A method, device and medium for comparing similarity of building information models

Abstract

The present application discloses a method, device and medium for comparing the similarity of building information models. First, a plurality of building information models are collected, each of which is composed of a plurality of components; then, based on these building information models, an information set of each component is extracted. Then, based on these information sets, the plurality of components are grouped and sorted to obtain model feature information of the building information model. Subsequently, these model feature information are split and processed to obtain segmented feature information of multiple dimensions. Next, based on these multi-dimensional segmented feature information, the feature values ​​of the building information model are calculated. Furthermore, by comparing these feature values, the similarity results between the plurality of building information models can be obtained. The embodiments of the present application can comprehensively, accurately and efficiently compare the similarity of building information models, thereby significantly improving work efficiency and the accuracy of judgment.

Description

Technical Field

[0001] The embodiments of the present application relate to but are not limited to the technical field of building information modeling, and in particular to a building information modeling similarity comparison method, device and medium. Background Art

[0002] Building Information Modeling (BIM) is an indispensable tool for modern building design, construction, and operation and maintenance management. BIM technology integrates various relevant information data of construction projects and realizes refined management of the entire life cycle of buildings based on three-dimensional models. However, in practical applications, it is often necessary to compare and analyze a large number of BIM models to evaluate the feasibility of design solutions. Traditional BIM model comparison methods mostly rely on manual review, which is inefficient, easy to miss, and difficult to conduct quantitative evaluation. In addition, with the increasing complexity of BIM models, the number of components, attribute information, and spatial relationships contained in the model are also becoming increasingly complex, further exacerbating the difficulty of manual comparison. Summary of the invention

[0003] The following is a summary of the subject matter described in detail herein. This summary is not intended to limit the scope of the claims.

[0004] The embodiment of the present application provides a building information model similarity comparison method, which can comprehensively, accurately and efficiently compare the similarity of building information models, thereby improving work efficiency and judgment accuracy.

[0005] In a first aspect, an embodiment of the present application provides a building information model similarity comparison method, comprising:

[0006] Acquire a plurality of building information models, wherein the building information models include a plurality of components;

[0007] Based on the building information model, extracting an information set of each component;

[0008] Grouping and sorting the plurality of components according to the information set to obtain model feature information of the building information model;

[0009] Splitting the model feature information to obtain segmented feature information of multiple dimensions;

[0010] Obtaining characteristic values ​​of the building information model according to the segment characteristic information of the multiple dimensions;

[0011] According to the characteristic values ​​of the plurality of building information models, similarity results between the plurality of building information models are obtained.

[0012] In combination with the first aspect, in an embodiment of the present application, obtaining an information set of each component based on the building information model includes: traversing and identifying the building information model to obtain type information of the component; extracting multiple parameter information of the component; obtaining an information set of the component based on the type information and the multiple parameter information of the component; wherein the parameter information includes at least position information, material information and vertex information of the component.

[0013] In combination with the first aspect, in an embodiment of the present application, the grouping and sorting of the multiple components according to the information set to obtain model feature information of the building information model includes: grouping the multiple components according to the type information to obtain multiple component type groups; sorting the multiple component type groups according to the position information, the material information and the vertex information to obtain multiple feature information groups; and obtaining model feature information according to the multiple feature information groups.

[0014] In combination with the first aspect, in an embodiment of the present application, the model feature information is split and processed to obtain segmented feature information of multiple dimensions, including: splitting the model feature information according to the type information of the component to obtain first segmented feature information of multiple specified component types, wherein each of the first segmented feature information includes the information set of multiple components in the specified component type; or splitting the model feature information according to the building floor area to obtain second segmented feature information of multiple specified floor location information, wherein each of the second segmented feature information includes the information set of multiple components in the specified floor location information; based on the first segmented feature information or the second segmented feature information, segmented feature information of multiple dimensions is obtained.

[0015] In combination with the first aspect, in an embodiment of the present application, obtaining the characteristic value of the building information model according to the segmented feature information of the multiple dimensions includes: obtaining the first characteristic value of the component type according to the first segmented feature information of the multiple specified component types; or obtaining the second characteristic value of the specified floor location information according to the second segmented feature information of the multiple specified floor location information; obtaining the characteristic value of the building information model according to the first characteristic value or the second characteristic value.

[0016] In combination with the first aspect, in an embodiment of the present application, obtaining the first characteristic value of the component type based on the first segmented characteristic information of the multiple specified component types includes: assigning a specified weight to the parameter information in each specified component type in the first segmented characteristic information; calculating the parameter information of the specified component type according to a preset function to obtain a mapping value of the parameter information; and obtaining the first characteristic value of the component type based on a combination of the specified weight and the mapping value of the parameter information.

[0017] In combination with the first aspect, in an embodiment of the present application, the combined calculation based on the specified weight and the mapping value of the parameter information to obtain the first characteristic value of the component type includes: performing weighted calculation based on the specified weight and the mapping value of the parameter information to obtain multiple specified weights; performing logical summation processing based on the multiple specified weights to obtain the first characteristic value of the component type.

[0018] In combination with the first aspect, in an embodiment of the present application, obtaining similarity results between multiple building information models based on the feature values ​​of multiple building information models includes: grouping the multiple feature values ​​according to different dimensions to obtain multiple feature value groups with the same dimensions, each feature value group including feature values ​​of multiple building information models; setting an initial difference value, comparing the multiple feature values ​​in the feature value group bit by bit, and when the number of bits of the multiple feature values ​​is different, adding one to the initial difference value to obtain a feature difference value; setting a dimension weight for the dimension corresponding to the feature difference value; performing weighted summation of the feature difference values ​​according to the dimension weight to obtain a weighted feature difference value; and obtaining the similarity results between the multiple building information models according to the weighted feature difference value.

[0019] On the other hand, an embodiment of the present application further provides a similarity calculation device, including:

[0020] at least one processor;

[0021] at least one memory for storing at least one program;

[0022] When at least one of the programs is executed by at least one of the processors, the aforementioned building information model similarity comparison method is implemented.

[0023] On the other hand, an embodiment of the present application further provides a computer-readable storage medium, which stores a computer program executable by a processor. When the computer program executable by the processor is executed by the processor, it is used to implement the above-mentioned building information model similarity comparison method.

[0024] A method for comparing the similarity of building information models provided in an embodiment of the present application comprises the following steps: first, collecting a plurality of building information models, wherein each building information model is composed of a plurality of components. Subsequently, based on these building information models, an information set of each component is extracted. Then, based on these information sets, the plurality of components are grouped and sorted to obtain the model feature information of the building information model. This process can more comprehensively reflect the structural situation of the model by comprehensively covering the information of each component in the building information model and performing reasonable grouping and sorting. Next, these model feature information are split and processed to obtain segmented feature information of multiple dimensions. Then, according to these segmented feature information of multiple dimensions, the feature values ​​of the building information model are calculated. Further, by comparing these feature values, the similarity results between the plurality of building information models can be obtained. This process makes the comparison result more accurate and reliable through the splitting process and the calculation of the feature values. At the same time, by calculating the feature values ​​and the similarity results, intuitive and easy-to-understand quantitative indicators are provided. These quantitative indicators not only make the comparison result clearer, but also greatly improve the accuracy and efficiency of the judgment. In summary, the embodiments of the present application can comprehensively, accurately and efficiently compare the similarities of building information models, significantly improving work efficiency and judgment accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 is a flow chart of a building information model similarity comparison method provided in an embodiment of the present application;

[0026] Figure 2 The embodiment of this application provides Figure 1 Specific flow chart of step 130;

[0027] Figure 3 The embodiment of this application provides Figure 1 Specific flow chart of step 140;

[0028] Figure 4 The embodiment of this application provides Figure 1 A specific flow chart of step 150;

[0029] Figure 5 The embodiment of this application provides Figure 1 Specific flow chart of step 160;

[0030] Figure 6 It is a schematic diagram of a similarity calculation device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0031] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0032] It should be noted that, although the logical order is shown in the flowchart, in some cases, the steps shown or described can be performed in a different order from that in the flowchart. The terms "first", "second", etc. in the specification, claims and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be noted that the structures, proportions, sizes, etc. illustrated in the drawings of this specification are only used to match the contents disclosed in the specification for people familiar with this technology to understand and read, and are not used to limit the limiting conditions that the present invention can be implemented, so they have no technical substantive significance. Any modification of the structure, change of the proportional relationship or adjustment of the size, without affecting the effects that the present invention can produce and the purposes that can be achieved, should still fall within the scope of the technical content disclosed by the present invention. At the same time, the terms such as "upper", "lower", "left", "right", "middle" and "one" quoted in this specification are only for the convenience of narration, and are not used to limit the scope of the implementation of the present invention. The change or adjustment of the relative relationship should also be regarded as the scope of the implementation of the present invention without substantially changing the technical content.

[0033] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application belongs. The terms used herein are only for the purpose of describing the embodiments of this application and are not intended to limit this application.

[0034] Building Information Modeling (BIM) is an indispensable tool for modern building design, construction, and operation and maintenance management. BIM technology integrates various relevant information data of construction projects and realizes refined management of the entire life cycle of buildings on the basis of three-dimensional models. However, in practical applications, it is often necessary to compare and analyze a large number of BIM models to evaluate the feasibility of design solutions. For example, in the BIM modeling competition scenario, the judges need to evaluate the similarity of the BIM models of the entries to identify whether there is plagiarism between candidates. In the design change management process of the construction BIM model, quickly identifying the specific scope of the BIM model change helps to accurately evaluate the various impacts that construction changes may bring. Traditional BIM model comparison methods mostly rely on manual review, which is inefficient, easy to miss, and difficult to quantitatively evaluate. In addition, with the increasing complexity of BIM models, the number of components, attribute information, and spatial relationships contained in the model are also becoming increasingly complex, further exacerbating the difficulty of manual comparison.

[0035] In view of this, a method for comparing similarity of building information models, a similarity calculation device and a computer-readable storage medium provided in an embodiment of the present application, first, a plurality of building information models are collected, wherein each building information model is composed of a plurality of components. Subsequently, based on these building information models, an information set of each component is extracted. Then, according to these information sets, the plurality of components are grouped and sorted to obtain model feature information of the building information model. This process can more comprehensively reflect the structural situation of the model by comprehensively covering the information of each component in the building information model and performing reasonable grouping and sorting. Next, these model feature information are split and processed to obtain segmented feature information of multiple dimensions. Then, according to these multi-dimensional segmented feature information, the feature value of the building information model is calculated. Further, by comparing these feature values, the similarity results between the plurality of building information models can be obtained. This process makes the comparison result more accurate and reliable through the splitting process and the calculation of the feature value. At the same time, by calculating the feature value and the similarity result, intuitive and easy-to-understand quantitative indicators are provided. These quantitative indicators not only make the comparison result clearer, but also greatly improve the accuracy and efficiency of the judgment. In summary, the embodiments of the present application can comprehensively, accurately and efficiently compare the similarity of BIM models, significantly improving work efficiency and judgment accuracy.

[0036] The embodiments of the present application are further described below in conjunction with the accompanying drawings.

[0037] like Figure 1 As shown, Figure 1 1 is a flow chart of a method for comparing building information model similarity provided by an embodiment of the present application. The method for comparing building information model similarity includes but is not limited to steps 110 to 160.

[0038] Step 110: Acquire multiple building information models, where each building information model includes multiple components;

[0039] Step 120: extracting an information set of each component based on the building information model;

[0040] Step 130: grouping and sorting the multiple components according to the information set to obtain model feature information of the building information model;

[0041] Step 140: splitting the model feature information to obtain segmented feature information of multiple dimensions;

[0042] Step 150: Obtaining feature values ​​of a building information model according to segment feature information of multiple dimensions;

[0043] Step 160: Obtain similarity results between the multiple building information models based on the feature values ​​of the multiple building information models.

[0044] Steps 110 to 160 are described in detail below.

[0045] In a feasible embodiment, Building Information Modeling (BIM) is a method and technology for information management using models and digital technology throughout the life cycle of construction project assets. BIM is based on a three-dimensional model and presents the various components and systems of a construction project in an accurate three-dimensional form to ensure the accuracy of design and construction. The components of a building information model refer to replaceable physical components in a BIM model. These components have irreplaceable specific functions, conform to the interface standards of the entire BIM model, and can be assembled with other components. Finally, different components together form a complete BIM model. Specifically, BIM components are basic units in a BIM model. They can be building components such as walls, doors and windows, floor slabs, roofs, structural components such as beams and columns, or electromechanical components such as electrical, water supply and drainage, HVAC, etc. These components are presented in a three-dimensional form in the model with clear geometric dimensions and shapes. Each BIM component has a specific function, such as walls for dividing spaces, doors and windows for ventilation and lighting, and beams and columns for supporting structures. These functions are defined and described in the model through the properties and parameters of the components. In addition, BIM components need to comply with the interface standards of the entire BIM model, which means that there needs to be a certain degree of compatibility between components, and they can be connected and assembled to form a complete building model. This helps ensure the consistency and accuracy of the model. In addition, BIM components are replaceable, that is, different components can be selected and used as needed in different projects or scenarios.

[0046] In a feasible embodiment, the BIM component contains detailed attribute information and parameter information in the building information model (BIM), which constitutes the information basis of the component. By extracting information from the building information model, the information set of each component can be obtained. Specifically, this extraction process follows the following steps: First, the BIM model is comprehensively traversed and identified to obtain and distinguish the type information of each component. This step is the basis for subsequent information extraction, which ensures that each component can be accurately identified and classified. Subsequently, the key information of each component is extracted, including various parameter information such as its position information, material information and vertex information. These information together describe the specific position of the component in space, the building materials used, and its geometric form. Finally, according to the type information, position information, material information and vertex information obtained in the previous steps, comprehensive processing and integration are performed to finally generate a complete information set of each component.

[0047] In a feasible embodiment, the type information of BIM components refers to the type or category of components. In the building information model, the types of components are varied, covering multiple aspects such as architecture, structure, and equipment. For example, building components such as walls, doors and windows, floor slabs, and roofs are the basic elements that constitute a building. Structural components such as beams, columns, foundations, and floor slabs constitute the skeleton of the building and support the entire building. Electromechanical components such as distribution cabinets, switches, sockets, lamps, pipes, valves, and pumps are components of electrical, water supply and drainage, HVAC, and other systems in the building. Decorative components such as floors, ceilings, and wall decoration materials (ceramic tiles, wallpapers, paints, etc.) can be used to improve the comfort of using buildings. In addition, the location information of BIM components refers to the spatial position of the components in the building information model. Through the location information, the specific location of the component in the building can be determined. For example, the location information of a wall component may include the starting and ending coordinates of the wall, the thickness and height of the wall, etc. The location information of a beam component may include the starting and ending coordinates of the beam, the cross-sectional size and span of the beam, etc. The location information of door and window components may include the specific location of the door and window on the wall (such as the distance from the edge of the wall), the size of the door and window, and the opening direction. In addition, the material information of the BIM component refers to the material used by the component. Different components may use different materials. For example, wall components may use materials such as concrete, bricks, and gypsum boards. Beam and column components may use materials such as steel, wood, or concrete. Door and window components may use materials such as wood, aluminum alloy, and plastic steel. The vertex information of BIM components refers to the key points of the component's geometric shape. Vertex information can describe the component's geometric shape and size. For example, in a wall component, the vertex information may include the coordinates of the four corner points of the wall. In a beam component, the vertex information may include the coordinates of the starting and ending points of the beam, as well as the coordinates of the key points on the beam (such as the bending point or the variable section point of the beam). In a door and window component, the vertex information may include the coordinates of the four corner points of the door and window, as well as the coordinates of the key points in the door and window opening direction. It can be seen that the type information, location information, material information, and vertex information of a BIM component together constitute a complete information set of the component.

[0048] In a feasible embodiment, after obtaining the information set of each BIM component, multiple components can be further grouped and sorted according to the information set to obtain model feature information of the building information model. Figure 2 As shown, the specific implementation steps of the process may include but are not limited to steps 210 to 230.

[0049] Step 210: grouping the multiple components according to the type information to obtain multiple component type groups;

[0050] Step 220: sorting the multiple component type groups according to the position information, material information and vertex information to obtain multiple feature information groups;

[0051] Step 230: Obtain model feature information according to the plurality of feature information groups.

[0052] In a feasible embodiment, in step 210, all components in the BIM model are traversed and grouped according to their type information (such as walls, doors and windows, beams, columns, etc.), aiming to classify components with similar properties and functions together for the convenience of subsequent processing and analysis. Through the grouping process, multiple component type groups can be obtained, each group containing a class of components with the same or similar type.

[0053] In a feasible embodiment, after obtaining the component type grouping, the components in each grouping are further sorted. The purpose is to arrange components with similar or related features together according to feature information such as component position information, material information, and vertex information to form feature information groups. It should be noted that the sorting process can be based on different rules, such as sorting according to the component position coordinates, or sorting according to the component material type. Through the sorting process, multiple feature information groups can be obtained, each of which contains a group of components with similar or related features.

[0054] In a feasible embodiment, after obtaining multiple feature information groups, the overall feature information of the model can be obtained by integrating and extracting the component information in each group. The purpose of this step is to aggregate the information scattered in each component to form a comprehensive description of the overall features of the model.

[0055] The steps 210 to 230 are described below with a specific example.

[0056] Suppose a building project is modeled using BIM, and the project contains multiple types of components, such as walls, doors and windows, beams, columns, stairs, etc. Use BIM software (such as Revit) to traverse the entire building model and identify all components. For each component, extract its type information, such as walls, doors and windows, beams, columns, etc. According to the type information, group components of the same or similar type together. For example, group all wall components into one group, group all door and window components into another group, and so on. Thus, multiple component type groups can be obtained, such as wall grouping, door and window grouping, beam and column grouping, etc. Further, for each component type grouping, extract its position information (such as coordinates), material information (such as concrete, steel, wood, etc.) and vertex information (such as the geometric shape and size of the component). Set sorting rules according to the specific needs of the project. For example, you can sort by the position coordinates of the components, or sort by material type. According to the set sorting rules, sort the components in each component type group. For example, in the wall grouping, the wall can be sorted according to its position coordinates to ensure that adjacent wall components are still adjacent after sorting. Thus, multiple feature information groups can be obtained, each of which contains a group of components with similar or related features, and these components are sorted according to the set rules within the group. Furthermore, for each feature information grouping, the component information therein is integrated, including type, quantity, location distribution, material usage, etc. Based on the integrated information, the overall characteristics of the model can be described. For example, the total number of walls, distribution locations, types of materials used, etc. can be described; the type, size, quantity of doors and windows and their distribution on the wall can be described, etc.

[0057] In a feasible embodiment, when a plurality of components are grouped and sorted according to the information set to obtain the model feature information of the building information model, the plurality of component types can also be directly sorted according to the type information, position information, material information and vertex information of the components to obtain the model feature information of the building information model. It should be noted that the embodiment of the present application does not set any restrictions on the grouping and sorting processing method of the plurality of components.

[0058] In a feasible embodiment, after obtaining the model feature information of the building information model, the information can be split according to established rules (such as component type, floor area or other relevant standards) to generate multiple segmented BIM model feature information. This process aims to refine the hierarchical structure of the model feature information for more accurate management and analysis. Figure 3 As shown, the specific process of splitting the model feature information in step 140 to obtain segmented feature information of multiple dimensions may include but is not limited to steps 310 to 320.

[0059] Step 310: splitting the model feature information according to the component type information to obtain first segment feature information of a plurality of specified component types, wherein each first segment feature information includes an information set of a plurality of components of the specified component type;

[0060] or,

[0061] The model feature information is split according to the building floor area to obtain a plurality of second segment feature information of the specified floor position information, wherein each second segment feature information includes an information set of a plurality of components in the specified floor position information;

[0062] Step 320: Obtain segment feature information of multiple dimensions according to the first segment feature information or the second segment feature information.

[0063] In a feasible embodiment, in order to extract segmented feature information based on multiple dimensions (covering component type, floor area and other relevant standards) from the building information model, the model feature information can be finely split according to the specific type information of the component, or divided according to the different floor areas of the building. Through this multi-dimensional splitting method, the hierarchical structure of the model feature information can be further refined, making it clearer, easier to manage and analyze.

[0064] In a feasible embodiment, when the model feature information is split according to the type information of the component, the type information of each component (such as wall, door and window, beam, column, etc.) can be identified and extracted from the model feature information. According to the component type, the model feature information is split into a plurality of first segment feature information, and each first segment feature information contains the information set of all components in the specified component type. For example, suppose there is a BIM, and the model contains multiple types of building components, such as wall, door and window, beam and column, etc. In order to conduct a deeper analysis and processing of this model, the model feature information can be split according to the type information of the component. Specifically, from the model feature information, the type information of components such as wall, door and window, beam and column can be identified. Further, according to the identified component type information, the model feature information is split into a plurality of first segment feature information. For example, the information of all walls is integrated into a first segment feature information, and this information set contains detailed information such as material information, position information, vertex information, etc. of all walls in the model. Similarly, the information of components such as door and window, beam and column can also be integrated into their respective first segment feature information.

[0065] In a feasible embodiment, when the model feature information is split according to the building floor area, the floor area where each component is located can be determined in the model feature information, for example, the floor area where each component is located can be determined according to the location information of the component. According to the floor area, the model feature information is split into a plurality of second segmented feature information, wherein each second segmented feature information contains a set of information of all components in the specified floor position. For example, suppose there is a BIM of a multi-story office building, and the model shows in detail all building components from the bottom to the top floor, such as walls, columns, beams, floors, stairs, doors and windows, etc. In the process of splitting the model feature information according to the building floor area, each component in the model feature information is first checked, especially their location information. This information usually includes the three-dimensional coordinates (X, Y, Z) of the component in space. By analyzing these coordinates, it can be determined in which floor area each component is located. For example, if the Z coordinate in the model represents the height, and the height range of each floor is known, then the component can be assigned to the corresponding floor according to the Z coordinate value. According to the information of the floor area, the feature information of the entire model can be split into a plurality of second segmented feature information. For example, the information of all components located at the bottom floor (such as the bottom floor walls, columns, floors, entrance doors, etc.) is integrated into one second segment feature information. Similarly, the component information of the second floor, the third floor and higher floors can also be integrated into the corresponding second segment feature information.

[0066] It should be noted that the embodiments of the present application do not set a fixed method for splitting model feature information. In addition to the splitting methods mentioned in the above embodiments, it also fully supports the use of multiple other splitting methods. For example, the splitting can be performed based on the material information of the component, that is, according to the different materials used by each component in the model (such as concrete, steel, wood, glass, etc.), the model feature information is divided into multiple segmented feature information with specific material attributes.

[0067] In a feasible embodiment, after obtaining the first segmented feature information (if the model feature information is split according to the component type information) or the second segmented feature information (if the model feature information is split according to the building floor area), multiple dimensional information corresponding thereto can be obtained. These dimensions cover different component types, such as walls, windows, doors, etc., and different floor areas, such as the bottom floor, middle floor, top floor, etc., thereby forming a segmented feature data set containing different dimensional information.

[0068] In a possible embodiment, if Figure 4 As shown, the process of obtaining the characteristic value of the building information model according to the segmented characteristic information of multiple dimensions in step 150 may include but is not limited to steps 410 to 420.

[0069] Step 410: obtaining a first characteristic value of a component type according to first segment characteristic information of a plurality of specified component types;

[0070] or,

[0071] Obtaining a second characteristic value of the designated floor location information according to the second segment characteristic information of the plurality of designated floor location information;

[0072] Step 420: Obtain multi-dimensional eigenvalues ​​of the building information model according to the first eigenvalue or the second eigenvalue.

[0073] In a feasible embodiment, the first segment feature information includes parameter information such as type information, position information, material information, vertex information, and component name of multiple components in the specified component type. For example, the information of all walls is integrated into one first segment feature information, and the information of all columns is integrated into another first segment feature information. Specifically, the first segment feature information that integrates the information of all walls may include parameters such as material information, position information, vertex information, and component name (e.g., "first wall") of all walls in the model. The first segment feature information that integrates the information of all columns may also include parameters such as material information, position information, vertex information, and component name (e.g., "first column") of all columns in the model.

[0074] In a feasible embodiment, in the process of obtaining the first characteristic value of a component type according to the first segmented characteristic information of multiple specified component types, a specified weight may be first assigned to each parameter information of each specified component type of the first segmented characteristic information, and then the parameter information of the specified component type is calculated according to a preset function to obtain the mapping value of each parameter information, and then the characteristic value of the specified component type is obtained by combining the specified weight and the mapping value of each parameter information. By analogy, the above steps are performed for each specified component type, so that the first characteristic value of the component type can be obtained.

[0075] In a feasible embodiment, when assigning weights to each parameter information of each specified component type, the weights can be flexibly assigned according to actual needs. For example, if the requirements for the component location are high, a relatively high weight can be assigned to it; on the contrary, if the importance of the component name is relatively low, its corresponding weight will be lowered accordingly.

[0076] In a feasible embodiment, in the process of calculating the various parameter information of the specified component type according to the preset function to obtain the mapping value of each parameter information, a preset hash function can be selected, for example. The function of this function is to perform a hash operation on the specified parameter information of the component (such as the component name) to generate a unique binary string as an identifier, and this string is the mapping value. Taking the actual operation as an example, assuming that the component name of a component is the first pillar, the hash operation is performed on this string using the preset hash function. The hash function converts the string "first pillar" into a binary string of fixed length, such as "1100". This binary string is the mapping value of the component name "first pillar". It should be noted that the process of calculating the various parameter information of the component using the preset function is similar to the process of processing the component name using the preset function. In view of the high consistency of the two in logic and operation, in order to avoid repetition, the former will not be elaborated in detail here.

[0077] In a feasible embodiment, in the process of obtaining the first characteristic value of the component type by combining and calculating the mapping values ​​of the specified weights and parameter information, the mapping values ​​of the parameter information corresponding to the specified weights can be weighted calculated first to obtain multiple specified weights; then logical summation processing can be performed based on the multiple specified weights to obtain the first characteristic value of the component type.

[0078] The following describes in detail a process of obtaining a first characteristic value of a component type according to first segment characteristic information of multiple specified component types by taking a specific example.

[0079] Suppose there is a building information model that contains a variety of wall components. Subsequently, the information of all walls is integrated into a first segment feature information, which records in detail the parameter information such as the type, position, material and vertex information of each wall. Suppose that in this first segment feature information, the following wall information is recorded: Component name: for example, "first wall", "second wall", etc. Component type: all are walls. Position information: the three-dimensional coordinates (X, Y, Z) and dimensions (length, width, height) of each wall. Material information: the material type (such as concrete, brick, etc.) of each wall and the physical properties of the material (such as density, strength, etc.). Vertex information: the vertex coordinate set of each wall, which is used to accurately describe the geometric shape of the wall. First, different weights are assigned to each part of the feature information according to actual needs, including: Component position information: Since the position information is crucial to determining the spatial layout of the wall, it is assigned a higher weight, such as 0.5. Component name: Since the name is mainly used to identify and distinguish different walls, it has little impact on subsequent analysis and processing, so it is assigned a lower weight, such as 0.1. Component material information: Material information has an important impact on the structural performance and construction selection of the wall, so it is also given a higher weight, such as 0.4. Component vertex information: Although vertex information can accurately describe the geometric shape of the wall, in some cases, its importance may be slightly lower than that of position and material information, so it is given a moderate weight, such as 0.2 (or adjusted according to the specific situation). Then, a hash value calculation is performed on each part of the feature information (such as position information, material information, etc.) to obtain multiple specified weights, where the specified weights are identified by binary strings. This process can be implemented by common hash algorithms (such as MD5, SHA-256, etc.). Next, each bit of the hash value (i.e., the specified weight) is weighted. Assuming that the hash value of a certain wall position information is "1010110" (binary string), it is weighted according to the weight of 0.5. For each bit of the hash value, if it is 1, it is multiplied by the weight positively (i.e., multiplied by 0.5), and if it is 0, it is multiplied by the weight negatively (i.e., multiplied by -0.5). It is worth noting that the "negative multiplication" here actually means treating the contribution of the bit as a negative value, rather than directly performing mathematical negative multiplication. Subsequently, the above-mentioned weighted processing is performed on each feature part (such as position information, material information, etc.), and the weighted result of each bit is recorded. Next, the same bit of all feature parts is summed. If the sum is greater than 0, the final result of this bit is 1; if the sum is less than or equal to 0, the final result of this bit is 0. Through the above steps, an eigenvalue (i.e., the first eigenvalue) with specific weights and hash value characteristics can be generated for the wall type component information. It is worth noting that for columns, beams and other types of component information, the above process is repeated to generate eigenvalues ​​of their respective types.In this way, a set of characteristic values ​​of different component type dimensions in the entire BIM model is obtained.

[0080] In a feasible embodiment, the second segment feature information includes type information, location information, material information and vertex information of multiple components in the specified floor location information. For example, information of all components located at the bottom floor (such as bottom floor walls, columns, floors, entrance doors, etc.) can be integrated into one second segment feature information, and information of all components located at the first floor can be integrated into another second segment feature information.

[0081] The following describes in detail a process of obtaining a second characteristic value of a specified floor location information based on second segment characteristic information of a plurality of specified floor location information by taking a specific example.

[0082] Suppose there is a building information model with multiple floors, and each floor has multiple types of components, such as walls, columns, floors, and entrance doors. Suppose that in the second segment feature information of the bottom layer, the following detailed information of the components is recorded: Component name: for example, "bottom wall 1", "bottom column A", "bottom floor", "bottom entrance door", etc. Component type: such as wall, column, floor, door, etc. Position information: the three-dimensional coordinates (X, Y, Z) of each component in the bottom layer and possible size information. Material information: the material type and physical properties of each component. Vertex information: the vertex coordinate set of each component, which is used to accurately describe its geometric shape. First, different weights are assigned to each part of the bottom layer component information according to actual needs. For example, the weight of the component location information is 0.4; the weight of the component name is 0.1; the weight of the component material information is 0.3; and the weight of the component vertex information is 0.2. Then, the location information, component name, material information, and vertex information of all components in the bottom layer component information are hashed to obtain a binary string identifier (i.e., hash value). Next, each bit of the hash value is weighted. Assuming that the calculated hash value of the location information of the bottom wall 1 is "1101001" (binary string), the hash value is weighted according to the weight of the location information (0.4). In the weighting process, for each bit of the hash value, if it is 1, it is positively multiplied by the weight (i.e., multiplied by 0.4), and if it is 0, it is negatively multiplied by the weight (i.e., multiplied by -0.4). Similarly, for the component name, material information, and vertex information in the bottom component information, the above weighting process is performed according to their corresponding weights, and the weighted result of each bit is recorded. Subsequently, the weighted results of the same bit in all the bottom component information are summed. If the sum result is greater than 0, the final result of this bit is 1; if the sum is less than or equal to 0, the final result of this bit is 0. Through the above steps, a feature value (i.e., the second feature value) with specific weight and hash value characteristics can be generated for the bottom component information. It is worth noting that for the component information of the second, third, and higher floors, the above process is repeated to generate feature values ​​for each floor respectively. In this way, a set of characteristic values ​​of different floor area dimensions in the entire BIM model is obtained.

[0083] In a feasible embodiment, after calculating and integrating the feature value sets of multiple dimensions, the multi-dimensional feature values ​​of the entire building information model (BIM) can be obtained. Furthermore, by comparing the differences in the multi-dimensional feature values ​​of different BIM models, the similarity between these models can be accurately quantified.

[0084] See also Figure 5 , Figure 5 is a specific flow chart of step 160 provided in the embodiment of the present application. The process may include but is not limited to steps 510 to 550.

[0085] Step 510: grouping the multiple eigenvalues ​​according to different dimensions to obtain multiple groups of eigenvalues ​​with the same dimensions, each eigenvalue group including eigenvalues ​​of specified dimensions of multiple building information models;

[0086] Step 520: setting an initial difference value, comparing multiple eigenvalues ​​in the eigenvalue group bit by bit, and when the number of bits of multiple eigenvalues ​​is different, adding one to the initial difference value to obtain a feature difference value;

[0087] Step 530: setting dimension weights for dimensions corresponding to feature difference values;

[0088] Step 540: performing weighted summation on the feature difference values ​​according to the dimension weights to obtain a weighted feature difference value;

[0089] Step 550: Obtain similarity results between multiple building information models based on the weighted feature difference values.

[0090] In a feasible embodiment, after obtaining multi-dimensional feature values ​​of different BIM models (e.g., feature values ​​of different floor area dimensions, feature values ​​of different component type dimensions, etc.), the feature values ​​of multiple different dimensions of the building information model can be grouped first, so that each feature value group includes feature values ​​of different BIM models in the same specified dimension. Subsequently, within the established feature value group, feature values ​​under the same dimension can be selected for comparison, such as selecting feature values ​​of the same floor (e.g., the eighth floor) in all BIM models for special comparison; components of the same type can also be selected across dimensions to compare the feature values ​​of these components in different floor areas or other related dimensions, such as specifically comparing the feature values ​​of components of the same type distributed on different floors in all BIM models. By analogy, through this process, the feature difference values ​​between multiple BIM models in multiple dimensions can be accurately calculated.

[0091] In a feasible embodiment, when comparing the feature values ​​of the same dimension, a bit-by-bit comparison method can be adopted. Specifically, each digit of the two feature values ​​is compared one by one, and once the digits on the corresponding digits are not equal, the difference value is increased by 1. This process will continue until all the digits of the two feature values ​​are compared. In this way, after all the digits of the two feature values ​​are compared, the total difference value on this dimension can be obtained. For example, suppose there are two BIM models with feature values ​​on the same dimension (assuming different floor area dimensions), which are "1010110" and "1001101" (both are binary strings). When comparing bit by bit, the digits of the 4th and 6th digits are different (counting from right to left, the 4th digit is 0 and 1 respectively, and the 6th digit is 0 and 0 respectively), so the difference value is increased by 1, and finally the difference value of this dimension is 1. Through this comparison method, the feature differences of different BIM models on a specific dimension can be accurately quantified.

[0092] In a feasible embodiment, after obtaining the differences in eigenvalues ​​in different dimensions, reasonable weights can be set for each dimension according to specific business needs. For example, in the similarity judgment scenario of the BIM modeling competition, since the component types (such as columns, walls, and foundations, etc.) often have a high degree of similarity or even consistency, relatively low weights can be set for these dimensions. On the contrary, higher weights can be given to those dimensions that are more likely to change or have differences. The differences in eigenvalues ​​of these different dimensions are combined with their respective weights and weighted summed to obtain the weighted feature difference value between the two BIM models. Furthermore, the similarity of the two models can be evaluated based on this weighted feature difference value, such as setting a similarity threshold. When the weighted feature difference value is higher than this threshold, it can be considered that the two models have a high degree of similarity, and then the similarity result between the BIM models can be obtained.

[0093] In a feasible embodiment, it is assumed that when judging the similarity between model A and model B, the difference between the columns of model A and model B is calculated to be 10. This difference can be further divided into a difference of 3 for the columns of the basement part and a difference of 7 for the columns of the ground part. The weight of the column in the overall evaluation is set to 0.5. Similarly, the difference of the wall is 50, which is further divided into a difference of 20 for the walls of the basement part and a difference of 30 for the walls of the ground part. The weight of the wall is 1. Based on these data and weight allocation, the weighted feature difference between the two models can be calculated to be 10×0.5+50×1=55. This value reflects the overall similarity between model A and model B in the two key features of columns and walls. Assuming the similarity threshold is 50, since the weighted feature difference value (55) is greater than the similarity threshold (50), model A and model B are similar. It should be noted that in this process, another dimension can also be used for weight allocation to calculate the weighted feature difference between model A and model B. Specifically, the weight of the basement area can be set to 1, and the weight of the ground area can be set to 10, so the weighted feature difference value between the two models is (3+20)×1+(7+30)×10=393. Based on the weights set in this dimension, the similarity threshold can be reset, for example, the similarity threshold is increased to 300. Since the new weighted feature difference value (393) is greater than the new similarity threshold (300), model A and model B are similar.

[0094] Reference Figure 6 The embodiment of the present application further discloses a similarity calculation device, the similarity calculation device 600 comprising:

[0095] at least one processor 601;

[0096] At least one memory 602, used to store at least one program;

[0097] When at least one program is executed by at least one processor 601, the building information model similarity comparison method described in the previous embodiment is implemented.

[0098] The embodiment of the present application further discloses a computer-readable storage medium, which stores a computer program executable by a processor. When the computer program executable by the processor is executed by the processor, it is used to implement the building information model similarity comparison method as described in the previous embodiment.

[0099] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A building information model similarity comparison method, characterized in that: include: Acquire a plurality of building information models, wherein the building information models include a plurality of components; Based on the building information model, extracting an information set of each component; Grouping and sorting the plurality of components according to the information set to obtain model feature information of the building information model; Splitting the model feature information to obtain segmented feature information of multiple dimensions; Obtaining characteristic values ​​of the building information model according to the segment characteristic information of the multiple dimensions; Obtaining similarity results between the plurality of building information models according to the feature values ​​of the plurality of building information models; The splitting process of the model feature information to obtain segmented feature information of multiple dimensions includes: Splitting the model feature information according to the type information of the component to obtain first segmented feature information of a plurality of specified component types, wherein each of the first segmented feature information includes the information set of a plurality of the components in the specified component type; Or, the model feature information is split according to the building floor area to obtain a plurality of second segment feature information of the specified floor position information, wherein each of the second segment feature information includes the information set of the plurality of components in the specified floor position information; The step of obtaining the characteristic value of the building information model according to the segment characteristic information of the multiple dimensions comprises: Obtaining a first characteristic value of the component type according to the first segment characteristic information of the plurality of specified component types; or, obtaining a second characteristic value of the designated floor location information according to the second segment characteristic information of the plurality of designated floor location information; A characteristic value of the building information model is obtained according to the first characteristic value or the second characteristic value.

2. The building information model similarity comparison method according to claim 1, characterized in that: The step of obtaining an information set of each component according to the building information model includes: Traversing and identifying the building information model to obtain type information of the component; extracting various parameter information of the component; Obtaining an information set of the component according to the type information and various parameter information of the component; The parameter information at least includes the position information, material information and vertex information of the component.

3. The building information model similarity comparison method according to claim 2, characterized in that: The step of grouping and sorting the plurality of components according to the information set to obtain model feature information of the building information model includes: According to the type information, a plurality of the components are grouped to obtain a plurality of component type groups; Sorting the plurality of component type groups according to the position information, the material information and the vertex information to obtain a plurality of feature information groups; According to the plurality of feature information groups, model feature information is obtained.

4. The building information model similarity comparison method according to claim 1, characterized in that: The obtaining, according to the first segment feature information of the plurality of specified component types, a first feature value of the component type comprises: assigning a specified weight to parameter information in each of the specified component types of the first segment feature information; Calculating the parameter information of the specified component type according to a preset function to obtain a mapping value of the parameter information; The first characteristic value of the component type is obtained by combining and calculating the specified weight and the mapping value of the parameter information.

5. The building information model similarity comparison method according to claim 4, characterized in that: The step of calculating according to the mapping value of the specified weight and the parameter information to obtain the first characteristic value of the component type includes: Performing weighted calculation according to the designated weights and the mapping values ​​of the parameter information to obtain a plurality of designated weights; A logical summation process is performed based on the plurality of designated weights to obtain a first characteristic value of the component type.

6. The building information model similarity comparison method according to claim 1, characterized in that: The obtaining, according to the feature values ​​of the plurality of building information models, similarity results between the plurality of building information models comprises: Grouping the plurality of eigenvalues ​​according to different dimensions to obtain a plurality of eigenvalue groups with the same dimensions, each of the eigenvalue groups including a plurality of eigenvalues ​​of the building information model; Setting an initial difference value, comparing the plurality of eigenvalues ​​in the eigenvalue group bit by bit, and when the number of bits of the plurality of eigenvalues ​​is different, adding one to the initial difference value to obtain a eigenvalue difference value; Setting dimension weights for the dimensions corresponding to the feature difference values; Performing weighted summation on the feature difference values ​​according to the dimension weights to obtain a weighted feature difference value; According to the weighted feature difference values, similarity results between the multiple building information models are obtained.

7. A similarity calculation device, characterized in that: include: at least one processor; at least one memory for storing at least one program; When at least one of the programs is executed by at least one of the processors, the building information model similarity comparison method according to any one of claims 1 to 6 is implemented.

8. A computer-readable storage medium, characterized in that: A computer program executable by a processor is stored therein, and when the computer program executable by the processor is executed by the processor, it is used to implement the building information model similarity comparison method as described in any one of claims 1 to 6.

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