Municipal road water permeability detection method based on BIM (Building Information Modeling)

Abstract

The invention discloses a BIM-based municipal road water permeability detection method, and belongs to the technical field of municipal road water permeability detection. The problems that an existing method is not high in accuracy, complex in operation, high in cost and the like are solved, the three-dimensional digital model of the municipal road is established through the BIM technology, and therefore the water accumulation conditions of the municipal road under different rainfall conditions are simulated; comparing and analyzing the change rules of road waterlogging under different rainfall conditions, formulating corresponding water permeability detection schemes according to different simulation results, and performing actual construction; performing clustering analysis on different simulation results and corresponding water permeability detection schemes through a decision tree model, so that after real-time water permeability data is obtained, the corresponding water permeability detection scheme is retrieved in the decision tree model by taking the real-time water permeability data as a feature basis; compared with a traditional method, the accuracy and timeliness of municipal road water permeability detection are improved, the construction risk is reduced, the construction efficiency is improved, and resource consumption is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of municipal highway water permeability detection, and in particular to a municipal highway water permeability detection method based on BIM. Background Art

[0002] Municipal highways, as crucial infrastructure for urban transportation, face increasingly arduous construction and maintenance tasks. During road construction, increasingly stringent requirements are placed on the permeability of the subsoil to ensure the safety and stability of road projects. Therefore, conducting water permeability testing on municipal highways is particularly important.

[0003] At present, there are mainly the following methods for municipal highway water permeability detection: Permeability test: This method determines soil permeability by immersing standard specimens in liquids of varying concentrations and observing the time it takes to saturate. This method is simple to perform, but is limited by the number of specimens and liquid concentration, and is easily affected by environmental factors.

[0004] Laser measurement: This method uses a laser scanner to measure soil porosity and moisture content, thereby calculating soil permeability. This method has high accuracy, but the equipment cost is high and the operation process is complicated.

[0005] On-site observation method: The permeability of soil is determined by observing whether water seeps from the soil surface. This method is simple and easy to use, but is subject to significant subjective factors.

[0006] Although the above methods have their own advantages and disadvantages, the existing municipal highway water permeability detection methods still have certain limitations, such as low accuracy, complex operation and high cost. Therefore, it does not meet the existing needs. Therefore, we propose a BIM-based municipal highway water permeability detection method. Summary of the Invention

[0007] The purpose of the present invention is to provide a municipal highway water permeability detection method based on BIM, which establishes a three-dimensional digital model of the municipal highway through BIM technology to simulate the water accumulation of the municipal highway under different rainfall conditions; and compares and analyzes the changing laws of road water accumulation under different rainfall conditions, formulates corresponding water permeability detection plans for different simulation results and carries out actual construction; and then uses a decision tree model to cluster analysis of different simulation results and their corresponding water permeability detection plans, so that after obtaining real-time water permeability data, the corresponding water permeability detection plan is retrieved from the decision tree model based on the real-time water permeability data; compared with traditional methods, not only the accuracy and timeliness of municipal highway water permeability detection are improved, but also the construction risks are reduced, the construction efficiency is improved, the resource consumption is saved, and the problems raised in the above-mentioned background technology are solved.

[0008] To achieve the above object, the present invention provides the following technical solutions: A BIM-based municipal highway water permeability detection method includes the following steps: Step 1: Collect historical and real-time water permeability data for municipal roads. The water permeability data includes road width, length, material, and drainage system data. Based on the historical water permeability data, set different rainfall conditions for 3D modeling. Step 2: Based on historical water permeability data, use BIM technology to build a three-dimensional digital model of the municipal highway; and input different rainfall conditions into the three-dimensional digital model in sequence to simulate the water accumulation of the municipal road under different rainfall conditions; Step 3: Record the simulation results of road waterlogging under different rainfall conditions in the three-dimensional digital model; compare the simulation results with the actual conditions to determine whether the simulation results are consistent with the actual conditions; if they are consistent, obtain a three-dimensional model that can predict road waterlogging; if not, analyze the accuracy of historical water permeability data and adjust the parameters of the three-dimensional digital model until the comparison results are consistent; Step 4: Analyze the simulation results to determine the changing patterns of road waterlogging under different rainfall conditions; formulate corresponding water penetration detection plans for different waterlogging conditions and form a solution database; and conduct actual construction of the formulated water penetration detection plans to verify their effectiveness; Step 5: Use a decision tree model to perform cluster analysis on different simulation results and corresponding water seepage detection schemes, so that each simulation result is clustered with one water seepage detection scheme; Step 6: Based on the real-time water seepage data, query the corresponding water seepage detection plan in the decision tree model; Step 7. Combine various data with charts to visually display the changing patterns of road waterlogging under different rainfall conditions.

[0009] Furthermore, after collecting historical water permeability data and real-time water permeability data of municipal roads, the first step specifically includes the following steps: The collected historical and real-time water permeability data were collated and cleaned, erroneous and duplicate data were deleted, and the missing data were supplemented using the average method; The formats of water permeability data from different data sources are converted, and then the different data attributes in the water permeability data are converted into a unified numerical format.

[0010] Furthermore, the step 1 is to set different rainfall conditions for the three-dimensional modeling, which specifically includes the following steps: Determine rainfall parameters based on historical permeability data. Rainfall parameters include the size, frequency, and duration of each rainfall event, which are used to simulate different rainfall conditions during modeling. Query the drainage system data corresponding to each rainfall parameter, including: water level height, flow rate and drainage speed at each location; Based on rainfall parameters and drainage system data, the parameters and input types of the three-dimensional digital model are formulated.

[0011] Furthermore, the second step is to use BIM technology to establish a three-dimensional digital model of the municipal highway, which specifically includes the following steps: Determine the scope and level of detail of the 3D digital model and use simulation software to build the 3D digital model; Use multiple input types to add different rainfall conditions and corresponding water seepage responses to the 3D numerical model; Add roads, curbs, roadside facilities, traffic lights, lighting systems, and drainage system components to the 3D digital model; For each component added to the 3D digital model, define the corresponding properties and characteristics, and then add the corresponding materials to the external components.

[0012] Furthermore, the second step simulates the waterlogging of municipal roads under different rainfall conditions, specifically including the following steps: After determining the parameters and input types of the 3D digital model, the simulation software is started to control the 3D digital model to simulate the water accumulation on municipal roads under different rainfall conditions; When simulating different rainfall conditions, by calculating the flood peak, flood volume, water permeability and drainage speed under each rainfall condition and comparing the differences between the values, the water accumulation situation of municipal roads under each rainfall condition is obtained, and then the corresponding calculation results are output.

[0013] Based on the calculation results, the water accumulation under different rainfall conditions was analyzed and compared to obtain the permeability response of the municipal highway and the performance of the drainage system.

[0014] Furthermore, after obtaining the permeability response of the municipal highway and the performance of the drainage system, the three-dimensional digital model parameters or input type are adjusted according to the output results of the three-dimensional digital model to optimize the performance of the three-dimensional digital model.

[0015] Furthermore, the fourth step is to analyze the changing pattern of road waterlogging under different rainfall conditions in the simulation results, which specifically includes the following steps: Analyze the changes in total water accumulation: observe whether there are significant changes in the total water accumulation on the road under different rainfall conditions; Analyze the changes in water depth: observe whether there are significant changes in the depth of road water under different rainfall conditions; Analyze the changes in the duration of waterlogging: observe whether there are significant changes in the duration of road waterlogging under different rainfall conditions; Analyze the changes in the location of water accumulation: observe whether there are obvious changes in the location of water accumulation on the road under different rainfall conditions.

[0016] Furthermore, the step five uses a decision tree model to perform cluster analysis on different simulation results and corresponding water penetration detection schemes, which specifically includes the following steps: Clarify the objectives and scope of the cluster analysis, and cluster the simulation results and corresponding water seepage detection plans according to different rainfall conditions and road types; Organize the water permeability data corresponding to different rainfall conditions and use the water permeability data as input features of the decision tree model; Use the decision tree algorithm to train the input features so that each internal node in the decision tree model represents a feature attribute, each branch represents a value of the attribute, and each leaf node represents a category label; The cluster analysis performance of the decision tree model was evaluated, the trained decision tree model was applied to different simulation results and corresponding water seepage detection schemes, and cluster analysis was performed based on the category labels output by the decision tree model.

[0017] Furthermore, the BIM-based municipal highway water permeability detection method also includes: Before using the 3D digital model to simulate road waterlogging, conduct a blockage analysis on the municipal pipelines; Adjust the 3D digital model based on the results of the siltation analysis; Among them, the blockage analysis of municipal pipelines includes: Determine each drainage outlet in the three-dimensional digital model and construct a state feature set based on the environment around each drainage outlet; According to the state feature set, the corresponding blockage analysis library is retrieved; Through the siltation analysis library, the drainage data corresponding to the drainage outlet is analyzed to obtain the corresponding siltation analysis results.

[0018] Among them, the drainage data corresponding to the drainage outlet is analyzed through the siltation analysis library to obtain the corresponding siltation analysis results, including: Segment the drainage data according to the water level inside the drainage pipe corresponding to the drainage outlet, obtain multiple data segments and number the data segments; Based on the segmentation basis, determine the type of each data segment; Determine the analysis method based on the type of each data segment; Based on the blockage analysis library, determine the analysis parameters corresponding to each analysis method and calculate the blockage parameter according to the following formula: ; Where, Indicates the number The congestion parameters corresponding to the data segment; Indicates the number The congestion parameters corresponding to the data segment; is a pre-configured transition coefficient; They are all coefficients corresponding to the analysis method retrieved from the blockage analysis library according to the type of data segment; The coefficients are preset for the corresponding state feature set from the blockage analysis library; is the preset pipeline roughness coefficient; is the cross-sectional area of the pipe; is the wetted radius of the water flow, is the slope of the water flow; is the preset correlation coefficient; is the preset sedimentation factor.

[0019] Among them, each drainage outlet is determined in the three-dimensional digital model and a state feature set is constructed based on the environment around each drainage outlet, including: With the drain outlet as the center, the preset segmentation grid is mapped into the three-dimensional digital model; By segmenting the grid and intercepting the corresponding area in the 3D digital model, each area is analyzed according to the pre-configured regional analysis library to determine the analysis value; Fill the analysis value into the corresponding position of the data set template corresponding to the segmentation grid; The data value of the corresponding position of the drain outlet corresponding to the dataset template is calculated according to the following formula: ; Where, The data value of the drain outlet corresponding to the corresponding position in the dataset template; The first Rank Column data; The total number of rows of data on the dataset template; The total number of columns of data on the dataset template; is a preset constant, which is the number of divided regions on the side length of the divided grid; Determine the analysis data corresponding to the data on the boundary of the dataset template from the line connecting the corresponding position of the drain outlet on the dataset template to the boundary, and calculate the data value on the boundary according to the following formula: ;

[0020] Where, is the data value on the boundary; For the The data value of the analyzed data, is the total number of analyzed data.

[0021] The present invention collects historical water permeability data of municipal roads as data samples, uses BIM technology to establish a three-dimensional digital model of the municipal roads, simulates the water accumulation of municipal roads under different rainfall conditions through the three-dimensional digital model, and compares and analyzes the changing patterns of road water accumulation under different rainfall conditions; formulates corresponding water permeability detection plans for different simulation results and carries out actual construction to ensure the effectiveness and feasibility of the plans; then, cluster analysis is performed on the different simulation results and their corresponding water permeability detection plans through a decision tree model, so that after obtaining real-time water permeability data, the corresponding water permeability detection plans are retrieved from the decision tree model based on the real-time water permeability data; compared with traditional methods, not only the accuracy and timeliness of municipal road water permeability detection are improved, but also the construction risks are reduced, the construction efficiency is improved, and resource consumption is saved. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 This is a flow chart of a BIM-based municipal highway water permeability detection method of the present invention. DETAILED DESCRIPTION

[0023] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0024] In order to solve the technical problems of the existing municipal highway water permeability detection methods, such as low accuracy, complex operation and high cost, please refer to Figure 1 , this embodiment provides the following technical solutions: A BIM-based municipal highway water permeability detection method includes the following steps: Step 1: Collect historical and real-time water permeability data for municipal roads. The water permeability data includes road width, length, material, and drainage system data. In this embodiment, the historical water permeability data for municipal roads is obtained, for example, by using data published by a public database, a meteorological bureau, or a civil engineering organization. After obtaining the historical and real-time water permeability data, the collected historical and real-time water permeability data need to be sorted and cleaned, and erroneous and duplicated data in the water permeability data need to be deleted. The missing data are supplemented using the average method to eliminate duplicate, erroneous, or inaccurate data. In addition, if the data has different formats, the water permeability data from different data sources need to be format converted, and then the different data attributes in the water permeability data need to be converted into a unified numerical format, such as converting height or distance into meters, so that the format of the water permeability data remains unified to ensure its suitability for subsequent analysis. Secondly, rainfall parameters were determined based on historical water permeability data. These parameters included the magnitude, frequency, and duration of each rainfall event, which were used to simulate different rainfall conditions during modeling. Drainage system data corresponding to each rainfall parameter was queried, including water level height, flow rate, and drainage velocity at each location. Based on these rainfall parameters and drainage system data, parameters and input types for the 3D digital model were developed, such as permeability coefficient, soil moisture content, and vegetation coverage. After cleaning the historical water permeability data, different rainfall conditions were set for the 3D modeling, such as rainfall intensity, duration, location, and wind direction, based on the historical water permeability data.

[0025] Step 2: Based on historical water permeability data, use BIM technology to build a three-dimensional digital model of the municipal highway; specifically, the following steps are included: Clarify the scope and level of detail of the 3D digital model, and use simulation software such as ArcGIS or Flood to build a 3D digital model; and use a variety of input types, such as raster, vector, and surface, to add different rainfall conditions and corresponding permeability responses to the 3D digital model; for example, you can set different rainfall intensities and durations to simulate precipitation processes of different intensities; you can set different wind directions to simulate the flow of rainwater in different directions; you can also set different surface types, ground elevations, and drainage facilities and other parameters to affect the path and speed of rainwater infiltration, flow, and discharge; then add roads, curbs, roadside facilities, traffic lights, lighting systems, and drainage system components to the 3D digital model. In the digital model, objects can be added to the 3D digital model through automatic placement, offset and rotation; for each component added to the 3D digital model, the corresponding properties and characteristics are defined, such as pavement material, thickness, drainage method and slope, which can be manually entered in the 3D digital model or automatically associated with records in the database using the attribute linker; then the corresponding materials are added to the external components; external components such as buildings and public facilities, add materials such as walls, roofs, windows and doors, which can be added to the 3D digital model through custom material libraries or directly importing DXF files; in order to make the 3D digital model more realistic and visual, daylight and shadows can also be added to the 3D digital model.

[0026] Different rainfall conditions are sequentially input into the three-dimensional digital model to simulate the water accumulation on municipal roads under different rainfall conditions. The specific steps include: After determining the parameters and input type of the three-dimensional digital model, the simulation software is started to control the three-dimensional digital model to simulate the waterlogging situation of municipal roads under different rainfall conditions; and during the simulation, the visualization tool is used to check whether the output of the three-dimensional digital model meets expectations; in this implementation, simulation software such as ArcGIS can automatically calculate the waterlogging depth and time within each grid, and output the results in the form of tables or graphs; when simulating different rainfall conditions, by calculating the flood peak, flood volume, permeability and drainage speed under each rainfall condition, and comparing the differences between the various values, the waterlogging situation of municipal roads under each rainfall condition is obtained, and then the corresponding calculation results are output; according to the calculation results, the waterlogging situation under different rainfall conditions is analyzed and compared, and the permeability response and drainage speed of municipal roads are obtained. The performance of the water system; for example, you can draw a distribution map of water depth under different rainfall conditions to understand which areas have the most serious waterlogging problems; you can also compare the drainage efficiency of different drainage facilities to find the optimal design solution; and export the simulation results to Excel, Word, PDF or other formats for easy sharing and reporting; you can also use visualization tools to create dashboards or instrument panels to more intuitively display the results; after obtaining the permeability response of municipal roads and the performance of the drainage system, adjust the 3D digital model parameters or input types according to the output results of the 3D digital model to optimize the performance of the 3D digital model; specifically, you can change parameters such as rainfall size, frequency and duration, and rerun the 3D digital model to better simulate the permeability response under different rainfall conditions.

[0027] Step 3: Record the simulation results of road waterlogging under different rainfall conditions in the 3D digital model; compare the simulation results with the actual conditions to determine whether the simulation results are consistent with the actual conditions; if they are consistent, a 3D model capable of predicting road waterlogging is obtained, from which it can be concluded that the digital model can be used to predict road waterlogging; at the same time, the 3D digital model needs to be evaluated, including: the accuracy, stability, and repeatability of the digital model; if they are inconsistent, analyze the accuracy of the historical water permeability data and adjust the parameters of the 3D digital model until the simulation results are consistent with the actual conditions; Step 4: Analyze the changing patterns of road waterlogging under different rainfall conditions in the simulation results; specifically, the following steps are included: Analyze changes in total water accumulation: Observe whether there are significant changes in the total water accumulation on roads under different rainfall conditions. When rainfall increases, the amount of water accumulated on roads also increases. However, in some cases, even with the same rainfall, different types of roads may experience different water accumulation situations. For example, factors such as road surface material and drainage system will affect the total water accumulation.

[0028] Analyze changes in water depth: Observe whether there are significant changes in the depth of water on roads under different rainfall conditions. When rainfall increases, the depth of water on roads increases accordingly. However, the depth of water may vary on different types of roads. For example, factors such as whether drainage facilities are complete and whether the road surface material is waterproof will affect the depth of water.

[0029] Analyze changes in the duration of waterlogging: Observe whether there are significant changes in the duration of road waterlogging under different rainfall conditions; for example, a short period of heavy rain may quickly wash away water on the road surface, while a long period of light rain may cause the depth of road waterlogging to deepen and last longer.

[0030] Analyze changes in the location of waterlogging: Observe whether the location of waterlogging on roads changes significantly under different rainfall conditions. For example, in some areas, rainfall can cause groundwater levels to rise, causing water that wasn't originally on the road to appear on the street, increasing the risk of waterlogging. This analysis can help us better understand the changing patterns of waterlogging on municipal roads under different rainfall conditions and propose targeted improvement measures to improve road safety and drainage capacity.

[0031] Develop corresponding water penetration detection plans for different water accumulation conditions and form a plan database; specifically, first clarify the classification standards for water accumulation conditions; for example: first, divide water accumulation conditions into different categories based on factors such as the degree, frequency, and duration of water accumulation; second, study and analyze existing water penetration detection plans to understand the current solutions and their advantages and disadvantages in order to develop better plans; third, develop new water penetration detection plans through field visits, experimental tests, etc., and modify the defects of the new water penetration detection plans to ensure the feasibility and effectiveness of the new solutions; finally, record and archive the formulated water penetration detection plans for future reference and use; specifically: establish a spreadsheet or database to record and store information such as the name, content, applicability, and implementation steps of the water penetration detection plan.

[0032] The formulated water permeability detection plan is actually implemented to check whether it is effective. When the formulated water permeability detection plan is actually implemented, strict acceptance and inspection are required. In this embodiment, professional quality control personnel are arranged to conduct on-site supervision and inspection to ensure that the construction meets the expected quality requirements. At the same time, by comparing the actual effects of different plans, problems can be discovered and solved in a timely manner, and improvements and optimizations can be made to ensure the effectiveness of the water permeability detection plan.

[0033] Step 5: Use a decision tree model to perform cluster analysis on different simulation results and corresponding water seepage detection schemes, so that each simulation result is clustered with one water seepage detection scheme; specifically, the following steps are included: Clarify the objectives and scope of cluster analysis, cluster simulation results and corresponding water seepage detection schemes according to different rainfall conditions and road types; organize water seepage data corresponding to different rainfall conditions, and use the water seepage data as input features for the decision tree model; use decision tree algorithms, such as ID3, C4.5, or CART, to train the input features; in the decision tree model, each internal node represents a feature attribute, each branch represents a value of the attribute, and each leaf node represents a category label; evaluate the cluster analysis performance of the decision tree model, with evaluation indicators including accuracy, precision, recall, and F1 score, to ensure the accuracy and reliability of the model; apply the trained decision tree model to different simulation results and corresponding water seepage detection schemes, and perform cluster analysis based on the category labels output by the decision tree model; and use visualization techniques, such as bar charts and dendrograms, to analyze the clustering results to better understand and interpret the results.

[0034] Step 6: Based on the real-time water permeability data, query the corresponding water permeability detection plan in the decision tree model; then adjust the water permeability detection plan based on the actual situation to make it suitable for the current municipal highway water permeability detection; Step 7. Combine various data with charts to visually display the changing patterns of road waterlogging under different rainfall conditions. Specifically, first determine the type of data to be displayed and select an appropriate data visualization method, such as drawing maps, time series charts, or stacked area charts to display data. Secondly, select visualization tools, such as Tableau or GIS software, through which you can import data and generate various types of charts. Finally, mark key information in the chart to ensure that the chart can intuitively reflect the changing patterns of road waterlogging under different rainfall conditions. In this way, the changing patterns of road waterlogging under different rainfall conditions are visualized, so that users can more intuitively understand and grasp the relevant data.

[0035] The beneficial effects achieved by the above content: Through the above operation, compared with the traditional method, not only the accuracy and timeliness of municipal highway water permeability detection are improved, but also the construction risk is reduced, the construction efficiency is improved, and resource consumption is saved.

[0036] Working principle: By collecting historical water permeability data of municipal roads as data samples, using BIM technology to build a three-dimensional digital model of the municipal roads, the three-dimensional digital model is used to simulate the water accumulation of municipal roads under different rainfall conditions, and the changing patterns of road water accumulation under different rainfall conditions are compared and analyzed; according to different simulation results, corresponding water permeability detection plans are formulated and actual construction is carried out to ensure the effectiveness and feasibility of the plans; then, a decision tree model is used to cluster the different simulation results and their corresponding water permeability detection plans, so that after obtaining real-time water permeability data, the corresponding water permeability detection plans can be retrieved from the decision tree model based on the real-time water permeability data.

[0037] In order to achieve a more accurate and realistic waterlogging simulation, in one embodiment, the BIM-based municipal highway water seepage detection method further includes: Before using the 3D digital model to simulate road waterlogging, conduct a blockage analysis on the municipal pipelines; The 3D digital model is adjusted based on the results of the siltation analysis. Each siltation analysis result corresponds to a different adjustment coefficient. Assuming the drainage coefficient is 1, the adjustment coefficient can be anywhere between 0 and 1. The adjusted drainage coefficient is the drainage coefficient before adjustment minus the adjustment coefficient. Among them, the blockage analysis of municipal pipelines includes: Determine each drainage outlet in the three-dimensional digital model and construct a state feature set based on the environment around each drainage outlet; Based on the state feature set, the corresponding blockage analysis library is retrieved; each blockage analysis library corresponds to a different standard state set; based on the matching of the state feature set and the standard state set, the corresponding blockage analysis library is retrieved to improve the accuracy of the blockage analysis; Through the siltation analysis library, the drainage data corresponding to the drainage outlet is analyzed to obtain the corresponding siltation analysis results.

[0038] Among them, the drainage data corresponding to the drainage outlet is analyzed through the siltation analysis library to obtain the corresponding siltation analysis results, including: Segment the drainage data according to the water level inside the drainage pipe corresponding to the drainage outlet, obtain multiple data segments and number the data segments; Based on the segmentation basis, the type of each data segment is determined; the type division is mainly based on the current water level in the drainage pipe and the change of the water level. For example, when the water level is always zero, it belongs to type number 1; when the water level is always maintained at a constant value greater than zero, it belongs to type number 2; when the water level is always greater than zero and decreases compared to the previous moment, it belongs to type number 3; when the water level is always greater than zero and increases compared to the previous moment, it belongs to type number 4; Determine the analysis method based on the type of each data segment; the analysis methods are mapped one by one in the siltation analysis library. The difference between the analysis methods lies in the different parameters used, including transition coefficient, correlation coefficient, sedimentation factor and other coefficients; Based on the blockage analysis library, determine the analysis parameters corresponding to each analysis method and calculate the blockage parameter according to the following formula: ;

[0039] Where, Indicates the number The congestion parameters corresponding to the data segment; Indicates the number The congestion parameters corresponding to the data segment; is a pre-configured transition coefficient; They are all coefficients corresponding to the analysis method retrieved from the blockage analysis library according to the type of data segment; The coefficients are preset for the corresponding state feature set from the blockage analysis library; is the preset pipeline roughness coefficient; is the cross-sectional area of the pipe; is the wetted radius of the water flow, is the slope of the water flow; is the preset correlation coefficient; is the preset sedimentation factor. When calculating the clogging of the data segment numbered 1, Set to zero; is a transition coefficient, which is determined by querying a preset first coefficient table according to the type number of the previous data segment and the type number of the current data segment; Among them, each drainage outlet is determined in the three-dimensional digital model and a state feature set is constructed based on the environment around each drainage outlet, including: With the drain outlet as the center, the preset segmentation grid is mapped into the three-dimensional digital model; The corresponding areas in the 3D digital model are intercepted by segmenting the grid. Each area is analyzed and the analysis value is determined based on the pre-configured regional analysis library. The regional analysis library mainly analyzes factors such as vegetation coverage and object type in each area to quantify the corresponding analysis value. Fill the analysis value into the corresponding position of the data set template corresponding to the segmentation grid; The data value of the corresponding position of the drain outlet corresponding to the dataset template is calculated according to the following formula: ; Where, The data value of the drain outlet corresponding to the corresponding position in the dataset template; The first Rank Column data; The total number of rows of data on the dataset template; is the total number of columns of data in the dataset template; the data in the second row and second column of the dataset template, the last row and the last column correspond to the segmented regions respectively; the first row, the last row, the first column and the last column correspond to the comprehensive description data to improve the accuracy of the construction of the state feature set; It is a preset constant, which is the number of regions divided on the side length of the split grid. Its function is to control the value of SG. Determine the analysis data corresponding to the data on the boundary of the dataset template from the line connecting the corresponding position of the drain outlet on the dataset template to the boundary, and calculate the data value on the boundary according to the following formula: ;

[0040] Where, is the data value on the boundary; For the The data value of the analyzed data, is the total number of analyzed data.

[0041] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "including," "having," or any other variations thereof are intended to cover non-exclusive possessors, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or includes elements that are inherent to such process, method, article, or apparatus.

[0042] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions, and alterations may be made to the embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A BIM-based municipal highway water permeability detection method, characterized in that: The following steps are involved: Step 1: Collect historical and real-time water permeability data for municipal roads. The water permeability data includes road width, length, material, and drainage system data. Based on the historical water permeability data, set different rainfall conditions for 3D modeling. Step 2: Based on historical water permeability data, use BIM technology to build a three-dimensional digital model of the municipal highway; and input different rainfall conditions into the three-dimensional digital model in sequence to simulate the water accumulation of the municipal road under different rainfall conditions; Step 3: Record the simulation results of road waterlogging under different rainfall conditions in the three-dimensional digital model; compare the simulation results with the actual conditions to determine whether the simulation results are consistent with the actual conditions; if they are consistent, obtain a three-dimensional model that can predict road waterlogging; if not, analyze the accuracy of historical water permeability data and adjust the parameters of the three-dimensional digital model until the comparison results are consistent; Step 4: Analyze the simulation results to determine the changing patterns of road waterlogging under different rainfall conditions; formulate corresponding water penetration detection plans for different waterlogging conditions and form a solution database; and conduct actual construction of the formulated water penetration detection plans to verify their effectiveness; Step 5: Use a decision tree model to perform cluster analysis on different simulation results and corresponding water seepage detection schemes, so that each simulation result is clustered with one water seepage detection scheme; Step 6: Based on the real-time water seepage data, query the corresponding water seepage detection plan in the decision tree model; Step 7. Combine various data with charts to visually display the changing patterns of road waterlogging under different rainfall conditions.

2. The BIM-based municipal highway water seepage detection method according to claim 1, characterized in that: The first step, after collecting historical water permeability data and real-time water permeability data of municipal roads, specifically includes the following steps: The collected historical and real-time water permeability data were collated and cleaned, erroneous and duplicate data were deleted, and the missing data were supplemented using the average method; The formats of water permeability data from different data sources are converted, and then the different data attributes in the water permeability data are converted into a unified numerical format.

3. The BIM-based municipal highway water seepage detection method according to claim 1, characterized in that: The first step is to set different rainfall conditions for 3D modeling, which specifically includes the following steps: Determine rainfall parameters based on historical permeability data. Rainfall parameters include the size, frequency, and duration of each rainfall event, which are used to simulate different rainfall conditions during modeling. Query the drainage system data corresponding to each rainfall parameter, including: water level height, flow rate and drainage speed at each location; Based on rainfall parameters and drainage system data, the parameters and input types of the three-dimensional digital model are formulated.

4. The BIM-based municipal highway water seepage detection method according to claim 1, characterized in that: The second step is to use BIM technology to establish a three-dimensional digital model of the municipal highway, which specifically includes the following steps: Determine the scope and level of detail of the 3D digital model and use simulation software to build the 3D digital model; Use multiple input types to add different rainfall conditions and corresponding water seepage responses to the 3D numerical model; Add roads, curbs, roadside facilities, traffic lights, lighting systems, and drainage system components to the 3D digital model; For each component added to the 3D digital model, define the corresponding properties and characteristics, and then add the corresponding materials to the external components.

5. The BIM-based municipal highway water seepage detection method according to claim 4, characterized in that: The second step is to simulate the waterlogging situation of municipal roads under different rainfall conditions, which specifically includes the following steps: After determining the parameters and input types of the 3D digital model, the simulation software is started to control the 3D digital model to simulate the water accumulation on municipal roads under different rainfall conditions; When simulating different rainfall conditions, by calculating the flood peak, flood volume, water permeability and drainage speed under each rainfall condition and comparing the differences between the values, the water accumulation situation of municipal roads under each rainfall condition is obtained, and then the corresponding calculation results are output; Based on the calculation results, the water accumulation under different rainfall conditions was analyzed and compared to obtain the water permeability response of municipal roads and the performance of drainage systems; After obtaining the permeability response of the municipal highway and the performance of the drainage system, the 3D digital model parameters or input types are adjusted according to the output results of the 3D digital model to optimize the performance of the 3D digital model.

6. The BIM-based municipal highway water seepage detection method according to claim 1, characterized in that: The fourth step is to analyze the changing pattern of road waterlogging under different rainfall conditions in the simulation results, which specifically includes the following steps: Analyze the changes in total water accumulation: observe whether there are significant changes in the total water accumulation on the road under different rainfall conditions; Analyze the changes in water depth: observe whether there are significant changes in the depth of road water under different rainfall conditions; Analyze the changes in the duration of waterlogging: observe whether there are significant changes in the duration of road waterlogging under different rainfall conditions; Analyze the changes in the location of water accumulation: observe whether there are obvious changes in the location of water accumulation on the road under different rainfall conditions.

7. The BIM-based municipal highway water seepage detection method according to claim 1, characterized in that: The fifth step is to perform cluster analysis on different simulation results and corresponding water penetration detection schemes using a decision tree model, which specifically includes the following steps: Clarify the objectives and scope of the cluster analysis, and cluster the simulation results and corresponding water seepage detection plans according to different rainfall conditions and road types; Organize the water permeability data corresponding to different rainfall conditions and use the water permeability data as input features of the decision tree model; Use the decision tree algorithm to train the input features so that each internal node in the decision tree model represents a feature attribute, each branch represents a value of the attribute, and each leaf node represents a category label; The cluster analysis performance of the decision tree model was evaluated, the trained decision tree model was applied to different simulation results and corresponding water seepage detection schemes, and cluster analysis was performed based on the category labels output by the decision tree model.

8. The BIM-based municipal highway water seepage detection method according to claim 1, characterized in that: Also includes: Before using the 3D digital model to simulate road waterlogging, conduct a blockage analysis on the municipal pipelines; Adjust the 3D digital model based on the results of the siltation analysis; Among them, the blockage analysis of municipal pipelines includes: Determine each drainage outlet in the three-dimensional digital model and construct a state feature set based on the environment around each drainage outlet; According to the state feature set, the corresponding blockage analysis library is retrieved; Through the siltation analysis library, the drainage data corresponding to the drainage outlet is analyzed to obtain the corresponding siltation analysis results.

9. The BIM-based municipal highway water seepage detection method according to claim 8, characterized in that: Through the siltation analysis library, the drainage data corresponding to the drain outlet is analyzed to obtain the corresponding siltation analysis results, including: Segment the drainage data according to the water level inside the drainage pipe corresponding to the drainage outlet, obtain multiple data segments and number the data segments; Based on the segmentation basis, determine the type of each data segment; Determine the analysis method based on the type of each data segment; Based on the blockage analysis library, determine the analysis parameters corresponding to each analysis method and calculate the blockage parameter according to the following formula: ； Where, Indicates the number The congestion parameters corresponding to the data segment; Indicates the number The congestion parameters corresponding to the data segment; is a pre-configured transition coefficient; They are all coefficients corresponding to the analysis method retrieved from the blockage analysis library according to the type of data segment; The coefficients are preset for the corresponding state feature set from the blockage analysis library; is the preset pipeline roughness coefficient; is the cross-sectional area of the pipe; is the wetted radius of the water flow, is the slope of the water flow; is the preset correlation coefficient; is the preset sedimentation factor.

10. The BIM-based municipal highway water seepage detection method according to claim 8, characterized in that: Identify each drainage outlet in the 3D digital model and construct a state feature set based on the environment around each drainage outlet, including: With the drain outlet as the center, the preset segmentation grid is mapped into the three-dimensional digital model; By segmenting the grid and intercepting the corresponding area in the 3D digital model, each area is analyzed according to the pre-configured regional analysis library to determine the analysis value; Fill the analysis value into the corresponding position of the data set template corresponding to the segmentation grid; The data value of the corresponding position of the drain outlet corresponding to the dataset template is calculated according to the following formula: ； Where, The data value of the drain outlet corresponding to the corresponding position in the dataset template; The first Rank Column data; The total number of rows of data on the dataset template; The total number of columns of data on the dataset template; is a preset constant, which is the number of divided regions on the side length of the divided grid; Determine the analysis data corresponding to the data on the boundary of the dataset template from the line connecting the corresponding position of the drain outlet on the dataset template to the boundary, and calculate the data value on the boundary according to the following formula: ； Where, is the data value on the boundary; For the The data value of the analyzed data, is the total number of analyzed data.

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