Three-dimensional simulation method based on model construction

Abstract

The invention belongs to the field of three-dimensional simulation, particularly relates to a three-dimensional simulation method based on model construction, and aims to solve the problems that simulation operation of a virtual environment is inconvenient and found problems cannot be timely processed in the prior art, and the method comprises the following steps: S1, building a three-dimensional simulation system, the three-dimensional simulation system comprises a data acquisition module, a model establishment module, a simulation environment setting module, a simulation calculation module, a simulation rendering module, a simulation operation module, a result analysis module, a problem acquisition module, an optimization matching module, a statistics module, a classification sorting module, an output module, a big data acquisition module and a scheme setting module. An execution module and a result feedback module; s2, geometric and physical data of a real object are obtained through the data collection module, simulation operation is conducted on the constructed three-dimensional simulation model, problems can be found in time, an optimization scheme can be matched in time, and the problems can be solved easily.

Description

Technical Field

[0001] The present invention relates to the technical field of three-dimensional simulation, and in particular to a three-dimensional simulation method based on model construction. Background Art

[0002] 3D simulation refers to a technology that uses computer technology to generate a realistic virtual environment with multiple senses such as sight, hearing, touch, and taste. Users can use various sensory devices through their natural skills to interact with entities in the virtual environment.

[0003] Announcement No.: CN116090405B discloses a three-dimensional simulation method, device, equipment and storage medium. The method includes: reading the data to be simulated; judging whether the data to be simulated is in gerber format or drilling file format; if the data to be simulated is in gerber format or drilling file format, when the data to be simulated is in gerber format, generating node data based on the operation command and coordinates of the data to be simulated, and generating PCB simulation data based on the node data; when the data to be simulated is in drilling file format, generating drilling preview data based on the drilling size and drilling coordinates of the data to be simulated, and generating PCB simulation data based on the drilling preview data; performing three-dimensional modeling and imaging processing on the PCB simulation data based on the webgl protocol to obtain three-dimensional simulation data.

[0004] In the prior art, after the three-dimensional simulation constructs the virtual environment, it is not convenient to simulate and run the virtual environment, and the problems found cannot be dealt with in time. Therefore, we propose a three-dimensional simulation method based on model construction to solve the above problems. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art that it is inconvenient to simulate and run a virtual environment and that the problems found cannot be dealt with in a timely manner, and a three-dimensional simulation method based on model construction is proposed.

[0006] In order to achieve the above object, the present invention adopts the following technical solutions:

[0007] The three-dimensional simulation method based on model construction includes the following steps:

[0008] S1. Build a three-dimensional simulation system, which includes a data acquisition module, a model building module, a simulation environment setting module, a simulation calculation module, a simulation rendering module, a simulation operation module, a result analysis module, a problem collection module, an optimization matching module, a statistics module, a classification and sorting module, an output module, a big data collection module, a solution setting module, an execution module and a result feedback module;

[0009] S2. The geometric and physical data of real objects are acquired through the data acquisition module to provide a basis for subsequent modeling. The environment parameters required for simulation are configured through the simulation environment setting module. A detailed three-dimensional model is established according to the acquired data through the model building module, and texture mapping is performed.

[0010] S3, dynamically simulate and render the model through the simulation calculation module and the simulation rendering module, simulate and run the constructed model through the simulation operation module, observe the results, and analyze the observed results through the result analysis module;

[0011] S4. The problem collection module extracts the problems that occur during simulation operation based on the analysis results. The optimization matching module matches the corresponding optimization plan based on the problems that occur. The optimization plan is executed through the execution module, and the result feedback module feeds back the execution results.

[0012] Preferably, the statistical module is used to count the problems collected by the problem collection module, classify and sort the problems through the classification and sorting module, and output the sorted content through the output module.

[0013] Preferably, the big data acquisition module includes a historical data acquisition unit, a data processing unit, a data identification unit and a data classification unit, the historical data acquisition unit is connected to the data processing unit, the data processing unit is connected to the data identification unit, and the data identification unit is connected to the data classification unit.

[0014] Preferably, the simulation environment setting module includes a hardware configuration unit, a software configuration unit, an environment parameter configuration unit and a confirmation unit. The hardware configuration unit is specifically as follows: Computer: must meet certain configurations, including CPU, memory, and graphics card to ensure the smoothness and effect of simulation operation; special external hardware: including external head-mounted devices and control handles to provide immersive VR experience; other devices: such as VR control platforms and projectors, are configured according to specific needs; the software configuration unit is specifically as follows: Operating system: such as Windows, must meet the running requirements of simulation software; Simulation software: select three-dimensional simulation software, such as Gazebo, for building and running the simulation environment; Related APIs and tools: including those for model import and script writing to improve simulation efficiency and flexibility.

[0015] Preferably, the environmental parameter configuration unit includes a gravity setting subunit, a lighting setting subunit, a material property setting subunit and a boundary condition setting subunit.

[0016] Preferably, the model building module is used to select modeling software, including AutoCAD and 3dsMax, according to modeling requirements; use the modeling software to convert the sketch into a real three-dimensional model, and increase the details and complexity of the model through subdivision and carving tools; add texture and material: add appropriate texture and material to the model.

[0017] Preferably, the simulation calculation module and the simulation rendering module dynamically simulate and render the model through a physical engine and a simulation algorithm. The physical engine calculates motion, rotation and collision reactions by giving real physical properties to rigid objects, including momentum, torque or elasticity. It enables objects in the simulation to operate according to physical parameters, providing a highly realistic experience. Physical engines include Bullet and PhysX.

[0018] Preferably, the result analysis module is used to collect the required data; then, the data is cleaned and preprocessed to eliminate noise and errors; then, descriptive statistical analysis is performed, including calculating the mean and variance to understand the overall characteristics of the data; inferential statistical analysis is performed, including hypothesis testing and regression analysis, to draw conclusions about the population from the sample data; finally, the analysis results are presented using data visualization technology to help users intuitively understand data patterns and trends.

[0019] Preferably, the big data acquisition module is used to obtain data from outside the system and input it into the system for statistics and analysis, collect simulation operation problems that have occurred and corresponding optimization solutions, and associate simulation operation problems with their optimization solutions.

[0020] Preferably, the solution setting module is used to store the associated simulation operation problems and their associated optimization solutions, and when receiving the problems sent by the optimization matching module, perform similarity matching on the problems, and after matching the same problems, feed back the associated optimization solutions.

[0021] In the present invention, the beneficial effects of the three-dimensional simulation method based on model construction are:

[0022] The data acquisition module is used to obtain the geometric and physical data of real objects, providing a basis for subsequent modeling. The simulation environment setting module is used to configure the environmental parameters required for simulation. The model building module is used to build a detailed three-dimensional model based on the collected data and perform texture mapping.

[0023] The model is dynamically simulated and rendered through the simulation calculation module and the simulation rendering module. The constructed model is simulated and run through the simulation operation module, and the results are observed. The results are analyzed through the result analysis module. The problem collection module extracts the problems that occur in the simulation operation according to the analysis results. The optimization matching module matches the corresponding optimization plan according to the problems that occur. The optimization plan is executed through the execution module, and the result feedback module feeds back the execution results.

[0024] The present invention can timely discover problems and timely match optimization solutions by simulating the constructed three-dimensional simulation model, which is conducive to solving the problems. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 A block diagram of a three-dimensional simulation system of a three-dimensional simulation method based on model building proposed by the present invention;

[0026] Figure 2 A block diagram of a big data acquisition module of a three-dimensional simulation method based on model building proposed by the present invention;

[0027] Figure 3 A block diagram of a simulation environment setting module of the three-dimensional simulation method based on model construction proposed by the present invention;

[0028] Figure 4 A block diagram of a simulation operation module of the three-dimensional simulation method based on model construction proposed by the present invention;

[0029] Figure 5 The present invention provides a block diagram of an environmental parameter configuration unit for a three-dimensional simulation method based on model construction. DETAILED DESCRIPTION

[0030] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0031] Embodiment 1

[0032] Reference Figure 1-Figure 5 , a three-dimensional simulation method based on model construction includes the following steps:

[0033] S1. Build a three-dimensional simulation system, which includes a data acquisition module, a model building module, a simulation environment setting module, a simulation calculation module, a simulation rendering module, a simulation operation module, a result analysis module, a problem collection module, an optimization matching module, a statistics module, a classification and sorting module, an output module, a big data collection module, a solution setting module, an execution module and a result feedback module;

[0034] S2. The geometric and physical data of real objects are acquired through the data acquisition module to provide a basis for subsequent modeling. The environment parameters required for simulation are configured through the simulation environment setting module. A detailed three-dimensional model is established according to the acquired data through the model building module, and texture mapping is performed.

[0035] S3, dynamically simulate and render the model through the simulation calculation module and the simulation rendering module, simulate and run the constructed model through the simulation operation module, observe the results, and analyze the observed results through the result analysis module;

[0036] S4. The problem collection module extracts the problems that occur during simulation operation based on the analysis results. The optimization matching module matches the corresponding optimization plan based on the problems that occur. The optimization plan is executed through the execution module, and the result feedback module feeds back the execution results.

[0037] In this embodiment, the statistics module is used to count the problems collected by the problem collection module, classify and sort the problems through the classification and sorting module, and output the sorted content through the output module.

[0038] In this embodiment, the big data acquisition module includes a historical data acquisition unit, a data processing unit, a data identification unit and a data classification unit. The historical data acquisition unit is connected to the data processing unit, the data processing unit is connected to the data identification unit, and the data identification unit is connected to the data classification unit.

[0039] In this embodiment, the simulation environment setting module includes a hardware configuration unit, a software configuration unit, an environment parameter configuration unit and a confirmation unit. The hardware configuration unit is specifically as follows: Computer: must meet certain configurations, including CPU, memory, and graphics card to ensure the smoothness and effect of simulation operation; special external hardware: including external head-mounted devices and control handles to provide immersive VR experience; other devices: such as VR control platforms and projectors, are configured according to specific needs; the software configuration unit is specifically as follows: Operating system: such as Windows, must meet the running requirements of simulation software; Simulation software: select three-dimensional simulation software, such as Gazebo, for building and running the simulation environment; Related APIs and tools: including those for model import and script writing to improve simulation efficiency and flexibility.

[0040] In this embodiment, the environmental parameter configuration unit includes a gravity setting subunit, a lighting setting subunit, a material property setting subunit and a boundary condition setting subunit.

[0041] In this embodiment, the model building module is used to select modeling software according to modeling requirements, including AutoCAD and 3dsMax; use the modeling software to convert the sketch into a real three-dimensional model, and increase the details and complexity of the model through subdivision and carving tools; add textures and materials: add appropriate textures and materials to the model.

[0042] In this embodiment, the simulation calculation module and the simulation rendering module dynamically simulate and render the model through the physical engine and simulation algorithm. The physical engine calculates the motion, rotation and collision reaction by giving real physical properties to rigid objects, including momentum, torque or elasticity. It enables the objects in the simulation to operate according to physical parameters and provide a highly realistic experience. The physical engines include Bullet and PhysX.

[0043] In this embodiment, the result analysis module is used to collect the required data; then, the data is cleaned and preprocessed to eliminate noise and errors; then, descriptive statistical analysis is performed, including calculating the mean and variance to understand the overall characteristics of the data; inferential statistical analysis is performed, including hypothesis testing and regression analysis, to draw conclusions about the population from the sample data; finally, the analysis results are presented using data visualization technology to help users intuitively understand data patterns and trends.

[0044] In this embodiment, the big data acquisition module is used to obtain data from outside the system and input it into the system for statistics and analysis, collect simulation operation problems that have occurred and corresponding optimization solutions, and associate simulation operation problems with their optimization solutions.

[0045] In this embodiment, the solution setting module is used to store the associated simulation operation problems and their associated optimization solutions. When receiving the problems sent by the optimization matching module, the similarity matching is performed on the problems. After matching the same problems, the associated optimization solutions are fed back.

[0046] Embodiment 2

[0047] The difference between this embodiment and the first embodiment is that the three-dimensional simulation method based on model construction includes the following steps:

[0048] S1. Build a three-dimensional simulation system, which includes a data acquisition module, a model building module, a simulation environment setting module, a simulation calculation module, a simulation rendering module, a simulation operation module, a result analysis module, a problem collection module, an optimization matching module, a statistics module, a classification and sorting module, an output module, a big data collection module, a solution setting module, an execution module, a result feedback module, and an effect evaluation module;

[0049] S2. The geometric and physical data of real objects are acquired through the data acquisition module to provide a basis for subsequent modeling. The environment parameters required for simulation are configured through the simulation environment setting module. A detailed three-dimensional model is established according to the acquired data through the model building module, and texture mapping is performed.

[0050] S3, dynamically simulate and render the model through the simulation calculation module and the simulation rendering module, simulate and run the constructed model through the simulation operation module, observe the results, and analyze the observed results through the result analysis module;

[0051] S4. The problem collection module extracts the problems that occur during simulation operation based on the analysis results. The optimization matching module matches the corresponding optimization plan based on the problems that occur. The optimization plan is executed by the execution module. The result feedback module feeds back the execution results. The optimization effect after the execution of the optimization plan is evaluated by the effect evaluation module.

[0052] Embodiment 3

[0053] The difference from the first embodiment is that:

[0054] The three-dimensional simulation method based on model construction includes the following steps:

[0055] S1. Build a three-dimensional simulation system, which includes a data acquisition module, a model building module, a simulation environment setting module, a simulation calculation module, a simulation rendering module, a simulation operation module, a result analysis module, a problem collection module, an optimization matching module, a statistics module, a classification and sorting module, an output module, a big data collection module, a solution setting module, an execution module, a result feedback module and a traceability module;

[0056] S2. The geometric and physical data of real objects are acquired through the data acquisition module to provide a basis for subsequent modeling. The environment parameters required for simulation are configured through the simulation environment setting module. A detailed three-dimensional model is established according to the acquired data through the model building module, and texture mapping is performed.

[0057] S3, dynamically simulate and render the model through the simulation calculation module and the simulation rendering module, simulate and run the constructed model through the simulation operation module, observe the results, and analyze the observed results through the result analysis module;

[0058] S4. The problem collection module extracts the problems that occur during simulation operation based on the analysis results. The optimization matching module matches the corresponding optimization plan based on the problems that occur. The optimization plan is executed through the execution module, and the result feedback module feeds back the execution results.

[0059] In this embodiment, the big data acquisition module is used to obtain data from outside the system and input it into the system for statistics and analysis, collect simulation operation problems that have occurred and corresponding optimization solutions, associate simulation operation problems with their optimization solutions, and register the data collected by the big data acquisition module through the traceability tracking module to facilitate later traceability.

[0060] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A three-dimensional simulation method based on model construction, characterized in that: The following steps are involved: S1. Build a three-dimensional simulation system, which includes a data acquisition module, a model building module, a simulation environment setting module, a simulation calculation module, a simulation rendering module, a simulation operation module, a result analysis module, a problem collection module, an optimization matching module, a statistics module, a classification and sorting module, an output module, a big data collection module, a solution setting module, an execution module and a result feedback module; S2. The geometric and physical data of real objects are acquired through the data acquisition module to provide a basis for subsequent modeling. The environment parameters required for simulation are configured through the simulation environment setting module. A detailed three-dimensional model is established according to the acquired data through the model building module, and texture mapping is performed. S3, dynamically simulate and render the model through the simulation calculation module and the simulation rendering module, simulate and run the constructed model through the simulation operation module, observe the results, and analyze the observed results through the result analysis module; S4. The problem collection module extracts the problems that occur during simulation operation based on the analysis results. The optimization matching module matches the corresponding optimization plan based on the problems that occur. The optimization plan is executed through the execution module, and the result feedback module feeds back the execution results.

2. The three-dimensional simulation method based on model building according to claim 1, characterized in that: The statistical module is used to count the problems collected by the problem collection module, classify and sort the problems through the classification and sorting module, and output the sorted content through the output module.

3. The three-dimensional simulation method based on model building according to claim 2, characterized in that: The big data acquisition module includes a historical data acquisition unit, a data processing unit, a data identification unit and a data classification unit. The historical data acquisition unit is connected to the data processing unit, the data processing unit is connected to the data identification unit, and the data identification unit is connected to the data classification unit.

4. The three-dimensional simulation method based on model building according to claim 3, characterized in that: The simulation environment setting module includes a hardware configuration unit, a software configuration unit, an environment parameter configuration unit and a confirmation unit. The hardware configuration unit is specifically as follows: computer: including CPU, memory, and graphics card to ensure the smoothness and effect of simulation operation, special external hardware: including external head-mounted devices and control handles to provide immersive VR experience, other equipment: VR control platform, projector, configured according to specific needs, the software configuration unit is specifically as follows: operating system: Windows, which must meet the running requirements of the simulation software; simulation software: select three-dimensional simulation software for building and running the simulation environment; related APIs and tools: including those for model import and script writing to improve simulation efficiency and flexibility.

5. The three-dimensional simulation method based on model building according to claim 4, characterized in that: The environmental parameter configuration unit includes a gravity setting subunit, an illumination setting subunit, a material property setting subunit and a boundary condition setting subunit.

6. The three-dimensional simulation method based on model building according to claim 5, characterized in that: The model building module is used to select modeling software, including AutoCAD and 3ds Max, according to modeling requirements; use the modeling software to convert the sketch into a real three-dimensional model, and increase the details and complexity of the model through subdivision and carving tools; add textures and materials: add appropriate textures and materials to the model.

7. The three-dimensional simulation method based on model building according to claim 6, characterized in that: The simulation calculation module and the simulation rendering module dynamically simulate and render the model through the physical engine and simulation algorithm. The physical engine calculates the motion, rotation and collision reaction by giving real physical properties to rigid objects, including momentum, torque or elasticity. It enables the objects in the simulation to run according to physical parameters and provide a highly realistic experience. The physical engines include Bullet and PhysX.

8. The three-dimensional simulation method based on model building according to claim 7, characterized in that: The result analysis module is used to collect the required data; then, the data is cleaned and preprocessed to eliminate noise and errors; Then, descriptive statistical analysis is performed, including calculating the mean and variance, to understand the overall characteristics of the data; inferential statistical analysis is performed, including hypothesis testing and regression analysis, to draw conclusions about the population from the sample data; finally, data visualization technology is used to present the analysis results to help users intuitively understand data patterns and trends.

9. The three-dimensional simulation method based on model building according to claim 8, characterized in that: The big data acquisition module is used to obtain data from outside the system and input it into the system for statistics and analysis, collect simulation operation problems that have occurred and corresponding optimization solutions, and associate simulation operation problems with their optimization solutions.

10. The three-dimensional simulation method based on model building according to claim 9, characterized in that: The solution setting module is used to store the associated simulation operation problems and their associated optimization solutions. When receiving the problems sent by the optimization matching module, the similarity matching is performed on the problems. After matching the same problems, the associated optimization solutions are fed back.

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