Green building digital collaborative design and optimization method based on BIM and cloud computing

Abstract

The invention relates to the technical field of green intelligent digital construction, and discloses a green building digital collaborative design and optimization method based on BIM and cloud computing, comprising the following steps: S1, project initialization and data collection, S2, preliminary design and simulation based on BIM, S3, sensor equipment layout and optimization, S4, fault detection and early warning processing, and S5, cloud computing. According to the method, a green intelligent digital construction key process technology is adopted, energy conservation and emission reduction benefits and environment quality improvement benefits generated in the whole life period of a green building technology can be improved, and digital intelligent technologies such as BIM, 5G, IoT, BMS and EMS are adopted, so that the construction period is shortened, and the construction efficiency is improved. Visualization and perceptibility of energy conservation and emission reduction benefits and environment quality improvement benefits generated in the whole life period of the green building technology can be achieved, and economic benefits are generated from the energy conservation and emission reduction benefits generated by the green building technology in a carbon trading mode.

Description

Technical Field

[0001] The present invention relates to the technical field of green intelligent digital construction, and specifically to a green building digital collaborative design and optimization method based on BIM and cloud computing. Background Art

[0002] Green intelligent digital construction is an innovative transformation method in the construction industry under the background of the new era, which integrates the concepts and practices of green construction, intelligent technology, and digital management.

[0003] Green construction refers to the use of environmentally friendly, energy-saving, efficient, and reusable materials and technologies throughout the entire life cycle of a building, from planning, design, construction to operation, to minimize the impact on the environment and improve the utilization efficiency of resources to the greatest extent.

[0004] Intelligent technologies mainly include new generation information technologies such as the Internet of Things (IoT), big data, cloud computing, artificial intelligence (AI), and building information modeling (BIM). The deep integration of these technologies with advanced manufacturing technologies and industrialized construction technologies can significantly improve the industrialization, digitization, and intelligence levels in the design, production, construction, and delivery stages.

[0005] Digital management uses cutting-edge technologies such as the Internet of Things, big data, and cloud computing to achieve in-depth information integration and collaborative management of the entire life cycle of a construction project.

[0006] After retrieval, the patent with the application number CN202410240760.3 discloses a digital intelligent green building design evaluation method, including: obtaining data points corresponding to a building, obtaining a local radius according to the range of each item of data of the building and the number of data points, and during the clustering of all data points, for the clustering domain that needs to be split, obtaining the local density of each data point in the clustering domain according to the local radius, and then obtaining the reference degree of each data point, screening discrete data points, obtaining the comprehensive outlier degree of each discrete data point relative to the nearest clustering domain, re-dividing the discrete data points to obtain outliers and new clustering domains, and through continuous iteration, obtaining the clustering result and the true outliers, and performing a design rating for each building according to the clustering result and the true outliers. The invention excludes the interference of true outliers, the clustering result is more accurate, and the building design rating based on the clustering result is more accurate.

[0007] The current digital monitoring and analysis models for green building design are imperfect and cannot comprehensively and accurately capture and evaluate all the benefits of green buildings in terms of energy conservation and emission reduction and environmental quality improvement; it is difficult to intuitively perceive and quantify the improvement of the quality and quality of green buildings. Therefore, we need to propose a green building digital collaborative design and optimization method based on BIM and cloud computing. Summary of the Invention

[0008] The object of the present invention is to provide a green building digital collaborative design and optimization method based on BIM and cloud computing. By adopting the key process technologies of green intelligent digital construction, it is possible to establish digital monitoring, calculation, and optimization analysis models for the energy conservation and emission reduction benefits and environmental quality improvement benefits generated during the entire life cycle of green building technologies, effectively enhancing the visualization and perceptibility of the green building performance, so as to solve the problems raised in the above background technology.

[0009] To achieve the above object, the present invention provides the following technical solution: A green building digital collaborative design and optimization method based on BIM and cloud computing, comprising the following steps:

[0010] S1. Project initialization and data collection: Determine the project objectives, scope, participants, and role assignments, and use 3D scanning technology to obtain the three-dimensional geometric information of the building, and integrate the obtained data information into the BIM platform;

[0011] S2. Preliminary design and simulation based on BIM: Establish a BIM model, perform performance simulation on the BIM model, and then adjust and optimize the design scheme according to the simulation results;

[0012] S3. Sensor device layout and optimization: Analyze the energy consumption situation inside the building and accurately allocate the number of sensor devices;

[0013] S4. Fault detection and early warning processing: Mark the fault information of energy-consuming equipment, identify the fault characteristics, and send out early warning information in a timely manner;

[0014] S5. Digital management during the construction stage: Use VR / AR technology to simulate the construction process of low-carbon materials and overlay digital information at the construction site;

[0015] S6. Digital management during the operation stage: Real-time monitor the energy consumption and environmental quality of the building, and establish digital monitoring, calculation, and optimization analysis models to evaluate and optimize the energy conservation and emission reduction benefits and environmental quality improvement benefits generated during the entire life cycle of green building technologies.

[0016] Preferably, in step S1, in addition to obtaining the three-dimensional geometric model of the building, external data around the building also needs to be obtained. The external data includes: topographic data that helps to determine the location, layout, and topographic adaptability of the building; climate data that affects material selection, ventilation, and lighting in building design.

[0017] Preferably, in step S2, when establishing the BIM model, first integrate the collected data into the BIM software, and then establish a three-dimensional model of the building according to the integrated data. The three-dimensional model of the building includes building structures, equipment systems, and pipeline layouts.

[0018] When performing BIM model performance simulation, first select a simulation tool, set simulation parameters. The simulation parameters include time range, climate conditions, and building usage patterns. Then run the simulation analysis by importing the BIM into the simulation tool. Finally, interpret and analyze the simulation results.

[0019] Preferably, in step S3, when analyzing the energy consumption situation inside the building, first collect the data of sensor devices and energy consumption data inside the building, and perform a trend analysis on the collected energy consumption data to determine the energy consumption hotspots inside the building. And based on the energy consumption analysis, identify the areas or equipment with energy-saving potential.

[0020] Preferably, in step S3, when arranging sensors, divide the building into several sub-regions, and analyze the intersection regions between each sub-region and its adjacent sub-regions. Arranging sensors in the intersection regions can capture the energy consumption changes between different regions; and allocate the number of sensor devices according to the size and energy consumption situation of the intersection regions.

[0021] Preferably, in step S4, when annotating fault information, first collect the historical operation data of the energy consumption equipment inside the building, identify the records of equipment failures from the historical data, and make detailed annotations on the fault information. Organize the annotated fault information into a database. The fault database includes fault characteristics, fault modes, and fault causes.

[0022] Preferably, in step S4, when identifying fault characteristics, first preprocess the collected historical data, and extract fault characteristics by comparing the data during the fault period and the normal period. The fault characteristics include abnormal energy consumption, temperature fluctuations, and pressure changes; and establish a fault detection model to accurately identify the abnormal state of the equipment and predict potential fault risks.

[0023] Deploy the fault detection model to the BMS to monitor the operation status of the equipment in real time. When a potential fault is detected, send out a warning message in time, and use the fault database to locate and diagnose the fault.

[0024] Preferably, in step S5, use VR / AR technology to provide an immersive training experience for workers, and intuitively understand the design scheme and construction requirements by simulating the real construction environment and operation process.

[0025] When superimposing digital information at the construction site, BIM and GIS technologies are used to superimpose digital information onto the construction site, providing real-time construction guidance for workers, and guiding construction through digital information to ensure that the construction process reduces errors and rework. The construction progress can also be monitored through digital information.

[0026] Preferably, in step S6, 5G and Internet of Things technologies are used to achieve digital and intelligent management of urban energy systems and environmental systems, and energy consumption and environmental data of buildings are collected and transmitted in real time through sensor networks and intelligent devices;

[0027] And the collected data is integrated into the digital and intelligent management platform for unified management and analysis, and an early warning and response mechanism is established. When abnormal energy consumption or unqualified environmental quality is detected, an early warning signal is automatically triggered.

[0028] Preferably, in step S6, the evaluation of energy conservation and emission reduction benefits includes the amount of energy saved and the reduction of carbon emissions, and the evaluation of environmental quality improvement benefits includes indoor air quality, daylighting, and ventilation indicators. Based on the evaluation results, optimization strategies are formulated to improve the energy conservation and emission reduction benefits and environmental quality improvement benefits generated during the entire life cycle of green building technologies. The optimization strategies include adjusting equipment operation parameters, optimizing building layouts, and adopting highly energy-efficient equipment.

[0029] Compared with the prior art, the beneficial effects of the present invention are:

[0030] 1. The present invention adopts key process technologies for green intelligent digital construction, which can establish digital and intelligent monitoring, calculation, and optimization analysis models for the energy conservation and emission reduction benefits and environmental quality improvement benefits generated during the entire life cycle of green building technologies, effectively improving the visualization and perceptibility of the green building performance of buildings;

[0031] 2. The perception, quantification, and visualization of the improvement of the quality and quality of green buildings require the support of digital technologies. Digital technologies such as BIM, 5G, IoT, BMS, and EMS can realize the visualization and perceptibility of the energy conservation and emission reduction benefits and environmental quality improvement benefits generated during the entire life cycle of green building technologies, and generate economic benefits through the "carbon trading" method for the energy conservation and emission reduction benefits generated by green building technologies, promoting the development and application of green and low-carbon technologies. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 It is a flowchart of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0033] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying 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 the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0034] Please refer to Figure 1 , the present invention provides a technical solution: a green building digital collaborative design and optimization method based on BIM and cloud computing, including the following steps:

[0035] S1. Project initialization and data collection: Determine the project goals, scope, participants, and role assignments, and use 3D scanning technology to obtain the three-dimensional geometric information of the building, and integrate the obtained data information into the BIM platform;

[0036] The project scope defines the specific work content covered by the project, including the type, scale, location of the building, and all tasks to be completed. Identifying participants and role assignments means listing all stakeholders related to the project, such as owners, designers, contractors, suppliers, etc., and assigning clear roles and responsibilities to each participant.

[0037] In addition to obtaining the three-dimensional geometric model of the building, external data around the building also needs to be obtained. The external data includes: topographic data (such as topographic maps, elevation data, etc.) that helps determine the location, layout, and terrain adaptability of the building; climate data (such as temperature, humidity, rainfall, etc.) that affects material selection, ventilation, and lighting in building design; and environmental data (such as soil type, vegetation cover, etc.).

[0038] Using advanced 3D scanning technology, the three-dimensional geometric information of the building can be obtained quickly and accurately, and these data are crucial for creating an accurate BIM model;

[0039] BIM (Building Information Modeling) is a digital model that integrates all relevant information of a building project, which allows the project team to collaborate, simulate, and analyze throughout the entire life cycle of the project. When integrating data, the accuracy and consistency of the data must be ensured. This involves data cleaning, verification, and standardization to ensure that the BIM model can accurately reflect the actual situation of the project. The BIM platform provides powerful data management and visualization functions, enabling the project team to access, analyze, and modify data more conveniently.

[0040] S2. Preliminary design and simulation based on BIM: Establish a BIM model, perform performance simulation on the BIM model, and then adjust and optimize the design scheme according to the simulation results;

[0041] When building a BIM model, first integrate the collected data such as topographic maps, building geometric information, equipment performance parameters, etc. into the BIM software, and then establish a three-dimensional model of the building based on the integrated data. The three-dimensional model of the building includes building structures (such as walls, floors, beams, and columns), equipment systems (such as air conditioning systems, water supply and drainage systems, electrical systems, etc.), and pipeline layouts (such as cable trays, water pipes, air ducts, etc.); during the modeling process, continuously verify the accuracy and integrity of the model. This includes checking aspects such as the geometric dimensions, structural connections, and equipment performance of the model to ensure that the model can truly reflect the actual situation of the construction project.

[0042] When performing BIM model performance simulation, first select simulation tools such as energy consumption simulation software, environmental simulation software, acoustic simulation software, and optical simulation software, set the simulation parameters, and the simulation parameters include time range, climate conditions, and building usage patterns. Then run the simulation analysis, import the BIM into the simulation tool, and run the simulation analysis. This process may involve a large amount of calculation and data processing, so it is necessary to utilize the high-performance computing power of the cloud computing platform to accelerate the simulation process; finally, interpret and analyze the simulation results, including evaluating aspects such as the energy consumption level, environmental adaptability, acoustic performance, and optical performance of the building, as well as identifying potential problems and improvement points.

[0043] Finally, according to the simulation results, adjust and optimize the design scheme, which involves modifying aspects such as changing the building structure, optimizing the equipment system, and adjusting the pipeline layout, and then re-run the simulation analysis to evaluate the effect of the optimized design scheme, including comparing the changes in aspects such as the energy consumption level and environmental adaptability before and after optimization. If the simulation results still do not meet the project's goals and requirements, continue to iteratively optimize the design scheme.

[0044] S3. Layout and optimization of sensor devices: Analyze the energy consumption situation inside the building and accurately allocate the number of sensor devices;

[0045] In step S3, when analyzing the energy consumption situation inside the building, first collect the sensor device data and energy consumption data inside the building, and conduct a trend analysis on the collected energy consumption data. The energy consumption data trends include identifying peak energy consumption periods, low peak periods, and energy consumption changes under different seasons and weather conditions, determining the energy consumption hotspots (areas with high or abnormal energy consumption) inside the building, and based on the energy consumption analysis, identifying areas or equipment with energy-saving potential.

[0046] The sensor device data includes temperature, humidity, light intensity, human activities, etc., and the energy consumption data includes electricity, water, gas, etc.

[0047] When laying out sensors, divide the building into several sub - regions, analyze the intersection regions between each sub - region and its adjacent sub - regions, and arranging sensors in the intersection regions can capture the energy consumption changes between different regions; and allocate the number of sensor devices according to the size and energy consumption situation of the intersection regions.

[0048] Precisely allocate the number of sensor devices according to the size of the intersection region, avoiding waste of resources and reducing the cost of sensor devices; by comparing the relationship between the maximum area of the data - receiving region of the sensor device and the area of the corresponding grid, different adjustment strategies can be adopted to adapt to different actual application scenarios, enhancing the self - adaptability and scalability of the system.

[0049] S4. Fault detection and early warning processing: Mark the fault information of energy - consuming devices, identify the fault characteristics, and send out early warning information in a timely manner;

[0050] When marking the fault information, first collect the historical operation data of the energy - consuming devices inside the building, identify the records of device failures from the historical data, and make detailed marks on the fault information. The marked content includes the fault type, occurrence time, affected range, and repair measures. Organize the marked fault information into a database for subsequent analysis and modeling. The fault database includes fault characteristics, fault modes, and fault causes.

[0051] When identifying the fault characteristics, first pre - process the collected historical data. The pre - processing includes operations such as data cleaning, data transformation, and data normalization to improve the data quality and analysis efficiency. By comparing the data during the fault period and the normal period, extract the fault characteristics. The fault characteristics include abnormal energy consumption, temperature fluctuations, and pressure changes; and establish a fault detection model to accurately identify the abnormal state of the device and predict potential fault risks;

[0052] Deploy the fault detection model to the BMS, monitor the operating status of the device in real - time. When a potential fault is detected, send out early warning information in a timely manner, and use the fault database to locate and diagnose the fault, determining the specific location, type, and possible causes of the fault.

[0053] And formulate corresponding emergency response plans to ensure that measures can be taken quickly for prevention or repair when a fault occurs, including shutting down the faulty device, starting standby devices, dispatching maintenance personnel, etc. Record and analyze the processed faults, summarize the fault causes, processing procedures, and lessons learned. It can be used to improve the fault detection model, optimize the device maintenance strategy, and enhance the safety of the building.

[0054] S5. Digital management during the construction stage: Use VR / AR technology to simulate the construction process of low - carbon materials and overlay digital information at the construction site;

[0055] Using VR / AR technology to provide workers with an immersive training experience, by simulating real construction environments and operation processes, they can intuitively understand the design plans and construction requirements; VR / AR training can help workers familiarize themselves with complex construction techniques and operation processes, improve their professional skills and the ability to handle emergencies. At the same time, by simulating construction challenges in different scenarios, the adaptability and safety awareness of workers can be enhanced. Through VR / AR training, workers can master construction essentials faster, reduce errors and delays in actual operations, thereby improving construction efficiency and quality.

[0056] When superimposing digital information on the construction site, using BIM and GIS technologies to overlay digital information on the construction site, providing real-time construction guidance for workers, and guiding construction through digital information to ensure that the construction process reduces errors and rework, and the construction progress can also be monitored through digital information.

[0057] Through digital management, the construction process can be optimized, reducing unnecessary energy consumption and carbon emissions. For example, by reasonably arranging the construction sequence and dispatching resources, the idling time and transportation distance of construction machinery can be reduced.

[0058] Selecting and using energy-saving construction machinery and equipment, such as electric excavators, energy-saving mixers, etc., can reduce energy consumption during construction. At the same time, regularly maintaining and servicing construction machinery and equipment to ensure it is in the best working condition can also reduce energy consumption and emissions.

[0059] Using renewable energy sources at the construction site, such as solar energy, wind energy, etc., can further reduce energy consumption and carbon emissions. For example, a solar power generation system can be set up to provide electricity for the construction site, or wind energy can be used to drive certain construction machinery.

[0060] S6. Digital management during the operation stage: Real-time monitoring of the energy consumption and environmental quality of buildings, and establishing a digital monitoring, calculation, and optimization analysis model to evaluate and optimize the energy conservation and emission reduction benefits and environmental quality improvement benefits generated during the entire life cycle of green building technologies.

[0061] Using 5G and Internet of Things technologies to achieve digital management of urban energy systems (such as power systems, water supply systems, gas systems, etc.) and environmental systems (such as air quality, temperature, humidity, etc.), and real-time collecting and transmitting the energy consumption and environmental data of buildings through sensor networks and intelligent devices;

[0062] And integrating the collected data into a digital management platform for unified management and analysis, using big data and artificial intelligence technologies to deeply mine and process the data to reveal the internal laws and trends of energy consumption and environmental quality, and establishing an early warning and response mechanism. When abnormal energy consumption or unqualified environmental quality is detected, an early warning signal is automatically triggered.

[0063] The evaluation of energy conservation and emission reduction benefits includes the amount of energy saved and the amount of carbon emissions reduced. The energy conservation and emission reduction benefits generated by green building technologies can be converted into economic benefits through the method of "carbon trading", which promotes the development and application of green and low-carbon technologies.

[0064] The evaluation of environmental quality improvement benefits includes indoor air quality, daylighting, and ventilation indicators. Based on the evaluation results, optimization strategies are formulated to improve the energy conservation and emission reduction benefits and environmental quality improvement benefits generated during the entire life cycle of green building technologies. The optimization strategies include adjusting equipment operation parameters, optimizing building layouts, and adopting highly efficient energy-saving equipment.

[0065] Although the embodiments of the present invention have been shown and described, those of ordinary skill in the art can understand that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A digital collaborative design and optimization method for green buildings based on BIM and cloud computing, characterized in that, It includes the following steps: S1. Project initialization and data collection: Determine the project objectives, scope, participants, and role assignments, and use 3D scanning technology to obtain the three-dimensional geometric information of the building, and integrate the acquired data information into the BIM platform; S2. Preliminary design and simulation based on BIM: Establish a BIM model, perform performance simulation on the BIM model, and then adjust and optimize the design scheme according to the simulation results; S3. Sensor device layout and optimization: Analyze the energy consumption situation inside the building and accurately allocate the number of sensor devices; S4. Fault detection and early warning processing: Mark the fault information of energy-consuming devices, identify the fault characteristics, and send out early warning information in a timely manner; S5. Digital management during the construction stage: Use VR / AR technology to simulate the construction process of low-carbon materials and overlay digital information at the construction site; S6. Digital and intelligent management during the operation stage: Monitor the energy consumption and environmental quality of the building in real time, and establish a digital and intelligent monitoring, calculation, and optimization analysis model to evaluate and optimize the energy conservation and emission reduction benefits and environmental quality improvement benefits generated during the entire life cycle of green building technologies.

2. The green building digital collaborative design and optimization method based on BIM and cloud computing according to claim 1, characterized in that: In step S1, in addition to obtaining the three-dimensional geometric model of the building, external data around the building also needs to be obtained. The external data includes: topographic data that helps determine the location, layout, and topographic adaptability of the building; climate data that affects material selection, ventilation, and daylighting in building design.

3. A green building digital collaborative design and optimization method based on BIM and cloud computing according to claim 1, characterized in that: In step S2, when establishing the BIM model, first integrate the collected data into the BIM software, and then establish a three-dimensional model of the building according to the integrated data. The three-dimensional model of the building includes building structure, equipment system, and pipeline layout; When performing BIM model performance simulation, first select the simulation tool, set the simulation parameters. The simulation parameters include time range, climate conditions, and building usage patterns. Then run the simulation analysis, import the BIM into the simulation tool, run the simulation analysis, and finally interpret and analyze the simulation results.

4. A green building digital collaborative design and optimization method based on BIM and cloud computing according to claim 1, characterized in that: In step S3, when analyzing the energy consumption situation inside the building, first collect the sensor device data and energy consumption data inside the building, and perform trend analysis on the collected energy consumption data to determine the energy consumption hotspots inside the building. Based on the energy consumption analysis, identify the areas or devices with energy-saving potential.

5. A green building digital collaborative design and optimization method based on BIM and cloud computing according to claim 4, characterized in that: In step S3, when laying out the sensors, divide the building into several sub-areas, and analyze the intersection areas between each sub-area and its adjacent sub-areas. Laying out sensors in the intersection areas can capture the energy consumption changes between different areas; and allocate the number of sensor devices according to the size and energy consumption situation of the intersection areas.

6. A green building digital collaborative design and optimization method based on BIM and cloud computing according to claim 1, characterized in that: In step S4, when marking the fault information, first collect the historical operation data of the energy-consuming devices inside the building, identify the records of device failures from the historical data, and mark the fault information in detail. Organize the marked fault information into a database. The fault database includes fault characteristics, fault modes, and fault causes.

7. A green building digital collaborative design and optimization method based on BIM and cloud computing according to claim 6, characterized in that: In step S4, when identifying fault characteristics, the historical data collected is first preprocessed, and by comparing the data during the fault period and the normal period, fault characteristics are extracted. The fault characteristics include abnormal energy consumption, temperature fluctuations, and pressure changes; And a fault detection model is established to accurately identify the abnormal state of the equipment and predict potential fault risks; The fault detection model is deployed into the BMS to monitor the operation state of the equipment in real time. When a potential fault is detected, a warning message is sent in a timely manner, and the fault database is used to locate and diagnose the fault.

8. A green building digital collaborative design and optimization method based on BIM and cloud computing according to claim 1, characterized in that: In step S5, VR / AR technology is used to provide an immersive training experience for workers. By simulating the real construction environment and operation process, they can intuitively understand the design scheme and construction requirements; When superimposing digital information at the construction site, BIM and GIS technologies are used to superimpose digital information on the construction site to provide real-time construction guidance for workers. And the construction process is guided by the digital information to ensure that the construction process reduces errors and rework, and the construction progress can also be monitored through the digital information.

9. A green building digital collaborative design and optimization method based on BIM and cloud computing according to claim 1, characterized in that: In step S6, 5G and Internet of Things technologies are used to realize the digital and intelligent management of the urban energy system and environmental system. The energy consumption and environmental data of buildings are collected and transmitted in real time through the sensor network and intelligent devices; And the collected data is integrated into the digital and intelligent management platform for unified management and analysis, and a warning and response mechanism is established. When abnormal energy consumption or unqualified environmental quality is detected, a warning signal is automatically triggered.

10. A green building digital collaborative design and optimization method based on BIM and cloud computing according to claim 1, characterized in that: In step S6, the evaluation of energy conservation and emission reduction benefits includes the amount of energy saved and the reduction of carbon emissions. The evaluation of environmental quality improvement benefits includes indoor air quality, lighting, and ventilation indicators. And based on the evaluation results, optimization strategies are formulated to improve the energy conservation and emission reduction benefits and environmental quality improvement benefits generated during the whole life cycle of green building technology. The optimization strategies include adjusting equipment operation parameters, optimizing building layout, and adopting highly energy-efficient equipment.

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