Model electronization verification optimization method, product, equipment and medium

Abstract

The invention relates to the technical field of model verification, in particular to a model electronization verification optimization method, a product, equipment and a medium. The method comprises the following steps: calling a constructed target model and target drawing parameters corresponding to the target model; inputting the target model and the target drawing parameters into a preset calibration model to obtain a parameter calibration result output by the preset calibration model; if the parameter verification result represents that the target model accords with the target drawing parameters, obtaining a simulation demand input by the user through the interactive interface; performing simulation analysis on the target model based on the simulation demand to obtain a simulation analysis result; and integrating the parameter calibration result and the simulation analysis result into a model calibration result of the target model. According to the invention, electronic comprehensive verification of the model can be realized.

Description

Technical Field

[0001] The present application relates to the field of model review technology, and in particular to a model electronic review optimization method, product, equipment and medium. Background Art

[0002] In the field of construction, Tekla Structures is used to build BIM building information models, allowing users to create, combine, manage and share accurate 3D models with rich information. The models can display various parts of the project in the form of three-dimensional models, making the project design more intuitive and visual.

[0003] The review of design models and construction drawings is an important part of ensuring construction quality and safety, so that the constructed model meets the requirements of the construction drawings. The traditional review process mainly relies on manual comparison of construction drawings and 3D building models. This method is not only time-consuming and labor-intensive, but also prone to errors due to human factors. Electronic review achieves a fast and accurate comparison of design models and construction drawings by introducing computer technology and information technology. However, the existing electronic review tools have a single function and it is difficult to achieve a comprehensive review of the model. Summary of the invention

[0004] In order to solve the problem of incomplete electronic review of models in the prior art, the present application provides a model electronic review optimization method, product, device and medium.

[0005] In the first aspect, the present application provides a model electronic review optimization method, which adopts the following technical solutions: A model electronic review optimization method, comprising: Retrieving the constructed target model and the target drawing parameters corresponding to the target model; Inputting the target model and the target drawing parameters into a preset review model to obtain a parameter review result output by the preset review model; If the parameter verification result indicates that the target model meets the target drawing parameters, then obtaining the simulation requirements input by the user through the interactive interface; Performing simulation analysis on the target model based on the simulation requirement to obtain a simulation analysis result; The parameter verification results and simulation analysis results are integrated into the model verification results of the target model.

[0006] By adopting the above technical solution, the target model and drawing parameters are retrieved to ensure the accuracy and pertinence of the review work. By presetting the review model, the automatic review of the target model and drawing parameters is realized, reducing manual intervention. Only when the target model and drawing parameters are consistent, the simulation requirements are determined, avoiding unnecessary simulation analysis. By obtaining the simulation requirements input by the user, the pertinence and personalized settings of the simulation analysis are ensured. Through simulation analysis, various situations in the actual application of the target model can be predicted, potential problems in the target model can be revealed, and guidance for optimized design can be provided. The parameter review results and simulation analysis results are integrated to ensure the comprehensiveness and accuracy of the target model review.

[0007] In a preferred example, the present application may be further configured as follows: the obtaining of the simulation requirements input by the user through the interactive interface includes: Sending simulation requirement options to the interactive interface; The simulation requirement selected by the user through the interactive interface is received, wherein the simulation requirement includes: one or more of mechanical simulation, fluid dynamics simulation, electromagnetic field simulation and fire simulation.

[0008] By adopting the above technical solution and sending simulation requirement options to the interactive interface, the system can display all available simulation types to the user in an intuitive manner, so that the user can clearly understand and select the simulation type they need, which greatly simplifies the operation process and improves the convenience and efficiency of user operation. The system supports users to select one or more of mechanical simulation, fluid dynamics simulation, electromagnetic field simulation and fire simulation. The system can handle a variety of different types of simulation requirements, thereby improving the flexibility and adaptability of the system.

[0009] In a preferred example, the present application may be further configured as follows: performing the mechanical simulation on the target model includes: Identify the material identification of each component in the target model, and extract material property parameters corresponding to the material identification from a preset material property library; extracting constraints from the target model; Perform mechanical simulation on the target model based on the material property parameters and the constraint conditions.

[0010] By adopting the above technical solution, the material identification of each component of the target model is identified and the corresponding material property parameters are extracted. At the same time, the constraints are extracted from the model, and then mechanical simulation analysis is performed based on these material properties and constraints. This can accurately evaluate the strength and stability of the civil structure, provide a scientific basis for drawing design and safety control, and effectively prevent potential risks.

[0011] In a preferred example, the present application may be further configured to: perform fluid dynamics simulation on the target model, including: Extracting geometric information of fluid system elements and fluid property information from the target model; acquiring fluid specification data, determining a first boundary condition of the fluid dynamics simulation based on the fluid specification data, A fluid dynamics simulation is performed on the target model based on the geometric information, the fluid property information and the first boundary condition.

[0012] By adopting the above technical solution, the geometric information and fluid property information of the target model are extracted, and the first boundary condition is set in combination with the fluid specification data. Fluid dynamics simulation can accurately simulate the operating status of the hydropower system and promptly discover and resolve potential drawing design defects and safety hazards.

[0013] In a preferred example, the present application may be further configured to: perform electromagnetic field simulation on the target model, including: extracting electrical property information and layout information of electrical system elements from the target model; Acquiring electrical specification data, and determining a second boundary condition for the electromagnetic field simulation based on the electrical specification data; An electromagnetic field simulation is performed on the target model based on the layout information, the electrical property information and the second boundary condition.

[0014] By adopting the above technical solution, the electrical property information and layout information of the target model are extracted, and the second boundary condition is set in combination with the electrical specification data. The electromagnetic field simulation can intuitively observe the distribution and changes of the electromagnetic field, providing strong support for design optimization, such as adjusting component positions, improving circuit layout, etc., to improve the electromagnetic performance and stability of the product.

[0015] In a preferred example, the present application may be further configured as follows: performing fire simulation on the target model, including: Acquiring historical fire data, wherein the historical fire data includes fire type, fire source location, fire source intensity, and environmental parameters; Setting simulated fire data for each fire type based on the fire source location, the fire source intensity and the environmental parameters; Obtain the evacuation path and expected personnel distribution of the target model; Firefighting simulation is performed on the target model based on the simulated fire data, the evacuation path and the expected personnel distribution.

[0016] By adopting the above technical solution, by integrating historical fire data with the evacuation path and expected personnel distribution of the target model, accurate simulated fire data can be set for various fire scenarios, and fire simulation analysis can be performed based on this. This can comprehensively evaluate the safety of buildings in fires and the efficiency of personnel evacuation, and on this basis, the rationality of the drawing parameter design can be judged.

[0017] In a preferred example, the present application can be further configured as follows: the method further includes: Acquire historical model parameters and historical drawing parameters, and set identifiers for model parameters and drawing parameters that represent the same component in the historical model parameters and the historical drawing parameters; Setting labels for model parameters and drawing parameters representing the same component, wherein the labels are used to represent parameter verification results; The model is trained based on the historical model parameters and historical drawing parameters after setting the identifiers and labels, and a trained preset review model is obtained.

[0018] By adopting the above technical solution, historical model parameters and historical drawing parameters are integrated, and identifiers and review result labels are set for parameters representing the same component, and then a preset review model is trained, which can automatically learn and identify the consistency between the model and the drawing, improve the accuracy and efficiency of parameter review, reduce human errors, and provide strong support for quality control in the architectural design and construction process.

[0019] In a second aspect, the present application provides a computer program product, which adopts the following technical solution: A computer program product includes a computer program. When the computer program is executed by a processor, it implements the model electronic review and optimization method as described in any one of the first aspects.

[0020] In a third aspect, the present application provides an electronic device, which adopts the following technical solution: one or more processors; Memory; At least one application, wherein the at least one application is stored in a memory and configured to be executed by at least one processor, and the at least one application is configured to: execute the model electronic review and optimization method as described in any one of the first aspects.

[0021] In a fourth aspect, the present application provides a computer-readable storage medium, which adopts the following technical solution: A computer-readable storage medium stores a computer program, which, when executed in a computer, causes the computer to execute the model electronic review and optimization method as described in any one of the first aspects.

[0022] In summary, this application includes the following beneficial technical effects: This application retrieves the target model and drawing parameters to ensure the accuracy and pertinence of the review work. By presetting the review model, it realizes the automatic review of the target model and drawing parameters, reduces manual intervention, and only when the target model and drawing parameters are consistent, the simulation requirements are determined, avoiding unnecessary simulation analysis. By obtaining the simulation requirements input by the user, the pertinence and personalized settings of the simulation analysis are ensured. Through simulation analysis, various situations in the actual application of the target model can be predicted, potential problems in the target model can be revealed, and guidance can be provided for optimized design. The parameter review results and simulation analysis results are integrated to ensure the comprehensiveness and accuracy of the target model review. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 It is a flow chart of a model electronic review optimization method provided in an embodiment of the present application; Figure 2 It is a structural schematic diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0024] The following is combined with Figure 1 -Attached Figure 2 This application is described in further detail.

[0025] This specific embodiment is merely an explanation of the present application and is not a limitation of the present application. After reading this specification, those skilled in the art may make modifications to the present embodiment without any creative contribution as needed. However, as long as it is within the scope of the claims of the present application, it shall be protected by the patent law.

[0026] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0027] In addition, the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article, unless otherwise specified, generally means that the associated objects before and after are in an "or" relationship.

[0028] It should be noted that in the optional embodiments of the present application, the object information and other related data involved, when the embodiments in the present application are applied to specific products or technologies, need to obtain the permission or consent of the object, and the collection, use and processing of the relevant data need to comply with the relevant laws, regulations and standards of the relevant countries and regions. In other words, if the embodiments of the present application involve data related to the object, it needs to be obtained with the authorization and consent of the object, the authorization and consent of the relevant departments, and in compliance with the relevant laws, regulations and standards of the country and region. If personal information is involved in the embodiments, the acquisition of all personal information needs to obtain the consent of the individual. If sensitive information is involved, the separate consent of the information subject needs to be obtained. The embodiments also need to be implemented with the authorization and consent of the object.

[0029] The present application embodiment provides a model electronic review optimization method, such as Figure 1 As shown, the method provided in the embodiment of the present application is performed by an electronic device, which can be a server or a terminal device, wherein the server can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services. The terminal device can be a smart phone, a tablet computer, a laptop computer, a desktop computer, etc., but is not limited thereto. The terminal device and the server can be directly or indirectly connected via wired or wireless communication, which is not limited in the embodiment of the present application. The method includes steps S101 to S105, wherein: S101, retrieve the constructed target model and the target drawing parameters corresponding to the target model.

[0030] Specifically, technicians can build a BIM model as a target model based on construction drawings and actual needs and store it in the database of the electronic device. At the same time, the database also stores the drawing parameters of the construction drawings. The drawing parameters are used as construction specifications, including size, material, location and other information. The drawing parameters are stored in the database in digital form. The drawing parameters are used to compare with the information of the target model to ensure the consistency of the model and the drawings.

[0031] S102, inputting the target model and target drawing parameters into a preset review model to obtain the parameter review result output by the preset review model.

[0032] Specifically, the data in the target model and the target drawing parameters correspond one-to-one through identifiers, and the data with the same identifier represent the same component. The attribute characteristics of the component, such as size, color, and material, are associated with the identifier. The preset review model can be built based on machine learning and deep learning algorithms. The preset review model accurately matches and compares the model parameters and drawing parameters representing the same component by identifying the identifier, and can automatically compare the information in the target model and the target drawing parameters, and output the parameter review results. The parameter review results include the consistency determination results of the data in the target model and the target drawing parameters.

[0033] S103: If the parameter verification result indicates that the target model meets the target drawing parameters, then the simulation requirements input by the user through the interactive interface are obtained.

[0034] If there is a data mismatch in the parameter verification result, a prompt signal can be sent to the technician's terminal device to remind the technician to correct the model through the prompt signal. The prompt signal includes mismatched data information. When the electronic device receives the correction completion signal sent by the technician, it re-compares the target model and the target drawing parameters through the preset verification model to obtain the parameter verification result. The above process is repeated until the parameter verification result output by the preset verification model is that the target model meets the target drawing parameters.

[0035] If the parameter review result indicates that the target model meets the target drawing parameters, simulation requirement options are sent to the interactive interface for the user to select. The user can be a technician who reviews the drawing parameters. The user selects one or more simulation requirement options based on actual needs. The simulation requirements include: one or more of mechanical simulation, fluid dynamics simulation, electromagnetic field simulation and fire simulation.

[0036] S104: Perform simulation analysis on the target model based on the simulation requirements to obtain simulation analysis results.

[0037] S105, integrating the parameter verification results and the simulation analysis results into the model verification results of the target model.

[0038] This embodiment ensures the accuracy and pertinence of the review work by retrieving the target model and drawing parameters. By presetting the review model, it realizes the automatic review of the target model and drawing parameters, reduces manual intervention, and only when the target model is consistent with the drawing parameters, the simulation requirements are determined, avoiding unnecessary simulation analysis. By obtaining the simulation requirements input by the user, the pertinence and personalized setting of the simulation analysis are ensured. Through simulation analysis, various situations in the actual application of the target model can be predicted, potential problems in the target model can be revealed, and guidance for optimized design can be provided. The parameter review results and simulation analysis results are integrated to ensure the comprehensiveness and accuracy of the target model review.

[0039] A possible implementation of the embodiment of the present application is to obtain a simulation requirement input by a user through an interactive interface, including: Send simulation requirement options to the interactive interface; The simulation requirements selected by the user through the interactive interface are received, and the simulation requirements include: one or more of mechanical simulation, fluid dynamics simulation, electromagnetic field simulation and fire simulation.

[0040] In this embodiment, by sending simulation requirement options to the interactive interface, the system can display all available simulation types to the user in an intuitive manner, so that the user can clearly understand and select the simulation type they need, which greatly simplifies the operation process and improves the convenience and efficiency of user operation. The system supports users to select one or more of mechanical simulation, fluid dynamics simulation, electromagnetic field simulation and fire simulation. The system can handle a variety of different types of simulation requirements, thereby improving the flexibility and adaptability of the system.

[0041] A possible implementation of the embodiment of the present application is to perform mechanical simulation on the target model, including: Identify the material identification of each component in the target model, and extract the material property parameters corresponding to the material identification from the preset material property library; Extract constraints from the target model; Perform mechanical simulation on the target model based on material property parameters and constraint conditions.

[0042] In this embodiment, a unique identifier corresponding to each component is identified, and a material identifier is associated with the identifier. The material identifier is used to characterize the material type. Material property parameters of the material type are extracted from a preset material property library based on the material identifier. The material property parameters include material density, elastic modulus, Poisson's ratio, yield strength, etc.

[0043] Furthermore, the constraint conditions include boundary conditions and load conditions. For boundary conditions, the components that need to be completely fixed, such as foundations and connection points, can be identified from the target model. After these components are determined, fixed end constraints are set for them to limit their movement and rotation in all directions; for components that allow rotation but limit movement, hinge constraints can be set for them; for components that allow movement in a certain direction but limit movement in other directions, sliding bracket constraints can be set. The constraints that need to be added to each component can be determined in advance by technicians according to construction requirements and stored in the database. The setting of constraint conditions can be achieved through plug-ins or integrated tools of BIM software (such as Tekla Structures), which can automatically identify the construction in the target model and automatically apply corresponding constraints to it.

[0044] For load conditions, gravity can be included. BIM software can automatically identify the mass distribution in the model and calculate the gravity load. Wind load, snow load, and live load (including people, homes, etc.) can also be applied. For wind load and snow load, they can be implemented through the wind load analysis tool and snow load analysis tool of the BIM software. For live load, it can be estimated by technicians based on the actual application scenario of the target model and input into the electronic device. For example, assuming that the target model is a residential building model, the live load can be estimated based on the number of users in the target model.

[0045] Furthermore, the above constraints and material property parameters are loaded by simulation software to perform mechanical simulation on the target model. After the simulation is completed, the simulation analysis results are extracted from the simulation software. The simulation analysis results include stress distribution diagrams, strain distribution diagrams, and displacement distribution diagrams, etc. Key information such as maximum stress value and maximum strain value can also be extracted.

[0046] This embodiment identifies the material identification of each component of the target model and extracts the corresponding material property parameters, while extracting the constraints from the model, and then performs mechanical simulation analysis based on these material properties and constraints. It can accurately evaluate the strength and stability of the civil structure, provide a scientific basis for drawing design and safety control, and effectively prevent potential risks.

[0047] A possible implementation of the embodiment of the present application is to perform fluid dynamics simulation on the target model, including: Extracting geometric information of fluid system elements and fluid property information from the target model; Obtaining fluid specification data, determining a first boundary condition for fluid dynamics simulation based on the fluid specification data, The fluid dynamics simulation is performed on the target model based on the geometric information, the fluid property information and the first boundary condition.

[0048] In this embodiment, the geometric information of the fluid system elements includes the location of the pipe size and shape, and the fluid property information includes the fluid type, flow rate, and pressure. The fluid property information can be manually annotated in the process of building the target model. The fluid specification data related to the fluid system is obtained by accessing the fluid specification database, including the maximum pressure limit of the pipeline material and the safe range of the fluid flow rate. The extracted fluid specification data is used as the first boundary condition, and the first boundary condition includes the inlet flow rate limit, the outlet flow rate limit, and the wall pressure limit. Then, the geometric information, the fluid property information, and the first boundary condition are imported into the simulation software, and the simulation software uses numerical methods (such as finite volume method, finite difference method, etc.) to solve the fluid dynamics equations to obtain the dynamic response of the fluid system. After the simulation is completed, the fluid dynamics simulation analysis results, such as flow velocity distribution, pressure distribution, vortex structure, etc., are extracted, and these results can be displayed and analyzed through visualization tools (such as color cloud maps, vector diagrams, etc.).

[0049] This embodiment extracts the geometric information and fluid property information of the target model, sets the first boundary condition in combination with the fluid specification data, and performs fluid dynamics simulation to accurately simulate the operating state of the hydropower system, and promptly discover and resolve potential drawing design defects and safety hazards.

[0050] A possible implementation of the embodiment of the present application is to perform electromagnetic field simulation on the target model, including: Extract electrical property information and layout information of electrical system elements from the target model; Acquiring electrical specification data, and determining a second boundary condition for electromagnetic field simulation based on the electrical specification data; Perform electromagnetic field simulation on the target model based on layout information, electrical property information and the second boundary condition.

[0051] In this embodiment, for electromagnetic field simulation, electrical property information includes voltage, current, and resistance, and layout information includes the location of electrical equipment and the direction of the line. Access the electrical specification database to obtain electrical specification data related to the electrical system, including current limit, voltage fluctuation range limit, and electromagnetic radiation standard. Use the electrical specification data as the second boundary condition. Then, the layout information, electrical property information, and the second boundary condition are input into the simulation software, and the simulation software will use numerical methods (such as finite element method, finite difference method, etc.) to solve Maxwell's equations to obtain the distribution and dynamic response of the electromagnetic field. After the simulation is completed, the electromagnetic field simulation analysis results are extracted, such as electric field intensity distribution, magnetic field intensity distribution, electromagnetic radiation level, etc., which can be displayed and analyzed through visualization tools.

[0052] This embodiment extracts the electrical property information and layout information of the target model, sets the second boundary condition in combination with the electrical specification data, and performs electromagnetic field simulation to intuitively observe the distribution and changes of the electromagnetic field, providing strong support for design optimization, such as adjusting component positions, improving circuit layout, etc., to improve the electromagnetic performance and stability of the product.

[0053] A possible implementation of the embodiment of the present application is to perform fire simulation on the target model, including: Obtain historical fire data, including fire type, fire source location, fire source intensity and environmental parameters; Set up simulated fire data for each fire type based on fire source location, fire source intensity and environmental parameters; Obtain the evacuation path and expected personnel distribution of the target model; Firefighting simulation is performed on the target model based on simulated fire data, evacuation routes and expected occupant distribution.

[0054] In this embodiment, the historical fire data may include data of a historical fire corresponding to each fire type, the fire type may include electrical fire and chemical fire, the fire source intensity may represent the heat release rate, and the environmental parameters may include temperature, humidity and wind speed. For any fire type, the fire source location, fire source intensity and environmental parameters in the historical fire data corresponding to the fire type are used as simulated fire data.

[0055] The evacuation path of the actual building corresponding to the target model can be obtained from the target model, and the expected distribution of personnel can be predicted by technicians through population density models or based on actual data and input into electronic equipment. The simulated fire data, evacuation path and expected distribution of personnel are imported into the simulation software, and the simulation analysis results can include simulated video of fire spread, evacuation time, casualty prediction, etc.

[0056] This embodiment integrates historical fire data with the evacuation path and expected personnel distribution of the target model, sets accurate simulated fire data for various fire scenarios, and conducts fire simulation analysis based on this data. It can comprehensively evaluate the safety of buildings and the efficiency of personnel evacuation in fires, and on this basis, it can judge the rationality of the design of drawing parameters.

[0057] In a possible implementation manner of the embodiment of the present application, the method further includes: Acquire historical model parameters and historical drawing parameters, and set identifiers for model parameters and drawing parameters that represent the same component in the historical model parameters and historical drawing parameters; Set labels for model parameters and drawing parameters that represent the same component. The labels are used to represent parameter verification results. The model is trained based on the historical model parameters and historical drawing parameters after setting the identifiers and labels, and a trained preset review model is obtained.

[0058] In this embodiment, historical model parameters and historical drawing parameters are collected from a database or a file storage system to ensure that the collected data contains model parameters and drawing parameters for the same component. The historical data is traversed, and a unique identifier (such as a component ID) is set for the model parameters and drawing parameters that characterize the same component to ensure that each component can be matched in the model parameters and drawing parameters through the identifier. According to the review records of the historical data, a label is set for each pair of matching model parameters and drawing parameters, and the label should clearly reflect the review results, such as "passed", "failed", etc. The data set with identifiers and labels is divided into a training set and a validation set (or test set), and the ratio can be 80% training set and 20% validation set. A machine learning or deep learning model is selected, and the optional models include: decision tree, random forest, support vector machine, neural network, etc. The selected model is trained using the training set data, and the input is the model parameters and drawing parameters after feature extraction, and the output is the label. The trained model is verified using the validation set data to evaluate the accuracy and generalization ability of the model. The trained preset review model is deployed to the production environment to automatically review the newly submitted model parameters and drawing parameters.

[0059] This embodiment integrates historical model parameters and historical drawing parameters, sets identifiers and verification result labels for parameters representing the same component, and then trains a preset verification model. The model can automatically learn and identify the consistency between the model and the drawing, improve the accuracy and efficiency of parameter verification, reduce human errors, and provide strong support for quality control in the architectural design and construction process.

[0060] In a possible implementation manner of the embodiment of the present application, the method further includes: Receive manual review results for the target model uploaded by multiple reviewers; Determine the review progress of each reviewer based on the manual review results, and generate a comprehensive review progress by combining the review progress of each reviewer; The comprehensive review progress is sent to each reviewer's terminal device.

[0061] This embodiment receives manual review results from multiple reviewers, tracks the progress of each reviewer in real time and generates a comprehensive review progress, and then feeds back the progress information to each reviewer, thereby effectively improving the collaborative efficiency and transparency of the review work and ensuring the smooth progress and timely completion of the review process.

[0062] An embodiment of the present application provides a computer program product, including a computer program. When the computer program is executed by a processor, the contents shown in the aforementioned model electronic review and optimization method embodiment are implemented.

[0063] An electronic device is provided in an embodiment of the present application, such as Figure 2 As shown, Figure 2 The electronic device 200 shown includes: a processor 201 and a memory 203. The processor 201 and the memory 203 are connected, such as through a bus 202. Optionally, the electronic device 200 may also include a transceiver 204. It should be noted that in actual applications, the transceiver 204 is not limited to one, and the structure of the electronic device 200 does not constitute a limitation on the embodiments of the present application.

[0064] The processor 201 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array) or other programmable logic devices, transistor logic devices, hardware components or any combination thereof. It may implement or execute various exemplary logic blocks, modules and circuits described in conjunction with the disclosure of this application. The processor 201 may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0065] The bus 202 may include a path to transmit information between the above components. The bus 202 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus. The bus 202 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 2 Only one thick line is used in the diagram, but it does not mean that there is only one bus or only one type of bus.

[0066] The memory 203 may be a ROM (Read Only Memory) or other types of static storage devices that can store static information and instructions, a RAM (Random Access Memory) or other types of dynamic storage devices that can store information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory) or other optical disk storage, optical disk storage (including compressed optical disk, laser disk, optical disk, digital versatile disk, Blu-ray disk, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto.

[0067] The memory 203 is used to store the application code for executing the solution of the present application, and the execution is controlled by the processor 201. The processor 201 is used to execute the application code stored in the memory 203 to implement the contents shown in the above-mentioned embodiment of the electronic model review optimization method.

[0068] Figure 2 The electronic device shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0069] An embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon. When the computer-readable storage medium is run on a computer, the computer can execute the contents shown in the aforementioned embodiment of the model electronic review and optimization method.

[0070] It should be understood that, although the steps in the flowchart of the accompanying drawings are displayed in sequence as indicated by the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least a part of the steps in the flowchart of the accompanying drawings may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be executed in turn or alternately with other steps or at least a part of the sub-steps or stages of other steps.

[0071] The above are only some implementation methods of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A model electronic review optimization method, characterized in that: include: Retrieving the constructed target model and the target drawing parameters corresponding to the target model; Inputting the target model and the target drawing parameters into a preset review model to obtain a parameter review result output by the preset review model; If the parameter verification result indicates that the target model meets the target drawing parameters, then obtaining the simulation requirements input by the user through the interactive interface; Performing simulation analysis on the target model based on the simulation requirement to obtain a simulation analysis result; The parameter verification results and simulation analysis results are integrated into the model verification results of the target model.

2. The model electronic review and optimization method according to claim 1, characterized in that: The obtaining of the simulation requirement input by the user through the interactive interface includes: Sending simulation requirement options to the interactive interface; The simulation requirement selected by the user through the interactive interface is received, wherein the simulation requirement includes: one or more of mechanical simulation, fluid dynamics simulation, electromagnetic field simulation and fire simulation.

3. The model electronic review and optimization method according to claim 2, characterized in that: Performing the mechanical simulation on the target model includes: Identify the material identification of each component in the target model, and extract material property parameters corresponding to the material identification from a preset material property library; extracting constraints from the target model; Perform mechanical simulation on the target model based on the material property parameters and the constraint conditions.

4. The model electronic review and optimization method according to claim 2, characterized in that: Performing fluid dynamics simulation on the target model, including: Extracting geometric information of fluid system elements and fluid property information from the target model; acquiring fluid specification data, determining a first boundary condition for the fluid dynamics simulation based on the fluid specification data, A fluid dynamics simulation is performed on the target model based on the geometric information, the fluid property information and the first boundary condition.

5. The model electronic review and optimization method according to claim 2, characterized in that: Performing electromagnetic field simulation on the target model includes: extracting electrical property information and layout information of electrical system elements from the target model; Acquiring electrical specification data, and determining a second boundary condition for the electromagnetic field simulation based on the electrical specification data; An electromagnetic field simulation is performed on the target model based on the layout information, the electrical property information and the second boundary condition.

6. The model electronic review and optimization method according to claim 2, characterized in that: Performing firefighting simulation on the target model includes: Acquiring historical fire data, wherein the historical fire data includes fire type, fire source location, fire source intensity, and environmental parameters; Setting simulated fire data for each fire type based on the fire source location, the fire source intensity and the environmental parameters; Obtain the evacuation path and expected personnel distribution of the target model; Firefighting simulation is performed on the target model based on the simulated fire data, the evacuation path and the expected personnel distribution.

7. The model electronic review and optimization method according to claim 1, characterized in that: The method further comprises: Acquire historical model parameters and historical drawing parameters, and set identifiers for model parameters and drawing parameters that represent the same component in the historical model parameters and the historical drawing parameters; Setting labels for model parameters and drawing parameters representing the same component, wherein the labels are used to represent parameter verification results; The model is trained based on the historical model parameters and historical drawing parameters after setting the identifiers and labels, and a trained preset review model is obtained.

8. A computer program product, characterized in that It comprises a computer program, which, when executed by a processor, implements the steps of the model electronic review and optimization method described in any one of claims 1 to 7.

9. An electronic device, characterized in that: include: at least one processor; Memory; At least one application, wherein the at least one application is stored in a memory and configured to be executed by at least one processor, and the at least one application is configured to: execute the model electronic review and optimization method described in any one of claims 1-7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed in a computer, the computer is caused to execute the model electronic review and optimization method described in any one of claims 1-7.

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