CN114254421A - Method for building three-dimensional space semantic model from BIM model without damage - Google Patents
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Abstract
The invention discloses a method from a BIM (building information modeling) model to a three-dimensional space semantic model construction in a lossless manner, which comprises the steps of classifying data based on attribute types to obtain multi-class model data, and performing semantic description on the model data to obtain target semantic description data; performing semantic description on the model data to obtain first semantic description information, wherein the first semantic description information comprises geometric features and coordinate features; the invention solves the problems of excessive redundant geometric information, high data rendering difficulty, difficult data transmission and pure geometric and attribute separation by setting multiple types of model data, and the method for building the three-dimensional space semantic model from the BIM model in a lossless manner has the advantages of classifying the data based on attributes, carrying out semantic description, building the incidence relation between the attribute information and the geometric information, improving the data compression ratio, facilitating data transmission, contributing to improving the rendering efficiency and relieving the hardware rendering pressure.
Description
Technical Field
The invention relates to the technical field of building of a three-dimensional space by using BIM, in particular to a method from a BIM model to a semantic model of the building of the three-dimensional space in a lossless manner.
Background
Building information model BIM is named as BIM model for short, is a new tool of architectural engineering and civil engineering, is a form-factor, is a computer aided design which mainly uses three-dimensional graphics, is object-oriented and related to architecture, has been widely accepted in the world, can help to realize the integration of building information, has important practical significance for industries such as building real estate authority and the like from the design, construction and operation of buildings to the end of the whole life cycle of the buildings along with the rise of digital intelligent cities, the application of the three-dimensional building BIM model is increased to fully utilize the existing BIM model data, automatically determine the room area, the volume and the like, and deeply realize the required process details such as the arrangement of embedded steel bars in a body factory compared with the prior BIM forward design, the method comprises the steps of reserving holes and the like, so that the quantity of geometric information needing to be displayed in one scene is increased exponentially, the instances are stored in a BIM model library in the prior art in an enumeration mode, redundant geometric information is excessive, data rendering difficulty is high, data transmission is difficult, pure geometry and attributes are separated, and in order to solve the problems, a method from the BIM model to the construction of the three-dimensional space semantic model in a lossless mode is provided.
Disclosure of Invention
The invention aims to provide a method from a BIM (building information modeling) model to a three-dimensional space semantic model construction in a lossless manner, which classifies data based on attributes and performs semantic description, constructs the incidence relation between attribute information and geometric information, improves the compression ratio of the data, facilitates data transmission, is beneficial to improving rendering efficiency and relieving hardware rendering pressure, and solves the problems of excessive redundant geometric information, high data rendering difficulty, data transmission difficulty and pure geometry and attribute separation.
In order to achieve the purpose, the invention provides the following technical scheme: a method of losslessly building a three-dimensional spatial semantic model from a BIM model, comprising the steps of:
step 1: classifying data based on attribute types to obtain multi-class model data, and performing semantic description on the model data to obtain target semantic description data;
step 2: performing semantic description on the model data to obtain first semantic description information, wherein the first semantic description information comprises geometric features and coordinate features, and performing deduplication on the first semantic description information with the same geometric features to obtain second semantic description information;
and step 3: converting the second semantic description information into specific semantic data and metadata to obtain target semantic description data;
and 4, step 4: storing the target semantic description data, the three-dimensional spatial relationship features and the target texture map in a server cache region;
and 5: generating three-dimensional space visualization models corresponding to the preset use ranges of the three-dimensional space data by utilizing the target semantic description data, and generating the three-dimensional space visualization models corresponding to the preset use ranges of the three-dimensional space data and the environment parameters;
step 6: based on modeling demand information, determining target semantic description data and three-dimensional spatial relationship features corresponding to the modeling demand information from the target semantic description data and the three-dimensional spatial relationship features obtained by using the BIM model data generation method;
and 7: matching the target dynamic geometric reconstruction rule base, and obtaining different three-dimensional spatial relationships and combinations under different model precision levels based on the three-dimensional spatial relationship characteristics corresponding to the modeling demand information;
and 8: and determining target semantic description corresponding to the modeling demand information from the target semantic description data and the three-dimensional spatial relationship characteristics based on the modeling demand information received from the opposite end.
Preferably, in step 1, the target semantic description data is used for characterizing geometric features and coordinate features of the model data; aiming at the coordinate characteristics, obtaining three-dimensional space relationship characteristics of the model data based on the geometric topological relationship among the model data; and storing the target semantic description data and the three-dimensional spatial relationship characteristics.
Preferably, in step 2, the model data includes a first texture map, and the generating method further includes: compressing the first texture map to obtain a target texture map: and storing the target texture map.
Preferably, after storing the target semantic description data and the three-dimensional spatial relationship feature in step 4, the generating method further includes: and establishing a relation index between the target semantic description data and the attribute type, and storing the relation index.
Preferably, in step 5, the method is specifically configured to calculate modified target three-dimensional space data according to the three-dimensional space data, and a preset data modification algorithm; and generating a three-dimensional space visualization model corresponding to the preset use range according to the target three-dimensional space data.
Preferably, in step 6, a target dynamic geometric reconstruction rule base is used to perform geometric reconstruction on the target semantic description data and the three-dimensional spatial relationship characteristics corresponding to the modeling demand information to obtain a geometric component, and the geometric component is converted into a target format.
Preferably, the using a target dynamic geometric reconstruction rule base to perform geometric reconstruction on the target semantic description data and the three-dimensional spatial relationship features corresponding to the modeling demand information to obtain a geometric component includes: and obtaining geometric description information based on the target semantic description data corresponding to the modeling demand information.
Preferably, in step 7, the combination is updated based on a target texture map, where the target texture map is obtained by compressing a first texture map in the model data: normal data of the model are defined, and the geometric member is obtained based on the geometric description information, the model and the normal data.
Preferably, the size of the preset use range, the size and the position of each object in the preset use range, and the position of the target smart device in the preset use range.
Preferably, in step 8, the geometric component is cached in a data caching manner, so that the acquisition rate is improved, meanwhile, the required generated geometric component is directly acquired through an open interface, so that the workload of a user is reduced, and based on the modeling demand information, the format of the geometric component is converted into a user demand format, and the geometric component is rendered to obtain the required target BIM model.
Compared with the prior art, the invention has the beneficial effects that: the invention solves the problems of excessive redundant geometric information, high data rendering difficulty, difficult data transmission and pure geometric and attribute separation by setting multiple types of model data, and the method for building the three-dimensional space semantic model from the BIM model in a lossless manner has the advantages of classifying the data based on attributes, carrying out semantic description, building the incidence relation between the attribute information and the geometric information, improving the data compression ratio, facilitating data transmission, contributing to improving the rendering efficiency and relieving the hardware rendering pressure.
Detailed Description
The present invention will now be described in more detail by way of examples, which are given by way of illustration only and are not intended to limit the scope of the present invention in any way.
The invention provides a technical scheme that: a method of losslessly building a three-dimensional spatial semantic model from a BIM model, comprising the steps of:
step 1: classifying data based on attribute types to obtain multi-class model data, and performing semantic description on the model data to obtain target semantic description data;
step 2: performing semantic description on the model data to obtain first semantic description information, wherein the first semantic description information comprises geometric features and coordinate features, and performing deduplication on the first semantic description information with the same geometric features to obtain second semantic description information;
and step 3: converting the second semantic description information into specific semantic data and metadata to obtain target semantic description data;
and 4, step 4: storing the target semantic description data, the three-dimensional spatial relationship features and the target texture map in a server cache region;
and 5: generating three-dimensional space visualization models corresponding to the preset use ranges of the three-dimensional space data by utilizing the target semantic description data, and generating the three-dimensional space visualization models corresponding to the preset use ranges of the three-dimensional space data and the environment parameters;
step 6: based on modeling demand information, determining target semantic description data and three-dimensional spatial relationship features corresponding to the modeling demand information from the target semantic description data and the three-dimensional spatial relationship features obtained by using the BIM model data generation method;
and 7: matching the target dynamic geometric reconstruction rule base, and obtaining different three-dimensional spatial relationships and combinations under different model precision levels based on the three-dimensional spatial relationship characteristics corresponding to the modeling demand information;
and 8: and determining target semantic description corresponding to the modeling demand information from the target semantic description data and the three-dimensional spatial relationship characteristics based on the modeling demand information received from the opposite end.
The first embodiment is as follows:
classifying data based on attribute types to obtain multi-class model data, and performing semantic description on the model data to obtain target semantic description data; performing semantic description on the model data to obtain first semantic description information, wherein the first semantic description information comprises geometric features and coordinate features, and performing deduplication on the first semantic description information with the same geometric features to obtain second semantic description information; converting the second semantic description information into specific semantic data and metadata to obtain target semantic description data; storing the target semantic description data, the three-dimensional spatial relationship features and the target texture map in a server cache region; generating three-dimensional space visualization models corresponding to the preset use ranges of the three-dimensional space data by utilizing the target semantic description data, and generating the three-dimensional space visualization models corresponding to the preset use ranges of the three-dimensional space data and the environment parameters; based on modeling demand information, determining target semantic description data and three-dimensional spatial relationship features corresponding to the modeling demand information from the target semantic description data and the three-dimensional spatial relationship features obtained by using the BIM model data generation method; matching the target dynamic geometric reconstruction rule base, and obtaining different three-dimensional spatial relationships and combinations under different model precision levels based on the three-dimensional spatial relationship characteristics corresponding to the modeling demand information; and determining target semantic description corresponding to the modeling demand information from the target semantic description data and the three-dimensional spatial relationship characteristics based on the modeling demand information received from the opposite end.
Example two:
classifying data based on attribute types to obtain multi-class model data, and performing semantic description on the model data to obtain target semantic description data; the target semantic description data is used for representing the geometric features and the coordinate features of the model data; aiming at the coordinate characteristics, obtaining three-dimensional space relationship characteristics of the model data based on the geometric topological relationship among the model data; storing the target semantic description data and the three-dimensional spatial relationship characteristics, performing semantic description on the model data to obtain first semantic description information, wherein the first semantic description information comprises geometric characteristics and coordinate characteristics, and performing duplication removal on the first semantic description information with the same geometric characteristics to obtain second semantic description information; the model data comprises a first texture map, and the generation method further comprises: compressing the first texture map to obtain a target texture map: storing the target texture map, and converting the second semantic description information into specific semantic data and metadata to obtain target semantic description data; storing the target semantic description data, the three-dimensional spatial relationship features and the target texture map in a server cache region; generating three-dimensional space visualization models corresponding to the preset use ranges of the three-dimensional space data by utilizing the target semantic description data, and generating the three-dimensional space visualization models corresponding to the preset use ranges of the three-dimensional space data and the environment parameters; based on modeling demand information, determining target semantic description data and three-dimensional spatial relationship features corresponding to the modeling demand information from the target semantic description data and the three-dimensional spatial relationship features obtained by using the BIM model data generation method; matching the target dynamic geometric reconstruction rule base, and obtaining different three-dimensional spatial relationships and combinations under different model precision levels based on the three-dimensional spatial relationship characteristics corresponding to the modeling demand information; and determining target semantic description corresponding to the modeling demand information from the target semantic description data and the three-dimensional spatial relationship characteristics based on the modeling demand information received from the opposite end.
Example three:
classifying data based on attribute types to obtain multi-class model data, and performing semantic description on the model data to obtain target semantic description data; the target semantic description data is used for representing the geometric features and the coordinate features of the model data; aiming at the coordinate characteristics, obtaining three-dimensional space relationship characteristics of the model data based on the geometric topological relationship among the model data; storing the target semantic description data and the three-dimensional spatial relationship characteristics, performing semantic description on the model data to obtain first semantic description information, wherein the first semantic description information comprises geometric characteristics and coordinate characteristics, and performing duplication removal on the first semantic description information with the same geometric characteristics to obtain second semantic description information; the model data comprises a first texture map, and the generation method further comprises: compressing the first texture map to obtain a target texture map: storing the target texture map, and converting the second semantic description information into specific semantic data and metadata to obtain target semantic description data; storing the target semantic description data, the three-dimensional spatial relationship features and the target texture map in a server cache region; after storing the target semantic description data and the three-dimensional spatial relationship feature, the generating method further includes: establishing a relation index between the target semantic description data and the attribute type, storing the relation index, generating a three-dimensional space visualization model corresponding to the preset use range of the three-dimensional space data by using the target semantic description data, and generating a three-dimensional space visualization model corresponding to the preset use range of the three-dimensional space data and the environment parameter; the system comprises a data processing unit, a data processing unit and a data processing unit, wherein the data processing unit is specifically used for calculating corrected target three-dimensional space data according to the three-dimensional space data, the three-dimensional space data and a preset data correction algorithm; generating a three-dimensional space visualization model corresponding to the preset use range according to the target three-dimensional space data, and determining target semantic description data and three-dimensional space relation characteristics corresponding to modeling demand information from the target semantic description data and the three-dimensional space relation characteristics obtained by using the BIM model data generation method based on modeling demand information; matching the target dynamic geometric reconstruction rule base, and obtaining different three-dimensional spatial relationships and combinations under different model precision levels based on the three-dimensional spatial relationship characteristics corresponding to the modeling demand information; and determining target semantic description corresponding to the modeling demand information from the target semantic description data and the three-dimensional spatial relationship characteristics based on the modeling demand information received from the opposite end.
Example four:
classifying data based on attribute types to obtain multi-class model data, and performing semantic description on the model data to obtain target semantic description data; the target semantic description data is used for representing the geometric features and the coordinate features of the model data; aiming at the coordinate characteristics, obtaining three-dimensional space relationship characteristics of the model data based on the geometric topological relationship among the model data; storing the target semantic description data and the three-dimensional spatial relationship characteristics, performing semantic description on the model data to obtain first semantic description information, wherein the first semantic description information comprises geometric characteristics and coordinate characteristics, and performing duplication removal on the first semantic description information with the same geometric characteristics to obtain second semantic description information; the model data comprises a first texture map, and the generation method further comprises: compressing the first texture map to obtain a target texture map: storing the target texture map, and converting the second semantic description information into specific semantic data and metadata to obtain target semantic description data; storing the target semantic description data, the three-dimensional spatial relationship features and the target texture map in a server cache region; after storing the target semantic description data and the three-dimensional spatial relationship feature, the generating method further includes: establishing a relation index between the target semantic description data and the attribute type, storing the relation index, generating a three-dimensional space visualization model corresponding to the preset use range of the three-dimensional space data by using the target semantic description data, and generating a three-dimensional space visualization model corresponding to the preset use range of the three-dimensional space data and the environment parameter; the system comprises a data processing unit, a data processing unit and a data processing unit, wherein the data processing unit is specifically used for calculating corrected target three-dimensional space data according to the three-dimensional space data, the three-dimensional space data and a preset data correction algorithm; generating a three-dimensional space visualization model corresponding to the preset use range according to the target three-dimensional space data, and determining target semantic description data and three-dimensional space relation characteristics corresponding to modeling demand information from the target semantic description data and the three-dimensional space relation characteristics obtained by using the BIM model data generation method based on modeling demand information; using a target dynamic geometric reconstruction rule base to perform geometric reconstruction on target semantic description data and three-dimensional spatial relationship characteristics corresponding to the modeling demand information to obtain a geometric component, converting the geometric component into a target format, and using the target dynamic geometric reconstruction rule base to perform geometric reconstruction on the target semantic description data and the three-dimensional spatial relationship characteristics corresponding to the modeling demand information to obtain the geometric component, wherein the method comprises the following steps: obtaining geometric description information based on target semantic description data corresponding to the modeling demand information, matching the target dynamic geometric reconstruction rule base, and obtaining different three-dimensional spatial relationships and combinations under different model precision levels based on three-dimensional spatial relationship characteristics corresponding to the modeling demand information; updating the combination based on a target texture map, wherein the target texture map is obtained by compressing a first texture map in the model data: the method comprises the steps of defining normal data of a model, obtaining the geometric component based on the geometric description information, the model and the normal data, determining a target semantic description corresponding to modeling demand information from target semantic description data and three-dimensional spatial relationship characteristics based on modeling demand information received from an opposite end, caching the geometric component in a data caching mode according to the target semantic description corresponding to the modeling demand information, improving the obtaining rate, directly obtaining the needed generated geometric component through an open interface, reducing the workload of a user, performing format conversion on the geometric component based on the modeling demand information, converting the format into a user demand format, and rendering to obtain the needed target BIM model.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (10)
1. A method for lossless construction of a three-dimensional spatial semantic model from a BIM model, characterized by: the method comprises the following steps:
step 1: classifying data based on attribute types to obtain multi-class model data, and performing semantic description on the model data to obtain target semantic description data;
step 2: performing semantic description on the model data to obtain first semantic description information, wherein the first semantic description information comprises geometric features and coordinate features, and performing deduplication on the first semantic description information with the same geometric features to obtain second semantic description information;
and step 3: converting the second semantic description information into specific semantic data and metadata to obtain target semantic description data;
and 4, step 4: storing the target semantic description data, the three-dimensional spatial relationship features and the target texture map in a server cache region;
and 5: generating three-dimensional space visualization models corresponding to the preset use ranges of the three-dimensional space data by utilizing the target semantic description data, and generating the three-dimensional space visualization models corresponding to the preset use ranges of the three-dimensional space data and the environment parameters;
step 6: based on modeling demand information, determining target semantic description data and three-dimensional spatial relationship features corresponding to the modeling demand information from the target semantic description data and the three-dimensional spatial relationship features obtained by using the BIM model data generation method;
and 7: matching the target dynamic geometric reconstruction rule base, and obtaining different three-dimensional spatial relationships and combinations under different model precision levels based on the three-dimensional spatial relationship characteristics corresponding to the modeling demand information;
and 8: and determining target semantic description corresponding to the modeling demand information from the target semantic description data and the three-dimensional spatial relationship characteristics based on the modeling demand information received from the opposite end.
2. The method of claim 1, comprising lossless transformation of BIM into semantic models of three-dimensional space, wherein: in step 1, the target semantic description data is used for characterizing geometric features and coordinate features of the model data; aiming at the coordinate characteristics, obtaining three-dimensional space relationship characteristics of the model data based on the geometric topological relationship among the model data; and storing the target semantic description data and the three-dimensional spatial relationship characteristics.
3. The method of claim 1, comprising lossless transformation of BIM into semantic models of three-dimensional space, wherein: in step 2, the model data includes a first texture map, and the generating method further includes: compressing the first texture map to obtain a target texture map: and storing the target texture map.
4. The method of claim 1, comprising lossless transformation of BIM into semantic models of three-dimensional space, wherein: after storing the target semantic description data and the three-dimensional spatial relationship feature in step 4, the generating method further includes: and establishing a relation index between the target semantic description data and the attribute type, and storing the relation index.
5. The method of claim 1, comprising lossless transformation of BIM into semantic models of three-dimensional space, wherein: in the step 5, the target three-dimensional space data after correction is calculated according to the three-dimensional space data, and a preset data correction algorithm; and generating a three-dimensional space visualization model corresponding to the preset use range according to the target three-dimensional space data.
6. The method of claim 1, comprising lossless transformation of BIM into semantic models of three-dimensional space, wherein: in step 6, a target dynamic geometric reconstruction rule base is used to perform geometric reconstruction on the target semantic description data and the three-dimensional spatial relationship characteristics corresponding to the modeling demand information to obtain a geometric component, and the geometric component is converted into a target format.
7. The method of claim 1, comprising lossless transformation of BIM into semantic models of three-dimensional space, wherein: the using of the target dynamic geometric reconstruction rule base to perform geometric reconstruction on the target semantic description data and the three-dimensional spatial relationship characteristics corresponding to the modeling demand information to obtain a geometric component includes: and obtaining geometric description information based on the target semantic description data corresponding to the modeling demand information.
8. The method of claim 1, comprising lossless transformation of BIM into semantic models of three-dimensional space, wherein: in step 7, the combination is updated based on the target texture map, where the target texture map is obtained by compressing the first texture map in the model data: normal data of the model are defined, and the geometric member is obtained based on the geometric description information, the model and the normal data.
9. The method of claim 1, comprising lossless transformation of BIM into semantic models of three-dimensional space, wherein: the size of the preset use range, the size and the position of each object in the preset use range, and the position of the target intelligent device in the preset use range.
10. The method of claim 1, comprising lossless transformation of BIM into semantic models of three-dimensional space, wherein: in step 8, the geometric component is cached in a data caching manner, so that the acquisition rate is improved, meanwhile, the required generated geometric component is directly acquired through the open interface, the workload of a user is reduced, format conversion is performed on the geometric component based on modeling demand information so as to convert the geometric component into a user demand format, and a required target BIM model is obtained through rendering.
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