Fabricated building component integrated manufacturing and construction method based on BIM and 3D printing

Abstract

The invention discloses an integrated manufacturing and construction method for fabricated building components based on BIM and 3D printing, and relates to the field of building construction, and the integrated manufacturing and construction method comprises a model creation module, a component splitting module, a printing path planning module, a material preparation module, a printing manufacturing module, a component transportation and storage module, a site construction module, a simulation analysis module and a quality tracing module. Creating a three-dimensional model by using BIM software, and reviewing by using VR; splitting the components according to capabilities, and recording the components by using a block chain; a 3D printing path is planned, and dynamic adjustment is conducted in combination with sensing; preparing an intelligent material, and performing plasma activation pretreatment; multi-nozzle collaborative printing and holographic monitoring are realized; intelligent packaging, unmanned driving and intelligent storage are achieved; aR auxiliary construction is combined with a brain-computer interface; and through simulation analysis and quality tracing, the quality and efficiency are guaranteed. According to the method, model creation is accurate, and multi-technology optimization components are split, printed, transported and constructed; the intelligent material, the robot and the AR are used for improving the quality efficiency; simulation analysis and quality tracing guarantee reliability, and intelligentization and sustainable development of buildings are promoted.

Description

Technical Field

[0001] The present invention relates to the technical field of building construction, and in particular to an integrated manufacturing and construction method for prefabricated building components based on BIM and 3D printing. Background Art

[0002] In the process of the continuous development of the construction industry, traditional building methods face many problems that need to be solved urgently. Traditional building construction relies on a large amount of manpower, not only with high labor intensity, but also difficult to improve construction efficiency, resulting in generally long construction periods for building projects and difficult to meet the large demand for buildings in the rapid urbanization process. At the same time, there are many human factors in the construction process, and it is difficult to control the quality, and the quality is prone to unevenness, bringing potential safety hazards to the safety and durability of buildings.

[0003] In terms of resource utilization, the waste of building materials in traditional building methods is relatively serious. In the on-site construction process, there is a lack of precise planning and control in the cutting, processing and other links of materials, resulting in a large amount of remaining materials that cannot be effectively utilized. Moreover, the amount of construction waste generated by traditional buildings is huge, causing serious pollution and damage to the environment. In addition, the energy consumption in the traditional building construction process is also high, which does not conform to the current concept of sustainable development.

[0004] As an emerging building model, prefabricated buildings provide new ideas for solving the above problems. It prefabricates building components in the factory and then transports them to the site for assembly, which can effectively improve construction efficiency, reduce labor costs, and reduce the generation of construction waste. However, at present, prefabricated buildings still face some challenges in the development process. In terms of component manufacturing, traditional manufacturing processes are difficult to meet the high-precision requirements of complex components, and the quality monitoring in the production process is not perfect enough, and problems such as component size deviation and unstable quality are prone to occur. In the construction link, the transportation and on-site assembly of components require precise coordination and planning, otherwise installation errors and construction schedule delays are likely to occur.

[0005] The emergence of Building Information Modeling (BIM) technology has brought a transformative impact on the construction industry. It creates a three-dimensional digital model of a building, integrates various information throughout the building life cycle, enables information sharing and collaborative work among all participating parties, and improves the efficiency and quality of building design and construction. However, at present, the application of BIM technology in prefabricated buildings is not deep enough, mainly concentrated in the visual display and collision detection in the design stage, and there is still a large room for improvement in the real-time data interaction and dynamic management in the component manufacturing and construction processes.

[0006] As an advanced manufacturing technology, 3D printing technology has a high degree of flexibility and customization ability, and can manufacture components with complex shapes. However, there are still some technical problems in the application of 3D printing technology in the construction field, such as the performance of printing materials, printing speed and accuracy, and the stability of printing equipment. Moreover, the integration of 3D printing technology with prefabricated buildings and BIM technology is still in its infancy, lacking a complete set of integrated manufacturing and construction methods.

[0007] In summary, it is of great practical significance to develop an integrated manufacturing and construction method for prefabricated building components based on BIM and 3D printing. This method can give full play to the information management advantages of BIM technology, the manufacturing advantages of 3D printing technology, and the construction advantages of prefabricated buildings, solve the problems existing in traditional buildings and existing prefabricated buildings, and promote the development of the construction industry towards the direction of intelligence, greenness and high efficiency. Summary of the Invention

[0008] The integrated manufacturing and construction method for prefabricated building components based on BIM and 3D printing proposed by the present invention is to solve the problems mentioned in the above prior art.

[0009] In order to achieve the above object, the present invention adopts the following technical solutions: An integrated manufacturing and construction method for prefabricated building components based on BIM and 3D printing, including:

[0010] BIM model creation step: Use BIM software with integrated multi-source heterogeneous data fusion to create a three-dimensional information model of the building, integrate geographic information system data, laser scanning data, and incorporate Internet of Things real-time monitoring data, specifically the temperature, humidity, and wind data at the construction site, as well as the raw material quality fluctuation data provided by building material suppliers;

[0011] Component splitting step: According to the construction process, transportation conditions, and the operation range and capabilities of new intelligent assembly robots, split the building in the BIM model into multiple prefabricated components; Use blockchain technology to record the decisions and data during the splitting process, and monitor the traceability and immutability of the splitting plan;

[0012] 3D printing path planning step: According to the split component model, use a combined genetic algorithm, ant colony algorithm, and hybrid intelligent algorithm to plan the 3D printing path; Introduce quantum sensors to real-time monitor the microscopic physical parameters of the printing environment, and combine historical printing data and real-time environmental parameters to dynamically adjust the printing path through quantum machine learning algorithms;

[0013] Material preparation step: According to the material property requirements of the components, prepare intelligent self-healing 3D printing materials, preprocess the materials, and use plasma activation technology to evaluate the activity and bonding performance of the materials;

[0014] 3D printing manufacturing steps: According to the planned path, use 3D printing equipment to manufacture prefabricated building components, adopt multi-nozzle collaborative printing technology, and use holographic projection monitoring technology to monitor printing parameters in real time;

[0015] Component transportation and storage steps: Intelligently package the printed components, and use driverless transport vehicles and intelligent warehousing management systems for component transportation and storage. The vehicle and the warehousing system interact data with the BIM model in real time through the 5G network;

[0016] On-site construction steps: According to the construction progress plan of the BIM model, use intelligent assembly robots and augmented reality technology on-site to assist construction workers in assembling and connecting components.

[0017] Furthermore, it also includes:

[0018] Simulation analysis steps: After the BIM model is created, conduct mechanical property simulation analysis of the building structure based on the quantum Monte Carlo method, synchronously conduct digital twin simulation of the construction process, and provide real-time feedback of actual construction data; Adopt a simulation result and actual deviation evaluation formula considering uncertainty factors Evaluate the design and construction plans, is the simulation result, is the actual result, U factor is the uncertainty factor influence index, λ is the uncertainty coefficient, and n is the number of analysis indicators.

[0019] Furthermore, it also includes:

[0020] Quality traceability steps: Each prefabricated building component is given a QR code and an electronic tag based on quantum encryption technology to record the full life cycle information of the component; Adopt an information integrity evaluation formula based on blockchain and quantum hash algorithm Complete traceability, is the number of completely recorded information, is the total number of information to be recorded, Q hash is the quantum hash verification index, and μ is the hash influence coefficient.

[0021] Furthermore, the BIM model creation step adopts multi-source data fusion technology, integrates geographic information system data, laser scanning data, and Internet of Things real-time monitoring data, and introduces building historical data and cultural heritage data; Adopt a data fusion accuracy evaluation formula based on quantum neural network Evaluate the accuracy of model creation, is the amount of fused and matched data, is the total amount of data, Q nn is the quantum neural network fusion effect index, v is the neural network influence coefficient, and n is the number of data types.

[0022] Furthermore, the printing path planning step introduces an artificial intelligence algorithm to dynamically adjust the printing path by combining historical printing data, real-time environmental parameters, and real-time mechanical performance feedback of the component; and adopts a path dynamic adjustment adaptability evaluation formula based on reinforcement learning and quantum annealing algorithms Evaluate the adjustment effect, is the number of successful adjustments, is the total number of adjustments, Q anneal is the optimization effect index of the quantum annealing algorithm, ξ is the annealing influence coefficient, and m is the number of adjustment stages.

[0023] Furthermore, the 3D printing manufacturing step adopts a multi-nozzle collaborative printing technology, and the nozzles adaptively adjust the material extrusion speed and direction, and perform printing according to different parts of the component and the real-time stress distribution; and uses a nozzle collaborative efficiency evaluation formula based on quantum entanglement state synchronization Evaluate the collaborative effect, is the actual printing volume of the multi-nozzle collaboration, is the maximum printing volume of a single nozzle, Q sync is the quantum entanglement state synchronization effect index, ω is the synchronization influence coefficient, and p is the number of printing time periods.

[0024] Furthermore, the on-site construction step uses augmented reality technology to assist construction workers in installing and connecting components, and adopts a construction accuracy evaluation formula based on brain-computer interface and AR technology Evaluate the assistance effect, is the number of component connection points correctly installed with the assistance of AR, is the total number of component connection points, B inter face is the brain-computer interface interaction effect index, ρ is the interface influence coefficient, and q is the number of construction stages.

[0025] Furthermore, it also includes:

[0026] BIM model creation module: Use BIM software that integrates multi-source heterogeneous data fusion, incorporate Internet of Things and historical and cultural data, use VR review, and adopt a model accuracy evaluation formula optimized by quantum computing (where is the actual component size, is the component size in the model, S i is the sensitivity coefficient of the i-th component affected by the environment and materials, α is the sensitivity adjustment coefficient, and n is the number of components) to ensure the model accuracy;

[0027] Component splitting module: Split in combination with the capabilities of intelligent assembly robots, record with blockchain, optimize the plan with formulas considering time and resources, and use a splitting rationality evaluation formula considering time cost and resource utilization rate (where is the optimal splitting cost, is the actual splitting cost, T j is the time required for the j-th splitting scheme, β is the time cost coefficient, and m is the number of splitting schemes) to optimize the splitting scheme;

[0028] 3D printing path planning module: Use a hybrid intelligent algorithm, combine quantum sensing and machine learning for dynamic adjustment, and adopt a path efficiency evaluation formula considering environmental adaptability (where L shortest is the shortest theoretical path length, L planned is the planned path length, E env is the influence factor of the environment on the printing path, and γ is the environmental influence coefficient) to improve the printing efficiency;

[0029] Material preparation module: Prepare intelligent self-healing materials, use plasma activation pretreatment, and apply a material quality evaluation formula considering the long-term stability of materials (where M qualified is the quality of qualified materials, M total is the total material quality, S long-term is the long-term stability index of the material, and δ is the stability coefficient) to ensure the material quality;

[0030] 3D printing manufacturing module: Adopt multi-material, multi-scale, multi-nozzle cooperation and quantum communication synchronous printing, holographic monitoring, and use a parameter stability evaluation formula based on the principle of quantum entanglement (where is the set parameter value, is the actual parameter value, Q entanglement is the quantum entanglement influence factor, ∈ is the entanglement influence coefficient, and p is the number of monitoring times) to ensure the printing quality;

[0031] Component transportation and storage module: Intelligent packaging, use unmanned driving and intelligent warehousing, and apply a transportation cost and risk evaluation formula considering transportation flexibility and warehousing space utilization rate C r =α×C transport +β×R risk +ζ×F flexibility +η×U space (where C transport is the transportation cost, R risk is the transportation risk, F flexibility is the transportation flexibility index, U space is the warehousing space utilization rate, and α, β, ζ, η are weight coefficients) to optimize the transportation plan;

[0032] On-site construction module: With the assistance of intelligent robots and AR, combined with brain-computer interfaces, intelligent assembly robots have the ability of autonomous learning and adaptive adjustment, and can optimize assembly actions according to the actual on-site situation. A construction quality assessment formula based on blockchain and digital twin technology is adopted. (where is the number of correctly installed component connection points, is the total number of component connection points, D twin is the similarity index between the digital twin model and the actual construction, θ is the similarity coefficient, and q is the number of construction stages) to ensure construction quality.

[0033] Furthermore, it also includes:

[0034] Simulation analysis module: Using quantum Monte Carlo and digital twin simulations, optimize the design and construction plans through formulas;

[0035] Quality traceability module: Using quantum encryption tags to record the whole life cycle information, and achieving traceability based on blockchain and quantum hash formulas.

[0036] Furthermore, it also includes:

[0037] Data management module: Adopting quantum encryption technology to store and manage various types of data in the entire manufacturing and construction process, and evaluating data security through a data security assessment formula based on quantum key distribution to evaluate data security, is the amount of securely stored data, is the total amount of data, Q key is the quantum key distribution effect index, and τ is the key influence coefficient.

[0038] Compared with the existing technologies, the beneficial effects of the present invention are:

[0039] In the design stage, by integrating multi-source heterogeneous data to create a BIM model, not only integrating geographical, laser scanning, Internet of Things and other data, but also incorporating historical and cultural data, making the model more accurate and distinctive. Using the accuracy assessment formula optimized by VR review and quantum computing to discover problems in advance and ensure the high precision of the model, laying a solid foundation for subsequent work.

[0040] In the component splitting link, combined with the capabilities of intelligent assembly robots, using blockchain records and an evaluation formula considering time resources to optimize the splitting plan, improving operability and efficiency, and reducing costs. The 3D printing path planning adopts a hybrid intelligent algorithm, combined with quantum sensing and machine learning, to dynamically adjust the path according to the real-time environment and component mechanical properties, improving printing efficiency and quality.

[0041] Material preparation uses intelligent self-healing materials and plasma activation pretreatment to improve material properties and quality, and ensure the long-term stability of components. 3D printing manufacturing adopts multi-material, multi-scale, multi-nozzle collaborative and quantum communication synchronous printing, and holographic monitoring and quantum entanglement evaluation formulas to ensure printing quality and accuracy.

[0042] Component transportation and storage adopt intelligent packaging, driverless and intelligent warehousing, combined with an evaluation formula considering flexibility and space utilization rate to optimize the transportation plan and reduce transportation risks and costs. On-site construction uses intelligent robots and AR assistance, combined with a brain-computer interface, and through an evaluation formula based on blockchain and digital twin to ensure construction quality and efficiency.

[0043] The simulation analysis module uses quantum Monte Carlo and digital twin simulations to optimize the plan considering uncertainties; the quality traceability module uses quantum encryption tags and blockchain technology to ensure information traceability. The data management module adopts quantum encryption, error correction codes and search algorithms to ensure data security and support decision-making.

[0044] Generally speaking, the method and system of this patent improve the quality and safety of buildings, reduce costs and construction periods, reduce resource waste and environmental pollution, and promote the intelligent and sustainable development of the construction industry. Description of the Drawings

[0045] Figure 1 It is a schematic block diagram of an integrated manufacturing and construction method for prefabricated building components based on BIM and 3D printing proposed by the present invention;

[0046] Figure 2 It is a schematic block diagram of an integrated manufacturing and construction system for prefabricated building components based on BIM and 3D printing proposed by the present invention. Detailed Embodiments

[0047] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the protection scope of the present invention.

[0048] In the description of the present invention, it should be understood that the orientation or positional relationship indicated by terms such as "center", "longitudinal", "transverse", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", etc. is based on the orientation or positional relationship shown in the drawings, and is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be construed as a limitation to the present invention.

[0049] In addition, the terms "first" and "second" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include one or more of the said features. In the description of the present invention, "a plurality of" means two or more unless otherwise specifically defined. In addition, the terms "mounted", "connected", "coupled" should be understood in a broad sense. For example, it may be a fixed connection, a detachable connection, or an integral connection; it may be a mechanical connection, an electrical connection; it may be directly connected, or indirectly connected through an intermediate medium, and it may be the communication inside two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific situations. The present invention will be further described in detail below with reference to the drawings.

[0050] Refer to Figure 1-2 : An integrated manufacturing and construction method for prefabricated building components based on BIM and 3D printing, comprising:

[0051] BIM model creation step: Use professional BIM software with integrated multi-source heterogeneous data fusion to create a three-dimensional information model of the building. In addition to integrating geographic information system (GIS) data and laser scanning data, real-time Internet of Things monitoring data is also incorporated, such as environmental data such as temperature, humidity, and wind force at the construction site, as well as raw material quality fluctuation data provided by building material suppliers. Use a model accuracy evaluation formula optimized by quantum computing (where is the actual component size, is the component size in the model, S i is the sensitivity coefficient of the i-th component affected by the environment and materials, α is the sensitivity adjustment coefficient, and n is the number of components) to ensure the model accuracy. At the same time, use virtual reality (VR) technology to conduct immersive review of the model, enabling the design team and construction personnel to discover potential problems in the virtual environment in advance.

[0052] Component splitting steps: According to the construction technology, transportation conditions, and the operation range and capabilities of the new intelligent assembly robot, the building in the BIM model is split into multiple prefabricated components. The blockchain technology is used to record all decisions and data during the splitting process to ensure the traceability and immutability of the splitting plan. A splitting rationality evaluation formula considering time cost and resource utilization rate is used (where is the optimal splitting cost, is the actual splitting cost, T j is the time required for the j-th splitting plan, β is the time cost coefficient, and m is the number of splitting plans) to optimize the splitting plan.

[0053] 3D printing path planning steps: Based on the split component model, a hybrid intelligent algorithm combining the advantages of genetic algorithm and ant colony algorithm is used to plan the 3D printing path. At the same time, quantum sensors are introduced to real-time monitor the microscopic physical parameters of the printing environment, such as electromagnetic field changes, microscopic particle movements, etc., and combined with historical printing data and real-time environmental parameters, the printing path is dynamically adjusted through quantum machine learning algorithm. A path efficiency evaluation formula considering environmental adaptability is used (where L shortest is the shortest theoretical path length, L planned is the planned path length, E env is the influence factor of the environment on the printing path, and γ is the environmental influence coefficient) to improve the printing efficiency.

[0054] Material preparation steps: According to the material property requirements of the components, 3D printing materials with intelligent self-healing function are prepared. These materials contain nano-level repair particles at the microscopic level. When tiny cracks appear in the components, the repair particles will automatically polymerize and fill the cracks under specific conditions. When preprocessing the materials, plasma activation technology is used to improve the activity and bonding performance of the materials. A material quality evaluation formula considering the long-term stability of the materials is used (where M qualified is the qualified material quality, M total is the total material quality, S long-term is the long-term stability index of the materials, and δ is the stability coefficient) to ensure the material quality.

[0055] 3D printing manufacturing steps: According to the planned path, a 3D printing device with multi-material and multi-scale printing capabilities is used to manufacture prefabricated building components. The multi-nozzle collaborative printing technology is adopted, and the nozzles achieve real-time precise synchronization through quantum communication technology to improve the printing efficiency. During the printing process, holographic projection monitoring technology is used to real-time monitor the printing parameters, such as temperature, pressure, etc., and a parameter stability evaluation formula based on the principle of quantum entanglement is used (where is the set parameter value, is the actual parameter value, Q entanglement is the quantum entanglement influence factor, ∈ is the entanglement influence coefficient, and p is the number of monitoring times) to ensure printing quality.

[0056] Component transportation and storage steps: Intelligently package the printed components. The packaging material uses degradable intelligent materials that can monitor the transportation status of the components in real time, such as vibration, impact, etc. Use driverless transport vehicles and intelligent warehouse management systems for component transportation and storage. The vehicle and the warehouse system interact data with the BIM model in real time through the 5G network. Use the transportation cost and risk assessment formula C r = α × C transport + β × R risk + ζ × F flexibility + η × U space (where C transport is the transportation cost, R risk is the transportation risk, F flexibility is the transportation flexibility index, U space is the warehouse space utilization rate, and α, β, ζ, η are weight coefficients) to optimize the transportation plan.

[0057] On-site construction steps: According to the construction progress plan of the BIM model, use intelligent assembly robots and augmented reality (AR) technology on-site to assist construction workers in assembling and connecting components. The intelligent assembly robot has the ability of autonomous learning and adaptive adjustment, and can optimize the assembly actions according to the actual on-site situation. Use the construction quality assessment formula based on blockchain and digital twin technology (where is the number of correctly installed component connection points, is the total number of component connection points, D twin is the similarity index between the digital twin model and the actual construction, θ is the similarity coefficient, and q is the number of construction stages) to ensure construction quality.

[0058] In the present invention, the following step blocks are further included:

[0059] Simulation analysis steps: After the BIM model is created, perform mechanical property simulation analysis of the building structure based on the quantum Monte Carlo method, which can more accurately consider the microscopic structure and uncertainty factors of the material. At the same time, perform digital twin simulation of the construction process, and continuously optimize the simulation model by real-time feedback of actual construction data. Use the simulation result and actual deviation assessment formula considering uncertainty factors (where is the simulation result, is the actual result, U factor is the uncertainty factor influence index, λ is the uncertainty coefficient, and n is the number of analysis indexes) to optimize the design and construction plans.

[0060] In the present invention, the following step blocks are further included:

[0061] Quality traceability step: Assign a unique QR code or electronic tag based on quantum encryption technology to each prefabricated building component, and record the full life cycle information of the component, including raw material procurement, each process parameter during the manufacturing process, environmental data during transportation, operation records during installation, etc. Use an information integrity evaluation formula based on blockchain and quantum hashing algorithm (where is the number of completely recorded information, is the total number of information to be recorded, Q hash is the quantum hashing verification index, μ is the hashing influence coefficient) to ensure information traceability.

[0062] In the present invention, the BIM model creation step adopts a multi-source data fusion technology. In addition to integrating geographic information system (GIS) data, laser scanning data, and Internet of Things real-time monitoring data, building historical data and cultural heritage data are also introduced to make the model more regionally characteristic and culturally connotative. Use a data fusion accuracy evaluation formula based on quantum neural network (where is the amount of fused and matched data, is the total amount of data, Q nn is the quantum neural network fusion effect index, v is the neural network influence coefficient, n is the number of data types) to improve the accuracy of model creation.

[0063] In the present invention, the printing path planning step introduces an artificial intelligence algorithm, combines historical printing data, real-time environmental parameters, and real-time mechanical performance feedback of the component, and dynamically adjusts the printing path. Use a path dynamic adjustment adaptability evaluation formula based on reinforcement learning and quantum annealing algorithm (where is the number of successful adjustments, is the total number of adjustments, Q anneal is the quantum annealing algorithm optimization effect index, ξ is the annealing influence coefficient, m is the number of adjustment stages) to evaluate the adjustment effect.

[0064] In the present invention, the 3D printing manufacturing step adopts a multi-nozzle collaborative printing technology. The nozzle has the ability to adaptively adjust the material extrusion speed and direction, and can perform precise printing according to different parts of the component and the real-time stress distribution. Use a nozzle collaborative efficiency evaluation formula based on quantum entanglement state synchronization (where is the actual printing volume of multi-nozzle collaboration, is the maximum printing volume of a single nozzle, Q syncis the quantum entanglement state synchronization effect index, ω is the synchronization influence coefficient, and p is the number of printing time periods) to evaluate the collaborative effect.

[0065] In the present invention, the on-site construction steps use augmented reality (AR) technology to assist construction workers in installing and connecting components. The AR device is deeply integrated with the intelligent assembly robot, and the construction workers can obtain the operation status of the robot and the installation position information of the components in real time through the AR device. An evaluation formula for construction accuracy based on the brain-computer interface and AR technology is adopted (where is the number of correctly installed component connection points assisted by AR, is the total number of component connection points, and B interface is the brain-computer interface interaction effect index, ρ is the interface influence coefficient, and q is the number of construction stages) to evaluate the assistance effect.

[0066] The present invention also discloses an integrated manufacturing and construction system for prefabricated building components based on BIM and 3D printing, including the following modules:

[0067] BIM model creation module: Using professional BIM software that integrates multi-source heterogeneous data fusion, integrating data such as the Internet of Things and historical culture, using VR review, and using a quantum computing optimization formula to ensure accuracy.

[0068] Component splitting module: Split in combination with the capabilities of the intelligent assembly robot, record with blockchain, and optimize the plan with a formula considering time and resources.

[0069] 3D printing path planning module: Using a hybrid intelligent algorithm, dynamically adjusting in combination with quantum sensing and machine learning, and evaluating efficiency with a formula considering the environment.

[0070] Material preparation module: Prepare intelligent self-healing materials, perform plasma activation pretreatment, and evaluate quality with a formula considering long-term stability.

[0071] 3D printing manufacturing module: Adopt multi-material multi-scale, multi-nozzle cooperation and quantum communication synchronous printing, holographic monitoring, and use a quantum entanglement formula to ensure quality.

[0072] Component transportation and storage module: Intelligent packaging, using driverless and intelligent warehousing, and optimizing the plan with a formula considering flexibility and space utilization rate.

[0073] On-site construction module: Using intelligent robots and AR assistance, combined with the brain-computer interface, and ensuring quality with a formula based on blockchain and digital twin

[0074] In the present invention, the following modules are also included:

[0075] Simulation analysis module: Using quantum Monte Carlo and digital twin simulations, and optimizing the design and construction plans with a formula considering uncertainty.

[0076] Quality traceability module: uses quantum encryption tags to record information throughout the life cycle, and uses blockchain and quantum hash formulas to ensure traceability.

[0077] In the present invention, the following modules are further included:

[0078] Data management module: uses quantum encryption technology to store and manage various types of data during the entire manufacturing and construction process, and uses quantum error correction codes to improve the reliability of data storage. Uses a data security evaluation formula based on quantum key distribution (where is the amount of data stored securely, is the total amount of data, Q key is the quantum key distribution effect index, and τ is the key influence coefficient) to evaluate data security, and at the same time provides functions such as data query, statistics, and analysis based on quantum search algorithms to support decision-making.

[0079] The above is only a preferred specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention, according to the technical solution and inventive concept of the present invention, makes equivalent substitutions or changes, and should be covered by the protection scope of the present invention.

Claims

1. An integrated manufacturing and construction method for prefabricated building components based on BIM and 3D printing, characterized in that: include: BIM model creation steps: Use integrated multi-source heterogeneous data fusion BIM software to create a three-dimensional information model of the building, integrate geographic information system data, laser scanning data, and integrate real-time monitoring data from the Internet of Things, specifically temperature, humidity, and wind data at the construction site, as well as raw material quality fluctuation data provided by building material suppliers; Component splitting steps: split the building in the BIM model into multiple prefabricated components based on the construction process, transportation conditions, and the operating range and capabilities of the new intelligent assembly robot; use blockchain technology to record decisions and data during the splitting process, and monitor the traceability and immutability of the splitting plan; 3D printing path planning steps: According to the split component model, the 3D printing path is planned by combining genetic algorithm, ant colony algorithm and hybrid intelligent algorithm; Introducing quantum sensors to monitor the microscopic physical parameters of the printing environment in real time, combining historical printing data and real-time environmental parameters, and dynamically adjusting the printing path through quantum machine learning algorithms; Material preparation steps: Prepare intelligent self-healing 3D printing materials according to the material property requirements of the components, pre-treat the materials, and use plasma activation technology to evaluate the activity and bonding properties of the materials; 3D printing manufacturing steps: according to the planned path, use 3D printing equipment to manufacture prefabricated building components, adopt multi-nozzle collaborative printing technology, and use holographic projection monitoring technology to monitor printing parameters in real time; Component transportation and storage steps: Intelligent packaging of printed components, use of unmanned transport vehicles and intelligent warehouse management systems for component transportation and storage, with vehicles and warehouse systems exchanging data with BIM models in real time through 5G networks; On-site construction steps: According to the construction schedule of the BIM model, intelligent assembly robots and augmented reality technology are used on-site to assist construction workers in assembling and connecting components.

2. The integrated manufacturing and construction method of prefabricated building components based on BIM and 3D printing according to claim 1 is characterized in that: Also includes: Simulation analysis steps: After the BIM model is created, the mechanical properties of the building structure are simulated and analyzed based on the quantum Monte Carlo method, and the digital twin simulation of the construction process is carried out simultaneously to provide real-time feedback of actual construction data; the simulation results and actual deviation evaluation formula that considers uncertainty factors are used Evaluate design and construction options, For the simulation results, For the actual result, U factor is the uncertainty factor affecting the index, λ is the uncertainty coefficient, and n is the number of analysis indicators.

3. The integrated manufacturing and construction method of prefabricated building components based on BIM and 3D printing according to claim 1 is characterized in that: Also includes: Quality traceability steps: Each prefabricated building component is given a QR code and electronic tag based on quantum encryption technology to record the full life cycle information of the component; Adopt information integrity assessment formula based on blockchain and quantum hash algorithm Complete traceability, is the number of complete recorded messages, is the total amount of information to be recorded, Q hash is the quantum hash verification indicator, and μ is the hash influence coefficient.

4. The integrated manufacturing and construction method of prefabricated building components based on BIM and 3D printing according to claim 1, characterized in that: The BIM model creation process uses multi-source data fusion technology to integrate geographic information system data, laser scanning data, and real-time monitoring data from the Internet of Things, and introduces architectural history data and cultural heritage data; it uses a data fusion accuracy evaluation formula based on quantum neural networks Evaluate the accuracy of model creation, is the amount of fusion matching data, is the total amount of data, Q nn is the quantum neural network fusion effect index, v is the neural network influence coefficient, and n is the number of data types.

5. The integrated manufacturing and construction method of prefabricated building components based on BIM and 3D printing according to claim 1, characterized in that: The printing path planning step introduces an artificial intelligence algorithm, which dynamically adjusts the printing path by combining historical printing data, real-time environmental parameters, and real-time mechanical performance feedback of components; a dynamic path adjustment adaptability evaluation formula based on reinforcement learning and quantum annealing algorithm is used Evaluate the effect of adjustments. To adjust the number of successes, is the total number of adjustments, Q anneal is the optimization effect index of the quantum annealing algorithm, ξ is the annealing influence coefficient, and m is the number of adjustment stages.

6. The integrated manufacturing and construction method of prefabricated building components based on BIM and 3D printing according to claim 1, characterized in that: The 3D printing manufacturing process uses multi-nozzle collaborative printing technology. The nozzles adaptively adjust the material extrusion speed and direction, and print according to the different parts of the component and the real-time stress distribution; the nozzle collaborative efficiency evaluation formula based on quantum entangled state synchronization is used Evaluate synergistic effects, The actual printing volume of multiple nozzles is coordinated. Q is the maximum printing volume of a single nozzle, sync is the quantum entangled state synchronization effect index, ω is the synchronization influence coefficient, and p is the number of printing time periods.

7. The integrated manufacturing and construction method of prefabricated building components based on BIM and 3D printing according to claim 1, characterized in that: The on-site construction steps use augmented reality technology to assist construction workers in the installation and connection of components, and adopt a construction accuracy evaluation formula based on brain-computer interface and AR technology. Evaluate the auxiliary effect, F l ar-correct is the number of component connection points that are correctly installed with the assistance of AR, is the total number of component connection points, B interface is the brain-computer interface interaction effect index, ρ is the interface influence coefficient, and q is the number of construction stages.

8. A system for implementing the integrated manufacturing and construction method of prefabricated building components based on BIM and 3D printing according to any one of claims 1 to 7, characterized in that: Includes the following modules: BIM model creation module: using BIM software that integrates multi-source heterogeneous data, integrating the Internet of Things and historical and cultural data, using VR for review, and using quantum computing to optimize the model accuracy evaluation formula Evaluate model accuracy, is the actual component size, is the size of the component in the model, S i is the sensitivity coefficient of the i-th component affected by the environment and materials, α is the sensitivity adjustment coefficient, and n is the number of components; Component splitting module: Combine the splitting of intelligent assembly robot capabilities, record with blockchain, consider time and resources to use formula optimization plan, and use the splitting rationality evaluation formula considering time cost and resource utilization Optimize the splitting plan. is the optimal splitting cost, is the actual split cost, T j is the time required for the jth splitting scheme, β is the time cost coefficient, and m is the number of splitting schemes; 3D printing path planning module: using hybrid intelligent algorithms, combined with quantum sensing and machine learning for dynamic adjustment, and adopting a path efficiency evaluation formula that takes environmental adaptability into account Evaluate printing performance, L shortest is the shortest theoretical path length, L planned is the planning path length, E env is the environmental impact factor on the printing path, γ is the environmental impact coefficient; Material preparation module: prepare smart self-healing materials, pre-treat with plasma activation, and apply material quality assessment formulas that take into account the long-term stability of the material Assessing material quality, M qualified For qualified material quality, M total is the total material mass, S long-term is the long-term stability index of the material, and δ is the stability coefficient; 3D printing manufacturing module: adopts multi-material, multi-scale, multi-nozzle coordination and quantum communication synchronous printing, holographic monitoring, and parameter stability evaluation formula based on quantum entanglement principle Evaluate print quality, To set the parameter value, is the actual parameter value, Q entanglement is the quantum entanglement influence factor, ∈ is the entanglement influence coefficient, and p is the number of monitoring times; Component transportation and storage module: intelligent packaging, unmanned driving and intelligent warehousing, and the use of transportation cost and risk assessment formula C that takes into account transportation flexibility and storage space utilization r =α×C transport +β×R risk +ζ×F flexibility +η×U space Optimize transportation plan, C transport is the transportation cost, R risk F is the transportation risk, flexibility is the transport flexibility index, U space is the utilization rate of storage space, α, β, ζ, η are weight coefficients; On-site construction module: Using intelligent robots and AR assistance, combined with brain-computer interfaces, intelligent assembly robots can learn and adjust autonomously, optimize assembly actions according to actual on-site conditions, and adopt construction quality evaluation formulas based on blockchain and digital twin technology. Assess construction quality, The number of component connection points for correct installation, is the total number of component connection points, D twin is the similarity index between the digital twin model and the actual construction, θ is the similarity coefficient, and q is the number of construction stages.

9. The integrated manufacturing and construction system for prefabricated building components based on BIM and 3D printing according to claim 8, characterized in that: Also includes: Simulation analysis module: uses quantum Monte Carlo and digital twin simulation to optimize design and construction plans through formulas; Quality traceability module: Use quantum encryption tags to record information on the entire life cycle, and use blockchain and quantum hash formulas to achieve traceability.

10. The integrated manufacturing and construction system for prefabricated building components based on BIM and 3D printing according to claim 8, characterized in that: Also includes: Data management module: Use quantum encryption technology to store and manage all kinds of data in the entire manufacturing and construction process, and use the data security assessment formula based on quantum key distribution Assess data security, The amount of data to be stored safely, is the total data volume, Qkey is the quantum key distribution effect index, and τ is the key influence coefficient.

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