BIM-based rail transit construction geological exploration profile generation method

Abstract

The invention provides a BIM (Building Information Modeling)-based rail transit construction geological exploration profile generation method, which belongs to the technical field of exploration measurement and comprises the step of comprehensively improving the accuracy of rail transit construction geological exploration through an advanced data acquisition and intelligent analysis method. In a construction site, multi-dimensional data of geological drilling, geological radar, geophysical prospecting testing and the like are acquired through various precise instruments, and a three-dimensional coordinate system is firstly established; and deep feature extraction is performed on complex data by using a deep learning algorithm, and key information such as geological stratification, rock and soil parameters and underground water level is accurately obtained. Intelligent fusion of multi-source data is realized by constructing a geological stratification model, a rock and soil parameter model and an underground water level model, and a comprehensive geological information model is generated. And importing the extracted geological profile data into a BIM platform, and carrying out strict precision verification and optimization by adopting a professional geological information collaborative equation set to finally form a highly accurate and reliable rail transit construction geological exploration profile.

Description

Technical Field

[0001] The present invention belongs to the field of surveying and measuring technology, and in particular, relates to a method for generating a geological survey profile for rail transit construction based on BIM. Background Art

[0002] As a complex infrastructure project, rail transit engineering construction requires comprehensive exploration and analysis of the geological environment of the construction site to provide a reliable geological reference for subsequent engineering design and construction. Traditional geological exploration methods mainly include geological drilling, geological radar detection and geophysical testing. By analyzing these data, key information such as stratum distribution, geotechnical parameters and groundwater level can be obtained. However, these geological exploration data usually have problems such as information fragmentation, inconsistent data format, and poor spatial correlation, making it difficult to provide complete three-dimensional geological information for the BIM (Building Information Model) platform.

[0003] On the other hand, with the widespread application of BIM technology in the field of rail transit engineering, it is urgent to seamlessly integrate geological information into the BIM system to support the geological environment management of the entire process of design and construction. The existing BIM geological information integration method mainly relies on simple geometric data import, which is difficult to reflect the actual distribution characteristics of the strata and the spatial variation laws of geotechnical parameters, thus affecting the accuracy of subsequent engineering design and construction. In addition, as an important constraint factor in the construction of rail transit engineering, the geological environment needs to be coupled with factors such as track alignment, structural size and load for analysis, but the existing BIM technology is difficult to meet this requirement.

[0004] Therefore, there is an urgent need for a new method that integrates geological exploration, geological information modeling and rail transit geological fusion analysis, in order to provide more accurate and reliable geological reference support for rail transit engineering construction. Summary of the invention

[0005] In view of this, the present invention provides a BIM-based method for generating geological survey profiles for rail transit construction, which can solve the technical problems in the prior art that it is difficult to realize geological survey, geological information modeling and rail transit geological fusion analysis.

[0006] The present invention is implemented as follows: The present invention provides a method for generating a geological survey profile for rail transit construction based on BIM, comprising the following steps: S10, collecting geological survey data at the rail transit construction site, obtaining geological drilling data, geological radar data, and geophysical test data; S20, establishing a three-dimensional coordinate system of geological survey points based on the geological drilling data, the geological radar data, and the geophysical test data; S30, using a deep learning algorithm to extract features from the geological drilling data, the geological radar data, and the geophysical test data to obtain geological stratification feature data, geotechnical parameter data, and groundwater level data; S40, establishing a geological stratification model according to the geological stratification characteristic data, establishing a geotechnical parameter model according to the geotechnical parameter data, and establishing a groundwater level model according to the groundwater level data; S50, fusing the geological stratification model, the geotechnical parameter model, and the groundwater level model to generate a geological information model; S60, extracting geological profile data of the rail transit construction route based on the geological information model; S70, importing the geological profile data into BIM to generate a geological survey profile for rail transit construction; S80, using a rail transit geological information collaborative equation group to verify and optimize the accuracy of the rail transit construction geological survey profile to obtain a final rail transit construction geological survey profile; S90, updating the optimized rail transit construction geological survey profile data into the BIM to complete the generation of the rail transit construction geological survey profile.

[0007] Furthermore, the rail transit geological information collaborative equation group includes a track linear constraint equation, a buried depth stress equation, a section deformation equation, a stratum bearing capacity equation, and a comprehensive optimization equation; The track alignment constraint equation is used to calculate the matching degree between the track alignment and the geological conditions. The input parameters of the track alignment constraint equation include the track plane alignment data, the longitudinal section alignment data, and the line curvature data extracted from the BIM. The output parameter of the track alignment constraint equation is the track alignment geological adaptability index. The buried depth stress equation is used to analyze the ground stress distribution state under the buried depth condition. The input parameters of the buried depth stress equation include the buried depth data of the station structure and the buried depth data of the tunnel structure extracted from the BIM, the physical and mechanical parameters of the soil extracted from the geotechnical parameter model, and the surface building load data extracted from the geological information model. The output parameter of the buried depth stress equation is the ground stress distribution data. The cross-sectional deformation equation is used to predict the stratum deformation during the construction process. The input parameters of the cross-sectional deformation equation include the tunnel structure cross-sectional data and support structure parameters extracted from the BIM, the soil physical and mechanical parameters extracted from the geotechnical parameter model, and the groundwater level data extracted from the groundwater level model. The output parameter of the cross-sectional deformation equation is the stratum deformation prediction data. The stratum bearing capacity equation is used to evaluate the bearing state of the foundation. The input parameters of the stratum bearing capacity equation include the foundation soil parameters extracted from the geotechnical parameter model, the foundation structure parameters extracted from the BIM, and the structural load data. The output parameter of the stratum bearing capacity equation is the stratum bearing capacity verification data. The comprehensive optimization equation is used to optimize the rail transit construction geological survey profile. The input parameters of the comprehensive optimization equation include the track line geological adaptability index, the ground stress distribution data, the stratum deformation prediction data, and the stratum bearing capacity verification data. The output parameter of the comprehensive optimization equation is the optimized rail transit construction geological survey profile data.

[0008] Furthermore, the track linear constraint equation is specifically expressed as follows: ; In the formula, It is the geological adaptability index of the track line; For the The radius of the plane curve of each measuring point; For the The longitudinal section elevation of each measuring point; For the The longitudinal slope of each measuring point; To allow the minimum curve radius; is the maximum allowable elevation difference; is the maximum allowable slope; is the distance between measuring points; is the total number of measuring points; is the weight coefficient; is the attenuation coefficient; is the correction factor; Correction item for geological conditions.

[0009] The buried depth stress equation is specifically expressed as follows: ; In the formula, is the total stress tensor; is the initial geostress tensor; For the Self-weight stress tensor of soil layer; For the Layer soil stress influence coefficient; is the number of soil layers; is the surface load influence coefficient; is the surface building load stress tensor.

[0010] The cross-sectional deformation equation is specifically expressed as follows: ; In the formula, For spatial location In time The amount of deformation at is the initial deformation distribution function; is the time effect coefficient; is the direction weight coefficient; is the number of spatial directions considered; is the water level influence coefficient; is the groundwater level change.

[0011] The formation bearing capacity equation is specifically expressed as follows: ; In the formula, is the bearing capacity of the stratum; is the soil cohesion; It is the weight of soil; The foundation burial depth; is the base width; is the base length; is the bearing capacity coefficient; is the safety factor; is the shape correction factor; is the tilt correction factor; is the base inclination angle.

[0012] The comprehensive optimization equation is specifically expressed as follows: ; In the formula, To optimize the overall goal; For the The calculated value of a performance indicator; For the target value of each performance indicator; is the weight coefficient; For the Constraints For the control variables; For the target value of a control variable; is the regularization coefficient; is the penalty coefficient; is the number of performance indicators; is the number of constraints; To control the number of variables.

[0013] Equation principle explanation: 1. The track line constraint equation adopts the exponential decay form because the influence of geological conditions on the line shape decreases with the increase of distance, and the exponential form can better describe this decay characteristic; the sub-item accumulation structure is adopted to consider the influence of plane, elevation and slope respectively, so as to make the evaluation more comprehensive; 2. The buried depth stress equation is expressed in tensor form because the underground stress state is three-dimensional and anisotropic, and the tensor form can fully describe the stress distribution state; the layered superposition principle is adopted, and the combined effect of the soil deadweight and the upper load is considered; 3. The cross-section deformation equation adopts the form of a combination of time function and space second-order derivative. The reason is that the deformation process is time-sensitive, and the deformation propagation conforms to the diffusion theory. The second-order derivative can describe the spatial propagation characteristics of the deformation. 4. The stratum bearing capacity equation is based on the classical bearing capacity theory and introduces multiple correction coefficients, taking into account the influence of factors such as foundation shape, burial depth, and inclination, making the calculation results more in line with engineering practice; 5. The comprehensive optimization equation adopts the least squares structure and introduces gradient regularization and penalty terms. The reason is that it is necessary to balance multiple objectives while ensuring the smoothness of the solution and the satisfaction of constraints.

[0014] Compared with the prior art, the present invention provides a method for generating geological survey profiles for rail transit construction based on BIM. First, the method uses multiple means such as drilling, geological radar and geophysical testing to obtain geological survey data and establish a standardized geological data set. Then, the geological survey data is feature extracted through a deep learning algorithm to obtain key information such as stratum distribution, geotechnical parameters and groundwater level, and the information is integrated to establish a complete three-dimensional geological information model. In addition, the method seamlessly integrates geological information into the BIM platform to generate high-precision geological profiles that meet engineering needs, providing reliable geological references for subsequent design and construction. It is worth mentioning that the method also introduces a group of coordinated equations for rail transit geological information to verify and optimize the accuracy of the generated geological profiles, ensuring the coordinated matching of geological information with factors such as track alignment, structural size and load. This not only improves the reliability of geological survey results, but also creates more favorable geological environment conditions for rail transit engineering design and construction.

[0015] Compared with traditional geological survey methods and BIM geological information integration technology, this method has the following advantages: 1) Through the integration of multi-source geological data, a comprehensive geological information model covering all elements of the geological environment is constructed; 2) It realizes the seamless integration of geological information and BIM system, providing a visual geological reference for engineering design and construction; 3) The method of rail transit geological information coordination is adopted to ensure the coordinated matching of geological conditions and engineering needs, and improve the accuracy and reliability of engineering construction. It solves the technical problems in the existing technology that are difficult to realize geological survey, geological information modeling and rail transit geological integration analysis. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 A flow chart of the method provided by the present invention; Figure 2 is a geological drilling profile in Example 2; Figure 3 is a graph showing the variation of unit weight and cohesion with depth in Example 2; Figure 4 is a graph showing the variation of the internal friction angle with depth in Example 2; Figure 5 This is a distribution diagram of formation bearing capacity and safety factor in Example 2. DETAILED DESCRIPTION

[0017] like Figure 1 As shown in FIG. 1 , it is a flow chart of a method for generating a geological survey profile for rail transit construction based on BIM provided by the present invention. The specific implementation method of each step in the method is described in detail below: The specific implementation method of step S10 is to collect geological survey data at the rail transit construction site. First, multiple geological drilling sampling points are arranged at the rail transit construction site, and drilling equipment is used to perform geological drilling and coring, obtain soil samples and rock cores at different depths, record rock and soil stratification information, rock and soil physical and mechanical properties, and groundwater level information, and form geological drilling data. Secondly, a geological radar detection grid is arranged along the rail transit construction route, and a geological radar device is used to scan the underground medium, obtain the electromagnetic wave reflection signal of the underground medium, and form a three-dimensional image of the underground geological structure through signal processing to generate geological radar data. Thirdly, geophysical detection test sites are arranged, and high-density electrical method, transient electromagnetic method, and seismic wave method are used to perform geological geophysical tests, obtain the resistivity distribution of the formation, the electromagnetic field response characteristics, and the seismic wave velocity distribution, and form geophysical test data. Finally, a geological data acquisition quality control system is established, and quality inspections are carried out on geological drilling data, geological radar data, and geophysical test data, and abnormal data are eliminated to form a standardized geological survey data set. In this way, the geological survey information of the rail transit construction site can be fully obtained.

[0018] The specific implementation method of step S20 is to establish a three-dimensional coordinate system of geological exploration points based on geological exploration data. First, select the reference point of the rail transit construction site, establish a global coordinate system, and use a total station to measure the three-dimensional coordinates of the geological drilling sampling points, geological radar detection grids, and geophysical detection test points. Secondly, the differential global positioning system is used to obtain the geodetic coordinates of the reference points, and a conversion relationship between the global coordinate system and the geodetic coordinate system is established. Then, according to the conversion relationship, the collection positions of the geological drilling data, geological radar data, and geophysical test data are uniformly converted to the geodetic coordinate system. Finally, a spatial index of geological exploration data is established to realize the spatial positioning and retrieval functions of geological exploration data. In this way, the spatial association and collaborative analysis of geological exploration data can be achieved.

[0019] The specific implementation method of step S30 is to use a deep learning algorithm to extract features from geological exploration data. First, a deep neural network model is constructed, including a convolution layer, a pooling layer, a fully connected layer, and an output layer, and a feature extraction network structure is designed according to the characteristics of geological exploration data. Secondly, a deep neural network model is used to extract features from geological drilling data to obtain rock and soil stratification interface characteristics, rock and soil physical and mechanical parameter characteristics, and groundwater level change characteristics. Next, a deep neural network model is used to extract features from geological radar data to obtain underground medium stratification characteristics, geological structure characteristics, and abnormal body distribution characteristics. Then, a deep neural network model is used to extract features from geophysical test data to obtain formation physical property parameter characteristics, formation structure characteristics, and geological anomaly characteristics. The deep learning algorithm can effectively extract the intrinsic characteristics of geological exploration data, laying the foundation for the establishment of subsequent geological information models.

[0020] The specific implementation method of step S40 is to construct a geological information model based on the characteristics of geological survey data. First, a three-dimensional geological stratification model is established based on the geological stratification feature data, including the morphology of the stratum interface, the distribution of stratum thickness and the characteristics of geological structure. Secondly, a three-dimensional geotechnical parameter model is established based on the geotechnical parameter data, including the distribution of stratum physical and mechanical parameters, the distribution of stratum bearing capacity and the evaluation of stratum stability. Thirdly, a three-dimensional groundwater level model is established based on the groundwater level data, including the distribution of groundwater level, the flow direction of groundwater and the dynamic change characteristics of groundwater. Finally, the geological modeling software is used to perform three-dimensional visualization of the geological stratification model, the geotechnical parameter model and the groundwater level model. By establishing a three-dimensional geological information model, the geological environment characteristics of the rail transit construction site can be systematically displayed.

[0021] The specific implementation method of step S50 is to perform data fusion on the geological information model. First, a geological information multi-source data fusion framework is established, including a data preprocessing module, a feature matching module, a data fusion module, and a quality control module. Secondly, the geological stratification model, the geotechnical parameter model, and the groundwater level model are spatially registered to establish a spatial correspondence between the models. Then, the registered model data is fused using a data fusion algorithm to generate a unified geological information model. Finally, a spatiotemporal update mechanism for the geological information model is established to achieve dynamic update and maintenance of the model data. Through the fusion of multi-source geological data, a comprehensive geological information model covering all elements of the geological environment can be constructed.

[0022] The specific implementation method of step S60 is to extract the geological profile data of the rail transit construction route from the geological information model. First, a three-dimensional path of the rail transit construction route is constructed in the geological information model. Secondly, a profile extraction line is set along the three-dimensional path, and profile extraction parameters are determined, including extraction width, extraction depth, and sampling spacing. Then, a profile extraction algorithm is used to extract geological profile data from the geological information model, including stratum distribution, geotechnical parameter distribution, and groundwater level distribution. Finally, the extracted geological profile data is interpolated to form a continuous geological profile data set. In this way, geological profile information that meets the needs of rail transit construction can be obtained.

[0023] The specific implementation method of step S70 is to import the geological profile data into the BIM system. First, establish a BIM geological profile data import interface, define data conversion rules and data format standards. Secondly, convert the geological profile data according to the predefined data format to generate geological profile data that meets the BIM standard. Then, import the converted geological profile data into the BIM system to establish a geological profile model. Finally, perform a three-dimensional visualization of the geological profile in the BIM system to support the query and analysis functions of the profile data. In this way, geological information can be seamlessly integrated into the BIM platform, providing a geological reference basis for subsequent rail transit construction.

[0024] The specific implementation method of step S80 is to use the rail transit geological information collaborative equation group to verify the accuracy and optimize the rail transit construction geological survey profile. First, the rail transit geological information collaborative equation group is used to verify the profile accuracy, and various index values ​​including the geological adaptability of the track line shape, the distribution of ground stress, the prediction of stratum deformation and the bearing capacity of the stratum are calculated. Secondly, the abnormal areas and unreasonable areas in the geological profile are identified according to the calculation results. Then, the optimization algorithm is used to correct the abnormal areas and unreasonable areas to improve the accuracy and reliability of the geological profile. Finally, a geological profile optimization record is established to record the optimization process and optimization results. Through the verification and optimization of the rail transit geological information collaborative equation group, it can be ensured that the geological survey profile meets the various requirements of rail transit engineering construction.

[0025] The specific implementation method of step S90 is to update the optimized geological survey profile data to the BIM system. First, the optimized geological profile data is converted into a format according to the BIM data standard. Secondly, the original geological profile data is updated in the BIM system to maintain the consistency and integrity of the data. Thirdly, a geological profile update log is generated to record the update time, update content and updater information. Finally, the updated geological profile is quality checked to ensure the correctness of the update operation. By regularly updating the geological survey profile information in the BIM system, it can be ensured that the design and construction of rail transit projects always have the latest geological condition data.

[0026] Specifically, the principles of the present invention are: systematic collection and feature extraction of geological exploration data, intelligent construction of geological information models, fusion integration of geological profiles and BIM systems, and coupled collaborative analysis of rail transit geological information.

[0027] First, this method makes full use of existing geological exploration methods, such as geological drilling, geological radar and geophysical testing, to systematically collect geological environment data at the rail transit construction site. For the three data sources of geological drilling data, geological radar data and geophysical testing data, a deep learning algorithm is used for feature extraction to obtain key geological information such as stratum distribution, geotechnical parameters and groundwater level. This feature extraction method based on machine learning can automatically identify and extract the most critical geological features for engineering construction from a large amount of complex geological exploration data, laying the foundation for the subsequent establishment of geological information models.

[0028] Secondly, the method integrates the extracted geological feature information to establish a three-dimensional geological layering model, a geotechnical parameter model, and a groundwater level model, thereby constructing a comprehensive geological information model covering all elements of the geological environment. In order to ensure the spatial correlation and data consistency between these geological information models, data fusion techniques are used, including spatial registration, information fusion, and dynamic update. This information fusion method based on multi-source geological data can overcome the limitations of a single exploration method and generate a more complete and reliable description of the geological environment.

[0029] Furthermore, this method seamlessly integrates the constructed geological information model into the BIM platform to generate geological profile data that meets the needs of rail transit engineering. Through operations such as spatial path extraction and data format conversion, key geological information in the three-dimensional geological model, such as stratum distribution, geotechnical parameters, and groundwater level, can be effectively imported into the BIM system, providing intuitive and visual geological reference for engineering design and construction. This integration of geological information and the BIM system not only improves the application efficiency of geological results, but also lays the foundation for subsequent joint optimization analysis.

[0030] Finally, the method introduces a group of coordinated equations of rail transit geological information to verify and optimize the accuracy of the generated geological profile. These coordinated equations include track alignment constraints, buried depth stress analysis, section deformation prediction, and stratum bearing capacity assessment, which can comprehensively evaluate the matching degree between geological conditions and rail transit engineering design parameters. By optimizing and adjusting the geological profile data, the coordination of factors such as track alignment, structural dimensions, and loads with the geological environment is ensured, thereby improving the overall reliability of engineering construction.

[0031] A specific embodiment 1 of the present invention is provided below. The specific implementation of each step in this embodiment 1 is described in detail as follows: The specific implementation of step S10 is to collect geological survey data at the rail transit construction site. For geological drilling sampling, the following formula can be used to represent the comprehensive information of each drilling sample point: ; in, Respectively represent the three-dimensional spatial position of the drilling coordinates; Indicates the depth information of stratigraphic division; Indicates the physical and mechanical properties of soil samples or cores; Indicates the depth information of groundwater level; Indicates other supplementary information. By collecting and recording these borehole information, a complete geological borehole data set can be constructed.

[0032] For geological radar scanning, the following formula can be used to express the three-dimensional geological structure image obtained by scanning: ; in, Represents the electromagnetic wave reflection signal of the underground medium; Indicates the formation resistivity distribution; Indicates the distribution of formation dielectric constant; It represents the distribution of stratum magnetic permeability. Through the inversion processing of these physical parameters, continuous three-dimensional geological structure information can be obtained.

[0033] For geological and geophysical testing, the following formula can be used to describe the formation parameter information obtained by various geophysical methods: High-density electrochemical method: ; Transient Electromagnetic Method: ; Seismic wave method: ; in, Indicates the formation resistivity distribution; Indicates the distribution of formation conductivity; They represent the distribution of P-wave and S-wave velocities respectively. By testing and analyzing these formation physical parameters, the characteristics of geological anomalies can be obtained.

[0034] Finally, by establishing a geological data acquisition quality control system, the acquired geological exploration data are quality inspected and outliers are eliminated to form a standardized geological exploration data set.

[0035] The specific implementation method of step S20 is to establish a three-dimensional coordinate system of geological exploration points based on geological exploration data. First, the three-dimensional coordinates of each geological exploration point can be measured using a total station. , establish a global coordinate system for rail transit construction sites Then, the differential global positioning system is used to obtain the geodetic coordinates of the reference points. , establish the transformation relationship between the global coordinate system and the geodetic coordinate system: ; in, is the coordinate of the reference point in the global coordinate system; is the coordinate of the reference point in the geodetic coordinate system; is the element of coordinate transformation matrix. Finally, the spatial index of geological exploration data is established to realize the rapid retrieval of data of each sampling point.

[0036] The specific implementation method of step S30 is to use a deep learning algorithm to extract features from geological survey data. The following deep neural network model can be constructed: ; in, represents the convolutional layer, represents the pooling layer, represents a fully connected layer; are the weight parameters of the convolutional layer and the fully connected layer respectively. By training this deep neural network model, the following features can be extracted from geological drilling data, geological radar data and geophysical test data: Geological drilling data characteristics: ; Geological radar data features: ; Geophysical test data characteristics: ; These characteristic data lay the foundation for the subsequent construction of geological information models.

[0037] The specific implementation of step S40 is to construct a geological information model based on the characteristics of geological exploration data. First, based on the geological stratification characteristic data Build a 3D geological layered model: ; in, For the The three-dimensional geometric morphology function of each stratum describes the morphology of the stratum interface and the distribution of stratum thickness.

[0038] Secondly, based on geotechnical parameter data Establishment of 3D geotechnical parameter model: ; in, They represent the three-dimensional distribution of soil cohesion, unit weight, internal friction angle, elastic modulus, Poisson's ratio and ultimate bearing capacity respectively.

[0039] Again, based on groundwater level data Build a 3D groundwater level model: ; in, represents the groundwater level distribution, Represents the components of groundwater flow velocity on three coordinate axes.

[0040] Finally, geological modeling software can be used to visualize these three-dimensional models.

[0041] The specific implementation of step S50 is to perform data fusion on the geological information model. An optional specific implementation is described as follows: First, establish the following data fusion framework: ; Among them, the functions of each module are as follows: Preprocessing module: preprocess the original model data, such as data cleaning, format conversion, etc.; FeatureMatching module: establish spatial associations between different models and determine the correspondence between models; DataFusion module: use data fusion algorithms, such as Kalman filtering, Dempster-Shafer theory, etc., to fuse the corresponding model data; QualityControl module: perform quality checks on the fused comprehensive geological information model to ensure data consistency and integrity.

[0042] Then, establish the spatial correspondence between the models: ; Finally, the Kalman filter algorithm is used to update the fused geological information model in time and space: ; in, are the relevant parameters of the Kalman filter algorithm, Input and measure values ​​to the system. Through this spatiotemporal update mechanism, it can ensure that the geological information model is always up to date.

[0043] The specific implementation of step S60 is to extract the geological profile data of the rail transit construction route from the geological information model. Constructing three-dimensional spatial paths for rail transit construction routes ,in represents the path length coordinate. Then, along the path Set the section extraction line and determine the width of the section extraction ,depth and sampling interval Next, the following profile extraction algorithm is used to extract geological profile data from the geological information model: ; Finally, the extracted geological profile data is interpolated twice to generate a continuous and smooth geological profile data set: ; In this way, geological profile information that meets the needs of rail transit construction is obtained.

[0044] The specific implementation of step S70 is to import the geological profile data into the BIM system (Autodesk BIM360, Bentley ProjectWise can be used). An optional specific implementation is: first, establish the following BIM geological profile data import interface: ; Among them, the DataTransformRule module defines the rules for converting geological profile data into the BIM standard data format, and the DataFormatStandard module defines the standard format of geological profile data in the BIM system. Then, the converted geological profile data is imported into the BIM system to generate a three-dimensional geological profile model: ; Finally, the geological profile model is displayed in the visual interface of the BIM system, and the query and analysis of geological profile data are supported.

[0045] The specific implementation method of step S80 is to use the rail transit geological information collaborative equation group to verify and optimize the accuracy of the rail transit construction geological survey profile. First, the linear adaptability of the geological profile is evaluated using the following track linear constraint equation: ; in, Respectively represent Plane curve radius, longitudinal section elevation and slope of each measuring point; The minimum curve radius, maximum elevation difference and maximum slope allowed; are weighting coefficients and correction terms.

[0046] Secondly, the underground stress distribution is calculated using the following buried depth stress equation: ; in, is the total stress tensor; is the initial geostress tensor; For the Self-weight stress tensor of soil layer; For the Layer soil stress influence coefficient; is the surface load influence coefficient; is the surface building load stress tensor.

[0047] Again, the following section deformation equation is used to predict the formation deformation: ; in, For point In time The amount of deformation; is the initial deformation distribution; is the time effect coefficient; is the spatial direction weight; is the groundwater level influence coefficient; is the groundwater level change.

[0048] Finally, the bearing capacity equation of the ground is used to evaluate the bearing state of the foundation: ; in, is the cohesion and weight of the soil; is the bearing capacity coefficient; is the safety factor; is the shape correction factor; is the tilt correction factor; is the base inclination angle.

[0049] According to the calculation results of the above indicators, the abnormal areas in the geological profile are identified and corrected using the following comprehensive optimization equation: ; in, For the The calculated value of each performance indicator; is the corresponding target value; is the indicator weight; is a constraint condition; is the control variable; is the regularization and penalty coefficient. The geological profile is adjusted through the optimization algorithm to meet the requirements of rail transit engineering construction.

[0050] The specific implementation of step S90 is to update the optimized geological survey profile data to the BIM system. An optional implementation is: first, update the optimized geological profile data to the BIM system. Convert to BIM standard data format and generate Then, update the original geological profile model in the BIM system , so that it is Keep it consistent. Next, generate a geological profile update log to record the update time, update content, and updater information. Finally, perform a quality check on the updated geological profile model to ensure the integrity and accuracy of the data. Through this series of steps, it can ensure that the geological profile data in the BIM system is always up to date, providing a reliable geological reference for the subsequent rail transit project design and construction.

[0051] In order to better understand and implement the present invention, the following provides Example 2 of a specific application scenario of the present invention: A certain urban rail transit Line 5 project is in the preliminary survey stage. In order to fully understand the geological environment conditions of the construction site, the engineering department decided to adopt the BIM-based rail transit construction geological survey profile generation method proposed in the present invention.

[0052] First, 20 geological drilling sampling points were set up at key locations along Line 5. These sampling points cover a total length of about 30km along the track, with an average spacing of about 1.5km. Drilling equipment was used to conduct geological drilling and coring at a depth of 50m at each sampling point, and a total of about 1,000 meters of rock and soil samples were obtained. During the drilling process, the staff recorded in detail the rock and soil stratification information, rock and soil physical and mechanical properties, and groundwater levels at each depth layer. For example, at a certain sampling point K3+450, the geological drilling data obtained are shown in Table 1: Table 1 Geological drilling data

[0053] like Figure 2 The following is a geological borehole profile showing the distribution of geological layers at different depths, including four main strata: plain fill, silty clay, moderately weathered granite, and strongly weathered granite. The groundwater level (blue dashed line) is also marked. The vertical axis represents depth (in meters) and the horizontal axis represents distance. Each stratum is filled with a different color for intuitive identification.

[0054] In addition, 30 geological radar detection grid points were set up along Line 5. The underground medium at these grid points was scanned using geological radar equipment to obtain the electromagnetic wave reflection signal of the underground medium. By processing and analyzing these signals, a three-dimensional underground geological structure image along the track line was constructed. Taking a certain detection grid point G2+800 as an example, the geological radar data obtained are shown in Table 2: Table 2 Geological radar data

[0055] At the same time, 15 geophysical exploration test points were set up along Line 5. High-density electrical method, transient electromagnetic method and seismic wave method were used to conduct geological geophysical tests on these points, and information such as formation resistivity distribution, electromagnetic field response characteristics and seismic wave velocity distribution was obtained. Taking a test point P1+200 as an example, the geophysical exploration data obtained are shown in Table 3: Table 3 Geophysical test data

[0056] After completing the collection of geological survey data, the engineering department established a corresponding quality control system. First, the three-dimensional coordinates of geological drilling sampling points, geological radar detection grid points and geophysical detection test points were measured using a total station to obtain their spatial position information at the rail transit construction site. Then, the differential GPS technology was used to determine the geodetic coordinates of the benchmark points at the construction site, and the conversion relationship between the global coordinate system and the geodetic coordinate system was established. Next, the collection location information of the geological survey data was uniformly converted to the geodetic coordinate system, and the spatial index of the geological data was established. Finally, the quality of the acquired geological drilling data, geological radar data and geophysical test data was checked, and outliers were eliminated to form a standardized geological survey data set.

[0057] With the standardized geological survey data, the engineering department immediately started to build a three-dimensional geological information model. First, the deep learning algorithm was used to extract features from the geological survey data. For geological drilling data, the algorithm can automatically identify key features such as rock-soil stratification interface, rock-soil physical and mechanical parameters, and groundwater level changes; for geological radar data, the algorithm can extract characteristic information such as underground medium stratification, geological structure, and abnormal body distribution; for geophysical test data, the algorithm can obtain features such as stratum physical parameters, stratum structure, and geological anomalies.

[0058] Based on the above characteristic data, the engineering department then constructed a three-dimensional geological layering model, a three-dimensional geotechnical parameter model and a three-dimensional groundwater level model. The three-dimensional geological layering model describes the spatial distribution of the stratum interface and the variation of stratum thickness, as shown in Table 4: Table 4 Geological stratification model

[0059] The three-dimensional geotechnical parameter model describes the spatial distribution of the physical and mechanical properties of each stratum, as shown in Table 5: Table 5 Geotechnical parameter model

[0060] like Figure 3 and Figure 4 As shown, Figure 3 is a graph of unit weight and cohesion as a function of depth, Figure 4 It is a graph of the variation of internal friction angle with depth, using different markers and colors to distinguish different parameters, and equipped with dual axes to simultaneously display parameters of different magnitudes.

[0061] The three-dimensional groundwater level model reflects the spatial distribution characteristics of the groundwater level, as shown in Table 6: Table 6 Groundwater level model

[0062] With the above three-dimensional geological information model, the engineering department then integrated it into the BIM platform. First, the three-dimensional construction path of Line 5 was constructed in the BIM system, and the relevant parameters for geological profile extraction were set, such as profile width of 50m, extraction depth of 60m, sampling interval of 10m, etc. Then, the geological profile extraction algorithm was used to extract geological profile data from the three-dimensional geological information model along the construction path, including information such as stratum distribution, geotechnical parameter distribution, and groundwater level distribution. Finally, the extracted geological profile data was formatted into BIM standards and imported into the BIM system to generate a three-dimensional geological profile model that meets engineering needs.

[0063] In order to further improve the accuracy and reliability of the geological profile, the engineering department also introduced the rail transit geological information collaborative equation group to optimize the geological profile. First, the track line constraint equation was used to evaluate the adaptability of geological conditions and track line shape. The results are shown in Table 7: Table 7 Assessment of track alignment geological adaptability

[0064] Secondly, the stress distribution of underground structures under geological conditions was calculated using the buried depth stress equation, as shown in Table 8: Table 8 Stress analysis of underground structures

[0065] Again, the cross-section deformation equation was used to predict the deformation of the stratum during the construction process, as shown in Table 9: Table 9 Prediction of formation deformation

[0066] Finally, the bearing capacity equation of the stratum was used to evaluate the bearing state of the foundation, as shown in Table 10: Table 10 Verification of stratum bearing capacity

[0067] like Figure 5 As shown in the figure, a bar chart is used to show the bearing capacity of different locations (station foundation, viaduct pier foundation, tunnel lining structure), and a broken line is used to show the corresponding safety factor. The left vertical axis represents the bearing capacity (kPa), and the right vertical axis represents the safety factor.

[0068] Based on the verification results of the above indicators, the engineering department identified some abnormal and unreasonable areas in the geological profile, mainly concentrated in K6+800 and K9+200. For these problem areas, the optimization algorithm was used to make targeted corrections, focusing on: 1) adjusting the track line shape, optimizing the curvature and slope indicators; 2) optimizing the structural dimensions of stations and tunnels to reduce the underground stress level; 3) strengthening the design of the supporting structure to control the deformation of the stratum. After multiple rounds of optimization calculations, a precision-verified and optimized rail transit construction geological survey profile was finally generated, providing a reliable geological reference for subsequent engineering design and construction.

[0069] By updating the optimized geological profile data to the BIM system and combining it with the visualization function of the BIM platform, engineering designers can more intuitively understand the geological environment conditions of the construction site. For example, they can view information such as stratum distribution, geotechnical parameters, and groundwater levels through a three-dimensional model, and design foundation structures, support schemes, and drainage systems in a targeted manner; they can combine the structural model in BIM to analyze the matching degree between geological conditions and engineering design parameters, and provide a basis for optimizing the design scheme; they can also dynamically track the impact of geological environment changes on engineering construction and take corresponding countermeasures in a timely manner.

[0070] In general, the BIM-based method for generating geological survey profiles for rail transit construction fully integrates multiple technical means such as geological survey technology, geological information modeling, and rail transit geological coupling analysis, providing strong geological reference support for the design and construction of Line 5. Compared with traditional geological survey methods, this method has the following advantages: 1) Through the integration of multi-source geological data, a more complete and reliable geological information model is constructed, providing a comprehensive description of the geological environment for engineering applications. 2) It realizes the seamless integration of geological information and BIM system, so that geological reference information can be intuitively presented to engineering design and construction personnel, greatly improving the application efficiency of geological results. 3) The method of collaborative analysis of rail transit geological information ensures the coordinated matching of geological conditions and engineering design requirements, and improves the overall reliability of engineering construction. 4) The geological information acquisition and optimization method based on intelligent computing technology improves the accuracy and reliability of geological survey results and creates more favorable geological conditions for engineering construction.

[0071] It should be noted that the explanations of the variables involved in the description of the present invention are shown in Table 11 below.

[0072] Table 11 Variable explanation table

[0073] The above description is only a specific implementation mode of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A method for generating geological survey profiles for rail transit construction based on BIM, characterized in that: The following steps are involved: S10, collecting geological survey data at the rail transit construction site, obtaining geological drilling data, geological radar data, and geophysical test data; S20, establishing a three-dimensional coordinate system of geological survey points based on the geological drilling data, the geological radar data, and the geophysical test data; S30, using a deep learning algorithm to extract features from the geological drilling data, the geological radar data, and the geophysical test data to obtain geological stratification feature data, geotechnical parameter data, and groundwater level data; S40, establishing a geological stratification model according to the geological stratification characteristic data, establishing a geotechnical parameter model according to the geotechnical parameter data, and establishing a groundwater level model according to the groundwater level data; S50, fusing the geological stratification model, the geotechnical parameter model, and the groundwater level model to generate a geological information model; S60, extracting geological profile data of the rail transit construction route based on the geological information model; S70, importing the geological profile data into BIM to generate a geological survey profile for rail transit construction; S80, using a rail transit geological information collaborative equation group to verify and optimize the accuracy of the rail transit construction geological survey profile to obtain a final rail transit construction geological survey profile; S90, updating the optimized rail transit construction geological survey profile data into the BIM to complete the generation of the rail transit construction geological survey profile.

2. The method according to claim 1, characterized in that The step S10 specifically includes: Step 101: Arrange multiple geological drilling sampling points, use drilling equipment to perform geological drilling and coring, obtain soil samples and rock cores at different depths, record rock and soil stratification information, rock and soil physical and mechanical properties, and groundwater level information, and form geological drilling data; Step 102: deploy a geological radar detection grid along the rail transit construction route, use geological radar equipment to scan the underground medium, obtain the electromagnetic wave reflection signal of the underground medium, form a three-dimensional image of the underground geological structure through signal processing, and generate geological radar data; Step 103: Arrange geophysical exploration test sites, use high-density electrical method, transient electromagnetic method and seismic wave method to conduct geological geophysical exploration tests, obtain formation resistivity distribution, electromagnetic field response characteristics and seismic wave velocity distribution, and form geophysical exploration test data; Step 104: Establish a geological data acquisition quality control system, perform quality inspection on the geological drilling data, the geological radar data and the geophysical test data, eliminate abnormal data, and form a standardized geological exploration data set.

3. The method according to claim 2, characterized in that The step S20 specifically includes: Step 201, select the reference points of the rail transit construction site, establish a global coordinate system, and use a total station to measure the three-dimensional coordinates of the geological drilling sampling points, the geological radar detection grid and the geophysical detection test points; Step 202: using a differential global positioning system to obtain the geodetic coordinates of the reference point, and establishing a conversion relationship between the global coordinate system and the geodetic coordinate system; Step 203, uniformly converting the acquisition positions of the geological drilling data, the geological radar data and the geophysical test data into a geodetic coordinate system according to the conversion relationship; Step 204: Establish a spatial index of geological exploration data to realize spatial positioning and retrieval functions of geological exploration data.

4. The method according to claim 3, characterized in that The step S30 specifically includes: Step 301: construct a deep neural network model, including a convolutional layer, a pooling layer, a fully connected layer, and an output layer, and design a feature extraction network structure according to the characteristics of geological exploration data; Step 302: Use the deep neural network model to extract features from the geological drilling data to obtain rock and soil stratification interface features, rock and soil physical and mechanical parameter features, and groundwater level change features; Step 303: Use the deep neural network model to extract features from the geological radar data to obtain underground medium stratification features, geological structure features, and abnormal body distribution features; Step 304: Use the deep neural network model to extract features from the geophysical test data to obtain formation physical property parameter features, formation structure features, and geological anomaly features.

5. The method according to claim 4, characterized in that The step S40 specifically includes: Step 401: Establish a three-dimensional geological stratification model based on the geological stratification feature data, including stratum interface morphology, stratum thickness distribution and geological structure characteristics; Step 402: establishing a three-dimensional geotechnical parameter model based on the geotechnical parameter data, including distribution of formation physical and mechanical parameters, distribution of formation bearing capacity, and evaluation of formation stability; Step 403: establishing a three-dimensional groundwater level model based on the groundwater level data, including groundwater level distribution, groundwater flow direction, and groundwater dynamic change characteristics; Step 404: Use geological modeling software to perform three-dimensional visualization on the geological layering model, the geotechnical parameter model, and the groundwater level model.

6. The method according to claim 5, characterized in that The step S50 specifically includes: Step 501, establishing a geological information multi-source data fusion framework, including a data preprocessing module, a feature matching module, a data fusion module and a quality control module; Step 502: spatially align the geological layering model, the geotechnical parameter model and the groundwater level model to establish a spatial correspondence between the models; Step 503: using a data fusion algorithm to fuse the registered model data to generate a unified geological information model; Step 504: Establish a spatiotemporal update mechanism for the geological information model to achieve dynamic update and maintenance of model data.

7. The method according to claim 6, characterized in that The step S60 specifically includes: Step 601: construct a three-dimensional path of a rail transit construction route in the geological information model; Step 602: setting a profile extraction line along the three-dimensional path, and determining profile extraction parameters, including extraction width, extraction depth, and sampling spacing; Step 603: extracting geological profile data from the geological information model using a profile extraction algorithm, including stratum distribution, geotechnical parameter distribution, and groundwater level distribution; Step 604: interpolate the extracted geological profile data to form a continuous geological profile data set.

8. The method according to claim 7, characterized in that The step S70 specifically includes: Step 701: Establish a BIM geological profile data import interface and define data conversion rules and data format standards; Step 702: convert the geological profile data according to a predefined data format to generate geological profile data that complies with the BIM standard; Step 703: import the converted geological profile data into the BIM system to establish a geological profile model; Step 704: Perform a three-dimensional visual display of the geological profile in the BIM system, and support query and analysis functions of the profile data.

9. The method according to claim 8, characterized in that The step S80 specifically includes: Step 801: Use the rail transit geological information collaborative equation group to verify the profile accuracy and calculate various index values; Step 802: Identify abnormal areas and unreasonable areas in the geological profile according to the calculation results; Step 803: Use optimization algorithms to correct abnormal areas and unreasonable areas to improve the accuracy and reliability of geological profiles; Step 804: Establish a geological profile optimization record to record the optimization process and optimization results.

10. The method according to claim 9, characterized in that The step S90 specifically includes: Step 901: convert the optimized geological profile data into a format according to the BIM data standard; Step 902: Update the original geological profile data in the BIM system to maintain the consistency and integrity of the data; Step 903: Generate a geological profile update log to record the update time, update content, and updater information; Step 904: Perform a quality check on the updated geological profile to ensure the correctness of the update operation.

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