CN115146883A - Management and control method and system for intelligent construction of building engineering - Google Patents
Management and control method and system for intelligent construction of building engineering Download PDFInfo
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Abstract
The invention discloses a control method for intelligent construction of building engineering, which comprises the following steps: s1, acquiring real-time building image data, and constructing a three-dimensional building model based on a real scene; s2, constructing a self-adaptive digital twin model based on the three-dimensional building model; s3, monitoring and predicting a construction site by utilizing the interactivity of the digital twin model; and S4, managing and controlling the construction site according to the preset construction progress and tasks. The invention also discloses a management and control system for the intelligent construction of the building engineering. The invention constructs a high-precision digital twin model fusing the construction engineering data by adopting a high-precision three-dimensional data and scene fusion technology combining land and air, realizes full connection between the construction engineering and an internet database, and comprehensively associates the construction site real-time engineering data with the three-dimensional scene model to form an intelligent construction system capable of realizing remote intelligent supervision, production multi-dimensional data monitoring and engineering task allocation scheduling.
Description
Technical Field
The invention relates to the technical field of constructional engineering, in particular to a management and control method and a management and control system for intelligent construction of constructional engineering.
Background
With the progress of scientific technology and the trend of new and old kinetic energy conversion, the traditional construction industry faces the examination of transformation and upgrading, the traditional construction and management mode cannot meet the current large-scale construction project, and the problems existing in the construction process can be effectively solved through a more scientific and intelligent management mode.
The intelligent construction is a new stage of the information development of modern construction engineering technology, and is to enhance information management and service by using the technology of the Internet of things and the equipment monitoring technology on the basis of digital construction engineering; the controllability of the building process is improved, and a high-efficiency, energy-saving, environment-friendly and environment-comfortable humanized building environment is constructed by combining green intelligent means, intelligent systems and other emerging technologies.
In the prior art, most of constructed digital management platforms mainly manage single sites such as construction sites or delivery sites, cannot form remote and unified comprehensive construction management and control, only manage a certain scene or a certain task, are difficult to realize data interaction among different engineering projects, and do not accord with a green and efficient intelligent construction concept.
An effective solution to the problems in the related art has not been proposed yet.
Disclosure of Invention
The invention provides a management and control method and a management and control system for intelligent building of building engineering, aiming at the problems in the related art and aiming at overcoming the technical problems in the prior related art.
Therefore, the invention adopts the following specific technical scheme:
according to one aspect of the invention, a management and control method for intelligent building of construction engineering is provided, which comprises the following steps:
s1, acquiring real-time building image data, and constructing a three-dimensional building model based on a real scene;
s2, constructing a self-adaptive digital twin model based on the three-dimensional building model;
s3, monitoring and predicting a construction site by utilizing the interactivity of the digital twin model;
and S4, managing and controlling the construction site according to the preset construction progress and tasks.
Further, the acquiring real-time building image data and constructing a three-dimensional building model based on the real scene comprises the following steps:
s11, acquiring color image data and spatial coordinate information of a target building by using an unmanned aerial vehicle image technology and a three-dimensional laser scanning technology;
s12, resolving laser point cloud data by using a PCL point cloud base, and performing a point cloud reconstruction model on the unmanned aerial vehicle image to form a three-dimensional topographic map;
and S13, fusing the three-dimensional topographic map with a pre-designed BIM model to construct a three-dimensional building model.
Further, the building of the adaptive digital twin model based on the three-dimensional building model comprises the following steps:
s21, constructing a basic digital model by associating and fusing building construction data by taking the three-dimensional building model as a carrier;
s22, monitoring a construction site in real time, periodically migrating and synchronizing construction information, and realizing periodic updating of the building construction data;
s23, merging the updated building construction data into the basic digital model to obtain a reconstructed updated self-adaptive digital twin model;
and S24, calculating the association degree between the digital twin model and the actual building engineering based on multiple dimensions, and maintaining to obtain the digital twin model with the association degree meeting the construction requirement.
Further, the building construction data comprises construction progress information, a construction process, three-dimensional building image data, meteorological data, temperature and humidity of a construction site, electromechanical data and constructor management information;
the digital twin model comprises a data storage operation, a quality prediction model and a model base, and the quality prediction model comprises a mechanism model and an algorithm model.
Further, the step of integrating the updated building construction data into the basic digital model to obtain a reconstructed updated adaptive digital twin model includes the following steps:
s231, the basic digital model preferentially performs self-updating of the mechanism model according to updated building construction data;
s232, matching a source model to be reconstructed from the algorithm model;
and S233, reconstructing and updating the digital model according to construction change analysis and corresponding updating strategies of the building engineering to obtain the self-adaptive digital twin model.
Further, the method comprises the following steps of calculating the association degree between the digital twin model and the actual building engineering based on multiple dimensions, maintaining the association degree to obtain the digital twin model with the association degree meeting the requirements, and the method comprises the following steps:
s241, determining a plurality of correlation indexes corresponding to all dimensions;
s242, determining and dividing the relevance grade between the digital twin model and the construction project, and taking the highest grade of the relevance grade as a safety grade;
s243, calculating the correlation index to obtain the correlation degree between the digital twin model and the building engineering;
s244, if the relevance level meets the safety level, judging that the digital twin model meets the construction requirement, and using the digital twin model as a final digital twin model;
and S245, if the relevance degree grade does not meet the safety grade, updating and adding corresponding relevance indexes to update and maintain the digital twin model until the relevance degree meets the safety grade.
Further, the multiple dimensions comprise five dimensions of a building entity, a mathematical model, model parameters, connection interaction and utility value.
Further, the operation of the correlation index to obtain the correlation degree between the digital twin model and the construction engineering includes the following operation steps:
in the formula (I), the compound is shown in the specification,a relevance value representing each relevance index;
represents a single correlation indexiThe relevance rank for promoting a level 1 relevance in the relevanceWeights within the index, and;
the highest level of relevance that can be achieved by a single relevance indexTo increase toAs requirediWhether or not the level of the degree of association is reached, and when the level of the degree of association is reachedWhen it is not reached;
representing a single dimensioniThe relevance grade of each relevance index is used for improving the weight of the relevance grade of 1 level in the dimension, and;
the first step of representing the degree of association grade up grade which can be achieved by all the association indexes in a single dimensioniWhether the relevance grade of each relevance index is reached or not, and when the relevance grade is reachedWhen it is not reached;
representing a single dimensioniThe relevance grade of each relevance index is weighted to promote the relevance grade of grade 1, and;
indicating the first order required to raise the current association level by one leveliWhether the relevance grade of each relevance index is reached or not, and when the relevance grade is reachedWhen it is not reached;
iA number indicating a correlation index.
According to another aspect of the invention, a management and control system for building engineering intelligent construction comprises the following modules:
the monitoring module is used for monitoring the construction site in real time to obtain engineering image data and building construction data;
the digital twin technical module is used for constructing a digital twin model and carrying out self-adaptive updating, relevance calculation and optimization on the digital twin model;
the supervision and scheduling module is used for carrying out centralized supervision on the construction site of the building engineering and distributing scheduling tasks of all levels;
and the field construction module is used for carrying out actual construction operation on a construction field to complete a construction task.
Furthermore, the monitoring module comprises a video monitoring camera, a strain displacement monitoring sensor for engineering and a temperature and humidity sensor;
the supervision and scheduling module comprises a multilayer structure which is an enterprise level management and control unit, a project level management and control unit and a production level management and control unit respectively.
The invention has the beneficial effects that: by adopting a high-precision three-dimensional data and scene fusion technology combined with the ground, a standard three-dimensional building model is constructed, and a high-precision digital twin model fusing building engineering data is constructed on the basis, so that full connection between the building engineering and an internet database can be realized, that is, the real-time engineering data of a construction site and the three-dimensional scene model are comprehensively associated, thereby forming an intelligent construction system capable of realizing remote intelligent supervision, production multi-dimensional data monitoring and engineering task distribution scheduling, and greatly improving the construction efficiency and the engineering precision of the actual building engineering; in addition, the self-adaptive digital twin model can be automatically reconstructed and updated in time according to construction site feedback data to ensure full connectivity with the construction project, and a correlation evaluation system is constructed to evaluate and calculate the model by adopting multiple correlation indexes, so that high correlation between the digital twin model and the actual construction project can be effectively ensured, and the potential safety hazard of the project due to difference is avoided.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.
FIG. 1 is a flow chart of a method for managing and controlling intelligent construction of a construction project according to the present invention;
fig. 2 is a system block diagram of a management and control system for building engineering intelligent construction according to the present invention.
In the figure:
1. a monitoring module; 2. a digital twinning technology module; 3. a supervision scheduling module; 4. and (5) a field construction module.
Detailed Description
According to an embodiment of the present invention, there is provided a method for managing and controlling intelligent building of a building engineering, as shown in fig. 1, the method includes the following steps:
s1, acquiring real-time building image data, and constructing a three-dimensional building model based on a real scene, wherein the method comprises the following steps:
s11, acquiring color image data and space coordinate information of a target building by using an unmanned aerial vehicle image technology and a three-dimensional laser scanning technology;
s12, resolving laser point cloud data by using a PCL point cloud base, and performing a point cloud reconstruction model on the unmanned aerial vehicle image to form a three-dimensional topographic map;
and S13, fusing the three-dimensional topographic map with a pre-designed BIM model to construct a three-dimensional building model.
S2, constructing an adaptive digital twin model based on the three-dimensional building model,
the digital twin model simulates the behavior and performance of the self in a real environment in real time by constructing a virtual model which completely corresponds and accords with physical entities in the real world.
The step S2 includes the steps of:
s21, constructing a basic digital model by associating and fusing building construction data by taking the three-dimensional building model as a carrier;
s22, monitoring a construction site in real time, periodically migrating and synchronizing construction information, and realizing periodic updating of the building construction data;
s23, integrating the updated building construction data into the basic digital twin model to obtain a reconstructed updated self-adaptive digital twin model;
the construction data comprises construction progress information, a construction process, three-dimensional building image data, meteorological data, construction site temperature and humidity, electromechanical data, constructor management information and the like, and basically covers factors influencing the quality of the building engineering in the whole construction process of the building engineering, so that a comprehensive analysis and supervision digital twin model is constructed.
The digital twin model comprises a data storage operation, a quality prediction model and a model base, and the quality prediction model comprises a mechanism model and an algorithm model.
Wherein, step S23 includes the steps of:
s231, the basic digital model preferentially performs self-updating of the mechanism model according to updated building construction data;
s232, matching a source model to be reconstructed from the algorithm model;
and S233, reconstructing and updating the digital model according to construction change analysis of the building engineering and a corresponding updating strategy to obtain a self-adaptive digital twin model.
In the operation principle of the quality prediction model, the mechanism model extracts the primary characteristics of the updated building construction data, and the algorithm model adopts a deep learning method to carry out deep characteristic extraction and quality prediction on the building construction data. Therefore, in the quality prediction model, the digital twin model is predicted by fusing the mechanism model and the algorithm model, namely when the conditions in the model change, the source model to be reconstructed and updated is obtained from the algorithm model base through characteristic data operation in a matching manner and is subjected to self-adaptive updating, and the data generated by the reconstructed and updated model is stored in the database again to serve as historical data to provide a basis for subsequent model reconstruction and update.
S24, calculating the relevance between the digital twin model and the actual construction project based on multiple dimensions, and maintaining to obtain the digital twin model with the relevance meeting the construction requirement, wherein the method comprises the following steps:
s241, determining a plurality of correlation indexes corresponding to all dimensions;
the multi-dimension comprises five dimensions of a building entity, a mathematical model, model parameters, connection interaction and utility value.
Each dimension has its own associated index for reflecting the characteristics of each dimension. The building entity dimension provides data and foundation related to an actual building body model, so that the dimension has relevance indexes in the aspects of monitoring sensors, data interfaces, control equipment and the like;
the mathematical model dimension shows the description of the building entity through a data technology to realize a high simulation function, so that the dimension adopts multi-angle correlation indexes such as effectiveness, intuition, connectivity, flexibility and the like to show the correlation degree of the model;
the model parameter dimensionality comprises correlation indexes such as compatibility, accessibility and quality, and is used for carrying out parameter embodiment on the digital twin model and further describing the influence of the model on the correlation degree on the aspect of actual parameters;
the connection interaction dimension comprises relevant related indexes such as connection modes, connection objects, connection time delay and the like;
the utility value dimension comprises related indexes such as diversity, integration degree and the like.
S242, determining and dividing the relevance grade between the digital twin model and the construction project, and taking the highest grade of the relevance grade as a safety grade;
in the invention, the relevance grade is divided into five grades which are respectively unqualified, qualified, general, good and safe from low to high, and four grades except the safety grade are defined as unsafe grades, if the result is lower than the safety grade in the calculation process, the unqualified relevance indexes are searched and positioned according to the relevance in the calculation process, and the safety grade in the aspect is improved by changing relevant parameter data, namely the model is maintained and updated.
S243, calculating the correlation index to obtain the correlation degree between the digital twin model and the construction engineering, and the method comprises the following calculation steps:
in the formula (I), the compound is shown in the specification,a relevance value representing each relevance index;
represents a single correlation indexiThe relevance grade is used for improving the weight of the relevance grade of 1 grade in the relevance index, and;
the highest level of relevance that can be achieved by a single relevance indexTo increase toAs required toiWhether the degree of correlation is reached or not, and when the degree of correlation is reachedWhen it is not reached;
representing a single dimensioniThe relevance grade of each relevance index is used for improving the weight of the relevance grade of 1 level in the dimension, and;
the first step of representing the degree of association grade up grade which can be achieved by all the association indexes in a single dimensioniWhether the relevance grade of each relevance index is reached or not, and when the relevance grade is reachedIf not, the time is up;
representing a single dimensioniThe relevance grade of each relevance index is weighted to promote the relevance grade of level 1, and;
indicating the first order required to raise the current association level by one leveliWhether the degree of correlation of each correlation index is reached or not, and when the degree of correlation is reachedWhen it is not reached;
iA number indicating a correlation index.
S244, if the relevance level meets the safety level, judging that the digital twin model meets the construction requirement, and taking the digital twin model as a final digital twin model;
and S245, if the relevance degree grade does not meet the safety grade, updating and adding corresponding relevance indexes to update and maintain the digital twin model until the relevance degree meets the safety grade.
S3, monitoring and predicting a construction site by utilizing the interactivity of the digital twin model;
the interactivity mainly refers to real-time dynamic interaction which can be realized between the virtual three-dimensional model and the building entity object thereof. In the process, the internet of things is used as a core technology for interaction between the virtual and the real. The virtual digital twin model realizes the functions of prediction and optimization through the digitalized function of the model, and then predicts and intervenes the building entity according to the optimization result, namely, transmits the next step instruction or the reference direction to the real world. Similarly, the building working conditions and real-time states of building entities in the real world need to be transmitted to the digital world in time, and finally intelligent construction of building engineering and accurate prediction and optimization of a construction site are achieved through the interaction of the building working conditions and the real-time states.
And S4, managing and controlling the construction site according to the preset construction progress and tasks.
According to another embodiment of the present invention, as shown in fig. 2, there is also provided a management and control system for building engineering intelligent construction, which includes the following modules:
the monitoring module 1 is used for monitoring a construction site in real time to obtain engineering image data and building construction data;
the digital twin technical module 2 is used for constructing a digital twin model and carrying out self-adaptive updating, relevance calculation and optimization on the digital twin model;
the supervision and scheduling module 3 is used for carrying out centralized supervision on the construction site of the building engineering and distributing scheduling tasks of various levels;
and the field construction module 4 is used for carrying out actual construction operation on a construction field and completing construction tasks.
The monitoring module 1 comprises a video monitoring camera, a strain displacement monitoring sensor for engineering and a temperature and humidity sensor;
the supervision and scheduling module 3 comprises a multilayer structure which is an enterprise level management and control unit, a project level management and control unit and a production level management and control unit respectively.
The enterprise-level management and control unit is used for managing and controlling overall macroscopic production progress, production value, safety early warning information and the like; the project level control unit controls specific projects, including meteorological conditions, production output values, material consumption, personnel distribution and the like; the production-level management and control unit is responsible for managing and controlling the multidimensional management of the process, the progress, the quality and the like of a construction site, and the management and control are carried out on the basis of four aspects of the construction process, project management, basic information, sensor monitoring and the like.
In conclusion, by means of the technical scheme, a standard three-dimensional building model is constructed by adopting a ground-air combined high-precision three-dimensional data and scene fusion technology, and a high-precision digital twin model fusing building engineering data is constructed on the basis, so that full connection between the building engineering and an internet database can be realized, namely, real-time engineering data of a construction site is comprehensively associated with the three-dimensional scene model, and thus, an intelligent building system capable of realizing remote intelligent supervision, production multi-dimensional data monitoring and engineering task allocation scheduling is formed, and the construction efficiency and the engineering precision of the actual building engineering are greatly improved; in addition, the self-adaptive digital twin model can be automatically reconstructed and updated in time according to construction site feedback data to ensure full connectivity with the construction project, and a correlation evaluation system is constructed to evaluate and calculate the model by adopting multiple correlation indexes, so that high correlation between the digital twin model and the actual construction project can be effectively ensured, and the potential safety hazard of the project due to difference is avoided.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (10)
1. A management and control method for intelligent building of constructional engineering is characterized by comprising the following steps:
s1, acquiring real-time building image data, and constructing a three-dimensional building model based on a real scene;
s2, constructing a self-adaptive digital twin model based on the three-dimensional building model;
s3, monitoring and predicting a construction site by utilizing the interactivity of the digital twin model;
and S4, managing and controlling the construction site according to the preset construction progress and tasks.
2. The method for controlling intelligent building of architectural engineering according to claim 1, wherein the step of obtaining real-time building image data to construct a three-dimensional building model based on real scenes comprises the following steps:
s11, acquiring color image data and spatial coordinate information of a target building by using an unmanned aerial vehicle image technology and a three-dimensional laser scanning technology;
s12, resolving laser point cloud data by using a PCL point cloud base, and performing a point cloud reconstruction model on the unmanned aerial vehicle image to form a three-dimensional topographic map;
and S13, fusing the three-dimensional topographic map with a pre-designed BIM model to construct a three-dimensional building model.
3. The method for managing and controlling intelligent building engineering according to claim 1, wherein the building of the adaptive digital twin model based on the three-dimensional building model comprises the following steps:
s21, constructing a basic digital model by associating and fusing building construction data by taking the three-dimensional building model as a carrier;
s22, monitoring a construction site in real time, periodically migrating and synchronizing construction information, and realizing periodic updating of the building construction data;
s23, merging the updated building construction data into the basic digital model to obtain a reconstructed updated self-adaptive digital twin model;
and S24, calculating the association degree between the digital twin model and the actual building engineering based on multiple dimensions, and maintaining to obtain the digital twin model with the association degree meeting the construction requirement.
4. The method for managing and controlling the intelligent building of the building engineering according to claim 3, wherein the building construction data comprises construction progress information, construction technology, three-dimensional building image data, meteorological data, temperature and humidity of a construction site, electromechanical data and constructor management information;
the digital twin model comprises a data storage operation, a quality prediction model and a model base, and the quality prediction model comprises a mechanism model and an algorithm model.
5. The method as claimed in claim 4, wherein the step of merging the updated construction data into the basic digital model to obtain a reconstructed updated adaptive digital twin model includes the following steps:
s231, the basic digital model preferentially carries out self-updating of the mechanism model according to the updated building construction data;
s232, matching a source model to be reconstructed from the algorithm model;
and S233, reconstructing and updating the digital model according to construction change analysis and corresponding updating strategies of the building engineering to obtain the self-adaptive digital twin model.
6. The method for managing and controlling intelligent building of building engineering according to claim 5, wherein the method for calculating the association degree between the digital twin model and the actual building engineering based on multiple dimensions and maintaining the digital twin model with the association degree meeting the requirement comprises the following steps:
s241, determining a plurality of correlation indexes corresponding to all dimensions;
s242, determining and dividing the relevance grade between the digital twin model and the building engineering, and taking the highest grade of the relevance grade as a safety grade;
s243, calculating the correlation index to obtain the correlation degree between the digital twin model and the building engineering;
s244, if the relevance level meets the safety level, judging that the digital twin model meets the construction requirement, and taking the digital twin model as a final digital twin model;
and S245, if the association degree grade does not meet the safety grade, updating and adding corresponding association indexes to update and maintain the digital twin model until the association degree grade meets the safety grade.
7. The method as claimed in claim 6, wherein the multiple dimensions include five dimensions of building entity, mathematical model, model parameters, connection interaction and utility value.
8. The method as claimed in claim 7, wherein the calculating the correlation index to obtain the correlation between the digital twin model and the construction project includes the following steps:
in the formula (I), the compound is shown in the specification,a relevance value representing each relevance index;
represents a single correlation indexiThe relevance grade is used for improving the weight of the relevance grade of 1 grade in the relevance index, and;
the highest level of relevance that can be achieved by a single relevance indexTo increase toAs required toiWhether the degree of correlation is reached or not, and when the degree of correlation is reachedWhen it is not reached;
representing a single dimensioniThe relevance grade of each relevance index is used for improving the weight of the relevance grade of the 1 level in the dimension, and;
the first step of representing the level of the relevance grade which can be reached by all the relevance indexes in a single dimension and is required to be improved by one stepiWhether the relevance grade of each relevance index is reached or not, and when the relevance grade is reachedWhen it is not reached;
representing a single dimensioniThe relevance grade of each relevance index is weighted to promote the relevance grade of level 1, and;
indicating the first order required to raise the current association level by one leveliWhether the relevance grade of each relevance index is reached or not, and when the relevance grade is reachedWhen it is not reached;
iA number indicating a correlation index.
9. A management and control system for intelligent construction of building engineering, which is used for executing the management and control method for intelligent construction of building engineering according to any one of claims 1-8, and is characterized in that the system comprises the following modules:
the monitoring module is used for monitoring the construction site in real time to obtain engineering image data and building construction data;
the digital twin technical module is used for constructing a digital twin model and carrying out self-adaptive updating, relevance calculation and optimization on the digital twin model;
the supervision and scheduling module is used for carrying out centralized supervision on the construction site of the building engineering and distributing scheduling tasks of all levels;
and the field construction module is used for carrying out actual construction operation on a construction field to complete a construction task.
10. The system according to claim 9, wherein the monitoring module comprises a video monitoring camera, a strain displacement monitoring sensor for engineering, and a temperature and humidity sensor;
the supervision and scheduling module comprises a multilayer structure which is an enterprise level management and control unit, a project level management and control unit and a production level management and control unit respectively.
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