Construction cost estimation method and estimation device based on three-dimensional scanning technology

Abstract

The present application relates to the technical field of building cost estimation, in particular to a construction cost estimation method and estimation device based on three-dimensional scanning technology. The present application firstly generates a design model point cloud from a building design model, then takes the design model point cloud as a target point cloud and the construction site point cloud as a source point cloud, and performs registration by calculating the rotation and translation matrix between the two point clouds to transform the source point cloud into the same coordinate system as the target point cloud, so that the construction site point cloud can be converted to the corresponding position of the design model. After registration, the number of components covered by the completed building design model is calculated, and finally the construction cost is calculated based on the number of completed components, the quantity of each component and the unit price of the quantity. Since the present application compares the design components with the site point cloud one by one to determine the completed components on site, the accuracy of the construction cost calculated based on the completed components is improved.

Description

Technical Field

[0001] This invention relates to the field of construction cost estimation technology, specifically to a construction cost estimation method and device based on three-dimensional scanning technology. Background Technology

[0002] Cost estimation during construction is a crucial part of building project management. In the process of settling progress payments, it requires project managers from the client, contractor, and auditor to repeatedly calculate the on-site construction volume based on the on-site construction progress report. Then, based on the construction volume and the unit price of the work, the cost required for the completed work is calculated. Calculating the on-site construction volume is a time-consuming, costly, and labor-intensive task with low automation.

[0003] For example, construction workers build a building on-site based on a complete BIM model (the drawings of the building to be completed). When calculating the amount of work completed for the building, and thus the associated construction cost, current technology involves manually comparing each component name in the BIM model with components already under construction on-site to determine the amount of work covered by the BIM model and then estimating the construction cost based on that amount. Because this technology relies on manual comparison of on-site components, it is highly susceptible to errors, leading to calculated construction costs that deviate from the actual construction costs.

[0004] In summary, the accuracy of construction costs calculated using existing technologies is relatively low.

[0005] Therefore, existing technologies still need to be improved and enhanced. Summary of the Invention

[0006] To address the aforementioned technical problems, this invention provides a construction cost estimation method and device based on three-dimensional scanning technology, which solves the problem of low accuracy in construction cost calculations by existing technologies.

[0007] To achieve the above objectives, the present invention adopts the following technical solution:

[0008] In a first aspect, the present invention provides a construction cost estimation method based on three-dimensional scanning technology, comprising:

[0009] The point cloud of the architectural design model is generated. The architectural design model is a complete model corresponding to the building under construction on site. The point cloud is used to represent the position of each point on the building.

[0010] The design model point cloud is registered with the site point cloud, which is the point cloud of the on-site construction building obtained using 3D scanning technology;

[0011] Based on the registered on-site point cloud and the unit price of the constructed components, the construction cost of the on-site construction building is estimated, and the components are used to assemble the on-site construction building.

[0012] In one implementation, the point cloud generated from the architectural design model is a complete model corresponding to the building under construction on site. The point cloud is used to represent the position of various points on the building, including:

[0013] Based on the architectural design model, the BIM model in the architectural design model is obtained;

[0014] The BIM model is converted to IFC format to obtain the BIM model in IFC format.

[0015] Extract the IFC entities from the BIM model in IFC format, convert them to the intermediate format OBJ, and then extract each group of triangular faces.

[0016] Based on the vertices and normal vectors described in each group, the point cloud is filled to generate the point cloud of the design model.

[0017] In one implementation, the design model point cloud is used for on-site point cloud registration, wherein the on-site point cloud is a point cloud of the on-site construction building obtained using 3D scanning technology, including:

[0018] The scale of the point cloud in the design model and the point cloud in the actual site are unified;

[0019] Set the same mesh size for the point cloud of the design model and the point cloud of the site after unifying the scale;

[0020] Voxel downsampling is performed on the point clouds of the design model point cloud and the point clouds of the field point cloud that are located in the same grid, respectively, to obtain the design sampling point cloud and the field sampling point cloud corresponding to the design model point cloud;

[0021] The field sampling point cloud and the design sampling point cloud are registered to obtain the registered field sampling point cloud. The registration is used to adjust the position of each point in the field sampling point cloud so that the position of each point in the field sampling point cloud matches the position of each point in the design sampling point cloud, thus completing the operation of registering the design model point cloud to the field point cloud.

[0022] In one implementation, the method for obtaining the constructed components in the site point cloud includes:

[0023] The positions of each component model in the architectural design model are obtained, and each component model is used to assemble the architectural design model.

[0024] The positions of each component model are matched one by one with the registered field sampling point cloud according to the attributes corresponding to each component model to obtain the constructed components.

[0025] In one implementation, the estimated construction cost of the on-site construction building is based on the registered on-site point cloud and the unit price of the constructed components, wherein the components are used to assemble the on-site construction building, including:

[0026] Based on the position of the components in each design model in the on-site point cloud, the corresponding neighborhood point clouds of each constructed component are obtained;

[0027] Based on the registration accuracy error, each of the neighboring point clouds is adjusted to obtain the point cloud of the constructed component. The registration accuracy error is used to characterize the distance between the points in the registered field sampling point cloud and the corresponding points in the design model point cloud.

[0028] Based on the point cloud of the constructed components and the unit price of the construction quantity of the point cloud of the constructed components, estimate the construction cost of the on-site construction building.

[0029] In one implementation, the calculation method for the registration accuracy error includes:

[0030] The distance between the points in the registered field sampling point cloud and the corresponding points in the design model point cloud is calculated using the K-nearest neighbor search algorithm.

[0031] Based on the distance between points in the field sampling point cloud and corresponding points in the design model point cloud, calculate the root mean square error between the field sampling point cloud and the design model point cloud;

[0032] Based on the root mean square error, the registration accuracy error is obtained.

[0033] In one implementation, estimating the construction cost of the on-site construction building based on the point cloud of the constructed components and the unit price of the quantity of the constructed component point cloud includes:

[0034] Calculate the first total number of grids covered by the point cloud of the constructed components;

[0035] Calculate a second total number of the grids covered by the design component, which corresponds to the point cloud of the constructed component;

[0036] Calculate the ratio of the first total quantity to the second total quantity;

[0037] Based on the quantity ratio and the project type corresponding to the point cloud of the constructed components, the completed project quantity corresponding to the point cloud of the constructed components is obtained;

[0038] Based on the completed work volume and the unit price of the work volume, estimate the construction cost of the on-site construction.

[0039] In one implementation, obtaining the completed project quantity corresponding to the point cloud of constructed components based on the quantity ratio and the project type corresponding to the point cloud of constructed components includes:

[0040] When the project type is a volume type, if the quantity ratio is greater than the first ratio, then the completed project quantity is the set actual volume of the component;

[0041] Alternatively, when the project type is a volume type, if the quantity ratio is less than the first ratio but greater than the second ratio, then the completed project quantity is the quantity ratio multiplied by the set actual volume of the component;

[0042] Alternatively, when the project type is a volume type, if the quantity ratio is less than the second ratio, then the completed project quantity is zero.

[0043] Alternatively, when the project type is a counting type, if the quantity ratio is greater than a set value, then the completed project quantity is the set project quantity;

[0044] Alternatively, when the project type is a counting type, if the quantity ratio is less than or equal to a set value, then the completed project quantity is zero.

[0045] Secondly, embodiments of the present invention also provide a terminal device, wherein the terminal device includes a memory, a processor, and a construction cost estimation program based on three-dimensional scanning technology stored in the memory and executable on the processor. When the processor executes the construction cost estimation program based on three-dimensional scanning technology, it implements the steps of the construction cost estimation method based on three-dimensional scanning technology described above.

[0046] Thirdly, embodiments of the present invention also provide a computer-readable storage medium storing a construction cost estimation program based on three-dimensional scanning technology. When the construction cost estimation program based on three-dimensional scanning technology is executed by a processor, it implements the steps of the construction cost estimation method based on three-dimensional scanning technology described above.

[0047] Beneficial Effects: This invention first generates a design model point cloud from the architectural design model, then registers the design model point cloud with the site point cloud. Registration means aligning the positions of points on the building in the site point cloud with their positions in the design model point cloud. If a component is located at a certain position in the registered design model point cloud, and a point cloud at that position also appears in the site point cloud, it indicates that the construction of that component has been completed on site. This process is repeated to calculate the number of components covered by the completed architectural design model on site. Finally, based on the number of completed components, the quantity of work for each component, and the unit price, the construction cost is calculated. Because this invention uses a method of comparing each design component with the site point cloud to determine the completed components on site, the accuracy of the construction cost calculated based on the completed components is improved. Attached Figure Description

[0048] Figure 1 This is an overall flowchart of the present invention;

[0049] Figure 2 This is a flowchart of the point cloud registration process in an embodiment of the present invention;

[0050] Figure 3 This is a flowchart illustrating the model data extraction and transformation process based on IFC in this embodiment of the invention.

[0051] Figure 4 This is a flowchart of the state determination process for volume-type elements in an embodiment of the present invention;

[0052] Figure 5 This is a flowchart of the state determination process for counting elements in an embodiment of the present invention;

[0053] Figure 6 This is a diagram showing the engineering quantity and cost estimation in an embodiment of the present invention;

[0054] Figure 7 This is a flowchart illustrating the estimation of project costs based on unit prices in an embodiment of the present invention.

[0055] Figure 8 This is a flowchart illustrating the process of inputting a BIM model and a site point cloud model into a cost estimation system to calculate costs in an embodiment of the present invention.

[0056] Figure 9 This is a block diagram illustrating the internal structure of a terminal device provided in an embodiment of the present invention. Detailed Implementation

[0057] The technical solutions of the present invention will be clearly and completely described below with reference to the embodiments and accompanying drawings. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0058] Research has revealed that actual cost estimation during construction is a crucial aspect of building project management. During progress payment settlements, project managers from the client, contractor, and auditor must repeatedly calculate the on-site construction volume based on the on-site construction progress report. Then, based on the construction volume and unit price, they must calculate the cost required for the completed work. Calculating the on-site construction volume is a time-consuming, costly, and labor-intensive task with low automation. For example, when construction workers build a building on-site according to a complete BIM model (the drawings of the building to be completed), it is necessary to calculate the volume of work completed for the building and then the cost required for that volume. Current technology manually compares each component name in the BIM model with the components already under construction on-site to determine the completed volume covered by the BIM model and then estimates the construction cost based on that volume. Because this technology relies on manual comparison of on-site components, it is highly susceptible to errors, leading to calculated construction costs that deviate from the actual construction costs.

[0059] To address the aforementioned technical problems, this invention provides a construction cost estimation method and apparatus based on 3D scanning technology, solving the problem of low accuracy in construction cost calculations using existing technologies. In specific implementation, firstly, a design model point cloud is generated for the building design model; then, the design model point cloud is registered with the site point cloud; finally, based on the constructed components and their unit prices in the registered site point cloud, the construction cost of the on-site building is estimated, where the components are used to assemble the on-site building. This invention improves the accuracy of the estimated construction cost.

[0060] For example, suppose the architectural design model is a factory building model, and a factory building needs to be constructed on-site based on this model. During the construction process, the investor needs to pay the construction company for the completed portion of the factory building. To calculate the completed construction cost, this embodiment first generates a design model point cloud (the design model consists of several design components, such as a column or a beam, and the point cloud represents the positions of points on a column in a coordinate system) from the component models covered by the factory building model. Simultaneously, 3D scanning technology is used to scan the completed factory building portion on-site, generating a corresponding on-site point cloud (the on-site point cloud represents the positions of points on the completed factory building portion in the aforementioned coordinate system). Then, the positions of the points in the on-site point cloud are adjusted to align with the design model point cloud. For example, if the factory building model includes column A and its position 'a' in the design model point cloud, column B and its position 'b', column C and its position 'c', and a beam and its position 's', the process is as follows: If there are points at positions a and s in the site point cloud (since the design model point cloud has been registered with the site point cloud, position a in the site point cloud and position a in the design model point cloud are at the same location in the coordinate system), but no points at positions b and c in the site point cloud, it indicates that the construction party has completed the construction of column A and beam (corresponding to the point cloud of constructed components), but has not completed the construction of column B and column C. Multiplying the quantities of work covered by column A and beam by their respective unit prices gives the construction cost that the investor needs to pay to the construction party.

[0061] Exemplary methods

[0062] The construction cost estimation method based on 3D scanning technology in this embodiment can be applied to terminal devices, which can be terminal products with image scanning capabilities, such as computers. In this embodiment, as... Figure 1 As shown, the construction cost estimation method based on 3D scanning technology specifically includes the following steps:

[0063] S100, Generate the design model point cloud of the architectural design model. The architectural design model is a complete model corresponding to the on-site construction building. The point cloud is used to represent the position of each point on the building.

[0064] The component model in the architectural design model is a graphical model. The position of each point in the model cannot be seen from the component model alone. The component model is converted into a design model point cloud. The point cloud of the design model records the coordinate position of each point on the architectural design model. That is, the graphical model is converted into a digital model, which is convenient for subsequent matching with the point cloud of the construction site to determine the amount of work completed on the construction site.

[0065] Step S100 includes the following steps:

[0066] S101, Based on the architectural design model, obtain the BIM model in the architectural design model.

[0067] S102, as Figure 3 As shown, the format of the BIM model is converted to IFC format to obtain the BIM model in IFC format.

[0068] The format of the BIM model itself cannot be used for subsequent extraction of triangular patches and filling of point clouds. Only by converting the BIM model to IFC format can the above operations be completed.

[0069] S103, extract the IFC entities from the BIM model in IFC format, convert them to the intermediate format OBJ, and then extract the triangular faces of each model component.

[0070] S104. Based on the vertices and normal vectors of each group, fill the point cloud to generate the design model point cloud.

[0071] In this embodiment, the various component models covered by the BIM model are first located, then the triangular facets of each component model are read, and then point clouds are filled on the surface of the component model according to the triangular facets of each component model to obtain the design model point cloud.

[0072] The specific method for filling the point cloud on the model surface is as follows: First, iterate through the triangular facets of the component, then calculate the area of ​​each triangular facet and insert them into an array in order of size; finally, select a triangular facet from the array according to a probability proportional to the area of ​​the triangular facet. For each selected triangular facet (with 3 vertices A, B, and C), generate a random sampling point on the inner surface of the triangular facet. The formula for generating the random sampling point is as follows:

[0073]

[0074] Where r1 and r2 are random numbers between 0 and 1. The sampling points of all facets are stored in a sampling point matrix until the number of discrete points generated by the sampling reaches a predetermined value.

[0075] For example, a BIM model might include column and beam component models. By extracting triangular facets from the column component models and filling the point cloud with these facets, we obtain the component point cloud for the column component model. The same operation is used to obtain the component point cloud for the beam component model. Once we have the component point clouds for both the column and beam component models, we generate the design model point cloud for the architectural design model, which consists of the column and beam component models.

[0076] In one embodiment, the BIM model records the attributes of the entity objects corresponding to each component model. The entity object attributes are extracted from the BIM model, and each entity object attribute is written into a table. The entity objects are converted into OBJ format according to the ifcBuildingElement type, and their GlobalID is used as the storage identifier.

[0077] For example, the BIM model records component models such as beams, lintels, column A, and column B. The entity objects of the beams and lintels are classified as beams, while the entity objects of column A and column B are classified as columns. When the beam component is found in the point cloud on site, the beam is marked as 1 in the BIM model, indicating that the construction of the beam has been completed on site.

[0078] S200, Register the design model point cloud to the site point cloud, wherein the site point cloud is the point cloud of the on-site construction building obtained using 3D scanning technology.

[0079] The design model point cloud is used as the target point cloud, and the on-site point cloud is used as the source point cloud. In other words, the design model point cloud is used as the standard so that every point in the on-site point cloud and the corresponding point in the design model point cloud are located at the same position in the coordinate system.

[0080] The various design components together form the complete BIM model. However, because the same point in the design model point cloud and the site point cloud has different positions in the same coordinate system, it is difficult to match the components in the BIM model with the site point cloud. Therefore, registration between the design model point cloud and the site point cloud is required. Registration means adjusting the corresponding points in the site point cloud and the design model point cloud to the same position in the coordinate system as much as possible. Step S200 includes the following steps S201 to S204:

[0081] S201, unify the scale of the design model point cloud and the on-site point cloud, wherein the design model point cloud is composed of each of the design components.

[0082] Using the design model point cloud as a reference, and the on-site point cloud as a reference, the scale of the on-site point cloud is adjusted to match the scale of the two point clouds. Scale matching means unifying the units of measurement between the two point clouds. For example, if the coordinate unit of the points in the on-site point cloud is meters, and the coordinate unit of the points in the design model point cloud is millimeters, converting the units of the points in the on-site point cloud to millimeters completes the scale matching.

[0083] In another embodiment, such as Figure 2 As shown, scale matching involves enlarging the on-site point cloud proportionally so that the enlarged on-site point cloud matches the point cloud involved.

[0084]

[0085] S202, Set the same size d1 mesh for the design model point cloud and the field point cloud after unifying the scale.

[0086] S203, voxel downsampling is performed on the point clouds of the design model point cloud located in the same grid and the point clouds of the field point cloud located in the same grid, respectively, to obtain the design sampling point cloud and the field sampling point cloud corresponding to the design model point cloud.

[0087] S204, the field sampling point cloud and the design sampling point cloud are registered to obtain the registered field sampling point cloud. The registration is used to adjust the position of each point in the field sampling point cloud so that the position of each point in the field sampling point cloud matches the position of each point in the design sampling point cloud, thus completing the operation of registering the design model point cloud to the field point cloud.

[0088] The position of the field sampling point cloud is adjusted using the designed sampling point cloud as a reference standard, so that the corresponding points in the field sampling point cloud and the designed sampling point cloud are registered. In this embodiment, the registration includes coarse registration and fine registration performed sequentially.

[0089] For example, the design sampling point cloud contains two points a1(xa1,ya1) and b1(xb1,yb1) representing the upper and lower centers of a pillar. The field sampling point cloud also contains two points a2(xa2,ya2) and b2(xb2,yb2) representing the upper and lower centers of the same pillar. Before registration, (xa1,ya1) is not equal to (xa2,ya2), and (xb1,yb1) is not equal to (xb2,yb2). After coarse registration, (xa1,ya1) equals (xa2,ya2), and (xb1,yb1) equals (xb2,yb2). Coarse registration only aligns local points in the two point clouds. For example, after coarse registration, the same point on the side of the pillar in both point clouds is not aligned. Therefore, a fine registration step is needed to ensure that the same point on the same side of the pillar in both point clouds is located at the same position in the coordinate system.

[0090] S300: Based on the registered construction components in the site point cloud and the unit price of the construction components, estimate the construction cost of the site construction building. The components are used to assemble the site construction building.

[0091] The term "constructed components" includes components that have been completed and components that have begun construction.

[0092] Step S300 includes the following steps:

[0093] S301, based on the positions of the components in each of the design models in the site point cloud, obtain the corresponding neighborhood point clouds for each of the constructed components.

[0094] In this embodiment, each design component is matched with the registered field sampling point cloud according to its corresponding attributes to obtain each neighborhood point cloud corresponding to each design component in the field sampling point cloud.

[0095] For example, the design components include main support column A (component), connecting column B (component), auxiliary support column C (component), main beam (component), and crossbeam (component). Main support column A, connecting column B, and auxiliary support column C all have the attribute of "column," while the main beam and crossbeam both belong to the "beam" attribute (the BIM model stores the attributes of these components). First, each component in the design with the attribute of "column" is matched against the on-site sampled point cloud. It is checked whether there is a point cloud at the location in the on-site sampled point cloud corresponding to the position of the main support column A in the design model point cloud. If there is a point cloud at that location, it indicates that the construction of the building under construction on site has completed the construction of the main support column A. Similarly, connecting column B, auxiliary support column C, as well as the main beam and crossbeam, are matched against the on-site sampled point cloud to determine whether the construction of the building under construction on site has completed the construction of connecting column B, auxiliary support column C, and the main beam and crossbeam.

[0096] If it is determined that the construction of a certain component has been completed on site, then the point cloud corresponding to that component in the on-site sampling point cloud is taken as the neighboring point cloud of that component.

[0097] S302, based on the registration accuracy error, adjust each of the neighboring point clouds to obtain the point cloud of the constructed component. The registration accuracy error is used to characterize the distance between the points in the registered field sampling point cloud and the corresponding points in the design model point cloud.

[0098] Although step S204 performs coarse and fine registration of the on-site sampling point cloud and the design sampling point cloud, the same point in the two point clouds will still have errors in position in the coordinate system after registration. Therefore, it is necessary to adjust the neighborhood point cloud obtained in step S205 so that the adjusted point cloud of the constructed components can truly reflect the actual number and distribution of the points cloud occupied by the constructed components.

[0099] In one embodiment, the neighborhood point cloud search threshold is adjusted based on the model registration accuracy to obtain the segmented point cloud components (the construction component point cloud is segmented from the design sampled point cloud).

[0100] In one embodiment, the calculation of registration accuracy error includes the following steps S3021, S3022, and S3023:

[0101] S3021, the distance between the registered points in the field sampling point cloud and the corresponding points in the design model point cloud is calculated using the K-nearest neighbor search algorithm.

[0102] S3022, Calculate the root mean square error between the field sampling point cloud and the design model point cloud based on the distance between the points in the field sampling point cloud and the corresponding points in the design model point cloud.

[0103] S3023, Based on the root mean square error, the registration accuracy error is obtained.

[0104] Steps S3021, S3022, and S3023 involve using K-nearest neighbor search to obtain the distance to each point in the registered field point cloud from the corresponding point in the design point cloud, calculating the root mean square error, and using it as the registration accuracy error.

[0105] S303, based on the point cloud of the constructed components and the unit price of the quantity of the point cloud of the constructed components, estimate the construction cost of the on-site construction building.

[0106] Step S303 includes the following steps SS3031 to SS3035:

[0107] S3031, calculate the first total number N1 (total number of voxels of the segmented component) of the mesh covered by the point cloud of the constructed component.

[0108] S3032, calculate the second total number N2 (total number of component voxels) of the mesh covered by the design component, the design component corresponding to the point cloud of the constructed component.

[0109] S3033, calculate the ratio of the first total quantity N1 to the second total quantity N2.

[0110] For example, the point cloud of a constructed component can be a point cloud A of a column under construction (containing N1 meshes), while the BIM model contains a component model B corresponding to column point cloud A (containing N2 meshes). By calculating the ratio of N1 to N2 (Rate), the construction progress of the column can be determined.

[0111] S3034. Based on the quantity ratio and the project type corresponding to the point cloud of the constructed components, the completed project quantity corresponding to the point cloud of the constructed components is obtained.

[0112] In one embodiment, such as Figure 4 As shown, when the project type is the volume type in Table 1, if the quantity ratio Rate is greater than the first ratio R1%, it can be determined that the component has been completed. Then, the completed project quantity is the set actual volume V of the component. 体积 .

[0113] If the quantity ratio Rate is less than the first ratio R1% but greater than the second ratio R2% (i.e., the quantity ratio is between R2% and R1%), then the completed work quantity is the quantity ratio multiplied by the set actual volume of the component.

[0114] If the percentage is between R2% and R1%, the component is considered to be under construction (the construction of the component has not yet been completed), and the output project quantity is Rate*V. 体积 .

[0115] If the quantity ratio is less than the second ratio R2%, it can be determined that the component has not started construction, and the completed work quantity is zero.

[0116] In another embodiment, such as Figure 5 As shown, when the project type is a counting type, if the quantity ratio Rate is greater than the set value r%, then the completed project quantity is the set project quantity (the set project quantity is 1).

[0117] If the quantity ratio Rate is less than or equal to the set value r%, then the completed work quantity is zero (it is determined that the component has not started construction).

[0118] Table 1

[0119]

[0120] The method for calculating the actual volume (solid volume) of a component in S3034 is as follows:

[0121] The solid voxelization algorithm for components and point clouds is based on the characteristics of buildings being constructed from bottom to top and being primarily cubic, making it easier to estimate the amount of work being done while the building is under construction.

[0122] First, determine the maximum and minimum values ​​of x in the X, Y, and Z coordinate directions for the point cloud data (site point cloud) and the model data (design model point cloud). min y min z min x max y max z max Then, determine the voxel resolution as 2d1, establish a voxel mesh, and define a 3D zero matrix. Determine the voxel coordinates (n, p, q) to which all triangular faces of the model component (the component model in the BIM model) and all 3D coordinates (x, y, z) of the point cloud belong. Set the corresponding element value in the 3D matrix to 1. Finally, calculate the corresponding entity voxels according to the following steps:

[0123] a. In a three-dimensional matrix, when (n, p) is determined, find if there is a value m with a corresponding element of 1.

[0124] b. When the existence of a value m is confirmed, it corresponds to one or more elements 1, thus determining the maximum value of m. Traverse the row and column values ​​(n, p) of the first page of the 3D matrix to obtain m. max A set of.

[0125] c. Based on the row and column values ​​(n, p), in [m = 1, m = m max Voxels are generated within the interval to achieve internal voxelization of the model.

[0126] Specifically, the membership relationship between the triangular facet and the voxel is determined by calculating the intermediate distance from the triangle to the voxelized mesh. First, the foot point t of the perpendicular from the point to the plane containing the triangular facet is calculated. Then, it is determined whether the foot point t is inside the triangular facet. If the foot point is inside the triangular facet, the shortest distance is the distance d from the spatial point to the foot point. If the foot point is not inside the triangular facet, the shortest distance s from the foot point to the triangular facet is calculated. The distance to be calculated is the hypotenuse of the right triangle formed by s and d.

[0127] S3035, Based on the completed work volume and the unit price of the work volume, estimate the construction cost of the on-site construction building.

[0128] Steps S301 to S304 complete the construction cost calculation for a component in one of the engineering types, such as... Figure 6 As shown, after calculating the cost of this component, the cost of all components of this project type is calculated (i.e., it is determined whether all components of this type have been completely traversed). After the cost of all components of this project type has been calculated, the cost of all project types is calculated. The sum of the costs of each project type is the construction cost of the building on site.

[0129] Figure 7 and Figure 8 This invention presents the overall process for estimating construction costs on-site:

[0130] S1. Convert the format of the designed BIM model, and extract and convert the model data based on IFC to generate complete building as-built point cloud data, and send it to S2. Send the relevant information of the extracted building component entity objects (attributes) to S3.

[0131] S2. Perform point cloud registration between the construction site point cloud obtained based on 3D scanning technology and the design model point cloud generated from BIM data, and calculate the registration accuracy based on the registered construction site point cloud, i.e., the average distance of the overlapping part of the two point clouds (the distance of the same point in the coordinate system between the site point cloud and the design model point cloud). Send the registered construction site point cloud and the registration accuracy to S3.

[0132] S3. Input the unit price information for the project, and combine it with the data collected in S1 and S2 to estimate the actual quantity of work and project cost (cost required for components that have been completed on site) in the progress management process according to the type of project.

[0133] In summary, this invention first generates a design model point cloud from the architectural design model, and then registers the design model point cloud with the site point cloud. Registration means aligning the positions of points on the building in the site point cloud with their positions in the design model point cloud. If a component is located at a certain position in the registered design model point cloud, and a point cloud at that position is also present in the site point cloud, it indicates that the construction of that component has been completed on site. This process is repeated to calculate the number of components covered by the completed architectural design model on site. Finally, based on the number of completed components, the quantity of work for each component, and the unit price, the construction cost is calculated. Because this invention uses a method of comparing each design component with the site point cloud one by one to determine the completed components on site, the accuracy of the construction cost calculated based on the completed components is improved.

[0134] Furthermore, based on research on construction progress perception in smart construction technology, this invention proposes a highly automated construction cost estimation method using 3D perception technology, IFC's BIM data extraction technology, and point cloud registration technology. This method enables the collection of real point cloud models of the construction site through a mobile backpack measurement system (integrating the cost estimation method of this invention into the measurement system, which can be set in a backpack), and then fusing the data with the design BIM model to automatically estimate part of the project quantity and project cost, thereby improving the development level of smart construction and developing smart construction site technology.

[0135] Exemplary device

[0136] This embodiment also provides a construction cost estimation device based on three-dimensional scanning technology, the device comprising the following components:

[0137] The design model point cloud generation module is used to generate the design model point cloud of the architectural design model. The architectural design model is a complete model corresponding to the on-site construction building. The point cloud is used to represent the position of each point on the building.

[0138] The matching module is used to register the design model point cloud with the on-site point cloud, wherein the on-site point cloud is the point cloud of the on-site construction building obtained by using 3D scanning technology;

[0139] The cost estimation module is used to estimate the construction cost of the on-site construction building based on the registered on-site point cloud and the unit price of the construction quantity of the constructed components. The components are used to assemble the on-site construction building.

[0140] Based on the above embodiments, the present invention also provides a terminal device, the principle block diagram of which can be as follows: Figure 9 As shown, the terminal device includes a processor, memory, network interface, display screen, and temperature sensor connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides the environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The network interface is used to communicate with external terminals via a network connection. When the computer program is executed by the processor, it implements a construction cost estimation method based on 3D scanning technology. The display screen can be an LCD screen or an e-ink screen. The temperature sensor is pre-installed inside the terminal device to detect the operating temperature of the internal components.

[0141] Those skilled in the art will understand that Figure 9 The block diagram shown is merely a partial structural diagram related to the present invention and does not constitute a limitation on the terminal device to which the present invention is applied. The specific terminal device may include more or fewer components than shown in the figure, or combine certain components, or have different component arrangements.

[0142] In one embodiment, a terminal device is provided, comprising a memory, a processor, and a construction cost estimation program based on 3D scanning technology stored in the memory and executable on the processor. When the processor executes the construction cost estimation program based on 3D scanning technology, it implements the following operation instructions:

[0143] The point cloud of the architectural design model is generated. The architectural design model is a complete model corresponding to the building under construction on site. The point cloud is used to represent the position of each point on the building.

[0144] The design model point cloud is registered with the site point cloud, which is the point cloud of the on-site construction building obtained using 3D scanning technology;

[0145] Based on the registered on-site point cloud and the unit price of the constructed components, the construction cost of the on-site construction building is estimated, and the components are used to assemble the on-site construction building.

[0146] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided by this invention can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and RAMbus dynamic RAM (RDRAM), etc.

[0147] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A construction cost estimation method based on three-dimensional scanning technology, characterized by, include: The point cloud of the architectural design model is generated. The architectural design model is a complete model corresponding to the building under construction on site. The point cloud is used to represent the position of each point on the building. The design model point cloud is used for on-site point cloud registration, where the on-site point cloud is the point cloud of the on-site construction building obtained using 3D scanning technology; Based on the registered on-site point cloud and the unit price of the constructed components, the construction cost of the on-site construction building is estimated, and the components are used to assemble the on-site construction building. Specifically, the design model point cloud is used for on-site point cloud registration. The on-site point cloud is the point cloud of the on-site construction building obtained using 3D scanning technology, including: The scale of the point cloud in the design model and the point cloud in the actual site are unified; Set the same mesh size for the point cloud of the design model and the point cloud of the site after unifying the scale; Voxel downsampling is performed on the point clouds of the design model point cloud and the point clouds of the field point cloud that are located in the same grid, respectively, to obtain the design sampling point cloud and the field sampling point cloud corresponding to the design model point cloud; The field sampling point cloud and the design sampling point cloud are registered to obtain the registered field sampling point cloud. The registration is used to adjust the position of each point in the field sampling point cloud so that the position of each point in the field sampling point cloud matches the position of each point in the design sampling point cloud, thus completing the operation of registering the design model point cloud to the field point cloud. The construction cost of the on-site construction building is estimated based on the registered on-site point cloud and the unit price of the constructed components. The components are used to assemble the on-site construction building and include: Based on the position of the components in each design model in the field point cloud, obtain the corresponding neighborhood point clouds of each component; Based on the registration accuracy error, each of the neighboring point clouds is adjusted to obtain the point cloud of the constructed component. The registration accuracy error is used to characterize the distance between the points in the registered field sampling point cloud and the corresponding points in the design model point cloud. Based on the point cloud of the constructed components and the unit price of the constructed components, the construction cost of the on-site construction building is estimated, including: calculating the first total number of the grids covered by the point cloud of the constructed components; Calculate the second total number of grids covered by the design component, which corresponds to the point cloud of the constructed component; Calculate the ratio of the first total quantity to the second total quantity; Based on the quantity ratio and the project type corresponding to the point cloud of the constructed components, the completed project quantity corresponding to the point cloud of the constructed components is obtained; Based on the completed work volume and the unit price of the work volume, estimate the construction cost of the on-site construction.

2. The construction cost estimation method based on three-dimensional scanning technology according to claim 1, wherein, The generated architectural design model point cloud, where the architectural design model is a complete model corresponding to the on-site construction building, is used to represent the position of various points on the building, including: Based on the architectural design model, the BIM model in the architectural design model is obtained; The BIM model is converted to IFC format to obtain the BIM model in IFC format. Extract the IFC entities from the BIM model in IFC format, convert them to the intermediate format OBJ, and then read the triangular facets of the components. Each group of triangular facets is a triangular facet of the component model. Based on each set of vertices and normal vectors, fill in the point cloud to generate the point cloud of the design model.

3. The construction cost estimation method based on three-dimensional scanning technology according to claim 1, wherein, The methods for obtaining the constructed components in the site point cloud include: The location and corresponding attributes of each component model in the architectural design model are obtained, and each component model is used to assemble the architectural design model. The positions of each component model are matched one by one with the registered field sampling point cloud to obtain the constructed components.

4. The construction cost estimation method based on three-dimensional scanning technology according to claim 1, wherein, The calculation method for the registration accuracy error includes: The distance between the points in the registered field sampling point cloud and the corresponding points in the design model point cloud is calculated using the K-nearest neighbor search algorithm. Based on the distance between points in the field sampling point cloud and corresponding points in the design model point cloud, calculate the root mean square error between the field sampling point cloud and the design model point cloud; Based on the root mean square error, the registration accuracy error is obtained.

5. The construction cost estimation method based on three-dimensional scanning technology according to claim 4, wherein, The process of obtaining the completed project quantity corresponding to the point cloud of constructed components based on the quantity ratio and the project type corresponding to the point cloud of constructed components includes: When the project type is a volume type, if the quantity ratio is greater than the first ratio, then the completed project quantity is the set actual volume of the component; Alternatively, when the project type is a volume type, if the quantity ratio is less than the first ratio but greater than the second ratio, then the completed project quantity is the quantity ratio multiplied by the set actual volume of the component; Alternatively, when the project type is a volume type, if the quantity ratio is less than the second ratio, then the completed project quantity is zero. Alternatively, when the project type is a counting type, if the quantity ratio is greater than a set value, then the completed project quantity is the set project quantity; Alternatively, when the project type is a counting type, if the quantity ratio is less than or equal to a set value, then the completed project quantity is zero.

6. A terminal device, characterized in that, The terminal device includes a memory, a processor, and a construction cost estimation program based on three-dimensional scanning technology stored in the memory and executable on the processor. When the processor executes the construction cost estimation program based on three-dimensional scanning technology, it implements the steps of the construction cost estimation method based on three-dimensional scanning technology as described in any one of claims 1-4.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a construction cost estimation program based on three-dimensional scanning technology. When the construction cost estimation program based on three-dimensional scanning technology is executed by a processor, it implements the steps of the construction cost estimation method based on three-dimensional scanning technology as described in any one of claims 1-4.

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