Fine three-dimensional geologic model modeling method and device based on BIM model

Abstract

The invention provides a refined three-dimensional geologic model modeling method and device based on a BIM model, and relates to the technical field of data processing, and the method comprises the steps: obtaining construction data and construction structure information of an underground construction region; carrying out geometric structure division to obtain a plurality of construction structure division areas; a multi-angle construction area image set is obtained, feature point extraction is carried out, and construction structure features are obtained; a construction BIM model is obtained; arranging a multi-dimensional geological detection device to obtain a multi-dimensional geological detection array; obtaining a multi-dimensional geological detection data set based on a preset time sequence window constraint and a polymorphic detection coverage constraint; and rendering to obtain a target three-dimensional geologic model, and performing underground construction auxiliary management. The technical problems of low construction management efficiency and decision lag caused by the fact that a geological detection and modeling method in the prior art generally depends on a small amount of static exploration data and is difficult to cope with dynamic changes of geology and construction conditions in the construction process are solved.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a method and device for modeling a refined three-dimensional geological model based on a BIM model. Background Art

[0002] With the expansion of the scale of construction and infrastructure projects, especially those involving complex geological conditions such as underground engineering, tunnel construction, subways, and mining, construction management faces severe challenges. These projects require accurate geological data, efficient real-time monitoring, and intelligent construction management methods. However, traditional geological monitoring methods and construction management models still have problems. On the one hand, underground construction involves complex and changeable geological conditions, including different types of soil, rock formations, and groundwater level changes. Traditional geological exploration methods rely on limited drilling and sampling, and the data obtained are often local and static, which makes it difficult to fully reflect the changes in the geological environment. This makes it impossible to fully estimate and control the risks in the construction process; on the other hand, traditional geological modeling methods are mostly based on two-dimensional design drawings or low-precision three-dimensional models. The model update is delayed and cannot reflect real-time changes in construction. Especially in complex underground projects, the insufficient accuracy of the model affects the effectiveness and safety of the construction plan. Summary of the invention

[0003] This application provides a refined three-dimensional geological modeling method and device based on the BIM model, aiming to solve the technical problems that the geological detection and modeling methods in the prior art usually rely on a small amount of static exploration data, which is difficult to cope with the dynamic changes of geological and construction conditions during the construction process, resulting in low construction management efficiency and delayed decision-making.

[0004] The first aspect disclosed in the present application provides a refined three-dimensional geological modeling method based on the BIM model, the method comprising: interacting with underground construction projects to obtain construction data and construction structure information of underground construction areas; performing geometric structure division on the underground construction area based on the construction structure information to obtain multiple construction structure division areas; obtaining a multi-angle construction area image set of the underground construction area, extracting feature points from the multi-angle construction area image set based on the multiple construction structure division areas, and obtaining construction structure features based on the feature point extraction results; constructing a BIM model based on the construction structure features and the construction data to obtain A construction BIM model is constructed; based on the multiple construction structure division areas, in combination with the multiple geological division areas, a multi-dimensional geological detection device is deployed to obtain a multi-dimensional geological detection array, wherein the multiple geological division areas correspond to multiple geological features; during the operation of the underground construction project, based on the preset timing window constraints and the polymorphic detection coverage constraints, the multi-dimensional geological detection array is controlled to perform real-time geological detection on the underground construction area to obtain a multi-dimensional geological detection data set; based on the multi-dimensional geological detection data set, the construction BIM model is rendered to obtain a target three-dimensional geological model, and the target three-dimensional geological model is combined to perform auxiliary management of underground construction.

[0005] In a second aspect disclosed in the present application, a refined three-dimensional geological modeling device based on a BIM model is provided. The device is used for the above-mentioned refined three-dimensional geological modeling method based on a BIM model, and the device includes: a construction data acquisition module for interacting with underground construction projects to obtain construction data and construction structure information of underground construction areas; a geometric structure division module for performing geometric structure division on the underground construction area based on the construction structure information to obtain multiple construction structure division areas; a feature point extraction module for obtaining a multi-angle construction area image set of the underground construction area, extracting feature points from the multi-angle construction area image set based on the multiple construction structure division areas, and obtaining construction structure features based on the feature point extraction results; a model building module for The BIM model is constructed based on the characteristics of the construction data to obtain a construction BIM model; a detection array acquisition module is used to deploy multidimensional geological detection devices based on the multiple construction structure division areas and in combination with the multiple geological division areas to obtain a multidimensional geological detection array, wherein the multiple geological division areas correspond to multiple geological features; a real-time geological detection module is used to control the multidimensional geological detection array to perform real-time geological detection on the underground construction area based on preset timing window constraints and polymorphic detection coverage constraints during the operation of the underground construction project to obtain a multidimensional geological detection data set; a model rendering module is used to render the construction BIM model based on the multidimensional geological detection data set to obtain a target three-dimensional geological model, and perform auxiliary management of underground construction in combination with the target three-dimensional geological model.

[0006] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0007] By extracting feature points based on construction data, construction structure information and multi-angle images, a high-precision construction BIM model is formed. This model not only includes the geometric shape of the construction area, but also integrates real-time construction structure features, making the model more accurate and dynamic, providing a comprehensive three-dimensional visualization tool for construction management; by combining the analysis of construction structure division areas and geological characteristics, it is ensured that the layout of multi-dimensional geological detection equipment is reasonable and efficient. In particular, through the analysis of spatial distribution and detection density, the layout position of monitoring equipment is optimized to ensure that the monitoring equipment is neither overly dense nor has a monitoring blind spot, thereby improving the effectiveness and resource utilization of geological monitoring equipment, making the monitoring of important geological feature areas more accurate, reducing equipment redundancy and monitoring blind spots, and reducing The monitoring cost of the project; through the multi-dimensional geological detection array and the preset time window constraints and multi-state monitoring coverage constraints, the geological change data of the construction area are obtained in real time. These data cover information such as settlement, stress strain, groundwater level, surface deformation, etc., ensuring that the data in the construction process is updated in real time, providing a reliable basis for decision-making; the real-time acquired geological monitoring data is integrated into the construction BIM model to generate a target three-dimensional geological model with high dynamics and accuracy. This model is constantly updated according to the geological monitoring data to reflect the actual geological conditions of the construction area, and realizes the accurate restoration and real-time reflection of the geological environment of the construction area, so that the construction management team can rely on the latest data for decision-making and can quickly respond to any sudden geological changes or construction anomalies.

[0008] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] Figure 1 A schematic diagram of a process flow of a refined three-dimensional geological modeling method based on a BIM model provided in an embodiment of the present application;

[0010] Figure 2 A schematic diagram of the structure of a refined three-dimensional geological modeling device based on a BIM model provided in an embodiment of the present application.

[0011] Explanation of the reference numerals: construction data acquisition module 10 , geometric structure division module 20 , feature point extraction module 30 , model building module 40 , detection array acquisition module 50 , real-time geological detection module 60 , model rendering module 70 . DETAILED DESCRIPTION

[0012] The embodiments of the present application provide a refined three-dimensional geological modeling method based on the BIM model, thereby solving the technical problems that the geological detection and modeling methods in the prior art usually rely on a small amount of static exploration data, are difficult to cope with the dynamic changes of geological and construction conditions during the construction process, and lead to low construction management efficiency and delayed decision-making.

[0013] After introducing the basic principles of the present application, various non-limiting implementation methods of the present application will be specifically introduced below in conjunction with the accompanying drawings of the specification. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0014] like Figure 1 As shown, the embodiment of the present application provides a refined three-dimensional geological modeling method based on a BIM model, the method comprising:

[0015] Interactive underground construction projects to obtain construction data and construction structure information of underground construction areas.

[0016] Through the construction management system, real-time data interaction is carried out with on-site construction personnel, equipment, sensors, etc. to obtain construction data and construction structure information of underground construction areas. Construction data refers to data related to project construction collected by various detection equipment during the underground construction process, including construction progress information, environmental detection data, and real-time location of construction equipment (such as excavators, shield machines, etc.), equipment operating status, etc.; construction structure information refers to the geometric shape of the underground construction area and its structural characteristics related to construction, such as the shape, size, and location of tunnels, underground pipelines, and foundation pits. This information can be obtained through measuring equipment.

[0017] The underground construction area is geometrically divided based on the construction structure information to obtain a plurality of construction structure divided areas.

[0018] Analyze the geometric form of the construction area and determine its structural layout, including the direction of the tunnel, the layout of underground pipelines, the depth and position of the pile foundation, etc. According to the actual needs of the project, construction technology, etc., formulate specific rules for geometric structure division. For example, the size of each divided area is set according to the difficulty of construction, the working range of the equipment, and safety requirements. For example, if the geological conditions in a certain area are complex, the divided construction area may be relatively small, which is convenient for centralized processing and monitoring, or different construction areas can be divided according to the time nodes of different construction stages to ensure that the construction progress of each area can be synchronized or gradually advanced. After completing the geometric structure division, multiple construction structure division areas are obtained. This division not only improves the refinement of construction management, but also provides a basis for subsequent multi-dimensional geological detection and construction auxiliary management.

[0019] A multi-angle construction area image set of the underground construction area is obtained, feature points of the multi-angle construction area image set are extracted based on the multiple construction structure division areas, and construction structure features are obtained based on the feature point extraction results.

[0020] By collecting images of the construction area from different angles, a multi-angle construction area image set is obtained. For example, a drone is used to collect multi-angle high-definition images of the underground construction area from the air, a laser scanner is used to collect and generate three-dimensional point cloud data of the construction area with high precision, or a fixed or mobile camera is used to take pictures of the construction site from different angles. On the basis of dividing the area into multiple construction structures, feature points are extracted from the multi-angle images, so that the feature point extraction has spatial constraints, and different areas can be analyzed in a targeted manner. Images from different angles are registered, and the key feature points of the same construction structure are found through the image feature matching algorithm. The feature points of the images at different angles are fused to generate a unified feature point set, and the construction structure features are obtained for subsequent BIM model construction.

[0021] A BIM model is constructed based on the construction structure characteristics and the construction data to obtain a construction BIM model.

[0022] BIM model construction is a process based on building information modeling. It uses construction structure features and construction data to generate a three-dimensional digital model. The BIM model is not only a geometric model, but also contains all information related to the building and construction. Specifically, based on the extracted feature points, the three-dimensional geometric form of the construction area is reconstructed, including tunnels, pile foundations, underground pipelines, etc. The BIM model can accurately reflect the actual structural form of the construction area, integrate the construction data into the BIM model, and through the dynamic update of the data, the BIM model can reflect the state changes in the construction process in real time, making the model more intelligent and dynamic.

[0023] Based on the multiple construction structure division areas and in combination with the multiple geological division areas, a multi-dimensional geological detection device is deployed to obtain a multi-dimensional geological detection array, wherein the multiple geological division areas correspond to multiple geological features.

[0024] Multiple geological division areas are divided based on geological conditions, such as soil layers, rocks, groundwater levels, etc., for example, soil thickness, geological fault zones, groundwater flow areas, etc. The construction structure division area is combined with the geological division area to form a refined regional division system. Multidimensional geological detection devices are devices that perform detection in multiple dimensions, such as space, time, and different geological parameters. These devices are used to detect the geological state and structural stability of underground construction areas in real time. For example, foundation settlement detection devices are used to detect ground settlement during underground construction, and settlement sensors, settlement plates and other equipment are often used; soil stress and strain detection devices are used to detect stress and strain changes in underground structures, and stress sensors, strain gauges and other equipment are used to ensure that the soil will not deform abnormally during construction.

[0025] Multi-dimensional geological detection devices are deployed according to the characteristics of geological division areas and construction structure division areas. Different types of detection equipment should be distributed in areas with different geological conditions. For example, groundwater detection equipment should be deployed in areas with frequent groundwater flow, while stress and strain detection equipment should be deployed in areas where rock sliding may occur. When the equipment is deployed, a multi-dimensional geological detection array covering different areas, dimensions and parameters is formed.

[0026] During the operation of the underground construction project, based on preset timing window constraints and multi-state detection coverage constraints, the multi-dimensional geological detection array is controlled to perform real-time geological detection on the underground construction area to obtain a multi-dimensional geological detection data set.

[0027] Timing window constraints refer to the control of detection frequency and duration within a specific time period. During the construction process, certain construction activities, such as excavation and support structure installation, may have a greater impact on the underground environment. Therefore, different time intervals or windows need to be set for real-time detection. These windows include timed detection, event-driven detection, long-term detection, etc. The setting of the timing window can be dynamically adjusted according to the different stages of construction.

[0028] Polymorphic detection coverage constraints are to cover different dimensions and parameters of the construction area through a variety of detection equipment under different construction states and geological conditions to ensure comprehensive detection effects. Construction states and geological conditions are changeable. The construction process may involve a variety of different construction processes, such as excavation, support, concrete pouring, etc., as well as different geological conditions, such as soft soil, hard rock, groundwater flow, etc. In order to adapt to these different states, polymorphic detection coverage constraints are set.

[0029] During the operation of underground construction projects, based on preset timing window constraints and multi-state detection coverage constraints, the multi-dimensional geological detection array is controlled to conduct real-time geological detection of the underground construction area, and various geological parameters of the construction area are continuously collected to form a multi-dimensional geological detection data set, including stress and strain data, which reflect the pressure and deformation of the soil or structure during the construction process; settlement data, which reflects the settlement changes of the surface and underground structures during the construction process; groundwater level and water flow data, which reflect the impact of the dynamic changes of groundwater on the construction area; vibration data, which reflects the impact of the vibration generated during the construction process on the surrounding environment.

[0030] The construction BIM model is rendered based on the multi-dimensional geological detection data set to obtain a target three-dimensional geological model, and auxiliary management of underground construction is performed in combination with the target three-dimensional geological model.

[0031] BIM model rendering refers to the integration of real-time detection data with the construction BIM model, so that the model is not only a static geometric structure display, but also can reflect the real-time construction situation and geological status. Specifically, the multi-dimensional geological detection data set is imported into the BIM platform, and the geological data is mapped to the corresponding construction structure according to the geometric division of the construction area. For example, settlement data can be mapped to the surface and underground structures to show the settlement of buildings in different areas. Stress-strain data can be displayed in the soil or support structure of the model with dynamic changes in color or shape to reflect the stress on the soil or structure during the construction process.

[0032] The rendered BIM model will present different visualization effects. For example, through different colors, transparency, shape changes and other visual elements, it can directly reflect the dynamic changes of the construction area. In this way, construction managers can directly observe the geological changes and potential risks of various areas during the construction process from the model. Through the rendered BIM model, the target three-dimensional geological model is finally obtained. This model not only reflects the geometric form and structural layout of the construction area, but also dynamically displays the real-time geological changes and construction environment, which is used for auxiliary management of underground construction. For example, once certain geological data (such as settlement, stress, etc.) exceed the safety range, the model can issue an early warning to prompt the construction team to take immediate measures.

[0033] Furthermore, the detection indicators of the multi-dimensional geological detection device include foundation settlement detection indicators, soil stress and strain detection indicators, groundwater level and water flow detection indicators, geological body deformation detection indicators, construction vibration detection indicators, and surface deformation detection indicators.

[0034] Specifically, the foundation settlement detection index is used to detect the vertical displacement of the foundation or building foundation during or after construction, usually expressed as the degree of sinking of the foundation or building; the soil stress and strain detection index is used to detect the stress and strain of the soil or rock layer under the external load during the construction process; the groundwater level and water flow detection index is used to detect the change of groundwater level and the flow rate and direction of groundwater flow in the construction area; the geological body deformation detection index is used to detect the deformation or displacement of geological bodies, such as rock layers, surface or underground structures, during or after construction; the construction vibration detection index is used to detect the vibration caused by construction activities such as mechanical equipment and blasting during construction, and evaluate its impact on surrounding buildings and geological bodies; the surface deformation detection index is used to detect the horizontal or vertical deformation of the surface during or after construction, including settlement, uplift or slip. The detection indicators of the above-mentioned multi-dimensional geological detection device cover multiple key geological parameters in the construction process, helping the construction management team to master the geological conditions of the construction site. Through effective data collection and analysis, these detection indicators can timely discover potential risks and ensure safety and efficiency during the construction process.

[0035] Furthermore, the method of dividing the regions based on the multiple construction structures and combining the multiple geological division regions to arrange a multi-dimensional geological detection device and obtain a multi-dimensional geological detection array includes:

[0036] Acquire preliminary geological exploration data of the underground construction area; extract geological features based on the preliminary geological exploration data to obtain multiple geological features and multiple geological division areas corresponding to the multiple geological features; acquire the original geological detection device layouts in the multiple construction structure division areas and the multiple geological division areas, and retrieve multiple original geological detection data of the original geological detection device layouts; fit the multiple original geological detection data to the construction BIM model, perform data spatial distribution analysis, and obtain N geological detection insufficient areas and M geological detection redundant areas according to the analysis results; perform point optimization analysis on the original geological detection device layout based on the N geological detection insufficient areas and the M geological detection redundant areas, and locate Q geological detection device layout points; perform multi-dimensional geological detection device layout at the Q geological detection device layout points to obtain the multi-dimensional geological detection array.

[0037] Preliminary geological exploration data refers to geological information of the underground construction area obtained through geological surveys and exploration methods before construction begins. It includes obtaining soil or rock samples at different depths through drilling, analyzing the physical properties of the soil, rock distribution, etc.; using geological radar to conduct underground scanning to detect soil layers, rock layers, groundwater levels and other information; using the principles of seismic wave reflection and refraction to analyze the geological structure at different depths underground and detect the thickness and density of rock layers.

[0038] Based on the previous geological exploration data, the geological features related to the construction are extracted, and the construction area is divided into different geological division areas based on these features. Each geological division area has different geological characteristics. Specifically, through drilling and radar detection, the main characteristics of the soil are extracted, such as density, particle size, soil bearing capacity, permeability, etc.; based on seismic wave detection and drilling data, the thickness, density, strength and distribution of underground rock layers are analyzed. Through multi-dimensional analysis of exploration data, the geological characteristics and distribution of each area are clarified, and the construction area is divided into different geological zones according to the geological characteristics, and multiple geological division areas are obtained.

[0039] In the designated areas, original geological detection devices have been deployed. These devices are used to detect in real time the geological changes occurring during the construction process and to retrieve the original geological detection data collected by these devices, including multi-dimensional detection information such as settlement, stress, strain, groundwater level, and vibration.

[0040] The collected data is spatially matched with the corresponding structure or geological area in the BIM model. Through data fitting, the data changes of each detection point and its distribution in space can be intuitively seen in the BIM model. According to the location of the sensor layout and its coverage, the number and distribution density of sensors in each area are calculated. Through this analysis, it is possible to identify which areas are densely covered by sensors and which areas are insufficiently covered. According to the results of the spatial distribution analysis, the construction area is divided into geological detection insufficient areas and geological detection redundant areas, and N geological detection insufficient areas and M geological detection redundant areas are obtained.

[0041] After dividing N geological detection insufficient areas and M geological detection redundant areas, the geological detection devices are rearranged through point optimization analysis to ensure that the distribution of detection equipment is more reasonable and efficient. Specifically, the existing sensor point data is obtained from the layout of the original geological detection device, and the spatial position and detection range of each device are determined. Based on the spatial distribution and detection density analysis, the insufficient detection areas are identified. In these areas, the existing detection equipment has insufficient coverage or the data accuracy is insufficient. These areas should be optimized and new points should be added. For redundant areas, there are too many detection devices. By analyzing the data of these devices, it is determined whether the points of these devices can be reduced or these devices can be transferred to the insufficient areas. According to the analysis results, a specific point adjustment plan is formulated to locate Q geological detection device layout points as the final optimized geological detection equipment layout points. These points cover the insufficient detection areas, reduce the redundant areas, and meet the overall construction safety and detection needs.

[0042] Various types of multidimensional geological detection devices are deployed at the optimized Q points to form a multidimensional geological detection array, which can monitor the geological changes occurring during the construction process in real time and in all directions, and provide real-time feedback to construction managers.

[0043] Furthermore, the data spatial distribution analysis is performed, and N geological detection insufficient areas and M geological detection redundant areas are obtained according to the analysis results, including:

[0044] After fitting the multiple original geological detection data to the construction BIM model, spatial interpolation analysis is performed on the multiple model division areas to obtain multiple detection data densities of the multiple model division areas; based on a preset data density interval, a first detection data density of a first model division area is judged; when the first detection data density is higher than the preset data density interval, the first model division area is added to the M geological detection redundant areas; when the first detection data density is lower than the preset data density interval, the first model division area is added to the N geological detection insufficient areas.

[0045] Spatial interpolation is a data processing method used to infer the values ​​of unknown points between known points. Through interpolation analysis, the geological state of undetected areas can be inferred based on existing geological detection data. For example, assuming that there are settlement sensors on both sides of an area, interpolation can be used to estimate the settlement trend of the middle area where no sensors are deployed. Through interpolation analysis, combined with the data and spatial position of each detection point, the detection data density in each model-divided area can be calculated. The detection data density refers to the distribution density of detection equipment in a model-divided area, as well as the coverage of detection data. It reflects the number of detection equipment, detection range and data coverage level in the area.

[0046] A preset data density interval is set as a standard for judging whether a certain area is adequately detected. If the detection data density of a certain area is higher than the upper limit, it means that there may be too many detection devices in the area, resulting in a waste of resources; if the detection data density of a certain area is lower than the lower limit, it means that there are insufficient detection devices, and there is a risk of blind spots or incomplete data coverage. The detection data density of the area divided by the first model is compared with the preset data density interval to determine whether the detection coverage of the area meets the standard.

[0047] When the first detection data density is higher than the preset data density interval, that is, higher than the preset upper limit value, it means that there are too many detection devices in the area and there is detection redundancy. This may be because too many sensors cover the same area, resulting in repeated and unnecessary detection data, wasting resources and equipment. In this case, the first model division area is added to the M geological detection redundant areas. The redundant area represents an area where sensors are too densely deployed, and it is necessary to reduce the deployment of redundant equipment and optimize detection resources.

[0048] When the first detection data density is lower than the preset data density interval, that is, lower than the preset lower limit, it means that the detection equipment in the area is insufficiently deployed and there is a risk of insufficient detection. Areas with insufficient detection density may have detection blind spots or incomplete data coverage, and the geological state of the area cannot be fully grasped. In this case, the area divided by the first model is added to N geological detection insufficient areas. The insufficient area represents an area with insufficient sensor deployment, and detection equipment needs to be added to ensure sufficient monitoring efforts.

[0049] Further, based on the N geological detection insufficient areas and the M geological detection redundant areas, the original geological detection device layout is optimized and analyzed, and the Q geological detection device layout points are located. The method includes:

[0050] Based on the original geological detection device layout, P original points are obtained; detection coverage analysis is performed on the N geological detection insufficient areas to locate N newly added points; the N newly added points and the P original points are integrated, point clustering is performed with the preset data density interval as the target, and the points are updated according to the clustering results to obtain the Q geological detection device layout points.

[0051] Based on the original geological detection device layout, P original points are obtained. The original points are the locations of detection equipment deployed based on geological exploration and detection needs in the initial or early stage of construction. These points cover some key geological detection points in the construction area.

[0052] Use the detection equipment data in the BIM model to analyze the detection range of each existing equipment and understand the radius and depth covered by the equipment. For example, the settlement sensor covers the radius range of surface deformation, and the stress strain sensor covers the stress range of soil and support structure. By comparing the coverage range of the current detection equipment with the location of the insufficient area, identify which areas are not covered by the detection equipment. Usually, geometric analysis or spatial analysis technology is used to identify the coverage blank areas. In these blind spots, set N new points according to the detection coverage requirements. These points should cover the areas that cannot be detected by the existing equipment.

[0053] The original points and the newly added points are combined to form a unified point set. Cluster analysis is performed with the previously defined data density range as the target. The density range stipulates that the number of sensors in each area should be controlled within a certain range to ensure the comprehensiveness and effectiveness of the data and avoid equipment redundancy. The K-means clustering algorithm can be used to divide the points into different clustering groups according to their spatial positions to ensure that the detection equipment in each area is reasonably distributed. According to the clustering results, the position or number of certain points is adjusted to optimize the overall layout. For example, if multiple points in a certain area are too dense, some equipment can be reduced and transferred to other locations, eventually forming Q geological detection device layout points. After these points are optimized, it can be ensured that the detection density of each area meets the preset requirements and the equipment is evenly distributed.

[0054] Furthermore, the method of extracting feature points from the multi-angle construction area image set based on the multiple construction structure division areas, and obtaining construction structure features based on the feature point extraction results includes:

[0055] Feature points are extracted from the multi-angle construction area image set according to the multiple construction structure division areas, and the feature point extraction results are aligned and analyzed based on the feature point similarity to obtain a construction area feature point set; feature fusion is performed on the feature point data in the construction area feature point set to obtain the construction area feature fusion information as the construction structure feature.

[0056] Feature points are significant and unique points in the image, such as edges, corners, and points with obvious changes in curvature. In construction images, these feature points usually reflect the key locations of building structures, such as intersections, edges, and pipeline connection points of supporting structures. By extracting feature points, significant features in images within the construction area can be identified to form a set of feature points.

[0057] In multi-angle images, feature points in different images need to be matched and compared. Similarity is used to measure whether feature points in different images point to the same object or location. For example, in two images from different perspectives, the edge of the same building may be extracted as two different feature points. By calculating the similarity of these points, it can be determined whether they represent the same location. Registration is to align images from different angles so that they are aligned in the same coordinate system for subsequent analysis. Registration analysis based on feature points uses feature point similarity to match feature points between images to ensure that feature points in images from different angles can be correctly aligned. Through feature point extraction and registration analysis, feature points in all images from different angles are integrated into a set of construction area feature points. These points represent the key geometric features of the construction area and provide a three-dimensional information basis for buildings or structures.

[0058] Feature fusion refers to merging and processing multiple feature point data extracted from different images to generate a unified feature description. By fusing feature point data from different perspectives, redundant information can be reduced and the accuracy and consistency of feature points can be improved. Specifically, the feature points are first spatially aligned to ensure that each feature point has a consistent position and direction in the same coordinate system. For multiple feature points at the same position, a merging operation is performed to retain the geometric properties of the feature points (such as position, angle, curvature) and their description information in different images. By calculating the similarity of feature points, redundant or repeated feature points are eliminated, and unique and representative feature points are retained.

[0059] The result of feature fusion is a set of feature points that contain all the key structural information of the construction area. These points reflect the key features of the construction area, such as the geometry, edges, and intersections. They represent the three-dimensional geometric information of the building structure, including walls, supporting structures, pipeline locations, etc. Through the BIM model, these feature points can be visualized to form a three-dimensional structural contour model that reflects the shape of the building.

[0060] Furthermore, obtaining a set of characteristic points of the construction area includes:

[0061] Image matching is performed on the multi-angle construction area image set according to the multiple construction structure division areas to obtain multiple regional multi-angle images; feature point extraction is performed on the multiple regional multi-angle images to obtain multiple regional multi-angle feature point sets; similarity analysis is performed on the feature points in the multiple regional multi-angle feature point sets, and feature points with similarities less than a similarity threshold are registered to obtain multiple registered feature points; conversion and fusion are performed based on the multiple registered feature points to obtain the construction area feature point set.

[0062] Image matching refers to the process of aligning multiple images taken from different angles and positions to ensure that they can be compared and analyzed in the same spatial coordinate system. The goal is to ensure that the same areas in each image can be correctly aligned to provide a basis for subsequent feature point extraction. For example, geometric transformations such as affine transformations and projection transformations are used to align images from different perspectives so that they can be compared in the same coordinate system. The matched image set contains images taken from different angles in each area. These images are spatially aligned and can be processed later.

[0063] Feature points are extracted from the aligned multi-angle images. Feature points are significant points in the image. These points usually represent the edges, corners, intersections, etc. of the building structure. The scale-invariant feature transform (SIFT) method can be used to extract feature points at different scales and rotation angles. This ensures that the same feature points can still be identified at different viewing angles and scales. Through the feature point extraction algorithm, a set of feature points at multiple angles in each construction structure area is obtained. These feature points reflect the geometric information at each viewing angle, including key features such as boundaries, intersections, and surfaces.

[0064] In multi-angle images, feature points of different images need to be matched through similarity analysis. The goal of similarity analysis is to identify feature points that represent the same physical location in images from different perspectives. The higher the similarity, the higher the matching degree of the two feature points. For example, the Euclidean distance method is used to calculate the Euclidean distance in the descriptor space of the feature points. If the distance is small, it means that the two feature points are highly similar. After the similarity analysis, feature points with similarity below the threshold are registered. The goal of registration is to ensure that feature points are correctly matched in images from different perspectives and to adjust or remove inconsistent feature points. For example, the best set of registration points is found through random sampling and model fitting, and feature points that are mismatched are removed. Through registration analysis, multiple registration feature points are finally obtained. These feature points are adjusted or matched to ensure alignment in images from different angles and reflect the same physical location, forming a more consistent geometric description.

[0065] These feature points are transformed and fused. The goal of transformation fusion is to merge the registered feature points from multiple perspectives into a unified feature point set. Specifically, if the coordinate systems of the feature points in different images are different, coordinate transformation is required to ensure that all feature points are in the same global coordinate system; for feature points at the same physical position, a merge operation is performed to retain their geometric characteristics while eliminating redundant points. Through transformation fusion, a set of construction area feature points is finally formed, which represents the geometric features of the construction area, including key structural information such as edges, intersections, and surfaces.

[0066] Based on the same inventive concept as the refined three-dimensional geological modeling method based on the BIM model in the aforementioned embodiment, Figure 2 As shown, the embodiment of the present application provides a refined three-dimensional geological modeling device based on a BIM model, the device comprising:

[0067] The construction data acquisition module 10 is used to interact with underground construction projects and obtain construction data and construction structure information of underground construction areas; the geometric structure division module 20 is used to perform geometric structure division on the underground construction area based on the construction structure information to obtain multiple construction structure division areas; the feature point extraction module 30 is used to obtain a multi-angle construction area image set of the underground construction area, extract feature points from the multi-angle construction area image set based on the multiple construction structure division areas, and obtain construction structure features based on the feature point extraction results; the model construction module 40 is used to construct a BIM model based on the construction structure features and the construction data to obtain a construction BIM model; the detection array acquisition module 50, used to deploy multidimensional geological detection devices based on the multiple construction structure division areas and in combination with the multiple geological division areas to obtain a multidimensional geological detection array, wherein the multiple geological division areas correspond to multiple geological features; a real-time geological detection module 60, used to control the multidimensional geological detection array to perform real-time geological detection on the underground construction area based on preset timing window constraints and polymorphic detection coverage constraints during the operation of the underground construction project to obtain a multidimensional geological detection data set; a model rendering module 70, used to render the construction BIM model based on the multidimensional geological detection data set to obtain a target three-dimensional geological model, and perform auxiliary management of underground construction in combination with the target three-dimensional geological model.

[0068] Furthermore, the detection indicators of the multi-dimensional geological detection device include foundation settlement detection indicators, soil stress and strain detection indicators, groundwater level and water flow detection indicators, geological body deformation detection indicators, construction vibration detection indicators, and surface deformation detection indicators.

[0069] Furthermore, the detection array acquisition module 50 further includes the following operation steps:

[0070] Acquire preliminary geological exploration data of the underground construction area; extract geological features based on the preliminary geological exploration data to obtain multiple geological features and multiple geological division areas corresponding to the multiple geological features; acquire the original geological detection device layouts in the multiple construction structure division areas and the multiple geological division areas, and retrieve multiple original geological detection data of the original geological detection device layouts; fit the multiple original geological detection data to the construction BIM model, perform data spatial distribution analysis, and obtain N geological detection insufficient areas and M geological detection redundant areas according to the analysis results; perform point optimization analysis on the original geological detection device layout based on the N geological detection insufficient areas and the M geological detection redundant areas, and locate Q geological detection device layout points; perform multi-dimensional geological detection device layout at the Q geological detection device layout points to obtain the multi-dimensional geological detection array.

[0071] Furthermore, the detection array acquisition module 50 further includes the following operation steps:

[0072] After fitting the multiple original geological detection data to the construction BIM model, spatial interpolation analysis is performed on the multiple model division areas to obtain multiple detection data densities of the multiple model division areas; based on a preset data density interval, a first detection data density of a first model division area is judged; when the first detection data density is higher than the preset data density interval, the first model division area is added to the M geological detection redundant areas; when the first detection data density is lower than the preset data density interval, the first model division area is added to the N geological detection insufficient areas.

[0073] Furthermore, the detection array acquisition module 50 further includes the following operation steps:

[0074] Based on the original geological detection device layout, P original points are obtained; detection coverage analysis is performed on the N geological detection insufficient areas to locate N newly added points; the N newly added points and the P original points are integrated, point clustering is performed with the preset data density interval as the target, and the points are updated according to the clustering results to obtain the Q geological detection device layout points.

[0075] Furthermore, the detection array acquisition module 30 further includes the following operation steps:

[0076] Feature points are extracted from the multi-angle construction area image set according to the multiple construction structure division areas, and the feature point extraction results are aligned and analyzed based on the feature point similarity to obtain a construction area feature point set; feature fusion is performed on the feature point data in the construction area feature point set to obtain the construction area feature fusion information as the construction structure feature.

[0077] Furthermore, the detection array acquisition module 30 further includes the following operation steps:

[0078] Image matching is performed on the multi-angle construction area image set according to the multiple construction structure division areas to obtain multiple regional multi-angle images; feature point extraction is performed on the multiple regional multi-angle images to obtain multiple regional multi-angle feature point sets; similarity analysis is performed on the feature points in the multiple regional multi-angle feature point sets, and feature points with similarities less than a similarity threshold are registered to obtain multiple registered feature points; conversion and fusion are performed based on the multiple registered feature points to obtain the construction area feature point set.

[0079] Through the above detailed description of the refined three-dimensional geological modeling method based on the BIM model in this specification, those skilled in the art can clearly understand the refined three-dimensional geological modeling device based on the BIM model in this embodiment. Since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part description.

[0080] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A refined three-dimensional geological modeling method based on BIM model, characterized in that: The method comprises: Interactive underground construction projects to obtain construction data and construction structure information of underground construction areas; Performing geometric structural division on the underground construction area based on the construction structure information to obtain a plurality of construction structure division areas; Acquire a multi-angle construction area image set of the underground construction area, extract feature points from the multi-angle construction area image set based on the multiple construction structure division areas, and obtain construction structure features based on the feature point extraction results; Constructing a BIM model based on the construction structure characteristics and the construction data to obtain a construction BIM model; Based on the multiple construction structure division areas, combined with the multiple geological division areas, a multi-dimensional geological detection device is deployed to obtain a multi-dimensional geological detection array, wherein the multiple geological division areas correspond to multiple geological features; During the operation of the underground construction project, based on preset timing window constraints and multi-state detection coverage constraints, the multi-dimensional geological detection array is controlled to perform real-time geological detection on the underground construction area to obtain a multi-dimensional geological detection data set; The construction BIM model is rendered based on the multi-dimensional geological detection data set to obtain a target three-dimensional geological model, and auxiliary management of underground construction is performed in combination with the target three-dimensional geological model.

2. The method for modeling a refined three-dimensional geological model based on a BIM model according to claim 1, characterized in that: The detection indicators of the multi-dimensional geological detection device include foundation settlement detection indicators, soil stress and strain detection indicators, groundwater level and water flow detection indicators, geological body deformation detection indicators, construction vibration detection indicators, and surface deformation detection indicators.

3. The method for modeling a refined three-dimensional geological model based on a BIM model according to claim 1, characterized in that: The method comprises: dividing the regions based on the multiple construction structures and combining the multiple geological division regions to arrange the multi-dimensional geological detection devices and obtain the multi-dimensional geological detection array. Obtaining preliminary geological exploration data of the underground construction area; Extracting geological features based on the preliminary geological exploration data to obtain a plurality of geological features and a plurality of geological division areas corresponding to the plurality of geological features; Acquire the original geological detection device layouts in the multiple construction structure division areas and the multiple geological division areas, and retrieve multiple original geological detection data of the original geological detection device layouts; Fitting the multiple original geological detection data to the construction BIM model, performing data spatial distribution analysis, and obtaining N geological detection insufficient areas and M geological detection redundant areas according to the analysis results; Based on the N geological detection insufficient areas and the M geological detection redundant areas, the point optimization analysis of the original geological detection device layout is performed to locate the Q geological detection device layout points; Multi-dimensional geological detection devices are deployed at the Q geological detection device deployment points to obtain the multi-dimensional geological detection array.

4. The method for modeling a refined three-dimensional geological model based on a BIM model as claimed in claim 3, characterized in that: The data spatial distribution analysis is performed, and N geological detection insufficient areas and M geological detection redundant areas are obtained according to the analysis results, including: After fitting the plurality of original geological detection data to the construction BIM model, performing spatial interpolation analysis on the plurality of model division areas to obtain a plurality of detection data densities of the plurality of model division areas; Based on a preset data density interval, determining the first detection data density of the first model divided area; When the first detection data density is higher than the preset data density interval, adding the first model division area to the M geological detection redundant areas; When the first detection data density is lower than the preset data density interval, the first model division area is added to the N geological detection insufficient areas.

5. The method for building a refined three-dimensional geological model based on a BIM model according to claim 4, characterized in that: Based on the N geological detection insufficient areas and the M geological detection redundant areas, the point optimization analysis of the original geological detection device layout is performed to locate the Q geological detection device layout points, and the method includes: Acquire P original points based on the original geological detection device layout; Conducting detection coverage analysis on the N geological detection-deficient areas and locating N new points; The N newly added points and the P original points are integrated, point clustering is performed with the preset data density interval as the target, and the points are updated according to the clustering results to obtain the Q geological detection device deployment points.

6. The method for building a refined three-dimensional geological model based on a BIM model according to claim 1, characterized in that: The method of extracting feature points from the multi-angle construction area image set based on the multiple construction structure division areas, and obtaining construction structure features based on the feature point extraction results includes: Extract feature points from the multi-angle construction area image set according to the multiple construction structure division areas, and perform registration analysis on the feature point extraction results based on feature point similarity to obtain a construction area feature point set; Feature fusion is performed on the feature point data in the construction area feature point set to obtain the construction area feature fusion information as the construction structure feature.

7. The method for building a refined three-dimensional geological model based on a BIM model according to claim 6, characterized in that: The step of obtaining a set of characteristic points in the construction area includes: Performing image matching on the multi-angle construction area image set according to the multiple construction structure division areas to obtain multiple area multi-angle images; Extracting feature points from the multiple regional multi-angle images to obtain multiple regional multi-angle feature point sets; Performing similarity analysis on the feature points in the multi-angle feature point sets of the multiple regions, registering the feature points whose similarities are less than a similarity threshold, and obtaining a plurality of registered feature points; The construction area feature point set is obtained by performing conversion and fusion based on the multiple registration feature points.

8. A refined three-dimensional geological modeling device based on a BIM model, characterized in that: The device is used to implement the refined three-dimensional geological modeling method based on the BIM model according to any one of claims 1 to 7, and comprises: The construction data acquisition module is used to interact with underground construction projects and obtain construction data and construction structure information of underground construction areas; A geometric structure division module, used to perform geometric structure division on the underground construction area based on the construction structure information to obtain a plurality of construction structure division areas; A feature point extraction module is used to obtain a multi-angle construction area image set of the underground construction area, extract feature points from the multi-angle construction area image set based on the multiple construction structure division areas, and obtain construction structure features based on the feature point extraction results; A model building module, used to build a BIM model based on the construction structure characteristics and the construction data to obtain a construction BIM model; A detection array acquisition module is used to arrange multi-dimensional geological detection devices based on the multiple construction structure division areas and in combination with the multiple geological division areas to obtain a multi-dimensional geological detection array, wherein the multiple geological division areas correspond to multiple geological features; A real-time geological detection module is used to control the multidimensional geological detection array to perform real-time geological detection on the underground construction area based on preset timing window constraints and multi-state detection coverage constraints during the operation of the underground construction project, and obtain a multi-dimensional geological detection data set; The model rendering module is used to render the construction BIM model based on the multi-dimensional geological detection data set to obtain a target three-dimensional geological model, and perform auxiliary management of underground construction in combination with the target three-dimensional geological model.

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