Fabricated building component intelligent matching and construction optimization method based on BIM

Abstract

The invention discloses a BIM-based fabricated building component intelligent matching and construction optimization method, relates to the technical field of fabricated building construction, and aims to solve the problem that the prior art lacks consideration of dynamic change factors of a construction site, and the method comprises the following steps: S1, establishing a BIM information model, and based on a fabricated building design drawing, establishing a BIM information model; building a three-dimensional information model including building structures, component geometric dimensions, material attributes and connection mode information by using BIM software, establishing a component database, and inputting related information of each component into the database; s2, dynamic information of the construction site is obtained, and environment information, construction equipment state information, constructor information and construction progress information of the construction site are obtained in real time through multiple sensors and a construction management system deployed on the construction site. The method has the advantage that construction optimization is carried out according to the dynamic change factors of the construction site.

Description

Technical Field

[0001] The present invention relates to the technical field of prefabricated building construction, and more specifically, to a method for intelligent matching and construction optimization of prefabricated building components based on BIM. Background Art

[0002] In the process of modernization of the construction industry, prefabricated buildings have become an important direction of industry development due to their advantages of high efficiency, environmental protection, and controllable quality. BIM technology, as the core tool of digital construction, realizes data integration and collaborative management of the entire life cycle of buildings by constructing three-dimensional information models. Its application in the field of prefabricated buildings has reached a certain scale.

[0003] However, in existing prefabricated building construction, although BIM technology has been widely used in component design and construction planning, its intelligent component matching and construction optimization often rely on static databases and preset rules, lacking consideration of dynamic factors such as weather, equipment status, and construction personnel scheduling. This leads to inefficient component matching and is prone to problems such as delayed component supply and installation conflicts during construction, which affect construction progress and quality and increase construction costs. In view of this, we propose a BIM-based method for intelligent component matching and construction optimization in prefabricated buildings. Summary of the Invention

[0004] The purpose of the present invention is to provide a BIM-based intelligent matching and construction optimization method for prefabricated building components, aiming to solve the problem that the existing technology lacks consideration of dynamic changing factors on the construction site.

[0005] To solve the above technical problems, the present invention provides the following technical solution: a BIM-based intelligent matching and construction optimization method for prefabricated building components, the method comprising the following steps: S1. Establish a BIM information model. Based on the prefabricated building design drawings, use BIM software to construct a three-dimensional information model containing building structure, component geometry, material properties, and connection method information. Establish a component database and enter the relevant information of each component into the database; S2. Obtain dynamic information of the construction site. Through the multi-sensor and construction management system deployed at the construction site, the environmental information of the construction site, the status information of construction equipment, the information of construction personnel and the construction progress information are obtained in real time. S3, intelligent component matching: Integrate and analyze the component information in the BIM information model with the acquired construction site dynamic information. Then, based on the intelligent matching algorithm, the assembly building components are intelligently matched to determine the optimal component combination and installation sequence required for each construction stage, taking into account the component installation sequence, installation location, connection relationship with other components, environmental conditions at the construction site, equipment status, and construction personnel arrangement factors. S4, construction plan optimization, based on the component combination and installation sequence obtained by intelligent matching, combined with the dynamic information of the construction site, uses optimization algorithms to optimize the construction plan, including construction schedule arrangement, construction equipment scheduling, and construction personnel allocation; S5. Construction process monitoring and adjustment. During the construction process, the dynamic information of the construction site is continuously monitored in real time, and the actual construction situation is compared and analyzed with the optimized construction plan. When deviations are found between the actual situation and the construction plan, the intelligent matching of components and the optimization of the construction plan are promptly re-performed according to the new dynamic information, and the construction process is adjusted.

[0006] Preferably, in the above step S1, the component is uniquely coded, and the code includes the type, specification, production batch, and installation location information of the component.

[0007] Preferably, in the above step S3, the algorithm formula of the intelligent matching algorithm is: , where Indicates the The construction phase and The matching degree of the components, is the foundation matching coefficient determined according to the construction stage and component type, For the The construction phase, The component in The scores under the influencing factors, For the The influencing factors are The construction phase, The dynamic weights in component matching are adjusted according to the real-time data of the construction site. For the The correction coefficients of the constraints are determined by studying and training a large amount of historical prefabricated building construction data to determine the values ​​of each coefficient and optimize the algorithm model.

[0008] Preferably, in the above step S4, the optimization algorithm adopts a multi-objective particle swarm optimization algorithm, and its optimization objective function formula is: , where To comprehensively optimize the target value, For construction plan The expected construction period, and are the minimum and maximum values ​​of the construction period, respectively. For construction plan The estimated cost of and are the minimum and maximum costs, respectively. For construction plan The estimated quality score of and are the minimum and maximum values ​​of the quality score, 、 、 The weight coefficient corresponding to the target is dynamically adjusted according to the actual needs of the project, and various constraints are comprehensively considered to generate the optimal construction plan.

[0009] Preferably, in the above step S5, it also includes setting an early warning threshold. When the dynamic information of the construction site exceeds the early warning threshold, an early warning signal is issued in time to trigger the process of re-conducting intelligent component matching and construction plan optimization.

[0010] Preferably, it also includes establishing a construction knowledge base, and storing the experience accumulated during each construction process and the optimized construction plan in the construction knowledge base.

[0011] Preferably, in the above step S5, the transportation cost and transportation time of the components are also taken into consideration, and component suppliers that are close to the construction site and have good transportation conditions are given priority.

[0012] Preferably, in the above step S2, blockchain technology is used to encrypt, store and transmit data collected by multiple sensors to ensure the integrity and security of the data.

[0013] Compared with the prior art, the present invention has the following beneficial effects: 1. The present invention obtains the environmental information, construction equipment status information, construction personnel information and construction progress information of the construction site in real time, and based on the intelligent matching algorithm, comprehensively considers the installation sequence, installation position, connection relationship with other components, environmental conditions of the construction site, equipment status and construction personnel arrangement factors of the components, and performs intelligent matching of prefabricated building components. At the same time, it continuously monitors the dynamic information of the construction site in real time. When it is found that the actual situation deviates from the construction plan, it promptly re-performs intelligent component matching and construction plan optimization based on the new dynamic information, thereby fully considering the dynamic changing factors of the construction site, improving the component matching efficiency, reducing the occurrence of problems such as untimely component supply and installation conflicts, thereby ensuring construction progress and quality and reducing construction costs.

[0014] 2. In the process of optimizing the construction plan, the present invention adopts a multi-objective particle swarm optimization algorithm, takes the construction period, cost and quality as the optimization objectives, dynamically adjusts the weight coefficient of each objective, comprehensively considers various constraints, and generates the optimal construction plan. It can shorten the construction period and reduce the cost to the greatest extent while ensuring the construction quality, realize the multi-objective optimization of the construction plan, and improve the scientificity and rationality of the construction plan.

[0015] 3. The present invention establishes a clear component identification system by uniquely encoding the components, which includes information such as the component type, specification, production batch, and installation location. This facilitates accurate identification and management of components in various links such as production, transportation, storage, and installation, improves the accuracy and efficiency of component management, and lays a good foundation for subsequent intelligent component matching and construction optimization. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 Schematic diagram of the process of the present invention. DETAILED DESCRIPTION

[0017] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0018] Example 1 A BIM-based intelligent matching and construction optimization method for prefabricated building components, the method comprising the following steps: S1. Establish a BIM information model. Based on the prefabricated building design drawings, use BIM software to construct a three-dimensional information model containing the building structure, component geometry, material properties, and connection methods. Establish a component database and enter the relevant information of each component into the database. Use the three-dimensional BIM model to achieve visualization and digital integration of component information. The component database provides standardized data support for subsequent matching and construction, ensuring information consistency in all links. S2. Acquire dynamic information on the construction site. Through the multi-sensor and construction management system deployed at the construction site, obtain real-time information on the construction site environment, construction equipment status, construction personnel, and construction progress. Real-time dynamic data collection makes the construction status transparent, provides a real-time basis for intelligent matching and solution optimization, and improves the timeliness of construction management. S3, intelligent component matching, integrates and analyzes the component information in the BIM information model with the acquired dynamic information of the construction site. Then, based on the intelligent matching algorithm, it comprehensively considers the installation sequence, installation location, connection relationship with other components, environmental conditions of the construction site, equipment status, and construction personnel arrangement factors of the components to intelligently match the prefabricated building components and determine the optimal component combination and installation sequence required for each construction stage. The intelligent matching algorithm achieves precise adaptation of components to the construction scene, avoids construction delays caused by component mismatch, and optimizes resource allocation efficiency. S4. Construction plan optimization: Based on the component combination and installation sequence obtained by intelligent matching, combined with the dynamic information of the construction site, the construction plan is optimized using an optimization algorithm, including construction schedule scheduling, construction equipment scheduling, and construction personnel allocation. The optimization algorithm balances the construction period, cost, and quality goals to generate a scientific and reasonable construction plan, thereby improving construction efficiency and economy. S5. Construction process monitoring and adjustment. During the construction process, the dynamic information of the construction site is continuously monitored in real time, and the actual construction situation is compared and analyzed with the optimized construction plan. When deviations are found between the actual situation and the construction plan, the components are intelligently matched and the construction plan is optimized in a timely manner according to the new dynamic information, and the construction process is adjusted. The dynamic monitoring and adjustment mechanism ensures that the construction process adapts to changes on site, reduces losses caused by emergencies, and ensures that construction proceeds as planned.

[0019] Furthermore, in the above step S1, the components are uniquely coded, and the code includes the type, specification, production batch, and installation location information of the component. The unique code is used to track the entire life cycle of the component, facilitate rapid positioning and management during construction, avoid component confusion, and improve construction accuracy.

[0020] Furthermore, in the above step S3, the algorithm formula of the intelligent matching algorithm is: , where Indicates the The construction phase and The matching degree of the components, is the foundation matching coefficient determined according to the construction stage and component type, For the The construction phase, The component in The scores under the influencing factors, For the The influencing factors are The construction phase, The dynamic weights in component matching are adjusted according to the real-time data of the construction site. For the The correction coefficients of the constraints are determined by studying and training a large amount of historical prefabricated building construction data to determine the values ​​of each coefficient and optimize the algorithm model.

[0021] Furthermore, in the above step S4, the optimization algorithm adopts the multi-objective particle swarm optimization algorithm, and its optimization objective function formula is: , where To comprehensively optimize the target value, For construction plan The expected construction period, and are the minimum and maximum values ​​of the construction period, respectively. For construction plan The estimated cost of and are the minimum and maximum costs, respectively. For construction plan The estimated quality score of and are the minimum and maximum values ​​of the quality score, 、 、 The weight coefficient corresponding to the target is dynamically adjusted according to the actual needs of the project, and various constraints are comprehensively considered to generate the optimal construction plan.

[0022] Furthermore, in the above step S5, it also includes setting an early warning threshold. When the dynamic information of the construction site exceeds the early warning threshold, an early warning signal is issued in time to trigger the process of re-optimizing the intelligent matching of components and the construction plan. The early warning mechanism is used to identify construction risks in advance, adjust the plan in time, avoid the expansion of problems, and ensure construction safety and progress.

[0023] Furthermore, it also includes establishing a construction knowledge base, storing the experience accumulated during each construction process and the optimized construction plan in the construction knowledge base, accumulating historical data and experience in the knowledge base, providing reference for subsequent projects, realizing knowledge reuse, and improving the efficiency and accuracy of construction optimization.

[0024] Furthermore, in the above step S5, the transportation cost and transportation time of the components are also taken into consideration, and component suppliers that are close to the construction site and have high transportation conditions are given priority, so as to optimize the transportation link to reduce costs, shorten the construction period, improve the supply chain efficiency, and reduce the impact of component transportation on the construction progress.

[0025] Furthermore, in the above step S2, blockchain technology is used to encrypt, store and transmit data collected by multiple sensors to ensure the integrity and security of the data. Blockchain technology is used to ensure that the data cannot be tampered with and is transmitted securely, prevent data forgery or leakage, and improve the credibility and security of construction information.

[0026] The embodiments disclosed in the present invention are preferred embodiments, but are not limited to them. Ordinary technicians in this field can easily understand the spirit of the present invention based on the above embodiments and make different extensions and changes. As long as they do not deviate from the spirit of the present invention, they are all within the scope of protection of the present invention.

Claims

1. A BIM-based intelligent matching and construction optimization method for prefabricated building components, characterized in that: The method comprises the following steps: S1. Establish a BIM information model. Based on the prefabricated building design drawings, use BIM software to construct a three-dimensional information model containing building structure, component geometry, material properties, and connection method information. Establish a component database and enter the relevant information of each component into the database; S2. Obtain dynamic information of the construction site. Through the multi-sensor and construction management system deployed at the construction site, the environmental information of the construction site, the status information of construction equipment, the information of construction personnel and the construction progress information are obtained in real time. S3, intelligent component matching: Integrate and analyze the component information in the BIM information model with the acquired construction site dynamic information. Then, based on the intelligent matching algorithm, the assembly building components are intelligently matched to determine the optimal component combination and installation sequence required for each construction stage, taking into account the component installation sequence, installation location, connection relationship with other components, environmental conditions at the construction site, equipment status, and construction personnel arrangement factors. S4, construction plan optimization, based on the component combination and installation sequence obtained by intelligent matching, combined with the dynamic information of the construction site, uses optimization algorithms to optimize the construction plan, including construction schedule arrangement, construction equipment scheduling, and construction personnel allocation; S5. Construction process monitoring and adjustment. During the construction process, the dynamic information of the construction site is continuously monitored in real time, and the actual construction situation is compared and analyzed with the optimized construction plan. When deviations are found between the actual situation and the construction plan, the intelligent matching of components and the optimization of the construction plan are promptly re-performed according to the new dynamic information, and the construction process is adjusted.

2. A BIM-based intelligent matching and construction optimization method for prefabricated building components according to claim 1, characterized in that: In the above step S1, the component is uniquely coded, and the code includes the type, specification, production batch, and installation location information of the component.

3. The method for intelligent matching and construction optimization of prefabricated building components based on BIM according to claim 1, characterized in that: In the above step S3, the algorithm formula of the intelligent matching algorithm is: , where Indicates the The construction phase and The matching degree of the components, is the foundation matching coefficient determined according to the construction stage and component type, For the The construction phase, The component in The scores under the influencing factors, For the The influencing factors are The construction phase, The dynamic weights in component matching are adjusted according to the real-time data of the construction site. For the The correction coefficients of the constraints are determined by studying and training a large amount of historical prefabricated building construction data to determine the values ​​of each coefficient and optimize the algorithm model.

4. The method for intelligent matching and construction optimization of prefabricated building components based on BIM according to claim 1, characterized in that: In the above step S4, the optimization algorithm adopts a multi-objective particle swarm optimization algorithm, and its optimization objective function formula is: , where To comprehensively optimize the target value, For construction plan The expected construction period, and are the minimum and maximum values ​​of the construction period, For construction plan The estimated cost of and are the minimum and maximum costs, respectively. For construction plan The estimated quality score of and are the minimum and maximum values ​​of the quality score, 、 、 The weight coefficient corresponding to the target is dynamically adjusted according to the actual needs of the project, and various constraints are comprehensively considered to generate the optimal construction plan.

5. The method for intelligent matching and construction optimization of prefabricated building components based on BIM according to claim 1, characterized in that: In the above step S5, it also includes setting an early warning threshold. When the dynamic information of the construction site exceeds the early warning threshold, an early warning signal is issued in time to trigger the process of re-conducting intelligent component matching and construction plan optimization.

6. The BIM-based intelligent matching and construction optimization method for prefabricated building components according to claim 1, characterized in that: It also includes establishing a construction knowledge base to store the experience accumulated during each construction process and the optimized construction plan in the construction knowledge base.

7. The method for intelligent matching and construction optimization of prefabricated building components based on BIM according to claim 1, characterized in that: In the above step S5, the transportation cost and transportation time of the components are also taken into consideration, and component suppliers that are close to the construction site and have good transportation conditions are given priority.

8. The method for intelligent matching and construction optimization of prefabricated building components based on BIM according to claim 1, characterized in that: In the above step S2, blockchain technology is used to encrypt, store and transmit data collected by multiple sensors to ensure the integrity and security of the data.

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