Project digital intelligence acceptance simulation method and device based on VR technology, and medium

Abstract

The invention discloses an engineering digital intelligent acceptance simulation method and device based on a VR technology and a medium, and relates to the technical field of intelligent construction, and the method comprises the steps: importing a construction BIM model into a domestic VR platform, carrying out asynchronous loading and format conversion through a resource system, binding material physical parameters, initializing a physical calculation engine load condition, and generating a parameterized BIM model; real-time physical calculation is carried out through a parameterized BIM model, risk early warning is triggered in combination with a structure response value, a defect thermodynamic diagram is generated through PBR rendering, and accurate coordinates of a high-risk area are obtained; and matching the accurate coordinates of the high-risk area with the construction BIM model, collecting the initial pose of AR glasses, establishing an AR space coordinate system, then carrying out space parameter calibration and virtual-real space matrix calculation, and generating a virtual-real space conversion matrix. According to the invention, the intelligentization, precision and operability of engineering construction acceptance are enhanced.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of intelligent construction, and in particular to an engineering digital acceptance simulation method and device based on VR technology and a medium. BACKGROUND

[0002] With the development of information technology, building information modeling (BIM) technology is increasingly widely used in engineering design, construction management and facility operation and maintenance. The BIM model created by three-dimensional modeling software not only provides rich geometric information, but also contains a large amount of non-geometric attributes such as material performance and cost estimation, thereby realizing efficient management of the whole life cycle of building engineering. In recent years, virtual reality (VR) and augmented reality (AR) technologies have also begun to be gradually applied to the construction industry, and have shown great potential in visualization, simulation training and interactive experience. How to effectively combine BIM models with VR / AR technology and conduct in-depth data analysis and physical calculation on this basis has become a hot research field.

[0003] Although the prior art has attempted to combine BIM with VR / AR technology, there are still some deficiencies. First, in terms of data processing, the traditional integration method usually adopts a synchronous loading strategy, resulting in low efficiency of importing large-scale BIM models, especially in resource-limited situations, which affects user experience. Secondly, most current systems fail to fully utilize the rich physical parameters contained in BIM models for accurate real-time physical simulation and structural response analysis. These limitations limit the comprehensive evaluation of the intrinsic quality of engineering projects, making it difficult to achieve real-time risk prediction and defect detection. SUMMARY

[0004] In view of the above existing problems, the present application is proposed.

[0005] Therefore, the present application provides an engineering digital acceptance simulation method and device based on VR technology, which solves the problems of low model loading efficiency and insufficient physical simulation accuracy in the integration of existing BIM and VR / AR.

[0006] To solve the above technical problems, the present application provides the following technical solutions: In a first aspect, the present application provides a simulation method for engineering digital acceptance based on VR technology, which comprises the following steps: importing a construction BIM model into a domestic VR platform, performing asynchronous loading and format conversion through a resource system, binding material physical parameters, initializing a physical calculation engine load case, generating a parameterized BIM model; performing real-time physical calculation through the parameterized BIM model, triggering a risk warning in combination with a structure response value, generating a defect heat map through PBR rendering, and obtaining accurate coordinates of a high-risk area; matching the accurate coordinates of the high-risk area with the construction BIM model, collecting an initial pose of AR glasses, establishing an AR space coordinate system, and then performing space parameter calibration and virtual-real space matrix calculation to generate a virtual-real space conversion matrix; marking the high-risk area through AR visualization according to the virtual-real space conversion matrix, and obtaining an acceptance report through deviation analysis.

[0007] As a preferred scheme of the simulation method for engineering digital acceptance based on VR technology, the method comprises the following steps in the step of importing the construction BIM model into the domestic VR platform and performing asynchronous loading and format conversion: performing format conversion on the construction BIM model to generate a format-matched construction BIM model; obtaining a distribution loading task according to the format-matched construction BIM model, and generating an in-memory optimized construction BIM model through asynchronous loading.

[0008] As a preferred scheme of the simulation method for engineering digital acceptance based on VR technology, the method comprises the following steps in the step of binding the material physical parameters, initializing the physical calculation engine load case, and generating the parameterized BIM model: selecting construction BIM model components one by one, binding corresponding material physical parameters, and generating a construction BIM model with physical parameter binding; adding a load condition to the construction BIM model with physical parameter binding, and generating a parameterized BIM model.

[0009] As a preferred scheme of the simulation method for engineering digital acceptance based on VR technology, the method comprises the following steps in the step of performing real-time physical calculation through the parameterized BIM model, triggering a risk warning in combination with a structure response value, generating a defect heat map through PBR rendering, and obtaining accurate coordinates of a high-risk area: analyzing the parameterized BIM model through a physical calculation engine to generate an in-memory parameterized BIM model; starting real-time physical calculation on the in-memory parameterized BIM model, and generating a parameterized BIM model with a structure response value in combination with the structure response value; The abnormal node marks in the parameterized BIM model of the scanning band structure response value are marked, and risk early warning is carried out according to the number of continuous abnormal nodes, and a parameterized BIM model with risk early warning marks is generated; The parameterized BIM model with risk early warning marks is rendered by PBR to generate a defect heat map; According to the RGB channel value in the defect heat map, the spatial coordinates of the high-risk area are screened, and the spatial coordinates are clustered to generate accurate coordinates of the high-risk area.

[0010] As a preferred scheme of the engineering digital intelligent acceptance simulation method based on the VR technology, wherein: the accurate coordinates of the high-risk area are matched with the construction BIM model, and the initial pose of the AR glasses is collected, and the specific steps are as follows: The accurate coordinates of the high-risk area are matched with the construction BIM model in space to generate high-risk area coordinates with BIM component IDs; The AR glasses are used to establish a spatial coordinate system in the entity engineering site, and the initial pose of the AR glasses is collected through a sensor fusion algorithm.

[0011] As a preferred scheme of the engineering digital intelligent acceptance simulation method based on the VR technology, wherein: after the AR spatial coordinate system is established, spatial parameter calibration and virtual-real space matrix calculation are carried out to generate a virtual-real space conversion matrix, and the specific steps are as follows: The initial pose of the AR glasses is converted into a rotation matrix through a quaternion conversion, and the calibrated AR device spatial parameters are generated by combining the construction BIM model origin offset calculation; Based on the calibrated AR device spatial parameters, the virtual-real space conversion matrix is calculated.

[0012] As a preferred scheme of the engineering digital intelligent acceptance simulation method based on the VR technology, wherein: according to the virtual-real space conversion matrix, the AR visualized high-risk area marking is carried out, and the acceptance report is obtained through deviation analysis, and the specific steps are as follows: The high-risk area coordinates with BIM component IDs are input into the virtual-real space conversion matrix to obtain entity space coordinates, and the AR visualized high-risk area marking is carried out through PBR rendering; According to the AR visualized high-risk area marking, deviation analysis is carried out to generate a spatial deviation analysis acceptance report.

[0013] In a second aspect, the present application provides a computer device comprising a memory and a processor, the memory storing a computer program, wherein: the computer program is executed by the processor to realize any step of the engineering digital intelligent acceptance simulation method based on the VR technology according to the first aspect of the present application.

[0014] In a third aspect, the present application provides a computer readable storage medium having stored thereon a computer program, wherein the computer program, when executed by a processor, implements any step of the method for simulating engineering digital acceptance based on VR technology according to the first aspect of the present application.

[0015] The present application has the beneficial effects that: by constructing a parameterized BIM model and realizing accurate mapping between virtual and real spaces, the physical simulation result is deeply integrated with AR field visualization, not only improving the large model processing efficiency and structural risk prediction capability, but also realizing a closed loop from virtual analysis to real guidance, and enhancing the intelligentization, accuracy and operability of engineering construction acceptance. BRIEF DESCRIPTION OF DRAWINGS

[0016] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0017] Figure 1 Flowchart of the method for simulating engineering digital acceptance based on VR technology.

[0018] Figure 2 Flowchart of asynchronous loading and physical parameter binding.

[0019] Figure 3 Flowchart of obtaining defect thermodynamic map.

[0020] Figure 4 Flowchart of generating virtual-real space conversion matrix. DETAILED DESCRIPTION

[0021] In order to make the above-mentioned purposes, features and advantages of the present application more apparent and easy to understand, the specific embodiments of the present application will be described in detail below with reference to the drawings.

[0022] In the following description, many specific details are set forth in order to provide a thorough understanding of the present application, but the present application can also be implemented in other ways different from those described herein, and those skilled in the art can make similar generalizations without departing from the connotation of the present application, therefore the present application is not limited to the specific embodiments disclosed below.

[0023] Secondly, the "one embodiment" or "embodiment" referred to herein means that the specific features, structures or characteristics can be included in at least one implementation of the present application. In this specification, "in one embodiment" does not mean the same embodiment, nor is it an independent or alternative embodiment that excludes other embodiments.

[0024] Reference Figure 1 For an embodiment of the present application, the embodiment provides a VR technology-based engineering digital acceptance simulation method, comprising the following steps: S1: import the construction BIM model into the domestic VR platform, perform asynchronous loading and format conversion through the resource system, bind the material physical parameters, initialize the physical calculation engine load case, generate the parameterized BIM model, please refer to Figure 2 .

[0025] S1.1: format conversion is performed on the construction BIM model to generate a format-matched construction BIM model; Further, the construction BIM model is processed by the resource format automatic recognition function in FBX, OBJ and other formats, compression is performed to reduce storage space occupation, baking is performed to optimize lighting and shadow information, and conversion is performed to generate a standardized format adapted to the domestic VR platform. The LOD technology is applied to grade and simplify the geometric structure of the construction BIM model, ensure the balance of resource quality at different viewing distances, and output a format-matched construction BIM model.

[0026] S1.2: according to the format-matched construction BIM model, load tasks are obtained and distributed, and a memory-optimized construction BIM model is generated through asynchronous loading; Further, based on the format-matched construction BIM model, unit loading tasks are divided, hierarchical loading is performed according to spatial position priority, core components in the first layer are loaded, adjacent areas in the second layer are loaded, and peripheral areas are loaded in delay. In the asynchronous mechanism, high-frequency components are preloaded into the memory cache, and low-frequency components are dynamically unloaded to the disk cache. The least recently used algorithm is used to manage the resource pool, maintain the stability of memory occupation, and generate a memory-optimized construction BIM model.

[0027] It should be noted that the resource system adopts a resource pool management mechanism to classify and manage resources, ensuring the orderliness and search efficiency of the resources. Through the resource pool, resources can be quickly located and obtained, and through the cache mechanism, unnecessary repeated loading is avoided.

[0028] S1.3: select the construction BIM model components one by one, bind the corresponding material physical parameters, and generate a construction BIM model with physical parameter binding.

[0029] Further, the construction BIM model components are selected one by one, the physical parameters in the material attribute library are associated, the metal components are bound with the metal degree and gloss parameters, the concrete components are bound with the roughness and normal map parameters, and the glass components are bound with the refractive index and transparency parameters. Through the physically-based rendering technology, the material visual characteristics are mapped to ensure that the metal reflection, wood texture and glass transmission effects are consistent with the real physical behavior, and a construction BIM model with physical parameter binding is generated.

[0030] It should be noted that the material attribute library is constructed by a physically-based rendering technology, a physically accurate light model is used to simulate real light propagation, reflection and refraction behavior, a metal degree parameter is defined and stored to control metal glossiness, a roughness parameter is used to simulate surface texture details, and a normal map parameter is used to enhance the geometric concave-convex sense, which directly maps the material visual effects such as metal reflection, wood particles and glass transparency; combined with high dynamic range image and environment mapping technology to collect complex environment light data such as sky reflection and indirect light information, integrated into the material attribute library to ensure the physical consistency of different materials in the virtual scene; the physical parameter source is based on standardized measurement and real material characteristic database.

[0031] S1.4: Add load conditions to the construction BIM model with physical parameter binding to generate a parameterized BIM model.

[0032] Further, load conditions are injected into the construction BIM model with physical parameter binding, static load binds the structure self-weight parameter, dynamic load binds the equipment operation vibration parameter, and environmental load binds the wind pressure and snow load parameter. When initializing the physical calculation engine, the load type is allocated to the working condition calculation path, the gravity load is directly connected to the rigid body dynamics calculation chain, and the fluid load triggers the particle system simulation chain. When multiple loads are superimposed, a parallel computing pipeline is enabled to generate a parameterized BIM model.

[0033] It should be noted that the load condition specifically refers to a set of physical force parameters acting on the construction BIM model, including static load, dynamic load and environmental load. Static load corresponds to the continuous pressure parameter generated by the structure self-weight, dynamic load corresponds to the periodic force parameter formed by the equipment operation vibration, and environmental load corresponds to the natural external force parameter such as wind pressure and snow load. Load conditions are converted into visual behaviors by the physical calculation engine, static load drives the rigid body dynamics calculation chain to realize structure settlement simulation, dynamic load triggers the particle system to generate equipment vibration ripples, and environmental load activates the fluid mechanics algorithm to render wind and snow erosion effects. When multiple loads are superimposed, the parallel computing pipeline synchronously processes the gravity chain, fluid chain and particle chain data streams to ensure real-time visualization of load interaction.

[0034] S2: Perform real-time physical calculation through the parameterized BIM model, and trigger risk warning combined with structure response value, generate defect thermodynamic map through PBR rendering (physically-based rendering), and obtain accurate coordinates of high-risk area.

[0035] S2.1: Analyze the parameterized BIM model through the physical calculation engine to generate a parameterized BIM model resident in memory.

[0036] Further, the parameterized BIM model is loaded into the memory pool by the physical calculation engine, and the model data is classified and stored by using the resource pool management mechanism. The engine parses the geometric topological relationship and load parameters, maps the structural dead weight, equipment vibration, and wind and snow load into the rigid body dynamics calculation chain, integrates vertex shading and physical property data through a unified rendering pipeline, and generates a parameterized BIM model that resides in memory.

[0037] It should be noted that the unified rendering pipeline is the core processing architecture of the physics-based rendering technology, which includes three levels of vertex processing stage to convert the geometric coordinate data of the parameterized BIM model, geometry processing stage to generate surface details and normal information, and pixel processing stage to perform material optical calculation; the pipeline integrates physical property data and optical rendering characteristics, the vertex shading stage maps the load parameter to the vertex displacement, the pixel shading stage converts the metallicity parameter to reflectivity, the roughness parameter controls the highlight scattering, and the normal map parameter drives the concave-convex light response; through the parallel computing architecture, the physical calculation data stream and the optical rendering data stream are processed synchronously, and the hardware acceleration fusion of the rigid body dynamics chain and the PBR material chain is realized on the domestic GPU.

[0038] S2.2: Start real-time physical calculation on the parameterized BIM model residing in memory, combine the structure response value, and generate a parameterized BIM model with structure response value.

[0039] Further, real-time physical calculation is started on the parameterized BIM model residing in memory, the gravity load triggers the rigid body displacement calculation chain, the dynamic load activates the particle system to simulate vibration ripples, and the environmental load drives the fluid mechanics erosion algorithm. The physical calculation engine calculates the structure deformation rate, stress distribution, and resonance frequency frame by frame, writes the displacement gradient and stress peak value into the vertex attribute buffer, and generates a parameterized BIM model with structure response value.

[0040] S2.3: Scan the abnormal node markers in the parameterized BIM model with structure response value, and generate a parameterized BIM model with risk warning markers according to the number of continuous abnormal nodes.

[0041] Further, please refer to Figure 3 Scan the vertex attribute buffer of the parameterized BIM model with structure response value, detect the deformation rate, and mark the nodes exceeding the deformation rate threshold as abnormal nodes. According to the spatial clustering density of continuous abnormal nodes, a three-level warning mechanism is triggered, isolated nodes are marked yellow, local clusters are marked orange, and continuous areas are marked red. The warning markers are directly written into the normal map channel of the parameterized BIM model, and a parameterized BIM model with risk warning markers is generated.

[0042] It should be noted that the deformation rate threshold setting is based on the yield strength limit in the material physical parameter library, combined with dynamic adjustment of load combination working conditions, using the standard yield strength of the material as the basic threshold under static load, and adjusting the threshold proportion under the device vibration frequency and resonance effect when dynamic load is superimposed, and using the reduction factor to calibrate the threshold in snow load environment. The critical deformation data in the historical accident database is fitted by machine learning as a spatial distribution function, and the deformation rate threshold changing with position is finally output.

[0043] S2.4: The parameterized BIM model with risk warning marks is rendered by PBR to generate a defect heat map.

[0044] Further, the parameterized BIM model with risk warning marks is input into the physical-based rendering pipeline, which converts the warning marks into material optical properties. The yellow warning is mapped to the metalness parameter decay, the orange warning enhances the roughness parameter, and the red warning superimposes the self-luminous parameter. Through screen space reflection technology, the deformation area is rendered with high light diffuse reflection, and a defect heat map is output.

[0045] S2.5: According to the RGB channel value in the defect heat map, the spatial coordinates of the high-risk area are screened and clustered to generate accurate coordinates of the high-risk area.

[0046] Further, the RGB channel value of the defect heat map is sampled by the convolution kernel, and the red channel peak value region is identified as the high-risk area. The spatial coordinates are clustered by octree index acceleration, and a three-dimensional bounding box is generated with continuous red pixels as the center. The centroid coordinates of the three-dimensional bounding box are taken as the high-risk points. After Gaussian filtering denoising, the accurate coordinates of the high-risk area are output.

[0047] S3: The accurate coordinates of the high-risk area are matched with the construction BIM model, and the initial pose of the AR glasses is collected. After establishing the AR space coordinate system, the space parameter calibration and virtual-real space matrix calculation are performed to generate the virtual-real space conversion matrix.

[0048] S3.1: The accurate coordinates of the high-risk area are matched with the construction BIM model to generate high-risk area coordinates with BIM component ID.

[0049] Further, the accurate coordinates of the high-risk area are matched with the construction BIM model through octree index and component vertex position, and the nearest neighbor search algorithm is executed to locate the coordinates belonging to the BIM component geometry. The unique identifier of the component is extracted and bound to the coordinate data to generate high-risk area coordinates with BIM component ID.

[0050] S3.2: Establish a spatial coordinate system in the entity engineering site using AR glasses, and collect the initial pose of the AR glasses through sensor fusion algorithm.

[0051] Further, the AR glasses are deployed at the entity engineering site, the gyroscope, accelerometer, and magnetometer sensors are activated, the sensor fusion algorithm is started to process the multi-source data stream in real time, the angle, acceleration, and magnetic field information are fused to calculate the initial position coordinates and attitude quaternion, the spatial coordinate system is established, and the initial pose is output.

[0052] S3.3: Perform quaternion conversion on the initial pose of the AR glasses to generate a rotation matrix, combine with the construction BIM model origin offset calculation to generate the calibrated AR device space parameters.

[0053] Further, the initial pose input attitude conversion algorithm performs mathematical transformation from quaternion to rotation matrix to generate a three-dimensional rotation matrix representing the AR glasses attitude direction; load the construction BIM model origin position offset vector data to represent the displacement of the construction BIM model space origin relative to the world coordinate system; perform matrix multiplication operation of the rotation matrix and the offset vector, apply the homogeneous transformation formula to expand the rotation matrix into a homogeneous matrix and combine with the offset vector, output the calibrated AR device space parameters containing rotation components and translation components, which completely describe the pose calibration state of the AR device in the virtual-real space.

[0054] S3.4: Calculate the virtual-real space conversion matrix based on the calibrated AR device space parameters.

[0055] Further, please refer to Figure 4 , the rotation matrix component and the translation vector component in the calibrated AR device space parameters are input into the space transformation algorithm, and the homogeneous coordinate transformation formula is applied to integrate the rotation matrix and the translation vector into a single model view matrix; the single model view matrix maps the virtual construction BIM model coordinate system to the AR glasses entity space coordinate system through matrix multiplication operation, where the rotation matrix aligns the direction and the translation vector compensates for the position offset, generating the virtual-real space conversion matrix, which realizes the accurate linear transformation of the virtual model coordinates to the entity space coordinates.

[0056] S4: According to the virtual-real space conversion matrix, mark the high-risk area for AR visualization, and obtain the acceptance report through deviation analysis.

[0057] S4.1: Input the high-risk area coordinates with BIM component ID into the virtual-real space conversion matrix to obtain the entity space coordinates, and mark the high-risk area for AR visualization through PBR rendering.

[0058] Further, the high-risk area coordinate input with BIM component ID performs homogeneous coordinate transformation through virtual-real space conversion matrix, and calculates to obtain entity space three-dimensional coordinates. The physical-based rendering pipeline loads entity space coordinates, the red warning coordinates activate the self-luminous parameter to generate pulse red light special effects, the orange warning coordinates enhance the roughness parameter to form a granular highlight area, and the yellow warning coordinates attenuate the metal degree parameter to present a semi-transparent wave. Through screen space reflection technology, it is projected in real time to the field of view of AR glasses, and the high-risk area marking is completed.

[0059] S4.2: According to the high-risk area marking of AR visualization, deviation analysis is performed to generate an acceptance report of spatial deviation analysis.

[0060] Further, the high-risk area marking of AR visualization is spatially registered with the construction BIM model design coordinates, and a sensor fusion algorithm is started to calculate the Euclidean distance deviation of the marking points. The static load area deviation value is mapped to the structure settlement acceptance table, the dynamic load area deviation value is written into the vibration frequency compliance report, and the environmental load area deviation value is filled into the wind and snow load resistance table. Finally, it is integrated into a three-dimensional spatial coordinate deviation matrix to output an acceptance report of spatial deviation analysis.

[0061] The embodiment also provides a computer device, including a memory and a processor; the memory is used to store computer executable instructions, and the processor is used to execute the computer executable instructions to realize the engineering digitalization acceptance simulation method based on VR technology proposed in the above embodiment.

[0062] The computer device can be a terminal, and the computer device includes a processor, a memory, a communication interface, a display screen and an input device connected through a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operating system and the computer program in the non-volatile storage medium to run. The communication interface of the computer device is used to communicate with external terminals in a wired or wireless manner. The wireless manner can be achieved through WIFI, operator network, NFC (near field communication) or other technologies. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen. The input device of the computer device can be a touch layer overlaid on the display screen, or a key, trackball or touchpad arranged on the shell of the computer device. In addition, it can also be an external keyboard, touchpad or mouse, etc.

[0063] The embodiment also provides a storage medium on which a computer program is stored, the program being executed by a processor to implement the simulation method for engineering digital acceptance of a project based on VR technology as proposed in the above embodiment. The storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as a static random access memory (SRAM), an electrically erasable programmable read-only memory (EEPROM), an erasable programmable read-only memory (EPROM), a programmable read-only memory (PROM), a read-only memory (ROM), a magnetic memory, a flash memory, a magnetic disk, or an optical disk.

[0064] To sum up, the application realizes the deep fusion of the physical simulation result and the AR field visualization by constructing the parameterized BIM model and realizing the accurate mapping between the virtual and real spaces, not only improves the processing efficiency of the large model and the structural risk prediction capability, but also realizes the closed loop from the virtual analysis to the real guidance, and enhances the intelligentization, precision and operability of the engineering construction acceptance.

[0065] It should be noted that the above embodiments are only used to illustrate the technical solutions of the application but not limit the application. Although the application has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the application can be modified or replaced equivalently without departing from the spirit and scope of the application, and all of them should be covered in the scope of the claims of the application.

Claims

1. A method for digital acceptance simulation of engineering projects based on VR technology, characterized in that: include: The construction BIM model is imported into the domestic VR platform, asynchronously loaded and converted in format through the resource system, and material physical parameters are bound. The physical calculation engine load conditions are initialized to generate a parametric BIM model. Real-time physical calculations are performed using a parametric BIM model, and risk warnings are triggered by combining structural response values. Defect heatmaps are generated through PBR rendering to obtain the precise coordinates of high-risk areas. The precise coordinates of high-risk areas are matched with the construction BIM model, and the initial pose of the AR glasses is collected. After establishing the AR spatial coordinate system, spatial parameters are calibrated and the virtual-real space matrix is ​​calculated to generate the virtual-real space transformation matrix. Based on the virtual-real space transformation matrix, high-risk areas are marked using AR visualization, and an acceptance report is obtained through deviation analysis.

2. The VR technology-based engineering digital acceptance test simulation method according to claim 1, characterized in that: The specific steps for importing the construction BIM model into the domestic VR platform and performing asynchronous loading and format conversion through the resource system are as follows: Convert the construction BIM model to a new format to generate a construction BIM model that matches the new format. Based on the construction BIM model with matching format, obtain the assigned loading tasks and generate a memory-optimized construction BIM model through asynchronous loading.

3. The VR technology-based engineering digital acceptance test simulation method according to claim 2, characterized in that: The steps for binding material physical parameters, initializing the physical calculation engine load cases, and generating a parametric BIM model are as follows: Select memory-optimized construction BIM model components one by one, bind the corresponding material physical parameters, and generate a construction BIM model with physical parameter binding; Add load conditions to the construction BIM model with physical parameter binding to generate a parametric BIM model.

4. The VR technology-based engineering digital acceptance test simulation method according to claim 3, characterized in that: The specific steps for performing real-time physical calculations using a parametric BIM model and triggering risk warnings based on structural response values ​​are as follows: The parametric BIM model is parsed by the physics calculation engine to generate a memory-resident parametric BIM model. Real-time physical calculations are initiated on the memory-resident parametric BIM model, and combined with the structural response values, a parametric BIM model with structural response values ​​is generated. Scan the abnormal node markers in the parametric BIM model with structural response values, and generate a parametric BIM model with risk warning markers based on the number of consecutive abnormal nodes.

5. The VR technology-based engineering digital acceptance test simulation method according to claim 4, characterized in that: The specific steps for generating a defect heatmap using PBR rendering and obtaining the precise coordinates of high-risk areas are as follows: The parametric BIM model with risk warning markers is rendered using PBR to generate a defect heatmap; Based on the RGB channel values ​​in the defect heatmap, the spatial coordinates of high-risk areas are filtered, and the spatial coordinates are clustered to generate accurate coordinates of high-risk areas.

6. The VR technology-based engineering digital acceptance test simulation method according to claim 5, characterized in that: The specific steps for matching the precise coordinates of high-risk areas with the construction BIM model and acquiring the initial pose of the AR glasses are as follows: Spatially match the precise coordinates of high-risk areas with the construction BIM model to generate high-risk area coordinates with BIM component IDs. AR glasses are used to establish a spatial coordinate system at the physical engineering site, and the initial pose of the AR glasses is collected through sensor fusion algorithms.

7. The VR technology-based engineering digital acceptance test simulation method according to claim 6, characterized in that: After establishing the AR spatial coordinate system, spatial parameter calibration and virtual-real space matrix calculation are performed to generate a virtual-real space transformation matrix. The specific steps are as follows: The initial pose of the AR glasses is converted into a quaternion to generate a rotation matrix, and combined with the construction BIM model origin offset calculation to generate the calibrated AR device space parameters; Based on the calibrated AR device space parameters, the virtual-real space conversion matrix is calculated.

8. The VR technology-based engineering digital acceptance test simulation method according to claim 7, characterized in that: According to the virtual-real space conversion matrix, the high-risk area marking of AR visualization is carried out, and the acceptance report is obtained through deviation analysis, and the specific steps are as follows: Input the high-risk area coordinates with BIM component ID into the virtual-real space conversion matrix to obtain the entity space coordinates, and mark the high-risk area of AR visualization through PBR rendering; According to the high-risk area marking of AR visualization, deviation analysis is carried out to generate the acceptance report of spatial deviation analysis. 9.A computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the computer device is characterized in that: The processor executes the computer program to realize the steps of the simulation method for engineering digital acceptance based on VR technology according to any one of claims 1-8.

10. A computer readable storage medium having stored thereon a computer program, characterized in that: The computer program is executed by the processor to realize the steps of the simulation method for engineering digital acceptance based on VR technology according to any one of claims 1-8.

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