association relation between the components; constructing an adjacency graph model of the BIM model to be matched according to the information of each component in the BIM model to be matched and the association relation between the components;
According to the implementation, an adjacency graph model is built according to the information of the components and the association relation between the components, and a basis is provided for similarity calculation of the BIM model. The adjacency graph model is an undirected and unauthorized graph and is represented by the triplet g= (V, E, L). Wherein v= { V 1 ,...,v n And the number is a vertex set of the adjacent graph model, and the number L is a mark of the vertex. E.epsilon.V.times.V is the edge set of the adjacency graph model. The sizes of the vertex set and the edge set are denoted by |v|, |e|, and |l|, respectively, of the kinds of vertex labels.
S103, calculating the editing distance between the adjacent graph model of the target BIM model and the adjacent graph model of the BIM model to be matched based on a graph editing distance algorithm, and calculating the similarity between the target BIM model and the BIM model to be matched according to the editing distance.
The graph editing distance algorithm can well consider the difference between vertex marks of two BIM models, and has good fault tolerance. And the editing distance between adjacent graph models is calculated by using a graph editing distance algorithm, and the similarity obtained based on the editing distance is accurate.
According to the method, the adjacent graph model of the BIM model is built by extracting the information of the components in the BIM model and the association relation between the components, similarity calculation of the BIM model is converted into the similarity between the adjacent graph models of the BIM model, the similarity between the two BIM models is determined by calculating the editing distance between the adjacent graph models, the similarity calculation is carried out on the BIM models from the component level, the influence of the association relation of the components and the information of the components on the BIM model is fully considered, the calculation of the similarity of the BIM model is more accurate, and the BIM retrieval result based on the similarity of the BIM model is more accurate.
On the basis of the above embodiment, the information of the component in this embodiment includes semantic information and original geometric information of the component;
the semantic information extracted in this embodiment mainly refers to the type of the component in the BIM model. The BIM model takes an IFC file as a source file, and the IFC file can summarize the information of the entity object through an attribute mechanism of the IFC file. After the IFC file is parsed, all components and types contained in the BIM model can be extracted. However, a large number of entity types are defined in the IFC standard, including furniture, pipes, holes, etc., so that the BIM model obtained after parsing includes various types of components. However, only a few of these types have a relatively large impact on the model structure, such as whether furniture is included in the model has a relatively small impact on the model structure, and walls and the like have a relatively large impact on the model structure. The types of the extracted members are shown in table 1. After the analysis of the BIM model is completed, screening is carried out according to the types of the components in the BIM model, and six key components in the table 1 are selected, so that the processing of the BIM model is completed.
TABLE 1 BIM model building blocks and IFC entity correspondence table
The IFC file stores various geometric model data, a calculation geometric entity expression method is adopted in the IFC file, and the entity geometric expression of the component is converted into triangular mesh data after analysis. The triangular mesh has simple and clear structure and easy reading, and is a geometric expression format which is relatively universal in graphic research at present. The geometric information of the member that needs to be used in this embodiment is the basic outline and position information of the member. Therefore, the triangular mesh vertices of the component need to be extracted. However, the position and coordinate system of the component defined in the IFC standard include absolute coordinates and relative coordinates, and the extracted data may be processed for use. In the embodiment, a BIM model which is analyzed and completed by a small red brick open platform is mainly adopted for research. The geometric data obtained from the small red brick open platform are a position coordinate matrix positions, an index matrix index and a rotation matrix. And multiplying the position coordinate matrix by the rotation matrix to obtain the position matrix under the world coordinates.
Correspondingly, the step of obtaining the association relationship between the components in the target BIM model and the association relationship between the components in the BIM model to be matched comprises the following steps: constructing an OBB bounding box of each component according to the original geometric information of each component in the target BIM model and the BIM model to be matched;
the BIM model contains all information of the building, the information are related to each other, and the connection relation exists when modeling. In this embodiment, the source file of the BIM model is an IFC file, and the IFC file includes all information of the BIM model, including component information, association relationships between components, and connection relationships, however, some BIM models are not standardized when being established, so that the IFC file loses such connection relationships after analysis is completed, and this embodiment uses the positional relationship of the components to avoid this problem.
The basic idea of bounding box technology is to replace complex geometry with simple geometry, and then determine whether the bounding geometry collides according to whether the bounding box overlaps on the separation axis. The bounding volume classes include spheres, axis aligned bounding boxes, OBBs (Oriented Bounding Box, directed bounding boxes), 8-DOPs, and convex shells. Currently, the application of the axis alignment bounding box and the OBB bounding box is wide, wherein the OBB bounding box always generates a minimum rectangular bounding box along the principal component direction of an object, and the bounding box can rotate along with the object and can be used for more accurate collision detection. Therefore, an OBB bounding box is used in this embodiment. Namely, constructing an OBB bounding box of each component according to the original geometric information of each component in the target BIM model and the BIM model to be matched. The members where the OBB bounding boxes collide are regarded as connected members.
Judging whether OBB bounding boxes of any two components in the target BIM model collide, if so, obtaining that the any two components intersect, wherein an association relationship exists between the any two components; judging whether the OBB bounding boxes of any two components in the BIM model to be matched collide, if so, obtaining that the any two components intersect, wherein an association relationship exists between the any two components.
On the basis of the above embodiment, in this embodiment, the step of constructing the OBB bounding box of each component according to the original geometric information of each component in the target BIM model and the BIM model to be matched includes: extracting triangular mesh vertexes of each component in the target BIM model and the BIM model to be matched according to the original geometric information of each component in the target BIM model and the BIM model to be matched;
according to the original coordinates of the triangular mesh vertexes of each component, obtaining feature vectors corresponding to each component based on a principal component analysis method, and taking the feature vectors corresponding to each component as the direction axis of the OBB bounding box of each component; acquiring the center of the OBB bounding box of each member according to the direction axis of the OBB bounding box of each member; and acquiring the OBB bounding box of each component according to the direction axis and the center of the OBB bounding box of each component.
Specifically, the basic principle of the construction of the OBB bounding box is to obtain a feature vector, that is, a principal axis of the OBB bounding box, by a principal component analysis method according to the vertices of the object surface. And (3) analyzing principal components by traversing triangular mesh vertexes expressing the geometry of the component, so as to obtain the principal axis of the OBB bounding box along the direction of the component main body all the time. The covariance matrix is introduced in principal component analysis:
where i and j are arbitrary triangular grid points within the member, and the correlation of 2 triangular grid points is expressed by calculating the covariance of the x, y and z values. And diagonalizing the covariance matrix, calculating to obtain a feature vector, wherein the feature vector is the direction axis of the OBB bounding box of the convex polyhedron, and calculating to obtain a center point, wherein the OBB bounding box is formed.
On the basis of the above embodiment, in this embodiment, the step of constructing the OBB bounding box of each component according to the original geometric information of each component in the target BIM model and the BIM model to be matched includes: for any two components in the target BIM model, moving one component in the any two components by a preset displacement amount according to a plurality of preset directions; constructing an OBB bounding box of the moving member in each preset direction according to the geometric information of the moving member in the two members after the moving member moves; and constructing an OBB bounding box of the other member according to the original geometric information of the other member in the two arbitrary members.
Specifically, the axis of the OBB bounding box is the perpendicular to its own side, and thus the separation axis law is adopted for determining whether the OBB bounding box collides. Separation axis law refers to the fact that if there is a vector such that the projections of the detected geometry on the axis do not intersect, then this axis is a separation axis, and if no separation axis is found, then the detected geometry intersects.
In collision detection, 4 potential separation axes of the convex polyhedron in the two-dimensional space are respectively OBB direction axes of the two convex polyhedrons. The potential separation axes of the convex polyhedrons in the three-dimensional space are 15 at most, namely 3 direction axes of each convex polyhedron, and the cross multiplication of one side vector of one convex polyhedron and the side vector of the other convex polyhedron is thatThe root is potentially separated from the shaft. According to the separation axis law, the projections of the OBB bounding boxes of the two components on all axes overlap, and the collision is determined, otherwise, the collision does not occur, and the flow chart is shown in fig. 2.
Two-dimensional examples are shown in FIG. 3, which shows the position coordinates P of the vertices of the triangular mesh constituting the component A and the component B A ＝(x A ,y A ) And P B ＝(x B ,y B ) Performing principal component analysis, and constructing an OBB bounding box, so that the OBB bounding boxes of four potential separation shafts A1, A2, B1 and B2 and two components can be obtained; and then collision detection is carried out according to the separation axis law, namely whether projections of the detection components A and B on four potential separation axes are overlapped or not is detected. In fig. 3, the projections of the component a and the component B on the axes A2 and B2 do not overlap, so the axes A2 and B2 are the separation axes of the components a and B, and the two components do not collide.
In view of OThe principle of the BB bounding box algorithm is to process coordinate information, so that the position coordinate information of the components can be converted to achieve the purpose of detecting the connected components. In the modified OBB bounding box algorithm in this embodiment, displacement amounts of one member are given, the displacement amounts in the two-dimensional scene are in four directions of up, down, left and right, and the displacement amounts in the three coordinate axes in the three-dimensional scene. As shown in fig. 4, the two-dimensional example converts the positional coordinate information of the triangular mesh vertices of the member B into P by a small displacement δ of the member B B ＝(x′ B ,y′ B ). Carrying out principal component analysis on position coordinates of triangular mesh vertexes of the component A and the component B to construct a bounding box; and then collision detection is carried out according to the separation axis law. As shown in fig. 4, projections of the component a and the component B on four potential separation axes overlap, so that it is determined that two components collide, thereby determining that the component a and the component B are connected components, and extracting semantic information in basic information of the components.
Based on the above embodiment, in this embodiment, the step of determining whether the OBB bounding boxes of any two members in the target BIM model collide, if yes, obtaining that the any two members intersect includes: judging whether the OBB bounding box of the moving component in each preset direction collides with the OBB bounding box of the other component or not based on a separation axis law; and if the OBB bounding box of the member in at least one preset direction collides with the OBB bounding box of the other member, knowing that any two members intersect.
Based on the foregoing embodiments, in this embodiment, the step of constructing the adjacency graph model of the target BIM model according to the information of each component in the target BIM model and the association relationship between the components includes: taking a component in the target BIM model as a vertex of an adjacency graph model of the target BIM model, and taking the type of the component as a mark of the vertex; connecting the vertexes corresponding to the components with the association relationship to construct the edge of the adjacency graph model; and assigning an index to each vertex, and taking the index as the vertex number of the vertex.
Specifically, a member in the BIM model is taken as a vertex of the adjacency graph, a connection relationship between members is taken as an edge of the adjacency graph, and an index i (i=1, 2, …, |v|) is assigned to each vertex, which is called a vertex number. For example, members A and B in the BIM model correspond to vertices A and B in the adjacency graph model, respectively, and edges (A, B) represent that members A and B are connected. The adjacency graph model of the BIM model to be matched is also generated by adopting the method. After the generation of the adjacent graph model is completed, the similarity calculation of the BIM model is converted into a similarity calculation problem of the adjacent graph model. In the embodiment, a graph edit distance algorithm is adopted to calculate the similarity of the target BIM model and the adjacent graph model of the BIM model to be matched.
On the basis of the above embodiments, the step of calculating the edit distance between the adjacent graph model of the target BIM model and the adjacent graph model of the BIM model to be matched based on the graph edit distance algorithm in this embodiment includes: obtaining mapping between the vertexes of the adjacent graph model of the target BIM model and the vertexes of the adjacent graph model of the BIM model to be matched based on a vertex mapping method; forming a mapping between the edges of the adjacent graph model of the target BIM model and the edges of the adjacent graph model of the BIM model to be matched according to the mapping between the vertexes; according to the mapping between the edges of the adjacent graph models of the target BIM model and the BIM model to be matched, respectively acquiring editing paths of the target BIM model and the BIM model to be matched based on a tree searching process; calculating the maximum editing distance between the target BIM model and the BIM model to be matched, and calculating the minimum editing distance between the target BIM model and the BIM model to be matched according to the editing paths of the target BIM model and the BIM model to be matched.
Specifically, the graph editing distance algorithm measures the matching degree between adjacent graph models mainly through dissimilarity between the adjacent graph models, dissimilarity is measured through distance values between the adjacent graph models, and the larger the distance value is, the larger the dissimilarity is, and the lower the similarity is. For a given two undirected graphs G and G'. Wherein g= (V, E, L), v= { u 1 ,u 2 ,...u i }，G＇＝(V＇,E＇,L＇)，V＇＝{v 1 ,v 2 ,...v i }. The graphic mapping isA bi-directional mapping relationship Γ may be established between vertices of finger graphs G and G': V→V' such thatΓ (u) ∈V' is present. And a mapping method based on vertexes is adopted, mapping is firstly established between vertexes, and then edge mapping is formed according to the mapping between vertexes.
If the number of vertices in G and G 'are the same, then computing the edit distance for the adjacency graph models G and G' typically uses a tree-based search process that searches all possible graph mappings. The search space may be organized as an ordered search tree, with the internal nodes representing partial graph maps and the leaf nodes representing complete graph maps. Such a search tree is created at run-time by iterative generation of subsequent dynamics linked by edges to the current node.
The embodiment adopts a Beam Stack (Beam Stack) searching method, which improves the general method, and can trim the search tree in the process of building the search tree so as to quickly find the optimal editing path. For node n in the search tree, its total edit cost is c (n) =c 1 (n)+c 2 (n), wherein c 1 (n) is the edit cost from root node to node n, c 2 (n) edit cost for the estimation from node n to the leaf node. The adjacency graph model is an undirected unauthorized graph, and cost values of vertex adding and deleting operations, edge adding and deleting operations and vertex label changing operations are all 1 each time. And the bundling width is set as B, c is compared with c before each step of depth expansion 2 And (n) estimating, sorting the total editing distance of the nodes n, and taking the B nodes with the smallest total editing distance values for the next depth expansion. And after the search tree is established, taking the editing path with the smallest editing distance value as a final editing path, and calculating according to the shortest path to obtain the smallest editing distance value. Meanwhile, the maximum edit distance value is calculated assuming that the two adjacency graph models are maximally dissimilar. And calculating the similarity between the two BIM models according to the minimum editing distance and the maximum editing distance between the target BIM model and the BIM model to be matched.
On the basis of the foregoing embodiments, in this embodiment, the step of forming, according to the mapping between the vertices, a mapping between an edge of the adjacency graph model of the target BIM model and an edge of the adjacency graph model of the BIM model to be matched includes: if the number of vertexes in the adjacent graph models of the target BIM model is different from the number of vertexes of the adjacent graph models of the BIM model to be matched, selecting an adjacent graph model with a smaller number of vertexes from the adjacent graph models of the target BIM model and the BIM model to be matched; introducing virtual vertexes into the selected adjacency graph model; the number of the virtual vertexes is equal to the difference between the number of vertexes of the adjacent graph models of the BIM model to be matched and the target BIM model; a mapping between the selected virtual vertex-introduced adjacency graph model and the unselected adjacency graph model is obtained.
Specifically, since the number of vertices of the adjacent graph models G and G' tends to be different, the concept of virtual vertices, i.e., V, needs to be introduced before the similarity is calculated by the above method ε = { ε } and |V ε |= |v| -V' |. Let |V|<The adjacency graph model after introducing the virtual vertex is g= (V, E, L), wherein V * ＝V∪V ε ，E * ＝E，L * =l. Thus, a mapping is established between the adjacency graph models G and G', with two edit paths p 1 ：G→G * And p 2 ：G * G'. If the editing cost is expressed as c (p 1 ) And c (p) 2 ) Then there is c (p 1 )＝ged(G,G * )＝|V ε |，c(p 2 )＝ged(G * G'). Therefore, the minimum edit distance between the adjacent graph models G and G 'is get (G, G')=c (p) 1 )+c(p 2 )。
Adjacency graph model G * Is generated by adding virtual vertexes to G to obtain get (G, G) * ) = |v| -V' |. After the complete mapping is established, an adjacency graph model G can be obtained * And G', selecting the best editing path to calculate the adjacent graph model G * And an edit distance of G' (G) * G'). Adjacency graph model G * The minimum edit distance between the sum G 'is get (G, G') =get (G, G) * )+ged(G * G'). Maximum editingDistance of get (G, G') max =max { |v|, |v ' | + (|v| -V ' |) +|e|+|e '. The maximum edit distance is an edit distance assuming that two adjacency graph models are maximally dissimilar. Where max { |v|, |v| } is an edit distance in the case where vertex labels are different between two adjacent graph models, v| -v|represents a difference in the number of vertices between the two adjacent graph models, and e|+|e| is an edit distance when edges of the two adjacent graph models are completely different.
On the basis of the above embodiments, in this embodiment, the similarity between the target BIM model and the BIM model to be matched is calculated according to the edit distance by the following formula:
wherein G represents an adjacent graph model with a smaller number of vertices in the adjacent graph models of the target BIM model and the BIM model to be matched, G ' represents an adjacent graph model with a larger number of vertices in the adjacent graph models of the target BIM model and the BIM model to be matched, G is an adjacent graph model with a smaller number of vertices after virtual vertices are introduced into the adjacent graph model, sim (G, G ') is a similarity between G and G ', sed (G, G ') represents a minimum edit distance between G and G ', V ' represents a total number of vertices in G ', E ' represents a total number of edges in G ', and E ' represents a total number of edges in G '.
The present embodiment verifies the feasibility of similarity calculation through two sets of BIM models. A living room A with furniture, two living rooms B, a model C with the same room as A but no house, a model D with the same room as B but no house, and a comparison BIM model E obtained by removing one wall from C, and calculating the similarity of the BIM models for A and B, A and C, A and D, B and C, B and D and C and E.
Firstly, processing a BIM model, extracting type information of components in the model, selecting 6 component types with larger contribution to the structure of the BIM model, and carrying out the processing on the components contained in the component typesAnd (5) subsequent treatment. Then extracting the geometric information of each component, performing collision detection by an improved OBB bounding box algorithm to obtain the connection relation among the components, generating an adjacent graph model by taking the components as vertexes, the type information of the components as vertex marks and the connection relation as edges, and respectively marking the adjacent graph models constructed by BIM models A, B, C, D and E as G A 、G B 、G C 、G D And G E . Computing adjacency graph G A 、G B 、G C 、G D And G E The similarity between every two models is calculated as the similarity between every two models of five BIM models. The calculation of the graph edit distance is performed according to the bundle stack search algorithm in the embodiment, and the calculation result is shown in table 2.
Table 2 five adjacency graph models edit distance table between each other
The root similarity formula can calculate G A 、G B 、G C 、G D And G E Similarity sim between, i.e. similarity between five BIM models. The calculation results are shown in Table 3.
Table 3 similarity table between five BIM models
Analysis of the results of the calculations in tables 2 and 3, since A and B are respectively a living room model and a two living room model with furniture, C and D are a living room model and a two living room model with the same room but without furniture, E is a control model with less than one wall for the C model, an adjacency graph G was constructed A And G C Same, G B And G D If the same, edit distance get (G A ,G C )＝0，ged(G B ,G D ) =0, similarity, sim (G A ,G C )＝1，sim(G B ,G D ) =1, the same as the calculation result in the present embodiment, so this phaseThe similarity calculation method is correct. And get (G) A ,G B )＝40，ged(G A ,G D )＝40，sim(G A ,G B )＝0.579，sim(G A ,G D ) It can be seen that the similarity of a living room with furniture is the same as a room but without furniture is higher than that of a living room with furniture. Edit distance ged (G) C ,G E ) =40, similarity sim (G C ,G E ) As can be seen from the following, the similarity between the model E and A, C, which is less than one wall, is still higher than the similarity between E and B, D, so the calculation result is accurate. Therefore, the calculation method of the similarity of the BIM model in the embodiment is feasible.
In another embodiment of the present invention, a similarity calculation device for a BIM model is provided, which is used to implement the method in the foregoing embodiments. Therefore, the descriptions and definitions in the embodiments of the similarity calculation method of the BIM model described above can be used for understanding the respective execution modules in the embodiments of the present invention. Fig. 5 is a schematic diagram of the overall structure of a similarity calculation device of a BIM model according to the embodiment of the present invention, where the device includes an obtaining module 501, a constructing module 502 and a calculating module 503; wherein, the liquid crystal display device comprises a liquid crystal display device,
The obtaining module 501 is configured to extract information of each component in any to-be-matched BIM model in a target BIM model and a pre-built BIM model library, and obtain an association relationship between components in the target BIM model and an association relationship between components in the to-be-matched BIM model;
the construction module 502 is configured to construct an adjacency graph model of the target BIM model according to the information of each component in the target BIM model and the association relationship between the components; constructing an adjacency graph model of the BIM model to be matched according to the information of each component in the BIM model to be matched and the association relation between the components;
the calculating module 503 is configured to calculate an edit distance between the adjacent graph model of the target BIM model and the adjacent graph model of the BIM model to be matched based on a graph edit distance algorithm, and calculate a similarity between the target BIM model and the BIM model to be matched according to the edit distance.
According to the method, the adjacent graph model of the BIM model is built by extracting the information of the components in the BIM model and the association relation between the components, similarity calculation of the BIM model is converted into the similarity between the adjacent graph models of the BIM model, the similarity between the two BIM models is determined by calculating the editing distance between the adjacent graph models, the similarity calculation is carried out on the BIM models from the component level, the influence of the association relation of the components and the information of the components on the BIM model is fully considered, the calculation of the similarity of the BIM model is more accurate, and the BIM retrieval result based on the similarity of the BIM model is more accurate.
On the basis of the above embodiment, the information of the component in this embodiment includes semantic information and original geometric information of the component; correspondingly, the acquisition module is specifically configured to: constructing an OBB bounding box of each component according to the original geometric information of each component in the target BIM model and the BIM model to be matched; judging whether OBB bounding boxes of any two components in the target BIM model collide, if so, obtaining that the any two components intersect, wherein an association relationship exists between the any two components; judging whether the OBB bounding boxes of any two components in the BIM model to be matched collide, if so, obtaining that the any two components intersect, wherein an association relationship exists between the any two components.
On the basis of the above embodiment, the obtaining module in this embodiment is further configured to: extracting triangular mesh vertexes of each component in the target BIM model and the BIM model to be matched according to the original geometric information of each component in the target BIM model and the BIM model to be matched; according to the original coordinates of the triangular mesh vertexes of each component, obtaining feature vectors corresponding to each component based on a principal component analysis method, and taking the feature vectors corresponding to each component as the direction axis of the OBB bounding box of each component; acquiring the center of the OBB bounding box of each member according to the direction axis of the OBB bounding box of each member; and acquiring the OBB bounding box of each component according to the direction axis and the center of the OBB bounding box of each component.
On the basis of the above embodiment, the obtaining module in this embodiment is further configured to: for any two components in the target BIM model, moving one component in the any two components by a preset displacement amount according to a plurality of preset directions; constructing an OBB bounding box of the moving member in each preset direction according to the geometric information of the moving member in the two members after the moving member moves; and constructing an OBB bounding box of the other member according to the original geometric information of the other member in the two arbitrary members.
On the basis of the above embodiment, the obtaining module in this embodiment is further configured to: judging whether the OBB bounding box of the moving component in each preset direction collides with the OBB bounding box of the other component or not based on a separation axis law; and if the OBB bounding box of the member in at least one preset direction collides with the OBB bounding box of the other member, knowing that any two members intersect.
On the basis of the above embodiments, the building module in this embodiment is specifically configured to: taking a component in the target BIM model as a vertex of an adjacency graph model of the target BIM model, and taking the type of the component as a mark of the vertex; connecting the vertexes corresponding to the components with the association relationship to construct the edge of the adjacency graph model; and assigning an index to each vertex, and taking the index as the vertex number of the vertex.
On the basis of the above embodiments, the calculation module in this embodiment is specifically configured to: obtaining mapping between the vertexes of the adjacent graph model of the target BIM model and the vertexes of the adjacent graph model of the BIM model to be matched based on a vertex mapping method; forming a mapping between the edges of the adjacent graph model of the target BIM model and the edges of the adjacent graph model of the BIM model to be matched according to the mapping between the vertexes; according to the mapping between the edges of the adjacent graph models of the target BIM model and the BIM model to be matched, respectively acquiring editing paths of the target BIM model and the BIM model to be matched based on a tree searching process; calculating the maximum editing distance between the target BIM model and the BIM model to be matched, and calculating the minimum editing distance between the target BIM model and the BIM model to be matched according to the editing paths of the target BIM model and the BIM model to be matched.
On the basis of the above embodiment, the calculation module in this embodiment is further configured to: if the number of vertexes in the adjacent graph models of the target BIM model is different from the number of vertexes of the adjacent graph models of the BIM model to be matched, selecting an adjacent graph model with a smaller number of vertexes from the adjacent graph models of the target BIM model and the BIM model to be matched; introducing virtual vertexes into the selected adjacency graph model; the number of the virtual vertexes is equal to the difference between the number of vertexes of the adjacent graph models of the BIM model to be matched and the target BIM model; a mapping between the selected virtual vertex-introduced adjacency graph model and the unselected adjacency graph model is obtained.
On the basis of the above embodiment, the calculation module in this embodiment calculates the similarity between the target BIM model and the BIM model to be matched according to the edit distance by the following formula:
wherein G represents an adjacent graph model with a smaller number of vertices in the adjacent graph models of the target BIM model and the BIM model to be matched, G ' represents an adjacent graph model with a larger number of vertices in the adjacent graph models of the target BIM model and the BIM model to be matched, G is an adjacent graph model with a smaller number of vertices after virtual vertices are introduced into the adjacent graph model, sim (G, G ') is a similarity between G and G ', sed (G, G ') represents a minimum edit distance between G and G ', V ' represents a total number of vertices in G ', E ' represents a total number of edges in G ', and E ' represents a total number of edges in G '.
Fig. 6 illustrates a physical schematic diagram of an electronic device, as shown in fig. 6, which may include: processor 601, communication interface (Communications Interface) 602, memory 603 and communication bus 604, wherein processor 601, communication interface 602, memory 603 complete the communication between each other through communication bus 604. The processor 601 may call logic instructions in the memory 603 to perform the following method: extracting information of each component in the two BIM models, and acquiring an association relationship between the components in the two BIM models; constructing an adjacency graph model of the two BIM models according to the information of each component in the two BIM models and the association relation between the components; and calculating the edit distance between the adjacent graph models of the two BIM models based on the graph edit distance algorithm, and calculating the similarity between the two BIM models according to the edit distance.
Further, the logic instructions in the memory 603 described above may be implemented in the form of software functional units and may be stored in a computer readable storage medium when sold or used as a stand alone product. Based on this understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The present embodiment provides a non-transitory computer readable storage medium storing computer instructions that cause a computer to perform the methods provided by the above-described method embodiments, for example, including: extracting information of each component in the two BIM models, and acquiring an association relationship between the components in the two BIM models; constructing an adjacency graph model of the two BIM models according to the information of each component in the two BIM models and the association relation between the components; and calculating the edit distance between the adjacent graph models of the two BIM models based on the graph edit distance algorithm, and calculating the similarity between the two BIM models according to the edit distance.
Those of ordinary skill in the art will appreciate that: all or part of the steps for implementing the above method embodiments may be implemented by hardware associated with program instructions, where the foregoing program may be stored in a computer readable storage medium, and when executed, the program performs steps including the above method embodiments; and the aforementioned storage medium includes: various media that can store program code, such as ROM, RAM, magnetic or optical disks.
The apparatus embodiments described above are merely illustrative, wherein the elements illustrated as separate elements may or may not be physically separate, and the elements shown as elements may or may not be physical elements, may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
From the above description of the embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus necessary general hardware platforms, or of course may be implemented by means of hardware. Based on this understanding, the foregoing technical solution may be embodied essentially or in a part contributing to the prior art in the form of a software product, which may be stored in a computer readable storage medium, such as ROM/RAM, a magnetic disk, an optical disk, etc., including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method described in the respective embodiments or some parts of the embodiments.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (8)
1. The similarity calculation method of the BIM model is characterized by comprising the following steps of:
extracting information of each component in any BIM model to be matched in a target BIM model and a pre-built BIM model library, and acquiring an association relationship between components in the target BIM model and an association relationship between components in the BIM model to be matched;
constructing an adjacency graph model of the target BIM model according to the information of each component in the target BIM model and the association relation between the components; constructing an adjacency graph model of the BIM model to be matched according to the information of each component in the BIM model to be matched and the association relation between the components;
Calculating the editing distance between the adjacent graph model of the target BIM model and the adjacent graph model of the BIM model to be matched based on a graph editing distance algorithm, and calculating the similarity between the target BIM model and the BIM model to be matched according to the editing distance;
the information of the component comprises semantic information and original geometric information of the component;
correspondingly, the step of obtaining the association relationship between the components in the target BIM model and the association relationship between the components in the BIM model to be matched comprises the following steps:
constructing an OBB bounding box of each component according to the original geometric information of each component in the target BIM model and the BIM model to be matched;
judging whether OBB bounding boxes of any two components in the target BIM model collide, if so, obtaining that the any two components intersect, wherein an association relationship exists between the any two components;
judging whether the OBB bounding boxes of any two components in the BIM to be matched collide, if so, obtaining that the any two components intersect, wherein the any two components have an association relationship;
the step of constructing an OBB bounding box of each component according to the original geometric information of each component in the target BIM model and the BIM model to be matched comprises the following steps:
For any two components in the target BIM model, moving one component in the any two components by a preset displacement amount according to a plurality of preset directions;
constructing an OBB bounding box of the moving member in each preset direction according to the geometric information of the moving member in the two members after the moving member moves;
constructing an OBB bounding box of the other member according to the original geometric information of the other member in the two members;
2. the method for calculating the similarity of BIM models according to claim 1, wherein the step of constructing an OBB bounding box for each component according to the original geometric information of each component in the target BIM model and the BIM models to be matched includes:
extracting triangular mesh vertexes of each component in the target BIM model and the BIM model to be matched according to the original geometric information of each component in the target BIM model and the BIM model to be matched;
according to the original coordinates of the triangular mesh vertexes of each component, obtaining feature vectors corresponding to each component based on a principal component analysis method, and taking the feature vectors corresponding to each component as the direction axis of the OBB bounding box of each component;
Acquiring the center of the OBB bounding box of each member according to the direction axis of the OBB bounding box of each member;
acquiring the OBB bounding box of each component according to the direction axis and the center of the OBB bounding box of each component;
3. the method for calculating the similarity of a BIM model according to claim 1, wherein the step of determining whether the OBB bounding boxes of any two members in the target BIM model collide, and if so, obtaining that the any two members intersect includes:
judging whether the OBB bounding box of the moving component in each preset direction collides with the OBB bounding box of the other component or not based on a separation axis law;
if the OBB bounding box of the member in at least one preset direction collides with the OBB bounding box of the other member, the intersection of any two members is known;
4. a similarity calculation method for a BIM model according to any one of claims 1 to 3, wherein the step of constructing an adjacency graph model of the target BIM model based on the information of each component in the target BIM model and the association relationship between the components includes:
taking a component in the target BIM model as a vertex of an adjacency graph model of the target BIM model, and taking the type of the component as a mark of the vertex;
Connecting the vertexes corresponding to the components with the association relationship to construct the edge of the adjacency graph model;
assigning an index to each vertex, and taking the index as the vertex number of the vertex;
5. a similarity calculation method for BIM models according to any one of claims 1 to 3, wherein the step of calculating the edit distance between the adjacency graph model of the target BIM model and the adjacency graph model of the BIM model to be matched based on a graph edit distance algorithm includes:
obtaining mapping between the vertexes of the adjacent graph model of the target BIM model and the vertexes of the adjacent graph model of the BIM model to be matched based on a vertex mapping method;
forming a mapping between the edges of the adjacent graph model of the target BIM model and the edges of the adjacent graph model of the BIM model to be matched according to the mapping between the vertexes;
according to the mapping between the edges of the adjacent graph models of the target BIM model and the BIM model to be matched, respectively acquiring editing paths of the target BIM model and the BIM model to be matched based on a tree searching process;
calculating the maximum editing distance between the target BIM model and the BIM model to be matched, and calculating the minimum editing distance between the target BIM model and the BIM model to be matched according to the editing paths of the target BIM model and the BIM model to be matched;
6. The method of calculating similarity of BIM models according to claim 5, wherein the step of forming a map between the edges of the adjacency graph model of the target BIM model and the edges of the adjacency graph model of the BIM model to be matched according to the map between the vertices includes:
if the number of vertexes in the adjacent graph models of the target BIM model is different from the number of vertexes of the adjacent graph models of the BIM model to be matched, selecting an adjacent graph model with a smaller number of vertexes from the adjacent graph models of the target BIM model and the BIM model to be matched;
introducing virtual vertexes into the selected adjacency graph model; the number of the virtual vertexes is equal to the difference between the number of vertexes of the adjacent graph models of the BIM model to be matched and the target BIM model;
acquiring mapping between the selected adjacency graph model with the virtual vertexes introduced and the unselected adjacency graph model;
7. the similarity calculation method of BIM models according to claim 6, wherein the similarity between the target BIM model and the BIM model to be matched is calculated from the edit distance by the following formula:
wherein G represents an adjacent graph model with a smaller number of vertices in the adjacent graph models of the target BIM model and the BIM model to be matched, G ' represents an adjacent graph model with a larger number of vertices in the adjacent graph models of the target BIM model and the BIM model to be matched, G is an adjacent graph model with a smaller number of vertices after virtual vertices are introduced into the adjacent graph model, sim (G, G ') is a similarity between G and G ', sed (G, G ') represents a minimum edit distance between G and G ', V ' represents a total number of vertices in G ', E ' represents a total number of edges in G ', and E ' represents a total number of edges in G '.
8. A similarity calculation device for a BIM model, comprising:
the acquisition module is used for extracting information of each component in any BIM model to be matched in a target BIM model and a pre-constructed BIM model library, and acquiring the association relationship between the components in the target BIM model and the association relationship between the components in the BIM model to be matched;
the building module is used for building an adjacency graph model of the target BIM model according to the information of each component in the target BIM model and the association relation between the components; constructing an adjacency graph model of the BIM model to be matched according to the information of each component in the BIM model to be matched and the association relation between the components;
the calculating module is used for calculating the editing distance between the adjacent graph model of the target BIM model and the adjacent graph model of the BIM model to be matched based on a graph editing distance algorithm, and calculating the similarity between the target BIM model and the BIM model to be matched according to the editing distance;
the information of the component comprises semantic information and original geometric information of the component;
accordingly, the acquisition module is configured to:
constructing an OBB bounding box of each component according to the original geometric information of each component in the target BIM model and the BIM model to be matched;
Judging whether OBB bounding boxes of any two components in the target BIM model collide, if so, obtaining that the any two components intersect, wherein an association relationship exists between the any two components;
judging whether the OBB bounding boxes of any two components in the BIM to be matched collide, if so, obtaining that the any two components intersect, wherein the any two components have an association relationship;
the acquisition module is used for:
for any two components in the target BIM model, moving one component in the any two components by a preset displacement amount according to a plurality of preset directions;
constructing an OBB bounding box of the moving member in each preset direction according to the geometric information of the moving member in the two members after the moving member moves;
and constructing an OBB bounding box of the other member according to the original geometric information of the other member in the two arbitrary members.
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