Earth excavation side slope shape and earth volume measuring and calculating method based on BIM (Building Information Modeling) technology

Abstract

The invention discloses an earthwork excavation slope shape and earthwork volume measuring and calculating method based on a BIM technology, and belongs to the field of earthwork construction. The problem that high-precision and comprehensive measurement of the terrain is not emphasized in existing earthwork construction is solved, the three-dimensional real-scene model is established through the three-dimensional laser scanning technology, and the three-dimensional laser scanning technology can monitor the terrain of a construction site in real time to obtain monitoring data. The method comprises the following steps: establishing a BIM model and determining a design scheme through original data obtained by an unmanned aerial vehicle, comparing the established BIM model with monitoring data to achieve the purposes of optimizing the BIM model and optimizing the design scheme, and fusing the BIM model with a three-dimensional real scene model to obtain a fusion model. A construction scheme and construction parameters can be determined by measuring and calculating the earthwork volume through the fusion model, comprehensive and accurate topographic data can be provided through the three-dimensional laser scanning technology, advantage complementation is achieved through fusion of the BIM model and the three-dimensional live-action model, and the planning, design and construction efficiency of earthwork is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of earthwork construction, and in particular to a method for calculating the shape of an earthwork excavation slope and the amount of earthwork based on BIM technology. Background Art

[0002] In the process of earthwork construction, since it is a very important part of the foundation pit location, in order to ensure the smooth construction of the foundation pit project, it is necessary to make scientific and reasonable planning for the earthwork construction. In earthwork engineering, measurement is a key link, which directly affects the quality and progress of the project. The existing earthwork construction is completely based on the construction drawings and excavation experience to determine the slope range and calculate the earthwork volume. It does not focus on high-precision and comprehensive measurement of the terrain, so it is impossible to obtain the three-dimensional information of the on-site terrain and buildings. As a result, when encountering complex-shaped earthwork excavation, the accurate earthwork volume cannot be calculated in time to guide subsequent construction; therefore, it does not meet the existing needs. For this, we propose a method for measuring the shape and volume of earthwork excavation slopes based on BIM technology. Summary of the invention

[0003] The purpose of the present invention is to provide a method for measuring the shape and amount of earthwork excavation slope based on BIM technology, establish a three-dimensional real-scene model through point cloud data obtained by three-dimensional laser scanning technology, and the three-dimensional laser scanning technology can provide comprehensive and accurate terrain data to help construction personnel understand the on-site terrain and landform conditions more accurately. At the same time, the terrain of the construction site can be monitored in real time by three-dimensional laser scanning technology to obtain monitoring data, and the BIM model is established with the original data obtained by the drone, and the design plan of the slope excavation is determined according to the BIM model, and the established BIM model is compared with the monitoring data to achieve the purpose of optimizing the BIM model, and the optimized BIM model and the constructed three-dimensional real-scene model are fused after registration to obtain a fusion model, and the slope excavation area is determined on the fusion model according to the design plan and the depth information is recorded, and an excavation range line is formed in the excavation area, and the earthwork volume is measured according to the excavation range line and the depth information, and the construction plan and construction parameters are determined according to the measurement results, thereby solving the problems raised in the above-mentioned background technology.

[0004] To achieve the above object, the present invention provides the following technical solution: a method for calculating the shape and volume of earthwork excavation slope based on BIM technology, comprising the following steps: Step 1: Use 3D laser scanning technology to scan the construction site, obtain point cloud data, build a 3D real-scene model based on the point cloud data, and use 3D laser scanning technology to monitor the terrain of the construction site in real time, and obtain monitoring data of the terrain of the construction site through real-time monitoring; Step 2: Use drones to obtain raw data, build a BIM model based on the raw data, determine the design plan for slope excavation by building the BIM model, compare the BIM model with the monitoring data, and optimize the BIM model; Step 3: Process the optimized BIM model and the constructed 3D real scene model, register the processed BIM model with the 3D real scene model, and fuse the registered BIM model with the point cloud model to obtain a fusion model; Step 4: Determine the slope excavation area on the fusion model according to the design plan, record the depth information of the excavation area, form an excavation range line in the excavation area, calculate the earthwork volume according to the excavation range line and depth information, and determine the construction plan and construction parameters according to the calculation results.

[0005] Furthermore, in step 1, a three-dimensional real scene model is established, and the following operations are specifically performed: Use 3D laser scanning technology to scan the construction site and obtain point cloud data, including topographic data and topographic information of the construction site and 3D coordinate information of the surface of the construction site; After scanning is completed, the acquired point cloud data is processed, and the data processing process includes point cloud reconstruction and noise filtering; Among them, point cloud reconstruction is to splice and optimize point cloud data to generate a more complete and continuous geometry; Establish a 3D real scene model based on point cloud data, and perform post-modification on the established 3D real scene model; Among them, post-modification enhances the realism of the 3D real-scene model through texture mapping, uses mesh correction tools to smooth the 3D real-scene model, and uses subdivision surface technology to refine the 3D real-scene model.

[0006] Furthermore, the data processing includes: Point cloud reconstruction for: The feature matching algorithm is used to perform point cloud registration on the point cloud data obtained by different scans. The different point cloud data are matched through registration so that the point cloud data are in the same coordinate system. Noise filtering for: Statistical methods are used to filter the noise of point cloud data. Based on statistical principles, point cloud data is analyzed to identify and eliminate outliers or noise points.

[0007] Furthermore, the step 2 comprises the following steps: Use drones to take photos and record all aspects of the site terrain to obtain original data, and then build a BIM model based on the original data and construction drawings; Based on the monitoring data obtained by real-time monitoring of the construction site terrain using 3D laser scanning technology, the BIM model is compared with the 3D scanning data to verify the accuracy and feasibility of the design plan and optimize the BIM model; Adjust the design plan in real time based on the optimized BIM model.

[0008] Furthermore, drones are used to take photos and record the terrain of the site being surveyed in all directions to obtain original data, including: Control the drone to take all-round photos and records of the terrain of the site being surveyed to obtain original data; Extracting each image data from the original data; Extracting the grayscale value of each pixel contained in the current image data; Compare the grayscale value of each pixel with a preset first grayscale threshold and a second grayscale threshold respectively; Extracting pixel points whose grayscale values ​​do not exceed the first grayscale threshold to form a first pixel point set; Extracting pixel points whose grayscale values ​​exceed the first grayscale threshold but do not exceed the second grayscale threshold to form a second pixel point set; Extracting pixel points whose grayscale values ​​exceed the second grayscale threshold to form a third pixel point set; Respectively obtaining a first grayscale coefficient, a second grayscale coefficient, and a third grayscale coefficient corresponding to the first pixel point set, the second pixel point set, and the third pixel point set by using the grayscale values ​​of the pixels in the first pixel point set, the second pixel point set, and the third pixel point set; The first grayscale coefficient, the second grayscale coefficient and the third grayscale coefficient are obtained by the following formula:

[0009] Among them, S 01 Represents the first grayscale coefficient; n 01 represents the number of pixels contained in the first pixel set; h 01i represents the gray value of the i-th pixel in the first pixel set; h max01 represents the maximum grayscale value of the pixels contained in the first pixel set; min01 represents the minimum grayscale value among the non-zero grayscale values ​​of the pixels included in the first pixel set; maxe01 h represents the grayscale value corresponding to the pixel whose grayscale value is second only to the grayscale maximum value in the first pixel set; y01 represents the first grayscale threshold;

[0010] Among them, S02 Represents the second grayscale coefficient; n 02 represents the number of pixels contained in the second pixel set; h 02i represents the gray value of the i-th pixel in the second pixel set; h max02 represents the maximum grayscale value of the pixels included in the second pixel set; min02 represents the minimum grayscale value among the non-zero grayscale values ​​of the pixels included in the second pixel set; maxe02 h represents the grayscale value corresponding to the pixel whose grayscale value is second only to the grayscale maximum value in the second pixel set; y01 represents the first grayscale threshold; h y02 represents the second grayscale threshold; H represents the adjustment coefficient;

[0011] Among them, S 03 Indicates the third grayscale coefficient; n 03 represents the number of pixels contained in the third pixel set; h 03i represents the gray value of the i-th pixel in the third pixel set; h max03 represents the maximum grayscale value of the pixels included in the third pixel set; min03 represents the minimum grayscale value among the non-zero grayscale values ​​of the pixels included in the third pixel set; maxe03 h represents the grayscale value corresponding to the pixel whose grayscale value is second only to the grayscale maximum value in the third pixel set; y02 represents the second grayscale threshold; Determine whether it is necessary to adjust the grayscale values ​​of the pixels in the first pixel point set, the second pixel point set and the third pixel point set based on the first grayscale coefficient, the second grayscale coefficient and the third grayscale coefficient corresponding to the first pixel point set, the second pixel point set and the third pixel point set.

[0012] Further, determining whether it is necessary to adjust the grayscale values ​​of pixels in the first pixel set, the second pixel set, and the third pixel set according to the first grayscale coefficient, the second grayscale coefficient, and the third grayscale coefficient corresponding to the first pixel set, the second pixel set, and the third pixel set includes: Compare the first grayscale coefficient, the second grayscale coefficient and the third grayscale coefficient with a preset first coefficient threshold and a preset second coefficient threshold respectively; When any one of the first grayscale coefficient, the second grayscale coefficient and the third grayscale coefficient is lower than the first coefficient threshold or higher than the second coefficient threshold, it is determined that the pixel point set corresponding to the value lower than the first coefficient threshold or higher than the second coefficient threshold needs to be taken as the target pixel set; Extracting the grayscale values ​​corresponding to all pixels in the target pixel set; The target grayscale value corresponding to each pixel point is obtained by using the quantitative relationship between the grayscale coefficient value corresponding to the target pixel set and the first coefficient threshold or the second coefficient threshold; wherein the target grayscale value is obtained by the following formula:

[0013] Among them, h t Indicates the target grayscale value corresponding to each pixel in the target pixel set; h x Indicates the grayscale value corresponding to each pixel in the target pixel set; h xi represents the gray value corresponding to the i-th pixel in the target pixel set; h yxi represents the value corresponding to the grayscale threshold with the smallest grayscale value difference with the i-th pixel point; S y01 and S y02 Respectively represent the first coefficient threshold and the second coefficient threshold; S x Indicates the grayscale coefficient value corresponding to the target pixel set; The grayscale value of each pixel in the target pixel set is adjusted according to the target grayscale value.

[0014] Furthermore, after the drone flies to an appropriate height, the onboard camera shoots vertically downward from the ground, and the drone moves back and forth in a certain direction of the site in a zigzag shape, and the height of the drone always remains at an altitude, so that the viewing angle of the onboard camera presents a strip-like shape and gradually covers the entire site in order, and the construction site is fully covered. The established BIM model is consistent with the construction drawings, and professionals will review the BIM model after it is established.

[0015] Furthermore, in the step three, the BIM model and the three-dimensional real-scene model belong to two different model forms. By processing the BIM model and the three-dimensional real-scene model, the BIM model and the three-dimensional real-scene model are placed in the same coordinate system. The processed BIM model and the three-dimensional real-scene model are used for subsequent model registration. Through the registration processing, the BIM model and the three-dimensional real-scene model are consistent. The registered BIM model is fused with the point cloud model to obtain a fused model.

[0016] Furthermore, the step 4 comprises the following steps: According to the design plan, determine the slope excavation area on the fusion model, record the depth information of the excavation area, and form an excavation range line in the excavation area; According to the formed excavation range line, the excavation area to be measured will be cut in the fusion model; According to the excavation range line and depth information, the earthwork volume of the cut excavation area is calculated; The construction plan and construction parameters are determined based on the measurement results, and on-site construction personnel carry out construction in accordance with the construction plan and construction parameters.

[0017] Furthermore, the model clipping, based on voxel grid clipping technology, converts the fused model into voxel representation, calculates the intersection of the clipping plane and the voxel, determines whether each voxel is inside or outside the clipping area, merges, deletes or retains the voxel according to the calculation result, and then clips the measured excavation area on the fused model.

[0018] Compared with the prior art, the present invention has the following beneficial effects: The present invention scans the construction site through 3D laser scanning technology to obtain point cloud data. After the scanning is completed, the point cloud data is processed and a 3D real-scene model is established. The established 3D real-scene model needs to be post-modified to enhance the sense of reality. At the same time, the 3D laser scanning technology can be used to monitor the terrain of the construction site in real time, so as to obtain monitoring data, and the original data obtained by the drone can be used to establish a BIM model. According to the BIM model, the design plan of the slope excavation can be determined, and the monitoring data is brought into the BIM model to compare the BIM model with the monitoring data, so as to compare and verify with the actual site, verify the accuracy and feasibility of the design plan, help construction personnel to discover and solve problems in time, and achieve the purpose of optimizing the BIM model, thereby achieving the purpose of optimizing the design plan and improving the efficiency and quality of engineering construction.

[0019] The present invention processes and aligns the optimized BIM model with the constructed 3D real-scene model, and fuses the aligned BIM model with the point cloud model to obtain a fused model; determines the slope excavation area on the fused model according to the design plan, records the depth information of the excavation area, forms an excavation range line in the excavation area, measures the earthwork volume according to the excavation range line and the depth information, determines the construction plan and construction parameters according to the measurement results, and the construction party performs construction according to the construction plan and construction parameters; 3D laser scanning technology can provide comprehensive and accurate terrain data to help construction personnel understand the on-site terrain and landform conditions more accurately; in earthwork engineering measurement, the BIM model and the 3D real-scene model are integrated to achieve complementary advantages and improve the planning, design and construction efficiency of earthwork engineering. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 It is a flow chart of the method for calculating the shape of earthwork excavation slope and earthwork volume of the present invention; Figure 2 This is a flow chart of the registration of the BIM model and the three-dimensional real scene model of the present invention. DETAILED DESCRIPTION

[0021] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. 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 creative work are within the scope of protection of the present invention.

[0022] In order to solve the technical problem that the existing earthwork construction is completely based on the construction drawings and excavation experience to determine the slope range and calculate the earthwork volume, without paying attention to the high-precision and comprehensive measurement of the terrain, so that the three-dimensional information of the on-site terrain and buildings cannot be obtained, resulting in the calculation of the earthwork volume to guide the subsequent construction in time when encountering complex shapes of earthwork excavation, please refer to Figure 1-Figure 2 , this embodiment provides the following technical solutions: The method for calculating the shape and volume of earthwork excavation slope based on BIM technology includes the following steps: Step 1: Use 3D laser scanning technology to scan the construction site, obtain point cloud data, build a 3D real-scene model based on the point cloud data, and use 3D laser scanning technology to monitor the terrain of the construction site in real time, and obtain monitoring data of the terrain of the construction site through real-time monitoring; Step 2: Use drones to obtain raw data, build a BIM model based on the raw data, determine the design plan for slope excavation by building the BIM model, compare the BIM model with the monitoring data, and optimize the BIM model; Step 3: Process the optimized BIM model and the constructed 3D real scene model, register the processed BIM model with the 3D real scene model, and fuse the registered BIM model with the point cloud model to obtain a fusion model; Step 4: Determine the slope excavation area on the fusion model according to the design plan, record the depth information of the excavation area, form an excavation range line in the excavation area, calculate the earthwork volume according to the excavation range line and depth information, and determine the construction plan and construction parameters according to the calculation results.

[0023] In step 1, a 3D real scene model is established. Specifically, the following operations are performed: Use 3D laser scanning technology to scan the construction site and obtain point cloud data, including topographic data and topographic information of the construction site and 3D coordinate information of the surface of the construction site; After scanning is completed, the acquired point cloud data is processed, and the data processing process includes point cloud reconstruction and noise filtering; Among them, point cloud reconstruction is to splice and optimize point cloud data to generate a more complete and continuous geometry; Point cloud reconstruction for: The feature matching algorithm is used to perform point cloud registration on the point cloud data obtained by different scans. The different point cloud data are matched through registration so that the point cloud data are in the same coordinate system. Noise filtering for: Use statistical methods to filter noise on point cloud data. Based on statistical principles, analyze point cloud data to identify and eliminate outliers or noise points. Establish a 3D real scene model based on point cloud data, and perform post-modification on the established 3D real scene model; Among them, post-modification enhances the realism of the 3D real-scene model through texture mapping, uses mesh correction tools to smooth the 3D real-scene model, and uses subdivision surface technology to refine the 3D real-scene model.

[0024] The technical effects of the above content are as follows: the construction site can be scanned by 3D laser scanning technology. When using 3D laser scanning technology, information collection of measurement targets can be realized in a larger range, thereby providing more comprehensive data information for the construction team. Point cloud data can be obtained by 3D laser scanning technology. The point cloud data obtained includes terrain data, terrain information and 3D coordinate information of the surface of the construction site, which can help construction personnel understand the terrain and landform conditions on site more accurately. Before modeling, the point cloud data needs to be reconstructed and noise filtered. The point cloud data is spliced ​​and optimized through point cloud reconstruction to generate a more complete and continuous geometric body. The feature matching algorithm can be used to identify the point cloud data obtained from different scans. Point cloud registration is performed based on the data, so that the point cloud data is in the same coordinate system, and noise filtering is performed on the point cloud data using statistical methods to eliminate noise points in the point cloud data. By processing the point cloud data, the quality of the point cloud data can be improved, which is convenient for subsequent modeling work. A 3D real-scene model is established based on the processed point cloud data, and the established 3D real-scene model needs to be modified later. The realism of the 3D real-scene model can be enhanced through texture mapping, the 3D real-scene model can be smoothed through the mesh correction tool, and the 3D real-scene model can be refined through the subdivision surface technology. Through the above operations, the realism and display effect of the 3D real-scene model can be enhanced, which is more conducive to the subsequent registration and fusion with the BIM model.

[0025] Step 2 includes the following steps: Use drones to take photos and record all aspects of the site terrain to obtain original data, and then build a BIM model based on the original data and construction drawings; Based on the monitoring data obtained by real-time monitoring of the construction site terrain using 3D laser scanning technology, the BIM model is compared with the 3D scanning data to verify the accuracy and feasibility of the design plan and optimize the BIM model; Adjust the design plan in real time based on the optimized BIM model; Among them, after the drone flies to an appropriate height, the onboard camera shoots vertically downward from the ground. The drone uses a zigzag shape to travel back and forth in a certain direction of the site, and the height of the drone always remains at an altitude, so that the field of view of the onboard camera presents a strip-like shape and gradually covers the entire site in order, and the construction site is fully covered. The established BIM model is consistent with the construction drawings, and professionals will review the BIM model after it is established.

[0026] The technical effects of the above content are as follows: drones can be used to take photos and record the terrain of the site being surveyed. When drones are used for surveying, the terrain of the site being surveyed can be photographed and recorded in all directions, thereby providing a data basis for the establishment of BIM models. After the drone is flown to an appropriate height, the onboard lens is used to shoot vertically downward from the ground. The drone uses a zigzag shape to go back and forth in a certain direction of the site, and the height of the drone is always maintained at an altitude, so that the viewing angle of the onboard lens can be presented in a strip-like manner and gradually cover the entire site in order. The construction site is photographed and recorded in all directions, thereby obtaining original data. Based on the existing construction drawings and the obtained original data, BIM can be established. IM model, and then the design plan of slope excavation can be determined according to the BIM model. According to the design plan, the excavation area of ​​the slope, that is, the shape of the slope excavation, and the depth information of the excavation area can be determined. Then, the monitoring data can be brought into the BIM model to compare the BIM model with the monitoring data, and then compared and verified with the actual site to verify the accuracy and feasibility of the design plan, so as to achieve the purpose of optimizing the BIM model, and then achieve the purpose of optimizing the design plan and improving the efficiency and quality of engineering construction. Real-time monitoring of the construction site terrain through 3D laser scanning technology can help construction personnel to discover and solve problems in time and ensure that the earthwork construction process is carried out according to the design plan.

[0027] In step three, the BIM model and the three-dimensional real-scene model belong to two different model forms. By processing the BIM model and the three-dimensional real-scene model, the BIM model and the three-dimensional real-scene model are placed in the same coordinate system. The processed BIM model and the three-dimensional real-scene model are used for subsequent model registration. Through the registration processing, the BIM model and the three-dimensional real-scene model are consistent. The registered BIM model is fused with the point cloud model to obtain a fused model.

[0028] Step 4 includes the following steps: According to the design plan, determine the slope excavation area on the fusion model, record the depth information of the excavation area, and form an excavation range line in the excavation area; According to the formed excavation range line, the excavation area to be measured will be cut in the fusion model; According to the excavation range line and depth information, the earthwork volume of the cut excavation area is calculated; The construction plan and construction parameters are determined based on the measurement results, and on-site construction personnel carry out construction in accordance with the construction plan and construction parameters.

[0029] Among them, model clipping, based on voxel grid clipping technology, converts the fusion model into voxel representation, calculates the intersection of the clipping plane and the voxel, determines whether each voxel is inside or outside the clipping area, and merges, deletes or retains the voxel according to the calculation result, and then clips the measured excavation area on the fusion model.

[0030] Technical effects of the above contents: Both the BIM model and the 3D real-scene model include earthwork construction data. The BIM model and the 3D real-scene model can be integrated to realize data sharing and integration. Before integration, the BIM model and the 3D real-scene model need to be processed first so that the BIM model and the 3D real-scene model are in the same coordinate system to facilitate subsequent integration. The processed BIM model and the 3D real-scene model need to be registered. The registration can make the BIM model and the 3D real-scene model consistent. The registered BIM model and the point cloud model can be fused to obtain a fused model. Through the fusion of the BIM model and the 3D real-scene model, the geometric information in the 3D real-scene model can be matched with the elements in the BIM model to realize spatial positioning and precise matching, so that the accurate earthwork volume can be calculated more accurately to guide subsequent construction. The above-determined design scheme can determine the slope excavation area on the fusion model, record the depth information of the excavation area, and form an excavation range line in the determined excavation area. Based on the voxel grid clipping technology and the formed excavation range line, the measured excavation area can be clipped on the fusion model, and the earthwork volume of the clipped excavation area is measured according to the excavation range line and the depth information to obtain the measurement result. The construction plan and construction parameters can be determined according to the measurement result. The on-site construction personnel carry out construction according to the construction plan and construction parameters. In the measurement of earthwork engineering, the use of 3D laser scanning technology can provide comprehensive and accurate terrain data to help construction personnel understand the on-site terrain and landform conditions more accurately. The fusion between the BIM model and the 3D real-life model can achieve complementary advantages, thereby improving the planning, design and construction efficiency of earthwork engineering.

[0031] Working principle: The construction site can be scanned by 3D laser scanning technology, so as to provide more comprehensive data information for the construction team, and help construction personnel to understand the terrain and landform conditions on site more accurately. Point cloud data is obtained by 3D laser scanning technology, and point cloud data needs to be reconstructed and noise filtered before modeling to improve the data quality for subsequent modeling work. A 3D real-life model is established based on the processed point cloud data, and the established 3D real-life model needs to be modified later. Texture mapping, smoothing and refinement can increase the sense of reality and display effect of the 3D real-life model, which is more conducive to the subsequent registration and fusion with the BIM model. The 3D laser scanning technology can also monitor the terrain of the construction site in real time to obtain monitoring data. At the same time, the drone can take pictures of the surveyed site terrain in an all-round way to obtain the original data. A BIM model can be established based on the existing construction drawings and the original data obtained, and then according to the BIM model Then the design plan for slope excavation can be determined, and then the monitoring data can be brought into the BIM model to compare the BIM model with the monitoring data to verify the accuracy and feasibility of the design plan, so as to achieve the purpose of optimizing the BIM model, and then achieve the purpose of optimizing the design plan and improving the efficiency and quality of engineering construction. Finally, the optimized BIM model is processed and aligned with the constructed 3D real-life model, and the aligned BIM model is fused with the point cloud model to obtain a fusion model. According to the design plan, the slope excavation area is determined on the fusion model, the depth information of the excavation area is recorded, and the excavation range line is formed in the excavation area. The construction plan and construction parameters can be determined by calculating the earthwork volume based on the excavation range line and depth information. In the measurement of earthwork engineering, 3D laser scanning technology can provide comprehensive and accurate terrain data to help construction personnel understand the on-site terrain and landform conditions more accurately. The BIM model and the 3D real-life model are integrated to achieve complementary advantages and improve the planning, design and construction efficiency of earthwork engineering.

[0032] In one embodiment of the present invention, a drone is used to take photos and record the terrain of the site being surveyed in an all-round manner to obtain raw data, including: Control the drone to take all-round photos and records of the terrain of the site being surveyed to obtain original data; Extracting each image data from the original data; Extracting the grayscale value of each pixel contained in the current image data; Compare the grayscale value of each pixel with a preset first grayscale threshold and a second grayscale threshold respectively; Extracting pixel points whose grayscale values ​​do not exceed the first grayscale threshold to form a first pixel point set; Extracting pixel points whose grayscale values ​​exceed the first grayscale threshold but do not exceed the second grayscale threshold to form a second pixel point set; Extracting pixel points whose grayscale values ​​exceed the second grayscale threshold to form a third pixel point set; Respectively obtaining a first grayscale coefficient, a second grayscale coefficient, and a third grayscale coefficient corresponding to the first pixel point set, the second pixel point set, and the third pixel point set by using the grayscale values ​​of the pixels in the first pixel point set, the second pixel point set, and the third pixel point set; The first grayscale coefficient, the second grayscale coefficient and the third grayscale coefficient are obtained by the following formula:

[0033] Among them, S 01 Represents the first grayscale coefficient; n 01 represents the number of pixels contained in the first pixel set; h 01i represents the gray value of the i-th pixel in the first pixel set; h max01 represents the maximum grayscale value of the pixels contained in the first pixel set; min01 represents the minimum grayscale value among the non-zero grayscale values ​​of the pixels included in the first pixel set; maxe01 h represents the grayscale value corresponding to the pixel whose grayscale value is second only to the grayscale maximum value in the first pixel set; y01 represents the first grayscale threshold;

[0034] Among them, S 02 Represents the second grayscale coefficient; n 02 represents the number of pixels contained in the second pixel set; h 02i represents the gray value of the i-th pixel in the second pixel set; h max02 represents the maximum grayscale value of the pixels included in the second pixel set; min02 represents the minimum grayscale value among the non-zero grayscale values ​​of the pixels included in the second pixel set; maxe02 h represents the grayscale value corresponding to the pixel whose grayscale value is second only to the grayscale maximum value in the second pixel set; y01 represents the first grayscale threshold; h y02 represents the second grayscale threshold; H represents the adjustment coefficient;

[0035] Among them, S 03 Indicates the third grayscale coefficient; n 03 represents the number of pixels contained in the third pixel set; h03i represents the gray value of the i-th pixel in the third pixel set; h max03 represents the maximum grayscale value of the pixels included in the third pixel set; min03 represents the minimum grayscale value among the non-zero grayscale values ​​of the pixels included in the third pixel set; maxe03 h represents the grayscale value corresponding to the pixel whose grayscale value is second only to the grayscale maximum value in the third pixel set; y02 represents the second grayscale threshold; Determine whether it is necessary to adjust the grayscale values ​​of the pixels in the first pixel point set, the second pixel point set and the third pixel point set based on the first grayscale coefficient, the second grayscale coefficient and the third grayscale coefficient corresponding to the first pixel point set, the second pixel point set and the third pixel point set.

[0036] The technical effect of the above technical solution is that by taking all-round photos of the surveyed site by drone, detailed and comprehensive raw data can be obtained. These data are then carefully processed, including the precise extraction and classification of the gray value of each pixel, ensuring the meticulousness and accuracy of topographic mapping.

[0037] By comparing the grayscale values ​​of pixels with the preset grayscale threshold and classifying them into different sets (first pixel set, second pixel set, third pixel set), this step achieves preliminary hierarchical processing of the image content, which helps subsequent more detailed image analysis and processing.

[0038] By calculating the grayscale coefficients of each set (first grayscale coefficient, second grayscale coefficient, third grayscale coefficient), the technical solution can evaluate the distribution of pixels in different grayscale intervals and determine whether the grayscale values ​​of pixels in a specific set need to be adjusted based on these coefficients. This adaptive adjustment method helps optimize image quality and improve the readability and accuracy of topographic mapping results.

[0039] The entire processing flow is highly automated, from drone photography to image data extraction, classification, grayscale coefficient calculation, and grayscale value adjustment decisions, all of which are automatically completed through preset algorithms and rules, reducing human intervention and improving work efficiency and accuracy.

[0040] The grayscale threshold and adjustment coefficient in this technical solution can be adjusted according to specific surveying and mapping needs, so that the solution can maintain high adaptability and flexibility in surveying and mapping tasks under different terrains and different lighting conditions. At the same time, with the advancement of technology, the solution can be further expanded and optimized to meet more complex surveying and mapping needs.

[0041] In summary, this technical solution improves the accuracy and efficiency of topographic surveying and mapping through sophisticated image processing and analysis, while enhancing the level of automation and intelligence, providing new ideas and methods for the development of the field of topographic surveying and mapping.

[0042] Specifically, determining whether it is necessary to adjust the grayscale values ​​of pixels in the first pixel set, the second pixel set, and the third pixel set according to the first grayscale coefficient, the second grayscale coefficient, and the third grayscale coefficient corresponding to the first pixel set, the second pixel set, and the third pixel set includes: Compare the first grayscale coefficient, the second grayscale coefficient and the third grayscale coefficient with a preset first coefficient threshold and a preset second coefficient threshold respectively; When any one of the first grayscale coefficient, the second grayscale coefficient and the third grayscale coefficient is lower than the first coefficient threshold or higher than the second coefficient threshold, it is determined that the pixel point set corresponding to the value lower than the first coefficient threshold or higher than the second coefficient threshold needs to be taken as the target pixel set; Extracting the grayscale values ​​corresponding to all pixels in the target pixel set; The target grayscale value corresponding to each pixel point is obtained by using the quantitative relationship between the grayscale coefficient value corresponding to the target pixel set and the first coefficient threshold or the second coefficient threshold; wherein the target grayscale value is obtained by the following formula:

[0043] Among them, h t Indicates the target grayscale value corresponding to each pixel in the target pixel set; h x Indicates the grayscale value corresponding to each pixel in the target pixel set; h xi represents the gray value corresponding to the i-th pixel in the target pixel set; h yxi represents the value corresponding to the grayscale threshold with the smallest grayscale value difference with the i-th pixel point; S y01 and S y02 Respectively represent the first coefficient threshold and the second coefficient threshold; S x Indicates the grayscale coefficient value corresponding to the target pixel set; The grayscale value of each pixel in the target pixel set is adjusted according to the target grayscale value.

[0044] The technical effect of the above technical solution is: by comparing the grayscale coefficients of the first pixel set, the second pixel set and the third pixel set by threshold, it is possible to accurately identify which pixel sets need to adjust the grayscale value. This targeted adjustment method can improve the problem of uneven grayscale distribution in the image, improve the overall quality of the image, and make the surveying and mapping results clearer and more accurate.

[0045] During the grayscale value adjustment process, the target grayscale value of each pixel is obtained by using the quantitative relationship between the grayscale coefficient value corresponding to the target pixel set and the first coefficient threshold or the second coefficient threshold. This method can retain the detail information in the image and avoid the loss or blurring of details during the adjustment process.

[0046] This technical solution adopts an adaptive adjustment strategy, that is, whether to adjust the grayscale value and how to adjust it are determined based on the comparison between the actual value of the grayscale coefficient and the preset threshold. This strategy makes the adjustment process more flexible and intelligent, and can adapt to the mapping needs under different terrain and lighting conditions.

[0047] The entire adjustment process is highly automated, reducing manual intervention and improving processing efficiency. At the same time, because the grayscale value is adjusted only for the set of pixels that need to be adjusted, unnecessary calculations and resource waste are avoided.

[0048] Through precise grayscale value calculation and adaptive adjustment strategy, this technical solution can ensure the reliability and accuracy of surveying and mapping results. The adjusted image will be closer to the real terrain, providing strong support for subsequent geographic information system construction, urban planning, etc.

[0049] In summary, this technical solution effectively improves image quality, enhances image detail expression, improves processing efficiency, and ensures the reliability and accuracy of surveying and mapping results through grayscale coefficient threshold comparison and adaptive grayscale value adjustment strategy. These technical effects are of great significance to the development and application of topographic surveying and mapping.

[0050] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0051] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for calculating the shape and volume of earthwork excavation slope based on BIM technology, characterized in that: The following steps are involved: Step 1: Use 3D laser scanning technology to scan the construction site, obtain point cloud data, build a 3D real-scene model based on the point cloud data, and use 3D laser scanning technology to monitor the terrain of the construction site in real time, and obtain monitoring data of the terrain of the construction site through real-time monitoring; Step 2: Use drones to obtain raw data, build a BIM model based on the raw data, determine the design plan for slope excavation by building the BIM model, compare the BIM model with the monitoring data, and optimize the BIM model; Step 3: Process the optimized BIM model and the constructed 3D real scene model, register the processed BIM model with the 3D real scene model, and fuse the registered BIM model with the point cloud model to obtain a fusion model; Step 4: Determine the slope excavation area on the fusion model according to the design plan, record the depth information of the excavation area, form an excavation range line in the excavation area, calculate the earthwork volume according to the excavation range line and depth information, and determine the construction plan and construction parameters according to the calculation results.

2. The method for calculating the shape and volume of earthwork excavation slope based on BIM technology according to claim 1, characterized in that: In the step 1, a three-dimensional real scene model is established, and the following operations are specifically performed: Use 3D laser scanning technology to scan the construction site and obtain point cloud data, including topographic data and topographic information of the construction site and 3D coordinate information of the surface of the construction site; After scanning is completed, the acquired point cloud data is processed, and the data processing process includes point cloud reconstruction and noise filtering; Among them, point cloud reconstruction is to splice and optimize point cloud data to generate a more complete and continuous geometry; Establish a 3D real scene model based on point cloud data, and perform post-modification on the established 3D real scene model; Among them, post-modification enhances the realism of the 3D real-scene model through texture mapping, uses mesh correction tools to smooth the 3D real-scene model, and uses subdivision surface technology to refine the 3D real-scene model.

3. The method for calculating the shape and volume of earthwork excavation slope based on BIM technology according to claim 2, characterized in that: The data processing includes: Point cloud reconstruction for: The feature matching algorithm is used to perform point cloud registration on the point cloud data obtained by different scans. The different point cloud data are matched through registration so that the point cloud data are in the same coordinate system. Noise filtering for: Statistical methods are used to filter the noise of point cloud data. Based on statistical principles, point cloud data is analyzed to identify and eliminate outliers or noise points.

4. The method for calculating the shape and volume of earthwork excavation slope based on BIM technology according to claim 1, characterized in that: The step 2 comprises the following steps: Use drones to take photos and record all aspects of the site terrain to obtain original data, and then build a BIM model based on the original data and construction drawings; Based on the monitoring data obtained by real-time monitoring of the construction site terrain using 3D laser scanning technology, the BIM model is compared with the 3D scanning data to verify the accuracy and feasibility of the design plan and optimize the BIM model; Adjust the design plan in real time based on the optimized BIM model.

5. The method for calculating the shape and volume of earthwork excavation slope based on BIM technology according to claim 4 is characterized in that: Use drones to take photos and record the terrain of the site being surveyed in all directions to obtain original data, including: Control the drone to take all-round photos and records of the terrain of the site being mapped to obtain original data; Extracting each image data from the original data; Extracting the grayscale value of each pixel contained in the current image data; Compare the grayscale value of each pixel with a preset first grayscale threshold and a second grayscale threshold respectively; Extracting pixel points whose grayscale values ​​do not exceed the first grayscale threshold to form a first pixel point set; Extracting pixel points whose grayscale values ​​exceed the first grayscale threshold but do not exceed the second grayscale threshold to form a second pixel point set; Extracting pixel points whose grayscale values ​​exceed the second grayscale threshold to form a third pixel point set; Respectively obtaining a first grayscale coefficient, a second grayscale coefficient, and a third grayscale coefficient corresponding to the first pixel point set, the second pixel point set, and the third pixel point set by using the grayscale values ​​of the pixels in the first pixel point set, the second pixel point set, and the third pixel point set; The first grayscale coefficient, the second grayscale coefficient and the third grayscale coefficient are obtained by the following formula: ； Among them, S 01 Represents the first grayscale coefficient; n 01 represents the number of pixels contained in the first pixel set; h 01i represents the gray value of the i-th pixel in the first pixel set; h max01 represents the maximum grayscale value of the pixels contained in the first pixel set; min01 represents the minimum grayscale value among the non-zero grayscale values ​​of the pixels included in the first pixel set; maxe01 h represents the grayscale value corresponding to the pixel whose grayscale value is second only to the grayscale maximum value in the first pixel set; y01 represents the first grayscale threshold; ； Among them, S 02 Represents the second grayscale coefficient; n 02 represents the number of pixels contained in the second pixel set; h 02i represents the gray value of the i-th pixel in the second pixel set; h max02 represents the maximum grayscale value of the pixels included in the second pixel set; min02 represents the minimum grayscale value among the non-zero grayscale values ​​of the pixels included in the second pixel set; maxe02 h represents the grayscale value corresponding to the pixel whose grayscale value is second only to the grayscale maximum value in the second pixel set; y01 represents the first grayscale threshold; h y02 represents the second grayscale threshold; H represents the adjustment coefficient; ； Among them, S 03 Indicates the third grayscale coefficient; n 03 represents the number of pixels contained in the third pixel set; h 03i represents the gray value of the i-th pixel in the third pixel set; h max03 represents the maximum grayscale value of the pixels included in the third pixel set; min03 represents the minimum grayscale value among the non-zero grayscale values ​​of the pixels included in the third pixel set; maxe03 h represents the grayscale value corresponding to the pixel whose grayscale value is second only to the grayscale maximum value in the third pixel set; y02 represents the second grayscale threshold; Determine whether it is necessary to adjust the grayscale values ​​of the pixels in the first pixel point set, the second pixel point set and the third pixel point set based on the first grayscale coefficient, the second grayscale coefficient and the third grayscale coefficient corresponding to the first pixel point set, the second pixel point set and the third pixel point set.

6. The method for calculating the shape and volume of earthwork excavation slope based on BIM technology according to claim 5 is characterized in that: Determining whether it is necessary to adjust the grayscale values ​​of pixels in the first pixel point set, the second pixel point set, and the third pixel point set according to the first grayscale coefficient, the second grayscale coefficient, and the third grayscale coefficient corresponding to the first pixel point set, the second pixel point set, and the third pixel point set, includes: Compare the first grayscale coefficient, the second grayscale coefficient and the third grayscale coefficient with a preset first coefficient threshold and a preset second coefficient threshold respectively; When any one of the first grayscale coefficient, the second grayscale coefficient and the third grayscale coefficient is lower than the first coefficient threshold or higher than the second coefficient threshold, it is determined that the pixel point set corresponding to the value lower than the first coefficient threshold or higher than the second coefficient threshold needs to be taken as the target pixel set; Extracting the grayscale values ​​corresponding to all pixels in the target pixel set; The target grayscale value corresponding to each pixel point is obtained by using the quantitative relationship between the grayscale coefficient value corresponding to the target pixel set and the first coefficient threshold or the second coefficient threshold; wherein the target grayscale value is obtained by the following formula: ； Among them, h t Indicates the target grayscale value corresponding to each pixel in the target pixel set; h x Indicates the grayscale value corresponding to each pixel in the target pixel set; h xi represents the gray value corresponding to the i-th pixel in the target pixel set; h yxi represents the value corresponding to the grayscale threshold with the smallest grayscale value difference with the i-th pixel point; S y01 and S y02 Respectively represent the first coefficient threshold and the second coefficient threshold; S x Indicates the grayscale coefficient value corresponding to the target pixel set; The grayscale value of each pixel in the target pixel set is adjusted according to the target grayscale value.

7. The method for calculating the shape and volume of earthwork excavation slope based on BIM technology according to claim 4, characterized in that: After the drone flies to an appropriate height, the onboard camera shoots vertically downward from the ground. The drone moves back and forth in a zigzag shape along a certain direction of the site, and the height of the drone always remains at an altitude, so that the viewing angle of the onboard camera presents a strip-like range and gradually covers the entire site in order, and the construction site is fully covered. The established BIM model is consistent with the construction drawings, and professionals will review the BIM model after it is established.

8. The method for calculating the shape and volume of earthwork excavation slope based on BIM technology according to claim 1, characterized in that: In the step three, the BIM model and the three-dimensional real-scene model belong to two different model forms. By processing the BIM model and the three-dimensional real-scene model, the BIM model and the three-dimensional real-scene model are placed in the same coordinate system. The processed BIM model and the three-dimensional real-scene model are used for subsequent model registration. Through the registration process, the BIM model and the three-dimensional real-scene model are consistent. The registered BIM model is fused with the point cloud model to obtain a fused model.

9. The method for calculating the shape and volume of earthwork excavation slope based on BIM technology according to claim 1, characterized in that: The step 4 comprises the following steps: According to the design plan, determine the slope excavation area on the fusion model, record the depth information of the excavation area, and form an excavation range line in the excavation area; According to the formed excavation range line, the excavation area to be measured will be cut in the fusion model; According to the excavation range line and depth information, the earthwork volume of the cut excavation area is calculated; The construction plan and construction parameters are determined based on the measurement results, and on-site construction personnel carry out construction in accordance with the construction plan and construction parameters.

10. The method for calculating the shape and volume of earthwork excavation slope based on BIM technology according to claim 9, characterized in that: The model clipping is based on voxel grid clipping technology, which converts the fused model into voxel representation, calculates the intersection of the clipping plane and the voxel, determines whether each voxel is inside or outside the clipping area, merges, deletes or retains the voxel according to the calculation result, and then clips the measured excavation area on the fused model.

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