Intelligent medical building design optimization method and system based on BIM

Abstract

The invention belongs to the technical field of data processing, particularly relates to a BIM-based intelligent medical building design optimization method and system, and aims to solve the problems of high error rate and low optimization efficiency when real-time data is processed by a BIM model. The method comprises the following steps: acquiring a BIM model of a medical building, construction data and user input, establishing a mirror image model, detecting and correcting real-time data, processing the corrected data, detecting the real-time data by using a dynamic data detection model, correcting the data according to an error result, and optimizing the BIM model in combination with historical data. According to the method, the accuracy and optimization efficiency of the BIM model are improved, and efficient design, operation and maintenance of an intelligent medical building are supported.

Description

Technical Field

[0001] The present invention belongs to the technical field of data processing, and in particular relates to a BIM-based intelligent medical building design optimization method and system. Background Art

[0002] BIM technology (Building Information Modeling) is widely used in the design and optimization of intelligent medical buildings. It provides a new solution for the design, construction, operation and maintenance of medical buildings through the digital carrying and visual expression of the physical characteristics and functional characteristics of the building. BIM technology can realize real-time monitoring of construction progress, quality, safety and other aspects, and improve the smooth progress of the construction process. Through 4D (3D+Time) simulation construction, the construction process of the entire building can be intuitively and accurately reflected, which is helpful for the reasonable formulation of construction plans and accurate grasp of construction progress during the project construction process. Operation and maintenance personnel can query detailed information on equipment and facilities through the BIM model, including equipment name, model, installation location, maintenance records, etc.

[0003] In the design and construction process of smart medical buildings, design changes are inevitable. Due to the frequency and complexity of design changes, the update of the BIM model needs to be consistent with the actual design, and the BIM model also needs to have higher complexity and precision. However, the existing BIM model will have errors when processing real-time update data, resulting in low efficiency in BIM model optimization. In order to improve the optimization efficiency of the BIM model, the present invention provides a BIM-based smart medical building design optimization method and system. Summary of the invention

[0004] The purpose of the present invention is to provide a BIM-based intelligent medical building design optimization method and system to solve the problem that errors may occur in the existing BIM model when processing real-time update data, resulting in low efficiency of BIM model optimization.

[0005] The technical solution adopted by the present invention is as follows: In a first aspect, the present invention provides a BIM-based intelligent medical building design optimization method, comprising: Step S101, obtaining a BIM model of a medical building, medical building construction data, and medical building construction user input data, wherein the BIM model of the medical building includes a building operation and maintenance model, a building structure model, a building electromechanical model, a building ventilation model, and a seismic simulation model, and the medical building construction data includes medical building construction estimated data and medical building construction real-time data; Step S102, establishing a mirror model for the BIM model of the medical building, obtaining a mirror building operation and maintenance model, a mirror building structure model, a mirror building electromechanical model, a mirror building ventilation model, and a mirror building seismic simulation model, and substituting the estimated medical building construction data and the real-time medical building construction data into the mirror building operation and maintenance model, the mirror building structure model, the mirror building electromechanical model, the mirror building ventilation model, and the mirror building seismic simulation model in sequence to obtain the estimated simulation results of the medical building and the real-time data simulation results of the medical building; Step S103, comparing the medical building real-time data simulation result with the medical building expected simulation result to obtain the medical building real-time data comparison result; if the medical building real-time data comparison result is greater than a preset error range, the medical building real-time data is detected by a dynamic data detection model to obtain a medical building real-time data dynamic detection result; the medical building real-time data is corrected according to the medical building real-time data dynamic detection result to obtain the corrected medical building real-time data; Step S104, classifying the corrected medical building real-time data to obtain the classified corrected medical building real-time data, establishing a matching relationship between the classified corrected medical building real-time data and the building operation and maintenance model, building structure model, building electromechanical model, building ventilation model, and earthquake simulation model in the BIM model of the medical building, substituting the classified corrected medical building real-time data into the corresponding model in the BIM model of the medical building to obtain building operation and maintenance real-time simulation data, building structure real-time simulation data, building electromechanical real-time simulation data, building ventilation real-time simulation data, and earthquake simulation data; Step S105, summarize the building operation and maintenance real-time simulation data, building structure real-time simulation data, building mechanical and electrical real-time simulation data, building ventilation real-time simulation data and ground and building earthquake real-time simulation data to obtain a revised BIM model simulation data set of the medical building; if the data in the revised BIM model simulation data set of the medical building is compared with the expected simulation result of the medical building, and the comparison result is still greater than the preset error range, the dynamic data detection model is optimized, and the optimized dynamic data detection model is used to detect the revised BIM model simulation data set of the medical building to obtain a revised BIM model simulation data set of the medical building; the revised BIM model simulation data set of the medical building is used in combination with the BIM model historical data of the medical building in the database to optimize the BIM model of the medical building to obtain the optimized BIM model of the medical building; the BIM model of the medical building is used to process the medical building construction data and the medical building construction user input data to obtain the optimized medical building construction operation and maintenance data.

[0006] Furthermore, the present invention provides a BIM-based intelligent medical building design optimization method, wherein step S103 comprises: Compare the medical building real-time data simulation results with the medical building expected simulation results, set a preset error range, if the medical building data real-time comparison result is greater than the preset error range; The dynamic data detection model detects the real-time data of medical buildings. The dynamic data detection model accurately detects the real-time data of medical buildings. Through the dynamic data detection model, the dynamic detection results of the real-time data of medical buildings are obtained; According to the dynamic detection results of real-time data of medical buildings, the difference between real-time data and expected data is calculated, and the source of error is analyzed. If the error exceeds the preset range, data correction is required; According to the error analysis results, a preset correction method is applied to process the real-time data to obtain modified data, and the corrected data is verified to obtain verified corrected data.

[0007] Furthermore, the present invention provides a BIM-based intelligent medical building design optimization method, wherein step S104 comprises: Classifying the corrected medical building real-time data, where the classification is based on the type, source, and timestamp information of the data, and obtaining a set of classified corrected medical building real-time data through the classification; Establish a matching relationship between the classified and corrected real-time data of medical buildings and the building operation and maintenance model, building structure model, building electromechanical model, building ventilation model and earthquake simulation model in the BIM model of the medical building, and substitute the classified and corrected real-time data of medical buildings into the corresponding models in the BIM model of the medical building. By substituting the data, the building operation and maintenance real-time simulation data, building structure real-time simulation data, building electromechanical real-time simulation data, building ventilation real-time simulation data and earthquake simulation data are obtained.

[0008] Furthermore, the present invention provides a BIM-based intelligent medical building design optimization method, wherein step S105 comprises: Compare the data in the revised BIM model simulation data set of the medical building with the expected simulation results of the medical building; If the comparison result shows that the data difference is greater than the preset error range, the BIM model or the dynamic data detection model still has deficiencies, and the dynamic data detection model is optimized, and the optimized dynamic data detection model is used to re-detect the BIM model simulation data set of the revised medical building; The revised BIM model simulation data set of the medical building is combined with the historical data of the BIM model of the medical building in the database. The BIM model of the medical building is optimized by combining historical data and real-time data. The optimized BIM model of the medical building is used to process the medical building construction data and the medical building construction user input data to obtain the optimized medical building construction operation and maintenance data.

[0009] In a second aspect, the present invention provides a BIM-based intelligent medical building design optimization system, which is applied to the BIM-based intelligent medical building design optimization method, comprising: An acquisition unit is used to acquire a BIM model of a medical building, medical building construction data, and medical building construction user input data. The BIM model of a medical building includes a building operation and maintenance model, a building structure model, a building electromechanical model, a building ventilation model, and a seismic simulation model. The medical building construction data includes estimated medical building construction data and real-time medical building construction data. A data simulation unit is used to establish a mirror model for the BIM model of the medical building, obtain a mirror building operation and maintenance model, a mirror building structure model, a mirror building electromechanical model, a mirror building ventilation model, and a mirror building seismic simulation model, and substitute the estimated medical building construction data and the real-time medical building construction data into the mirror building operation and maintenance model, the mirror building structure model, the mirror building electromechanical model, the mirror building ventilation model, and the mirror building seismic simulation model in sequence to obtain the estimated simulation results of the medical building and the real-time data simulation results of the medical building; A data comparison unit is used to compare the medical building real-time data simulation result with the medical building expected simulation result to obtain the medical building real-time data comparison result; if the medical building real-time data comparison result is greater than a preset error range, the medical building real-time data is detected by a dynamic data detection model to obtain the medical building real-time data dynamic detection result; the medical building real-time data is corrected according to the medical building real-time data dynamic detection result to obtain the corrected medical building real-time data; A data matching unit is used to classify the corrected medical building real-time data to obtain the classified corrected medical building real-time data, establish a matching relationship between the classified corrected medical building real-time data and the building operation and maintenance model, building structure model, building electromechanical model, building ventilation model and earthquake simulation model in the BIM model of the medical building, substitute the classified corrected medical building real-time data into the corresponding model in the BIM model of the medical building, and obtain the building operation and maintenance real-time simulation data, building structure real-time simulation data, building electromechanical real-time simulation data, building ventilation real-time simulation data and earthquake simulation data; The optimization unit is used to aggregate the real-time simulation data of building operation and maintenance, the real-time simulation data of building structure, the real-time simulation data of building mechanical and electrical equipment, the real-time simulation data of building ventilation, and the real-time simulation data of earthquake and seismic construction to obtain a revised BIM model simulation data set of the medical building. If the data in the revised BIM model simulation data set of the medical building is compared with the expected simulation result of the medical building, and the comparison result is still greater than the preset error range, the dynamic data detection model is optimized, and the optimized dynamic data detection model is used to detect the revised BIM model simulation data set of the medical building to obtain a revised BIM model simulation data set of the medical building. The revised BIM model simulation data set of the medical building is used in combination with the historical data of the BIM model of the medical building in the database to optimize the BIM model of the medical building to obtain the optimized BIM model of the medical building. The BIM model of the medical building is used to process the construction data of the medical building and the user input data of the medical building construction to obtain the optimized construction and operation data of the medical building.

[0010] Furthermore, the present invention provides a BIM-based intelligent medical building design optimization system, characterized in that the data comparison unit is also used to: Compare the medical building real-time data simulation results with the medical building expected simulation results, set a preset error range, if the medical building data real-time comparison result is greater than the preset error range; The dynamic data detection model detects the real-time data of medical buildings. The dynamic data detection model accurately detects the real-time data of medical buildings. Through the dynamic data detection model, the dynamic detection results of the real-time data of medical buildings are obtained; According to the dynamic detection results of real-time data of medical buildings, the difference between real-time data and expected data is calculated, and the source of error is analyzed. If the error exceeds the preset range, data correction is required; According to the error analysis results, a preset correction method is applied to process the real-time data to obtain modified data, and the corrected data is verified to obtain verified corrected data.

[0011] Furthermore, the present invention provides a BIM-based intelligent medical building design optimization system, characterized in that the data matching unit is also used to: Classifying the corrected medical building real-time data, where the classification is based on the type, source, and timestamp information of the data, and obtaining a set of classified corrected medical building real-time data through the classification; Establish a matching relationship between the classified and corrected real-time data of medical buildings and the building operation and maintenance model, building structure model, building electromechanical model, building ventilation model and earthquake simulation model in the BIM model of the medical building, and substitute the classified and corrected real-time data of medical buildings into the corresponding models in the BIM model of the medical building. By substituting the data, the building operation and maintenance real-time simulation data, building structure real-time simulation data, building electromechanical real-time simulation data, building ventilation real-time simulation data and earthquake simulation data are obtained.

[0012] Furthermore, the present invention provides a BIM-based intelligent medical building design optimization system, characterized in that the optimization unit is also used to: Compare the data in the revised BIM model simulation data set of the medical building with the expected simulation results of the medical building; If the comparison result shows that the data difference is greater than the preset error range, the BIM model or the dynamic data detection model still has deficiencies, and the dynamic data detection model is optimized, and the optimized dynamic data detection model is used to re-detect the BIM model simulation data set of the revised medical building; The revised BIM model simulation data set of the medical building is combined with the historical data of the BIM model of the medical building in the database. The BIM model of the medical building is optimized by combining historical data and real-time data. The optimized BIM model of the medical building is used to process the medical building construction data and the medical building construction user input data to obtain the optimized medical building construction operation and maintenance data.

[0013] The technical effects achieved by the present invention are: First, through the dynamic data detection model and optimized data processing flow, the present invention significantly improves the accuracy of the BIM model when processing real-time data. This improves the design, construction and operation and maintenance of medical buildings, and the BIM model can reflect the latest and accurate information, thereby reducing decision-making errors caused by data errors.

[0014] Secondly, the present invention improves the efficiency of medical building design and operation and maintenance. Through automated data acquisition, processing and analysis processes, as well as optimized BIM models, the present invention reduces manual intervention and data processing time, making the design, construction and operation and maintenance of medical buildings faster and more efficient.

[0015] In addition, the present invention enhances the collaborative work of each phase of the medical building project. Through the integrated system and user interface, the project team can more easily share information, collaborate, and promote smooth transitions between phases. This improves the overall collaborative efficiency of the project and reduces problems caused by poor communication or inconsistent information.

[0016] Finally, the invention improves the flexibility and scalability of the final result through multiple simulations and optimizations. The system supports adjustment and expansion according to project requirements, so that the design optimization of medical buildings can be more flexibly adapted to different project requirements and conditions. This provides greater flexibility and innovation space for the design of medical buildings.

[0017] In summary, the BIM-based intelligent medical building design optimization method and system of the present invention provide strong technical support for the design, construction, and operation and maintenance of medical buildings, improve accuracy, efficiency, coordination, and flexibility, and bring positive impacts to the development of the medical building industry. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 It is a flow chart of a BIM-based intelligent medical building design optimization method and system of the present invention. DETAILED DESCRIPTION

[0019] In order to make the purpose and advantages of the present invention more clearly understood, the present invention is specifically described below in conjunction with embodiments. It should be understood that the following text is only used to describe one or several specific embodiments of the present invention, and does not strictly limit the scope of protection of the specific claims of the present invention.

[0020] The present invention provides a BIM-based intelligent medical building design optimization method and system, comprising: In a first aspect, the present invention provides a BIM-based intelligent medical building design optimization method, comprising: Step S101, obtaining a BIM model of a medical building, medical building construction data, and medical building construction user input data, wherein the BIM model of the medical building includes a building operation and maintenance model, a building structure model, a building electromechanical model, a building ventilation model, and a seismic simulation model, and the medical building construction data includes medical building construction estimated data and medical building construction real-time data; In step S101, the system needs to obtain key data from multiple sources for subsequent intelligent medical building design optimization processing, mainly including the BIM model of the medical building, the medical building construction data, and the user input data during the medical building construction process.

[0021] BIM model of medical buildings: including building operation and maintenance model, building structure model, building electromechanical model, building ventilation model and earthquake simulation model. These models represent different aspects of medical buildings, such as operation and maintenance, structure, electromechanical, ventilation and earthquake resistance.

[0022] Medical building construction data: Medical building construction estimated data: including various construction parameters and data predicted in the planning stage of the construction project, which are used for initial simulation and optimization.

[0023] Real-time data of medical building construction: data collected in real time during the construction process, such as construction progress, material consumption, equipment status, etc. These data reflect the actual situation of the current construction.

[0024] BIM model acquisition: Import the complete BIM model of the medical building from the BIM design software or BIM model library, involving multiple sub-models (such as operation and maintenance, structure, mechanical and electrical, ventilation and earthquake simulation models), each of which describes a specific aspect of the building in detail.

[0025] Construction data acquisition: Estimated data is extracted from project plans and design documents and entered into the system. Real-time data is collected in real time through sensors, monitoring equipment and construction management systems at the construction site and transmitted to the data processing center through the network.

[0026] User input data: During the construction process, there will be feedback on design changes or on-site issues. Users (such as architects, engineers or project managers) can input this information through the user interface, and the system will use these inputs as a reference for the optimization process.

[0027] In actual applications, step S101 involves interfacing with multiple systems such as BIM software, project management software, and real-time monitoring systems to ensure that data can be accurately transmitted to the optimization system. At the same time, the system needs to have data parsing and processing capabilities to integrate data from different sources into a unified data processing framework.

[0028] Through the above steps, the system can collect all the key data required for intelligent medical building design optimization, laying a solid foundation for subsequent data simulation, comparison, optimization and other steps.

[0029] Step S102, establishing a mirror model for the BIM model of the medical building, obtaining a mirror building operation and maintenance model, a mirror building structure model, a mirror building electromechanical model, a mirror building ventilation model, and a mirror building seismic simulation model, and substituting the estimated medical building construction data and the real-time medical building construction data into the mirror building operation and maintenance model, the mirror building structure model, the mirror building electromechanical model, the mirror building ventilation model, and the mirror building seismic simulation model in sequence to obtain the estimated simulation results of the medical building and the real-time data simulation results of the medical building; Step S102 is one of the key steps in the BIM-based intelligent medical building design optimization method proposed in the present invention, and its specific content and execution method are as follows: The core of step S102 is to establish a mirror model for the BIM (Building Information Model) of the medical building. This includes creating a mirror building operation and maintenance model, a mirror building structure model, a mirror building electromechanical model, a mirror building ventilation model, and a mirror earthquake simulation model. The mirror model is a replica of the original BIM model and is used for data analysis, simulation, and testing without interfering with the original model.

[0030] Copy BIM model: First, copy each component from the existing medical building BIM model, including the building operation and maintenance model, building structure model, building mechanical and electrical model, building ventilation model, and earthquake simulation model. The copied model is the mirror model, which is consistent with the original model in content, but remains independent in the data processing process to avoid direct modification of the original model.

[0031] Establish mirror model: Mark each copied model as a mirror model, such as mirror building operation and maintenance model, mirror building structure model, etc. Each mirror model retains all necessary information and properties of the original model for subsequent data processing and simulation.

[0032] Data input and simulation: The estimated data of medical building construction and the real-time data of medical building construction are input into each mirror model in turn. For each mirror model, the corresponding data is used for simulation calculation to generate the estimated simulation results of medical buildings and the real-time data simulation results of medical buildings.

[0033] For example, the estimated construction progress, material usage and other data are substituted into the mirror building structure model to simulate the structural construction; the real-time equipment operation status, energy consumption and other data are substituted into the mirror building electromechanical model to simulate the electromechanical system.

[0034] Simulation result output: After each mirror model completes the simulation based on the input data, it will output the corresponding simulation results. The simulation results include but are not limited to the expected completion of the construction progress, the operating status of the electromechanical system, the efficiency of the ventilation system, and the building stability in the earthquake simulation.

[0035] The mirror model remains independent, and the original BIM model is not affected by any potential impact during data processing. All key sub-models (operation and maintenance, structure, electromechanical, ventilation, and earthquake simulation) need to be mirrored to improve the comprehensiveness and accuracy of data simulation. The mirror model makes data processing and simulation more flexible, and multiple simulations and optimizations can be performed without destroying the original design.

[0036] Through step S102, the present invention provides a solid foundation for subsequent data comparison, optimization and real-time data correction, and improves the accuracy and efficiency of the intelligent medical building design optimization process.

[0037] Step S103, comparing the medical building real-time data simulation result with the medical building expected simulation result to obtain the medical building real-time data comparison result; if the medical building real-time data comparison result is greater than a preset error range, the medical building real-time data is detected by a dynamic data detection model to obtain a medical building real-time data dynamic detection result; the medical building real-time data is corrected according to the medical building real-time data dynamic detection result to obtain the corrected medical building real-time data; Step S103 is a key step in the BIM-based intelligent medical building design optimization method, which mainly involves the processing and correction of real-time data of medical buildings to improve the accuracy of data and the reliability of the model. The following is a detailed explanation of the specific content and execution method of step S103: The main purpose of step S103 is to compare the real-time data simulation results of the medical building with the expected simulation results, and to make necessary corrections to the real-time data according to the comparison results.

[0038] Data comparison: First, the real-time data simulation results of the medical building are compared with the expected simulation results of the medical building. This comparison is to find the difference between the real-time data and the expected data.

[0039] Set a preset error range: Before comparison, you need to set a preset error range. This range is used to determine whether the difference between real-time data and expected data is within an acceptable range.

[0040] Dynamic data detection: If the difference between the real-time data simulation result and the expected simulation result is greater than the preset error range, the dynamic data detection model needs to be activated to further detect the real-time data. The dynamic data detection model can accurately detect the real-time data and generate dynamic detection results.

[0041] Error analysis and data correction: Based on the dynamic data detection results, calculate the difference between real-time data and expected data, and analyze the source of the error. If the error exceeds the preset range, it means that there is a problem with the real-time data and correction is required. Apply the preset correction method to process the real-time data to reduce or eliminate the error. Correction methods include data cleaning, interpolation, smoothing, etc.

[0042] Data Validation: Validate the revised data to improve the validity and accuracy of the revision. The validation process includes comparing with data from other sources or re-running simulations to check whether the revised data can produce better results.

[0043] Step S103 compares the real-time data simulation results with the expected simulation results, and uses the dynamic data detection model to discover and correct errors in the real-time data, thereby improving the accuracy and reliability of subsequent BIM model simulations. This process is an indispensable part of the optimization of intelligent medical building design, which helps to improve the efficiency and quality of building design, construction, and operation and maintenance.

[0044] Step S104, classifying the corrected medical building real-time data to obtain the classified corrected medical building real-time data, establishing a matching relationship between the classified corrected medical building real-time data and the building operation and maintenance model, building structure model, building electromechanical model, building ventilation model, and earthquake simulation model in the BIM model of the medical building, substituting the classified corrected medical building real-time data into the corresponding model in the BIM model of the medical building to obtain building operation and maintenance real-time simulation data, building structure real-time simulation data, building electromechanical real-time simulation data, building ventilation real-time simulation data, and earthquake simulation data; Step S104 plays a key role in the BIM-based intelligent medical building design optimization method. It is mainly responsible for matching and substituting the corrected medical building real-time data with each sub-model in the BIM model to generate real-time simulation data. The following is a detailed explanation of the specific content and execution method of step S104: Classify the corrected real-time data of medical buildings. The classification is based on the type of data (such as temperature, humidity, pressure, etc.), source (such as sensor, user input, etc.) and timestamp information. This step is to better organize the data so that it can be matched with the corresponding sub-model in the BIM model later.

[0045] Establish a matching relationship between the classified and corrected real-time data of medical buildings and the various sub-models in the BIM model of the medical building (building operation and maintenance model, building structure model, building electromechanical model, building ventilation model and seismic simulation model).

[0046] Substitute the classified and corrected real-time data of medical buildings into the corresponding sub-model in the BIM model of medical buildings. Through this step, the BIM model will be re-simulated according to the real-time data to generate real-time simulation data of building operation and maintenance, real-time simulation data of building structure, real-time simulation data of building mechanical and electrical, real-time simulation data of building ventilation, and real-time simulation data of ground and building earthquakes.

[0047] The specific implementation method of step S104 is as follows: First, the corrected real-time data of medical buildings is preprocessed, including data cleaning, conversion and formatting, to improve the data to meet the requirements of BIM model processing.

[0048] Use a preset data classification algorithm to classify the corrected real-time data based on data type, source, and timestamp information. The classification algorithm can be a rule-based classifier, a clustering algorithm, or a machine learning model.

[0049] According to the classification results, a matching relationship is established for each type of data with the corresponding sub-model in the BIM model, which is achieved through database query, programming interface call or middleware service. Using the programming interface or API, the classified real-time data is imported into the corresponding sub-model in the BIM model one by one. This requires the development of a special data exchange interface or adapter to improve the correct transmission and processing of data.

[0050] Simulation execution: After receiving real-time data, the BIM model performs simulation calculations based on built-in rules and algorithms to generate various real-time simulation data. These simulation data will be used for subsequent analysis, monitoring and optimization work.

[0051] Validate the generated real-time simulation data to improve its accuracy and reliability. This can be done through comparison with historical data, expert review, or user feedback.

[0052] Through the execution of step S104, the BIM model can dynamically generate simulation results based on real-time medical building data, providing strong support for the design, construction, and operation and maintenance of intelligent medical buildings.

[0053] Step S105, summarize the building operation and maintenance real-time simulation data, building structure real-time simulation data, building mechanical and electrical real-time simulation data, building ventilation real-time simulation data and ground and building earthquake real-time simulation data to obtain a revised BIM model simulation data set of the medical building; if the data in the revised BIM model simulation data set of the medical building is compared with the expected simulation result of the medical building, and the comparison result is still greater than the preset error range, the dynamic data detection model is optimized, and the optimized dynamic data detection model is used to detect the revised BIM model simulation data set of the medical building to obtain a revised BIM model simulation data set of the medical building; the revised BIM model simulation data set of the medical building is used in combination with the BIM model historical data of the medical building in the database to optimize the BIM model of the medical building to obtain the optimized BIM model of the medical building; the BIM model of the medical building is used to process the medical building construction data and the medical building construction user input data to obtain the optimized medical building construction operation and maintenance data.

[0054] Step S105 plays a key role in the BIM-based intelligent medical building design optimization method in aggregating data, comparing results, optimizing models, and finally generating optimized data. The following is a detailed explanation of the specific content and execution method of this step: First, the various real-time simulation data generated in step S104 (building operation and maintenance real-time simulation data, building structure real-time simulation data, building mechanical and electrical real-time simulation data, building ventilation real-time simulation data, and ground and building earthquake real-time simulation data) are aggregated to form a revised BIM model simulation data set for the medical building. The purpose of this step is to integrate all relevant simulation data to prepare for subsequent data comparison and optimization operations.

[0055] Next, the data in the modified BIM model simulation data set of the medical building is compared with the expected simulation results of the medical building. This comparison operation is aimed at checking the difference between the actual simulation data and the expected data and evaluating the effect of model optimization.

[0056] If the comparison result shows that the data difference is greater than the preset error range, it means that the current BIM model or dynamic data detection model still has deficiencies in processing real-time data. At this time, the dynamic data detection model needs to be optimized to improve its accuracy and stability.

[0057] The optimized dynamic data detection model is used to re-detect the revised BIM model simulation data set of the medical building to reduce data errors and improve the accuracy of the simulation results.

[0058] The BIM model simulation data set of the medical building after the re-test is combined with the historical data of the BIM model of the medical building in the database, and the BIM model of the medical building is deeply optimized by integrating historical data and real-time data. This step not only takes into account the current data status, but also draws on historical experience to make the optimized BIM model more complete and reliable.

[0059] Finally, the optimized BIM model of the medical building is used to process the medical building construction data and the medical building construction user input data to obtain the optimized medical building construction operation and maintenance data. These optimized data can further support the design, construction and operation and maintenance decisions of the medical building.

[0060] Data aggregation: Use data processing tools or scripts to automatically extract data from each simulation module and integrate them to form a unified simulation data set.

[0061] Data comparison: Write a program or script, set a preset error range, and compare and analyze the summarized simulation data set with the expected simulation results.

[0062] Model optimization: Based on the comparison results, adjust the parameters or improve the algorithm of the dynamic data detection model to improve its performance. This step requires multiple iterations until a satisfactory error range is reached.

[0063] Re-detection: Use the optimized dynamic data detection model to reprocess real-time data to improve data accuracy and reliability.

[0064] Comprehensive optimization of BIM models: Combine historical data with real-time data to fine-tune the various components of the BIM model to improve the model's adaptability and predictive capabilities.

[0065] Data processing and output: Use the optimized BIM model for data processing, generate the final optimization results, and output them in an appropriate form for use by relevant personnel.

[0066] Through the above steps, we can achieve continuous improvement and perfection of BIM-based intelligent medical building design optimization methods, and provide more accurate and efficient support for the design, construction, operation and maintenance of medical buildings.

[0067] Specifically, the present invention provides a BIM-based intelligent medical building design optimization method, wherein step S103 comprises: Compare the medical building real-time data simulation results with the medical building expected simulation results, set a preset error range, if the medical building data real-time comparison result is greater than the preset error range; The dynamic data detection model detects the real-time data of medical buildings. The dynamic data detection model accurately detects the real-time data of medical buildings. Through the dynamic data detection model, the dynamic detection results of the real-time data of medical buildings are obtained; According to the dynamic detection results of real-time data of medical buildings, the difference between real-time data and expected data is calculated, and the source of error is analyzed. If the error exceeds the preset range, data correction is required; According to the error analysis results, a preset correction method is applied to process the real-time data to obtain modified data, and the corrected data is verified to obtain verified corrected data.

[0068] Specifically, the present invention provides a BIM-based intelligent medical building design optimization method, wherein step S104 comprises: Classifying the corrected medical building real-time data, where the classification is based on the type, source, and timestamp information of the data, and obtaining a set of classified corrected medical building real-time data through the classification; Establish a matching relationship between the classified and corrected real-time data of medical buildings and the building operation and maintenance model, building structure model, building electromechanical model, building ventilation model and earthquake simulation model in the BIM model of the medical building, and substitute the classified and corrected real-time data of medical buildings into the corresponding models in the BIM model of the medical building. By substituting the data, the building operation and maintenance real-time simulation data, building structure real-time simulation data, building electromechanical real-time simulation data, building ventilation real-time simulation data and earthquake simulation data are obtained.

[0069] Specifically, the present invention provides a BIM-based intelligent medical building design optimization method, wherein step S105 comprises: Compare the data in the revised BIM model simulation data set of the medical building with the expected simulation results of the medical building; If the comparison result shows that the data difference is greater than the preset error range, the BIM model or the dynamic data detection model still has deficiencies, and the dynamic data detection model is optimized, and the optimized dynamic data detection model is used to re-detect the BIM model simulation data set of the revised medical building; The revised BIM model simulation data set of the medical building is combined with the historical data of the BIM model of the medical building in the database. The BIM model of the medical building is optimized by combining historical data and real-time data. The optimized BIM model of the medical building is used to process the medical building construction data and the medical building construction user input data to obtain the optimized medical building construction operation and maintenance data.

[0070] In a second aspect, the present invention provides a BIM-based intelligent medical building design optimization system, which is applied to the BIM-based intelligent medical building design optimization method, comprising: An acquisition unit is used to acquire a BIM model of a medical building, medical building construction data, and medical building construction user input data. The BIM model of a medical building includes a building operation and maintenance model, a building structure model, a building electromechanical model, a building ventilation model, and a seismic simulation model. The medical building construction data includes estimated medical building construction data and real-time medical building construction data. A data simulation unit is used to establish a mirror model for the BIM model of the medical building, obtain a mirror building operation and maintenance model, a mirror building structure model, a mirror building electromechanical model, a mirror building ventilation model, and a mirror building seismic simulation model, and substitute the estimated medical building construction data and the real-time medical building construction data into the mirror building operation and maintenance model, the mirror building structure model, the mirror building electromechanical model, the mirror building ventilation model, and the mirror building seismic simulation model in sequence to obtain the estimated simulation results of the medical building and the real-time data simulation results of the medical building; A data comparison unit is used to compare the medical building real-time data simulation result with the medical building expected simulation result to obtain the medical building real-time data comparison result; if the medical building real-time data comparison result is greater than a preset error range, the medical building real-time data is detected by a dynamic data detection model to obtain the medical building real-time data dynamic detection result; the medical building real-time data is corrected according to the medical building real-time data dynamic detection result to obtain the corrected medical building real-time data; A data matching unit is used to classify the corrected medical building real-time data to obtain the classified corrected medical building real-time data, establish a matching relationship between the classified corrected medical building real-time data and the building operation and maintenance model, building structure model, building electromechanical model, building ventilation model and earthquake simulation model in the BIM model of the medical building, substitute the classified corrected medical building real-time data into the corresponding model in the BIM model of the medical building, and obtain the building operation and maintenance real-time simulation data, building structure real-time simulation data, building electromechanical real-time simulation data, building ventilation real-time simulation data and earthquake simulation data; The optimization unit is used to aggregate the real-time simulation data of building operation and maintenance, the real-time simulation data of building structure, the real-time simulation data of building mechanical and electrical equipment, the real-time simulation data of building ventilation, and the real-time simulation data of earthquake and seismic construction to obtain a revised BIM model simulation data set of the medical building. If the data in the revised BIM model simulation data set of the medical building is compared with the expected simulation result of the medical building, and the comparison result is still greater than the preset error range, the dynamic data detection model is optimized, and the optimized dynamic data detection model is used to detect the revised BIM model simulation data set of the medical building to obtain a revised BIM model simulation data set of the medical building. The revised BIM model simulation data set of the medical building is used in combination with the historical data of the BIM model of the medical building in the database to optimize the BIM model of the medical building to obtain the optimized BIM model of the medical building. The BIM model of the medical building is used to process the construction data of the medical building and the user input data of the medical building construction to obtain the optimized construction and operation data of the medical building.

[0071] Specifically, the present invention provides a BIM-based intelligent medical building design optimization system, characterized in that the data comparison unit is also used to: Compare the medical building real-time data simulation results with the medical building expected simulation results, set a preset error range, if the medical building data real-time comparison result is greater than the preset error range; The dynamic data detection model detects the real-time data of medical buildings. The dynamic data detection model accurately detects the real-time data of medical buildings. Through the dynamic data detection model, the dynamic detection results of the real-time data of medical buildings are obtained; According to the dynamic detection results of real-time data of medical buildings, the difference between real-time data and expected data is calculated, and the source of error is analyzed. If the error exceeds the preset range, data correction is required; According to the error analysis results, a preset correction method is applied to process the real-time data to obtain modified data, and the corrected data is verified to obtain verified corrected data.

[0072] Specifically, the present invention provides a BIM-based intelligent medical building design optimization system, characterized in that the data matching unit is also used to: Classifying the corrected medical building real-time data, where the classification is based on the type, source, and timestamp information of the data, and obtaining a set of classified corrected medical building real-time data through the classification; Establish a matching relationship between the classified and corrected real-time data of medical buildings and the building operation and maintenance model, building structure model, building electromechanical model, building ventilation model and earthquake simulation model in the BIM model of the medical building, and substitute the classified and corrected real-time data of medical buildings into the corresponding models in the BIM model of the medical building. By substituting the data, the building operation and maintenance real-time simulation data, building structure real-time simulation data, building electromechanical real-time simulation data, building ventilation real-time simulation data and earthquake simulation data are obtained.

[0073] Specifically, the present invention provides a BIM-based intelligent medical building design optimization system, characterized in that the optimization unit is also used to: Compare the data in the revised BIM model simulation data set of the medical building with the expected simulation results of the medical building; If the comparison result shows that the data difference is greater than the preset error range, the BIM model or the dynamic data detection model still has deficiencies, and the dynamic data detection model is optimized, and the optimized dynamic data detection model is used to re-detect the BIM model simulation data set of the revised medical building; The revised BIM model simulation data set of the medical building is combined with the historical data of the BIM model of the medical building in the database. The BIM model of the medical building is optimized by combining historical data and real-time data. The optimized BIM model of the medical building is used to process the medical building construction data and the medical building construction user input data to obtain the optimized medical building construction operation and maintenance data.

[0074] Aiming at the problem that the existing BIM model is prone to errors when processing real-time update data, resulting in low BIM model optimization efficiency, the present invention proposes a BIM-based intelligent medical building design optimization method and system. The method effectively solves this problem through a series of refined data processing and model optimization steps. The specific solution is as follows: First, obtain the BIM model of the medical building, which contains multiple sub-models, such as the building operation and maintenance model, building structure model, building electromechanical model, building ventilation model, and seismic simulation model. At the same time, obtain the medical building construction data (including estimated data and real-time data) and user input data.

[0075] A mirror model is established for the BIM model, and the expected data and real-time data are substituted into each mirror sub-model for simulation to obtain the expected simulation results and the real-time data simulation results. The real-time data simulation results are compared with the expected simulation results. If the difference is greater than the preset error range, the real-time data is tested using the dynamic data detection model. The dynamic data detection model can accurately identify anomalies or errors in the data and correct the real-time data accordingly.

[0076] The corrected real-time data is classified according to data type, source, timestamp, etc. The classified data is matched with each sub-model in the BIM model and substituted into the corresponding model for real-time simulation to generate real-time simulation data in operation and maintenance, structure, electromechanical, ventilation, earthquake, etc.

[0077] All real-time simulation data are summarized and compared with the expected simulation results. If the difference is still greater than the preset error range, the dynamic data detection model is optimized, the data is detected and corrected again, and the BIM model itself is optimized in combination with the BIM model historical data. The optimized BIM model is used to process the medical building construction data and user input data to obtain optimized medical building operation and maintenance data. Through this closed-loop optimization process, the BIM model can be improved to continuously and efficiently reflect the actual situation of medical buildings.

[0078] Through the above steps, the present invention not only improves the accuracy of the BIM model when processing real-time updated data, but also significantly improves the optimization efficiency of the BIM model through continuous model optimization and data correction, thereby more effectively supporting the design, construction and operation and maintenance of smart medical buildings.

[0079] The above is only a preferred embodiment of the present invention. It should be noted that, for those skilled in the art, several improvements and modifications can be made without departing from the principles of the present invention, and these improvements and modifications should also be considered as the protection scope of the present invention. The structures, devices and operating methods not specifically described and explained in the present invention shall be implemented according to the conventional means in the art unless otherwise specified and limited.

Claims

1. A BIM-based intelligent medical building design optimization method, characterized in that: include: Step S101, obtaining a BIM model of a medical building, medical building construction data, and medical building construction user input data, wherein the BIM model of the medical building includes a building operation and maintenance model, a building structure model, a building electromechanical model, a building ventilation model, and a seismic simulation model, and the medical building construction data includes medical building construction estimated data and medical building construction real-time data; Step S102, establishing a mirror model for the BIM model of the medical building, obtaining a mirror building operation and maintenance model, a mirror building structure model, a mirror building electromechanical model, a mirror building ventilation model, and a mirror building seismic simulation model, and substituting the estimated medical building construction data and the real-time medical building construction data into the mirror building operation and maintenance model, the mirror building structure model, the mirror building electromechanical model, the mirror building ventilation model, and the mirror building seismic simulation model in sequence to obtain the estimated simulation results of the medical building and the real-time data simulation results of the medical building; Step S103, comparing the medical building real-time data simulation result with the medical building expected simulation result to obtain the medical building real-time data comparison result; if the medical building real-time data comparison result is greater than a preset error range, the medical building real-time data is detected by a dynamic data detection model to obtain a medical building real-time data dynamic detection result; the medical building real-time data is corrected according to the medical building real-time data dynamic detection result to obtain the corrected medical building real-time data; Step S104, classifying the corrected medical building real-time data to obtain the classified corrected medical building real-time data, establishing a matching relationship between the classified corrected medical building real-time data and the building operation and maintenance model, building structure model, building electromechanical model, building ventilation model, and earthquake simulation model in the BIM model of the medical building, substituting the classified corrected medical building real-time data into the corresponding model in the BIM model of the medical building to obtain building operation and maintenance real-time simulation data, building structure real-time simulation data, building electromechanical real-time simulation data, building ventilation real-time simulation data, and earthquake simulation data; Step S105, summarize the building operation and maintenance real-time simulation data, building structure real-time simulation data, building mechanical and electrical real-time simulation data, building ventilation real-time simulation data and ground and building earthquake real-time simulation data to obtain a revised BIM model simulation data set of the medical building; if the data in the revised BIM model simulation data set of the medical building is compared with the expected simulation result of the medical building, and the comparison result is still greater than the preset error range, the dynamic data detection model is optimized, and the optimized dynamic data detection model is used to detect the revised BIM model simulation data set of the medical building to obtain a revised BIM model simulation data set of the medical building; the revised BIM model simulation data set of the medical building is used in combination with the BIM model historical data of the medical building in the database to optimize the BIM model of the medical building to obtain the optimized BIM model of the medical building; the BIM model of the medical building is used to process the medical building construction data and the medical building construction user input data to obtain the optimized medical building construction operation and maintenance data.

2. The BIM-based intelligent medical building design optimization method according to claim 1 is characterized in that: The step S103 includes: Compare the medical building real-time data simulation results with the medical building expected simulation results, set a preset error range, if the medical building data real-time comparison result is greater than the preset error range; The dynamic data detection model detects the real-time data of medical buildings. The dynamic data detection model accurately detects the real-time data of medical buildings. Through the dynamic data detection model, the dynamic detection results of the real-time data of medical buildings are obtained; According to the dynamic detection results of real-time data of medical buildings, the difference between real-time data and expected data is calculated, and the source of error is analyzed. If the error exceeds the preset range, data correction is required; According to the error analysis results, a preset correction method is applied to process the real-time data to obtain modified data, and the corrected data is verified to obtain verified corrected data.

3. The BIM-based intelligent medical building design optimization method according to claim 1 is characterized in that: The step S104 includes: Classifying the corrected medical building real-time data, where the classification is based on the type, source, and timestamp information of the data, and obtaining a set of classified corrected medical building real-time data through the classification; Establish a matching relationship between the classified and corrected real-time data of medical buildings and the building operation and maintenance model, building structure model, building electromechanical model, building ventilation model and earthquake simulation model in the BIM model of the medical building, and substitute the classified and corrected real-time data of medical buildings into the corresponding models in the BIM model of the medical building. By substituting the data, the building operation and maintenance real-time simulation data, building structure real-time simulation data, building electromechanical real-time simulation data, building ventilation real-time simulation data and earthquake simulation data are obtained.

4. The BIM-based intelligent medical building design optimization method according to claim 1 is characterized in that: The step S105 includes: Compare the data in the revised BIM model simulation data set of the medical building with the expected simulation results of the medical building; If the comparison result shows that the data difference is greater than the preset error range, the BIM model or the dynamic data detection model still has deficiencies, and the dynamic data detection model is optimized, and the optimized dynamic data detection model is used to re-detect the BIM model simulation data set of the revised medical building; The revised BIM model simulation data set of the medical building is combined with the historical data of the BIM model of the medical building in the database. The BIM model of the medical building is optimized by combining historical data and real-time data. The optimized BIM model of the medical building is used to process the medical building construction data and the medical building construction user input data to obtain the optimized medical building construction operation and maintenance data.

5. A BIM-based intelligent medical building design optimization system, applied to the BIM-based intelligent medical building design optimization method, characterized in that: include: An acquisition unit is used to acquire a BIM model of a medical building, medical building construction data, and medical building construction user input data. The BIM model of a medical building includes a building operation and maintenance model, a building structure model, a building electromechanical model, a building ventilation model, and a seismic simulation model. The medical building construction data includes estimated medical building construction data and real-time medical building construction data. A data simulation unit is used to establish a mirror model for the BIM model of the medical building, obtain a mirror building operation and maintenance model, a mirror building structure model, a mirror building electromechanical model, a mirror building ventilation model, and a mirror building seismic simulation model, and substitute the estimated medical building construction data and the real-time medical building construction data into the mirror building operation and maintenance model, the mirror building structure model, the mirror building electromechanical model, the mirror building ventilation model, and the mirror building seismic simulation model in sequence to obtain the estimated simulation results of the medical building and the real-time data simulation results of the medical building; A data comparison unit is used to compare the medical building real-time data simulation result with the medical building expected simulation result to obtain the medical building real-time data comparison result; if the medical building real-time data comparison result is greater than a preset error range, the medical building real-time data is detected by a dynamic data detection model to obtain the medical building real-time data dynamic detection result; the medical building real-time data is corrected according to the medical building real-time data dynamic detection result to obtain the corrected medical building real-time data; A data matching unit is used to classify the corrected medical building real-time data to obtain the classified corrected medical building real-time data, establish a matching relationship between the classified corrected medical building real-time data and the building operation and maintenance model, building structure model, building electromechanical model, building ventilation model and earthquake simulation model in the BIM model of the medical building, substitute the classified corrected medical building real-time data into the corresponding model in the BIM model of the medical building, and obtain the building operation and maintenance real-time simulation data, building structure real-time simulation data, building electromechanical real-time simulation data, building ventilation real-time simulation data and earthquake simulation data; The optimization unit is used to aggregate the real-time simulation data of building operation and maintenance, the real-time simulation data of building structure, the real-time simulation data of building mechanical and electrical equipment, the real-time simulation data of building ventilation, and the real-time simulation data of earthquake and seismic construction to obtain a revised BIM model simulation data set of the medical building; if the data in the revised BIM model simulation data set of the medical building is compared with the expected simulation result of the medical building, and the comparison result is still greater than the preset error range, the dynamic data detection model is optimized, and the optimized dynamic data detection model is used to detect the revised BIM model simulation data set of the medical building to obtain a revised BIM model simulation data set of the medical building; the revised BIM model simulation data set of the medical building is used in combination with the historical data of the BIM model of the medical building in the database to optimize the BIM model of the medical building to obtain the optimized BIM model of the medical building; the BIM model of the medical building is used to process the construction data of the medical building and the user input data of the medical building construction to obtain the optimized construction and operation data of the medical building.

6. The BIM-based intelligent medical building design optimization system according to claim 5 is characterized in that: The data comparison unit is further used for: Compare the medical building real-time data simulation results with the medical building expected simulation results, set a preset error range, if the medical building data real-time comparison result is greater than the preset error range; The dynamic data detection model detects the real-time data of medical buildings. The dynamic data detection model accurately detects the real-time data of medical buildings. Through the dynamic data detection model, the dynamic detection results of the real-time data of medical buildings are obtained; According to the dynamic detection results of real-time data of medical buildings, the difference between real-time data and expected data is calculated, and the source of error is analyzed. If the error exceeds the preset range, data correction is required; According to the error analysis results, a preset correction method is applied to process the real-time data to obtain modified data, and the corrected data is verified to obtain verified corrected data.

7. The BIM-based intelligent medical building design optimization system according to claim 5 is characterized in that: The data matching unit is further used for: Classifying the corrected medical building real-time data, where the classification is based on the type, source, and timestamp information of the data, and obtaining a set of classified corrected medical building real-time data through the classification; Establish a matching relationship between the classified and corrected real-time data of medical buildings and the building operation and maintenance model, building structure model, building electromechanical model, building ventilation model and earthquake simulation model in the BIM model of the medical building, and substitute the classified and corrected real-time data of medical buildings into the corresponding models in the BIM model of the medical building. By substituting the data, the building operation and maintenance real-time simulation data, building structure real-time simulation data, building electromechanical real-time simulation data, building ventilation real-time simulation data and earthquake simulation data are obtained.

8. The BIM-based intelligent medical building design optimization system according to claim 5 is characterized in that: The optimization unit is further used for: Compare the data in the revised BIM model simulation data set of the medical building with the expected simulation results of the medical building; If the comparison result shows that the data difference is greater than the preset error range, the BIM model or the dynamic data detection model still has deficiencies, and the dynamic data detection model is optimized, and the optimized dynamic data detection model is used to re-detect the BIM model simulation data set of the revised medical building; The revised BIM model simulation data set of the medical building is combined with the historical data of the BIM model of the medical building in the database. The BIM model of the medical building is optimized by combining historical data and real-time data. The optimized BIM model of the medical building is used to process the medical building construction data and the medical building construction user input data to obtain the optimized medical building construction operation and maintenance data.

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