CN116843107B - Building information intelligent management system based on BIM technology - Google Patents
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Abstract
The application discloses a building information intelligent management system based on BIM technology, which comprises a building information acquisition module and an information format analysis module, and relates to the technical field of information management.
Description
Technical Field
The application relates to the technical field of information management, in particular to a building information intelligent management system based on a BIM technology.
Background
The building construction refers to the production activity of engineering construction implementation stage, is the construction process of various buildings, also can be said to be the process of changing various lines on a design drawing into real objects at a designated place, and the building information model is a new tool of architecture, engineering and civil engineering.
According to the patent display of application number CN202210126099.4, the patent comprises a building information input system, a manual input system, a building model construction system, a setting model system, a building information data analysis system, a management end control system, an administrator information extraction system and a building construction information supervision system, and the application relates to the technical field of building information. According to the building information intelligent management system based on the BIM technology, the building model is formed based on the BIM technology by arranging the building model construction system, the constructed building model outline is supplemented in real time, continuity and intuitiveness of building information monitoring are guaranteed, the building model completion degree can be prompted in real time by matching with the model setting system and the building information data analysis system, parameter information is displayed in real time, supervision and instruction of building information are carried out on a construction unit by matching with the management end control system, and the intellectualization of the building information management system is realized.
When the existing building information management system is used, building information is not well stored reasonably, the existing storage modes are usually stored and displayed according to time sequence, the storage modes are inconvenient for subsequent personnel to read the building information, reasonable distribution is not carried out by combining the characteristics of the building information, and further the condition of data storage confusion is caused.
Disclosure of Invention
Aiming at the defects of the prior art, the application provides a building information intelligent management system based on a BIM technology, which solves the problem that storage confusion can be caused by reasonably distributing and storing building information without combining the characteristics of the building information.
In order to achieve the above purpose, the application is realized by the following technical scheme: building information intelligent management system based on BIM technique includes:
the building information acquisition module is used for acquiring basic information of a target object and transmitting the basic information to the information format analysis module, wherein the target object comprises building information, and the basic information comprises capacity, format type, conversion speed and generation time;
the information format analysis module is used for acquiring and analyzing the transmitted basic information of the target object, analyzing the format type in the basic information, classifying the target object into conversion information and non-conversion information according to whether the target object can be converted into a uniform format, transmitting the conversion information to the format conversion analysis module, and transmitting the non-conversion information to the self-adaptive analysis module;
the format conversion analysis module is used for acquiring and analyzing the transmitted conversion information, carrying out different storage on the conversion information according to the capacity of the converted format, generating corresponding storage information, and transmitting the storage information to the analysis information output module;
the self-adaptive analysis module is used for acquiring and analyzing the transmitted non-conversion information, and obtaining a corresponding non-conversion information classification result by classifying the non-conversion information, wherein the self-adaptive analysis module comprises the following components: the convertible type and the non-convertible type are respectively stored in different modes, corresponding storage information is generated, and the storage information is transmitted to the analysis information output module.
As a further aspect of the application: the specific judging mode of the information format analysis module is as follows:
acquiring all the target objects and the format types corresponding to the target objects, acquiring a unified format, judging the format types of the target objects and the unified format, and marking the target objects as conversion information when the format types of the target objects can be subjected to unified format conversion, otherwise marking the target objects as non-conversion information; what needs to be explained here is: the unified format is expressed as a format which can be identified by the system, and the unified format has the advantage that the information corresponding to the format is a format type which is frequently used by operators.
As a further aspect of the application: the format conversion analysis module specifically analyzes the following modes:
s1: acquiring all conversion information and judging the integrity of the conversion information, marking the corresponding conversion information as defect information when the incomplete data exists in the conversion information, and eliminating the defect information, otherwise marking the corresponding conversion information as complete information when the conversion information is complete, and reserving the complete information;
s2: acquiring all the complete information, classifying the complete information according to format types, acquiring the same type of complete information, acquiring the capacity corresponding to the complete information, sequencing the complete information from small to large, storing the complete information and generating corresponding storage information; what needs to be explained here is: the same type of complete information indicates that the format type is the same between the conversion to the unified format.
S3: then obtaining all incomplete information, obtaining the corresponding capacity of the incomplete information, simultaneously carrying out label processing according to the sequence from small to large, recording as incomplete label information i, wherein i=1, 2, … and n, simultaneously obtaining the reading speed record corresponding to the incomplete label information i as Vi, calculating the average value record of the incomplete label information reading speeds as a reading average value Vp, comparing the reading speed Vi corresponding to the incomplete label information i with the reading average value Vp, classifying the incomplete label information i as quick reading information when Vi is more than or equal to Vp, and otherwise classifying the incomplete label information i as slow reading information when Vi is less than Vp;
s4: all the slow reading information is obtained, two equal parts of the slow reading information are equally divided according to the capacity to generate divided slow reading information, then the divided slow reading information is independently stored to generate corresponding storage information, all the fast reading information is obtained and is directly stored, and corresponding storage information is generated.
As a further aspect of the application: the specific mode of the self-adaptive analysis module for generating the storage information is as follows:
p1: acquiring all non-conversion information and acquiring corresponding conversion speed marks as SD, screening a non-conversion information conversion format corresponding to the conversion speed SD with the fastest conversion speed and marking the conversion format as a non-standard conversion format, simultaneously matching all the non-conversion information with the non-standard conversion format, classifying the corresponding non-conversion information as a convertible type when the non-conversion information can be converted into the non-standard conversion format, and classifying the non-conversion information as a non-convertible type otherwise;
p2: then, all the convertible types are obtained, the corresponding use times are obtained at the same time, the convertible types are classified according to the same types to generate corresponding same type convertible information, and the convertible types are sequenced from near to far according to time and stored to generate corresponding storage information; what needs to be explained here is: by time-near-far it is meant that the current time is used as a node, ordered from near to far from the current time, and then stored.
P3: the method comprises the steps of obtaining all types which cannot be converted, obtaining the type with the highest use times among the types, taking the type as the type to be converted, carrying out conversion matching on all types which cannot be converted, classifying the types into successful conversion information and failed conversion information according to a matching result, and then respectively storing the two types, wherein the specific storage mode is as follows:
p31: acquiring successful conversion information, correspondingly acquiring the capacity of the information, sequencing the information according to the capacity of the information, storing the information at the same time, and generating corresponding storage information;
p32: the method comprises the steps of obtaining failure conversion information, classifying the failure conversion information in the same type, obtaining the reading speed of the failure conversion information in the same type, sequencing and storing the failure conversion information according to the reading speed from large to small, and generating corresponding storage information.
As a further aspect of the application: the analysis information output module is used for acquiring the transmitted storage information and transmitting the storage information to the cloud, and storing the target object according to the transmitted storage information through the cloud.
Advantageous effects
The application provides a building information intelligent management system based on BIM technology. Compared with the prior art, the method has the following beneficial effects:
according to the application, by analyzing the building information, judging whether the conversion of the unified format can be performed or not according to the format of the building information, classifying the building information according to the judging result, and then respectively storing the classified building information, and reasonably storing the capacity, the reading speed and the data integrity, on one hand, the data can be ensured not to be difficult to read due to self reasons when being read, the condition of disordered storage is avoided, and on the other hand, the storage is performed according to the characteristics of the information, so that the subsequent operators can conveniently read, and the time of the operators is saved.
Drawings
FIG. 1 is a block diagram of a system of the present application.
Detailed Description
The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
Referring to fig. 1, the present application provides a building information intelligent management system based on a BIM technology, including:
and the building information acquisition module is used for acquiring basic information of the target object and transmitting the basic information to the information format analysis module, wherein the target object comprises building information, and the basic information comprises capacity, format type, conversion speed and generation time.
The information format analysis module is used for acquiring and analyzing the transmitted basic information of the target object, classifying the target object into conversion information and non-conversion information according to whether the target object can be converted into a uniform format or not by analyzing the format type in the basic information, transmitting the conversion information to the format conversion analysis module, and transmitting the non-conversion information to the self-adaptive analysis module, wherein the specific judgment mode is as follows:
acquiring all the target objects and the format types corresponding to the target objects, acquiring a unified format, judging the format types of the target objects and the unified format, and marking the target objects as conversion information when the format types of the target objects can be subjected to unified format conversion, otherwise marking the target objects as non-conversion information; what needs to be explained here is: the unified format is expressed as a format which can be identified by the system, and the unified format has the advantage that the information corresponding to the format is a format type which is frequently used by operators.
The format conversion analysis module is used for acquiring and analyzing the transmitted conversion information, carrying out different storage on the conversion information according to the capacity of the converted format, generating corresponding storage information, and transmitting the storage information to the analysis information output module, wherein the specific analysis mode is as follows:
s1: acquiring all conversion information and judging the integrity of the conversion information, marking the corresponding conversion information as defect information when the incomplete data exists in the conversion information, and eliminating the defect information, otherwise marking the corresponding conversion information as complete information when the conversion information is complete, and reserving the complete information;
s2: acquiring all the complete information, classifying the complete information according to format types, acquiring the same type of complete information, acquiring the capacity corresponding to the complete information, sequencing the complete information from small to large, storing the complete information and generating corresponding storage information; what needs to be explained here is: the same type of complete information indicates that the format type is the same between the conversion to the unified format.
S3: then obtaining all incomplete information, obtaining the corresponding capacity of the incomplete information, simultaneously carrying out label processing according to the sequence from small to large, recording as incomplete label information i, wherein i=1, 2, … and n, simultaneously obtaining the reading speed record corresponding to the incomplete label information i as Vi, calculating the average value record of the incomplete label information reading speeds as a reading average value Vp, comparing the reading speed Vi corresponding to the incomplete label information i with the reading average value Vp, classifying the incomplete label information i as quick reading information when Vi is more than or equal to Vp, and otherwise classifying the incomplete label information i as slow reading information when Vi is less than Vp;
s4: all the slow reading information is obtained, two equal parts of the slow reading information are equally divided according to the capacity to generate divided slow reading information, then the divided slow reading information is independently stored to generate corresponding storage information, all the fast reading information is obtained and is directly stored, and corresponding storage information is generated.
The analysis information output module is used for acquiring the transmitted storage information and transmitting the storage information to the cloud end, and the storage information is stored through the cloud end.
In the second embodiment, the difference between the second embodiment and the first embodiment is that the information format analysis module analyzes the generated non-converted information.
The self-adaptive analysis module is used for acquiring and analyzing the transmitted non-conversion information, and obtaining a corresponding non-conversion information classification result by classifying the non-conversion information, wherein the self-adaptive analysis module comprises the following components: the convertible type and the non-convertible type are respectively stored in different modes, corresponding storage information is generated, the storage information is transmitted to the analysis information output module, and the specific mode for generating the storage information is as follows:
p1: acquiring all non-conversion information and acquiring corresponding conversion speed marks as SD, screening a non-conversion information conversion format corresponding to the conversion speed SD with the fastest conversion speed and marking the conversion format as a non-standard conversion format, simultaneously matching all the non-conversion information with the non-standard conversion format, classifying the corresponding non-conversion information as a convertible type when the non-conversion information can be converted into the non-standard conversion format, and classifying the non-conversion information as a non-convertible type otherwise;
p2: then, all the convertible types are obtained, the corresponding use times are obtained at the same time, the convertible types are classified according to the same types to generate corresponding same type convertible information, and the convertible types are sequenced from near to far according to time and stored to generate corresponding storage information; what needs to be explained here is: by time-near-far it is meant that the current time is used as a node, ordered from near to far from the current time, and then stored.
P3: the method comprises the steps of obtaining all types which cannot be converted, obtaining the type with the highest use times among the types, taking the type as the type to be converted, carrying out conversion matching on all types which cannot be converted, classifying the types into successful conversion information and failed conversion information according to a matching result, and then respectively storing the two types, wherein the specific storage mode is as follows:
p31: acquiring successful conversion information, correspondingly acquiring the capacity of the information, sequencing the information according to the capacity of the information, storing the information at the same time, and generating corresponding storage information;
p32: the method comprises the steps of obtaining failure conversion information, classifying the failure conversion information in the same type, obtaining the reading speed of the failure conversion information in the same type, sequencing and storing the failure conversion information according to the reading speed from large to small, and generating corresponding storage information.
The analysis information output module is used for acquiring the transmitted storage information, transmitting the storage information to the cloud end, and storing the storage information through the cloud end.
Embodiment III as embodiment III of the present application, the emphasis is on combining the implementation procedures of embodiment I and embodiment II.
Some of the data in the above formulas are numerical calculated by removing their dimensionality, and the contents not described in detail in the present specification are all well known in the prior art.
The above embodiments are only for illustrating the technical method of the present application and not for limiting the same, and it should be understood by those skilled in the art that the technical method of the present application may be modified or substituted without departing from the spirit and scope of the technical method of the present application.
Claims (4)
1. Building information intelligent management system based on BIM technique, characterized by comprising:
the building information acquisition module is used for acquiring basic information of a target object and transmitting the basic information to the information format analysis module, wherein the target object comprises building information, and the basic information comprises capacity, format type, conversion speed and generation time;
the information format analysis module is used for acquiring and analyzing the transmitted basic information of the target object, analyzing the format type in the basic information, classifying the target object into conversion information and non-conversion information according to whether the target object can be converted into a uniform format, transmitting the conversion information to the format conversion analysis module, and transmitting the non-conversion information to the self-adaptive analysis module;
the format conversion analysis module is used for acquiring and analyzing the transmitted conversion information, carrying out different storage on the conversion information according to the capacity of the converted format, generating corresponding storage information, and transmitting the storage information to the analysis information output module;
the self-adaptive analysis module is used for acquiring and analyzing the transmitted non-conversion information, and obtaining a corresponding non-conversion information classification result by classifying the non-conversion information, wherein the self-adaptive analysis module comprises the following components: the type can be converted and the type can not be converted, then the two types are respectively stored in different modes, corresponding stored information is generated, the stored information is transmitted to the analysis information output module, and the specific mode of generating the stored information by the self-adaptive analysis module is as follows:
p1: acquiring all non-conversion information and acquiring corresponding conversion speed marks as SD, screening a non-conversion information conversion format corresponding to the conversion speed SD with the fastest conversion speed and marking the conversion format as a non-standard conversion format, simultaneously matching all the non-conversion information with the non-standard conversion format, classifying the corresponding non-conversion information as a convertible type when the non-conversion information can be converted into the non-standard conversion format, and classifying the non-conversion information as a non-convertible type otherwise;
p2: then, all the convertible types are obtained, the corresponding use times are obtained at the same time, the convertible types are classified according to the same types to generate corresponding same type convertible information, and the convertible types are sequenced from near to far according to time and stored to generate corresponding storage information;
p3: the method comprises the steps of obtaining all types which cannot be converted, obtaining the type with the highest use times among the types, taking the type as the type to be converted, carrying out conversion matching on all types which cannot be converted, classifying the types into successful conversion information and failed conversion information according to a matching result, and then respectively storing the two types, wherein the specific storage mode is as follows:
p31: acquiring successful conversion information, correspondingly acquiring the capacity of the information, sequencing the information according to the capacity of the information, storing the information at the same time, and generating corresponding storage information;
p32: the method comprises the steps of obtaining failure conversion information, classifying the failure conversion information in the same type, obtaining the reading speed of the failure conversion information in the same type, sequencing and storing the failure conversion information according to the reading speed from large to small, and generating corresponding storage information.
2. The building information intelligent management system based on the BIM technology according to claim 1, wherein the specific judging mode of the information format analysis module is as follows:
and acquiring all the target objects and the format types corresponding to the target objects, acquiring a unified format, judging the format types of the target objects and the unified format, and marking the target objects as conversion information when the format types of the target objects can be subjected to unified format conversion, and otherwise marking the target objects as non-conversion information.
3. The building information intelligent management system based on the BIM technology according to claim 1, wherein the specific analysis mode of the format conversion analysis module is as follows:
s1: acquiring all conversion information and judging the integrity of the conversion information, marking the corresponding conversion information as defect information when the incomplete data exists in the conversion information, and eliminating the defect information, otherwise marking the corresponding conversion information as complete information when the conversion information is complete, and reserving the complete information;
s2: acquiring all the complete information, classifying the complete information according to format types, acquiring the same type of complete information, acquiring the capacity corresponding to the complete information, sequencing the complete information from small to large, storing the complete information and generating corresponding storage information;
s3: then obtaining all incomplete information, obtaining the corresponding capacity of the incomplete information, simultaneously carrying out label processing according to the sequence from small to large, recording as incomplete label information i, wherein i=1, 2, … and n, simultaneously obtaining the reading speed record corresponding to the incomplete label information i as Vi, calculating the average value record of the incomplete label information reading speeds as a reading average value Vp, comparing the reading speed Vi corresponding to the incomplete label information i with the reading average value Vp, classifying the incomplete label information i as quick reading information when Vi is more than or equal to Vp, and otherwise classifying the incomplete label information i as slow reading information when Vi is less than Vp;
s4: all the slow reading information is obtained, two equal parts of the slow reading information are equally divided according to the capacity to generate divided slow reading information, then the divided slow reading information is independently stored to generate corresponding storage information, all the fast reading information is obtained and is directly stored, and corresponding storage information is generated.
4. The building information intelligent management system based on the BIM technology according to claim 1, wherein the analysis information output module is used for acquiring the transmitted storage information and transmitting the acquired storage information to the cloud, and storing the target object according to the transmitted storage information through the cloud.
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| CN117078213B (en) * | 2023-10-11 | 2024-03-29 | 潍坊威尔信息技术有限公司 | Building engineering management platform based on big data integration analysis |
| CN118586599A (en) * | 2024-06-19 | 2024-09-03 | 北京毅通信息技术有限公司 | Intelligent analysis system for digital experimental data |
| CN118484741B (en) * | 2024-07-16 | 2024-09-17 | 烟台磐能电气控制系统有限公司 | Data processing intelligent analysis method based on AI algorithm |
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