Method for determining excavation precision of excavation engineering

Abstract

The embodiment of the invention relates to the field of exploration, in particular to a method for determining the excavation precision of excavation engineering. According to the method for determining the mining precision of the mining project provided by the embodiment of the invention, the actual three-dimensional point cloud model and the ideal three-dimensional point cloud model of the disposal pit are respectively determined by acquiring the actual physical data and the design data of the disposal pit; the difference of the average distances of the corresponding points between the actual three-dimensional point cloud model and the ideal three-dimensional point cloud model is determined; segmenting the actual three-dimensional point cloud model to obtain a plurality of actual sub-three-dimensional point cloud models, so as to determine the maximum horizontal distance between internal points of the actual sub-three-dimensional point cloud models and the offset of each actual sub-three-dimensional point cloud model relative to the ideal three-dimensional point cloud model, and calculating the actual three-dimensional point cloud model according to the difference of the average distances, the maximum horizontal distance and the offset. And determining and comprehensively evaluating the excavation precision of the disposal pit so as to guide later buffer material building block installation and research and development of disposal pit excavation equipment.

Description

Technical Field

[0001] Embodiments of the present application relate to the field of surveying, and in particular to a method for determining excavation accuracy of an excavation project. Background Art

[0002] The statements herein merely provide background information related to the present application and do not necessarily constitute prior art.

[0003] High-level waste usually requires special shielding and safe handling during operation and transportation due to its high content or concentration of radionuclides. At present, high-level waste is generally disposed of by deep geological means, that is, high-level waste wrapped in waste cans is placed in underground disposal pits and filled with buffer materials in the middle.

[0004] Disposal pits are usually located in areas with stable geological structures and scarce groundwater. By digging to a sufficient depth, high-level radioactive waste can be permanently isolated deep underground. This method uses the surrounding rocks and soil to form a natural barrier, and together with the artificial barrier system, it constitutes a multi-barrier system that effectively prevents the migration and release of radioactive materials, thereby ensuring the long-term safety of humans and the ecosystem. Summary of the invention

[0005] A brief overview of the present application is provided below in order to provide a basic understanding of certain aspects of the present application. It should be understood that this overview is not an exhaustive overview of the present application. It is not intended to identify the key or important parts of the present application, nor is it intended to limit the scope of the present application. Its purpose is merely to present certain concepts in a simplified form as a prelude to a more detailed description discussed later.

[0006] The embodiment of the present application provides a method for determining the excavation accuracy of an excavation project, and the excavation project is suitable for excavating a disposal pit, and the disposal pit is suitable for storing high-level radioactive waste, which includes the following steps: S10: obtaining physical data of the disposal pit; S20: determining the actual three-dimensional point cloud model of the disposal pit based on the physical data obtained in step S10; S30: obtaining design data of the disposal pit, and determining the ideal three-dimensional point cloud model of the disposal pit based on the design data; S40: determining a one-to-one correspondence between points of the actual three-dimensional point cloud model and points of the ideal three-dimensional point cloud model; and determining the difference in average distance between corresponding points of the points of the actual three-dimensional point cloud model and the ideal three-dimensional point cloud model; S50: segmenting the actual three-dimensional point cloud model according to a predetermined direction and a predetermined interval to obtain a plurality of actual sub-three-dimensional point cloud models; S60: determining the maximum horizontal distance of the actual sub-three-dimensional point cloud model and the offset between the center point at any position in the predetermined direction and the central axis formed by the ideal three-dimensional point cloud model; S70: determining the excavation accuracy of the excavation project based on the difference in average distance, the maximum horizontal distance and the offset.

[0007] The embodiment of the present application provides a method for determining the excavation accuracy of an excavation project. By acquiring actual physical data and design data of the disposal pit, the actual three-dimensional point cloud model and the ideal three-dimensional point cloud model of the disposal pit are respectively determined, and the difference in average distances of corresponding points between the actual three-dimensional point cloud model and the ideal three-dimensional point cloud model is determined; the actual three-dimensional point cloud model is segmented to obtain multiple actual sub-three-dimensional point cloud models, thereby determining the maximum horizontal distance between internal points of the actual sub-three-dimensional point cloud model and the offset of each actual sub-three-dimensional point cloud model compared to the ideal three-dimensional point cloud model, and based on the difference in average distance, the maximum horizontal distance and the offset, the excavation accuracy of the disposal pit is determined and comprehensively evaluated, thereby guiding the later installation of buffer material blocks and the development of disposal pit excavation equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] In order to further illustrate the above and other advantages and features of the present application, the specific embodiments of the present application are further described in detail below in conjunction with the accompanying drawings. The accompanying drawings together with the following detailed description are included in this specification and form a part of this specification. Elements with the same function and structure are represented by the same reference numerals. It should be understood that these drawings only describe typical examples of the present application and should not be regarded as limiting the scope of the present application.

[0009] Figure 1 is a schematic diagram of an actual three-dimensional point cloud model of a disposal pit provided in an embodiment of the present application; Figure 2 is a schematic diagram of an updated actual three-dimensional point cloud model of a disposal pit provided in an embodiment of the present application; Figure 3 It is a schematic diagram of the correspondence between the points of the actual three-dimensional point cloud model and the points of the ideal three-dimensional point cloud model provided in the embodiment of the present application; Figure 4 It is a schematic diagram of the offset distance between corresponding points of an actual three-dimensional point cloud model and an ideal three-dimensional point cloud model provided in an embodiment of the present application.

[0010] Description of reference numerals: 100, ideal 3D point cloud model; 102, neighborhood corresponding points; 110, second plane; 200, actual 3D point cloud model; 201, predetermined points; 202, neighborhood points; 210, first plane; 300, local normal vector. DETAILED DESCRIPTION

[0011] Exemplary embodiments of the present application will be described below in conjunction with the accompanying drawings. For the sake of clarity and conciseness, not all features of the actual implementation are described in the specification. However, it should be understood that many implementation-specific decisions must be made in the process of developing any such actual implementation in order to achieve the developer's specific goals, such as meeting those constraints related to the system and business, and these constraints may vary from implementation to implementation. In addition, it should be understood that although the development work may be very complex and time-consuming, it is only a routine task for those skilled in the art who benefit from the content of this application.

[0012] It is also necessary to explain here that, in order to avoid obscuring the present application due to unnecessary details, only the device structure and / or processing steps closely related to the scheme according to the present application are shown in the accompanying drawings, while other details that are not very relevant to the present application are omitted.

[0013] The disclosure below provides a plurality of different embodiments or examples to implement the present application. In order to simplify the disclosure of the present application, the parts and methods of specific examples are described below. Of course, they are merely examples, and the purpose is not to limit the present application. In the description of the embodiments of the present application, the meaning of "multiple" is at least two, such as two, three, etc., unless otherwise clearly and specifically limited.

[0014] In the process of excavating the disposal pit, the actual excavation results will inevitably deviate from the theoretical design value, and the deviation value is called the offset. The size of the disposal pit offset will affect the installation of the buffer material blocks in the later stage and affect the stability of the entire barrier system. Therefore, comprehensive and reasonable measurement of the excavation accuracy of the disposal pit can guide the subsequent installation of buffer materials and the research and development of disposal pit excavation equipment.

[0015] At present, manual measurement methods are mostly used, such as manual tape measure, laser ranging and other methods, to obtain the excavation diameter of the disposal pit, but these methods have shortcomings: on the one hand, the measurement data obtained by the test means itself has limited accuracy; on the other hand, the amount of data obtained is limited and the analysis results have large deviations. Most of them only characterize the excavation accuracy of the disposal pit by measuring the average excavation diameter at certain depths of the disposal pit, which is difficult to fully reflect the excavation accuracy of the disposal pit.

[0016] The embodiment of the present application provides a method for determining the excavation accuracy of an excavation project, and the excavation project is suitable for excavating a disposal pit, and the disposal pit is suitable for storing high-level radioactive waste, which includes the following steps: S10: obtaining physical data of the disposal pit; S20: determining the actual three-dimensional point cloud model of the disposal pit based on the physical data obtained in step S10; S30: obtaining design data of the disposal pit, and determining the ideal three-dimensional point cloud model of the disposal pit based on the design data; S40: determining a one-to-one correspondence between points of the actual three-dimensional point cloud model and points of the ideal three-dimensional point cloud model; and determining the difference in average distance between corresponding points of the points of the actual three-dimensional point cloud model and the ideal three-dimensional point cloud model; S50: segmenting the actual three-dimensional point cloud model according to a predetermined direction and a predetermined interval to obtain a plurality of actual sub-three-dimensional point cloud models; S60: determining the maximum horizontal distance of the actual sub-three-dimensional point cloud model and the offset between the center point at any position in the predetermined direction and the central axis formed by the ideal three-dimensional point cloud model; S70: determining the excavation accuracy of the excavation project based on the difference in average distance, the maximum horizontal distance and the offset.

[0017] The embodiment of the present application provides a method for determining the excavation accuracy of an excavation project. By acquiring actual physical data and design data of the disposal pit, the actual three-dimensional point cloud model and the ideal three-dimensional point cloud model of the disposal pit are respectively determined, and the difference in average distances of corresponding points between the actual three-dimensional point cloud model and the ideal three-dimensional point cloud model is determined; the actual three-dimensional point cloud model is segmented to obtain multiple actual sub-three-dimensional point cloud models, thereby determining the maximum horizontal distance between internal points of the actual sub-three-dimensional point cloud model and the offset of each actual sub-three-dimensional point cloud model compared to the ideal three-dimensional point cloud model, and based on the difference in average distance, the maximum horizontal distance and the offset, the excavation accuracy of the disposal pit is determined and comprehensively evaluated, thereby guiding the later installation of buffer material blocks and the development of disposal pit excavation equipment.

[0018] In some embodiments, since the acquisition of the physical data of the disposal pit in step S10 is easily affected by environmental factors, there may be obvious meaningless points in the physical data. In order to prevent the construction of the actual three-dimensional point cloud model of the disposal pit determined in step S20 from being affected, the meaningless points in the physical data can be deleted in a predetermined manner to make the actual three-dimensional point cloud model of the disposal pit more accurate. Among them, the meaningless points can be removed by statistical analysis. For example, the neighborhood of each point in the point cloud data set composed of the physical data acquired in step S10 can be statistically analyzed to remove points in the neighborhood that do not meet the predetermined standard. The predetermined standard can be determined based on the number of neighboring points within a predetermined radius of each point. At least a predetermined number of neighboring points within a predetermined radius of each point is set as a threshold. Points that do not meet the threshold are meaningless points, thereby removing meaningless points from the point cloud data set.

[0019] In some embodiments, in step S20, the following steps are also included: S21: determine a predetermined point and a predetermined radius in the actual three-dimensional point cloud model; S22: determine a neighborhood of the predetermined point based on the predetermined point and the predetermined radius; S23: determine the spatial distance from the points in the neighborhood to the predetermined point based on the neighborhood of the predetermined point; S24: determine the spatial weight of the points in the neighborhood based on the spatial distance; S25: determine the scalar difference in reflection intensity between the predetermined point and the points in the neighborhood; S26: determine the attribute weight of the points in the neighborhood based on the scalar difference; S27: determine the comprehensive weight of the points in the neighborhood based on the spatial weight determined in step S24 and the attribute weight determined in step S26; S28: determine the comprehensive weight and threshold based on step S27, and determine the points to be removed in the neighborhood; S29: repeat steps S21-S28 for all points in the actual three-dimensional point cloud model, determine all removed points in the actual three-dimensional point cloud model, and determine an updated actual three-dimensional point cloud model of the disposal pit based on all remaining points in the point cloud.

[0020] Figure 1 A schematic diagram showing an actual three-dimensional point cloud model of a disposal pit provided in an embodiment of the present application is shown. Figure 2 A schematic diagram of an updated actual three-dimensional point cloud model of a disposal pit provided by an embodiment of the present application is shown. In some embodiments, Figure 1 and Figure 2 As shown in the figure, after 3D reconstruction and rendering, the updated actual 3D point cloud model can present a clearer and smoother surface of the disposal pit wall than the initial actual 3D point cloud model. Therefore, removing meaningless points in the actual 3D point cloud model can improve the quality and availability of the point cloud data, reduce errors and uncertainties in subsequent processing; reduce the total number of points in the point cloud model, improve data processing efficiency; and maintain the geometric feature information in the point cloud data, making the point cloud model closer to the surface of the disposal pit.

[0021] In some embodiments, in step S24, the spatial distance and the spatial weight conform to the following expression: .

[0022] Among them, W spatial represents the spatial weight, d represents the spatial distance, p represents the predetermined point in the actual 3D point cloud model, q represents the point in the neighborhood of the predetermined point in the actual 3D point cloud model, σ s Represents the spatial standard deviation.

[0023] In some embodiments, the neighborhood may be determined by determining a fixed radius, and all points within a predetermined radius are selected as neighborhood points for a predetermined point in the actual three-dimensional point cloud model. For example, the fixed radius may be 10 mm.

[0024] In some embodiments, the closer the point is to the predetermined point in the actual three-dimensional point cloud model, the greater its spatial weight value is, and the farther the point is from the predetermined point in the actual three-dimensional point cloud model, the smaller its spatial weight value is. s is the spatial standard deviation, which can control the impact of spatial distance on spatial weight, σ s Can be set to 1.0.

[0025] In some embodiments, in step S26, the attribute weight and the scalar difference conform to the following expression: .

[0026] Among them, W attribute represents the attribute weight, I represents the scalar difference, p represents the predetermined point in the actual 3D point cloud model, q represents the point in the neighborhood of the predetermined point in the actual 3D point cloud model, σ r Represents the attribute standard deviation.

[0027] In some embodiments, the attribute weight measures the difference between the predetermined attribute of the predetermined point in the actual 3D point cloud model and its neighboring points, for example, the difference in color, reflection intensity or normal vector, σ r is the attribute standard deviation, which can control the impact of attribute differences on weights, σ r Can be set to 50.

[0028] In some embodiments, the comprehensive weight may be the product of the spatial weight and the attribute weight, indicating the degree of influence of a predetermined point in the actual three-dimensional point cloud model on the points in its neighborhood. The comprehensive weight threshold may be set to 0.5, and points in the neighborhood whose comprehensive weight is less than the threshold may be removed, and the above operation may be repeated for all points in the actual three-dimensional point cloud model, thereby removing all meaningless points in the actual three-dimensional point cloud model, and obtaining an updated actual three-dimensional point cloud model of the disposal pit.

[0029] In some embodiments, step S40 also includes the following steps: S41: roughly correspond the points of the actual three-dimensional point cloud model with the points of the ideal three-dimensional point cloud model; S42: determine the normal vector and curvature of each point in the actual three-dimensional point cloud model and the ideal three-dimensional point cloud model; S43: determine the distance between the corresponding points in the actual three-dimensional point cloud model and the ideal three-dimensional point cloud model; S44: determine the one-to-one correspondence between the points of the actual three-dimensional point cloud model and the points of the ideal three-dimensional point cloud model based on the normal vector, curvature and the distance between the corresponding points.

[0030] In some embodiments, by constructing a one-to-one correspondence between the points of the actual three-dimensional point cloud model and the points of the ideal three-dimensional point cloud model, the relative posture between the points of the actual three-dimensional point cloud model and the ideal three-dimensional point cloud model can be obtained, thereby reducing the impact of different point cloud densities, partial point loss, surface roughness and different sampling positions on distance measurement.

[0031] In some embodiments, in step S43, the difference threshold between the angle of the curvature and the normal vector of the corresponding point is set to be less than 1×10 -5 , the distance range of the corresponding points is set to 5mm-15mm.

[0032] Figure 3 A schematic diagram showing the correspondence between points of an actual three-dimensional point cloud model and points of an ideal three-dimensional point cloud model provided by an embodiment of the present application. In some embodiments, Figure 3 As shown, in step S40, the following steps are also included: S45: determine the points of the actual three-dimensional point cloud model 200 and the adjacent points of the corresponding points on the ideal three-dimensional point cloud model 100 within a predetermined range; S46: determine the first plane of the points of the actual three-dimensional point cloud model 200 and the adjacent points and the second plane of the corresponding points on the ideal three-dimensional point cloud model 100 and the adjacent points according to the adjacent points; S47: determine the local normal vector 300 of the plane according to the first plane and the second plane determined in step S46; S48: determine the cylinder of the actual three-dimensional point cloud model 200 according to the first plane and the local normal vector 300; S49: determine the difference in the average distance between the points of the actual three-dimensional point cloud model 200 and the points on the ideal three-dimensional point cloud model 100 within the cylinder.

[0033] In some embodiments, Figure 3 As shown, a predetermined point 201 can be determined in the actual three-dimensional point cloud model 200, and points within a predetermined radius around the predetermined point 201 form a neighborhood, for example, the radius is D / 2, where D is greater than 2 times the scanning resolution, so that the number of neighborhood points 202 of the predetermined point 201 can be fitted to obtain a first plane 210; for the neighborhood point 202, there is a corresponding neighborhood corresponding point 102 in the ideal three-dimensional point cloud model 100, and points within a predetermined radius around the neighborhood corresponding point 102 form a neighborhood, where the predetermined radius is equal to the predetermined radius of the neighborhood of the predetermined point 201, so that the neighborhood corresponding point 102 and the points in its neighborhood can be fitted to obtain a second plane 110.

[0034] In some embodiments, a local normal vector 300 can be determined based on the first plane 210 and the second plane 110. The local normal vector 300 is perpendicular to the first plane 210 and the second plane 110. Starting from the first plane 210 along the direction of the local normal vector 300 and with a predetermined length as the projection radius, a cylinder passing through the predetermined point 201 and with the local normal vector 300 as the axis can be determined. The cylinder intersects the ideal three-dimensional point cloud model 100 and the actual three-dimensional point cloud model 200.

[0035] In some embodiments, the points of the actual three-dimensional point cloud model 200 within the cylinder and the points on the ideal three-dimensional point cloud model 100 are determined. The average position of the two groups of points within the cylinder can be determined based on the local normal vector 300. The difference in the average position of the two groups of points is the change distance of the actual three-dimensional point cloud model 200 relative to the ideal three-dimensional point cloud model 100. Repeating the above operation for all points in the entire actual three-dimensional point cloud model 200 can obtain the change of the actual three-dimensional point cloud model 200 relative to the ideal three-dimensional point cloud model 100, thereby reducing measurement errors.

[0036] In some embodiments, step S60 also includes the following steps: S61: determining the circle or ellipse where the points of the actual sub-3D point cloud model are located based on the actual sub-3D point cloud model; S62: determining the center of the circle or the center of the ellipse; S63: determining the central axis of the ideal 3D point cloud model; S64: determining the distance between the center of the circle or the center and the central axis based on the center of the circle, the center and the central axis; S65: determining the offset based on the distance determined in step S64.

[0037] In some embodiments, in step S60, the distance formula between two points can be used to calculate the maximum horizontal distance between the internal points of each actual sub-3D point cloud model, and each actual sub-3D point cloud model can be fitted into a predetermined shape. For example, the actual sub-3D point cloud model can be fitted into a circle or an ellipse, and the least squares method can be used to fit the maximum horizontal distance between the internal points of each actual sub-3D point cloud model, and the center or center coordinates of the fitted circle or ellipse, so as to determine the offset of each actual sub-3D point cloud model relative to the ideal 3D point cloud model according to the center or center coordinates of different actual sub-3D point cloud models and the center coordinates of the ideal 3D point cloud model.

[0038] Figure 4 A schematic diagram showing the offset distance between corresponding points of an actual 3D point cloud model and an ideal 3D point cloud model provided by an embodiment of the present application. In some embodiments, Figure 4 As shown, the offset distance between the corresponding points of the actual 3D point cloud model and the ideal 3D point cloud model is concentrated between 0-8.16 mm, which reflects the unevenness of the wall of the actual excavated disposal pit relative to the wall of the theoretically designed disposal pit.

[0039] In some embodiments, the average value of the diameters of the multiple actual sub-three-dimensional point cloud models fitted in step S62 can represent the excavation diameter of the actual disposal pit. Therefore, according to the above steps, the difference in average distance between point cloud models, the maximum horizontal distance, and the offset multiple quantitative indicators can fully reflect the excavation accuracy of the excavation project.

[0040] In some embodiments, step S10 also includes the following steps: S11: determining the three-dimensional scanning laser measurement parameters of the disposal pit, including scanning resolution and quality; S12: determining the disposal pit scanning method, which may be manual handheld scanning, automatic scanning, etc., and the automatic scanning method is preferably used to scan the complete outline of the disposal pit.

[0041] In some embodiments, in step S11, two scanning parameters, scanning resolution and quality, can be determined by manual scanning calibration. The resolution is set to a predetermined value, for example, the resolution can be set to 0.5 mm, so that the scanner can identify the minimum distance between two points when scanning.

[0042] In some embodiments, in step S12, a three-dimensional scanning device may be used to scan the actual excavated disposal pit, thereby obtaining physical data of the actual excavated disposal pit. A laser scanner or an optical scanner may be used as the three-dimensional scanning device, and the scanning method may be manual dynamic scanning, and the scanning object may be the contour of the wall of the actual excavated disposal pit.

[0043] In some embodiments, in step S30, random sampling can be performed based on the design size data of the disposal pit to establish an ideal three-dimensional point cloud model of the disposal pit, and the number of points in the point cloud is set to a predetermined value, such as 500,000.

[0044] In some embodiments, in step S50, the actual three-dimensional point cloud model is segmented according to a predetermined direction and a predetermined interval, wherein the predetermined direction may be the excavation direction of the disposal pit; the length of the predetermined interval should be greater than the disposal pit scanning resolution, so that the density of the point cloud data obtained by segmentation is sufficient to form a sub-three-dimensional point cloud model, which is convenient for subsequent analysis and processing. For example, the disposal pit is excavated downward, the predetermined direction of segmentation is vertically downward, the disposal pit scanning resolution is 0.5 mm, and the segmentation interval length is 1 mm, thereby obtaining a plurality of columnar actual sub-three-dimensional point cloud models with a depth of 1 mm.

[0045] Regarding the embodiments of the present application, it should also be noted that, in the absence of conflict, the embodiments of the present application and the features therein can be combined with each other to obtain new embodiments.

[0046] The above are only specific implementation methods of the present application, but the protection scope of the present application is not limited thereto. The protection scope of the present application shall be based on the protection scope of the claims.

Claims

1. A method for determining the excavation accuracy of an excavation project, wherein the excavation project is suitable for excavating a disposal pit, wherein the disposal pit is suitable for storing high-level radioactive waste, characterized in that: It includes the following steps: S10: Acquire physical data of the disposal pit; S20: Determine an actual three-dimensional point cloud model of the disposal pit according to the physical data acquired in step S10; S30: Acquire design data of the disposal pit, and determine an ideal three-dimensional point cloud model of the disposal pit according to the design data; S40: determining a one-to-one correspondence between points of the actual three-dimensional point cloud model and points of the ideal three-dimensional point cloud model; and determining a difference in average distance between corresponding points of the actual three-dimensional point cloud model and points of the ideal three-dimensional point cloud model; S50: segmenting the actual three-dimensional point cloud model according to a predetermined direction and a predetermined interval to obtain a plurality of actual sub-three-dimensional point cloud models; S60: Determine the maximum horizontal distance of the actual sub-three-dimensional point cloud model and the offset between the center point at any position in the predetermined direction and the central axis formed by the ideal three-dimensional point cloud model; S70: Determine the excavation accuracy of the excavation project according to the difference in the average distance, the maximum horizontal distance, and the offset.

2. The determination method according to claim 1, characterized in that: In step S20, the following steps are also included: S21: Determine a predetermined point and a predetermined radius in the actual three-dimensional point cloud model; S22: Determine a neighborhood of the predetermined point according to the predetermined point and the predetermined radius; S23: determining, according to the neighborhood of the predetermined point, a spatial distance from a point in the neighborhood to the predetermined point; S24: Determine the spatial weight of the points in the neighborhood according to the spatial distance; S25: Determine a scalar difference in reflection intensity between the predetermined point and the points within the neighborhood; S26: Determine the attribute weights of the points in the neighborhood according to the scalar difference; S27: Determine the comprehensive weight of the points in the neighborhood according to the spatial weight determined in step S24 and the attribute weight determined in step S26; S28: Determine the comprehensive weight and threshold according to step S27, and determine the points to be removed in the neighborhood; S29: Repeat steps S21-S28 for all points in the actual three-dimensional point cloud model, determine all removed points in the actual three-dimensional point cloud model, and determine an updated actual three-dimensional point cloud model of the disposal pit based on all remaining points in the point cloud.

3. The determination method according to claim 2, characterized in that: In step S24, the spatial distance and the spatial weight conform to the following expression: ， Among them, W spatial represents the spatial weight, d represents the spatial distance, p represents the predetermined point in the actual three-dimensional point cloud model, q represents the point in the neighborhood of the predetermined point in the actual three-dimensional point cloud model, σ s Represents the spatial standard deviation.

4. The determination method according to claim 2, characterized in that: In step S26, the attribute weight and the scalar difference conform to the following expression: ， Among them, W attribute represents the attribute weight, I represents the scalar difference, p represents the predetermined point in the actual three-dimensional point cloud model, q represents the point in the neighborhood of the predetermined point in the actual three-dimensional point cloud model, σ r Represents the attribute standard deviation.

5. The determination method according to claim 1, characterized in that: In step S40, the following steps are also included: S41: roughly matching the points of the actual three-dimensional point cloud model with the points of the ideal three-dimensional point cloud model; S42: Determine the normal vector and curvature of each point in the actual three-dimensional point cloud model and the ideal three-dimensional point cloud model; S43: Determine the distance between corresponding points in the actual three-dimensional point cloud model and the ideal three-dimensional point cloud model; S44: Determine a one-to-one correspondence between points of the actual three-dimensional point cloud model and points of the ideal three-dimensional point cloud model according to the normal vector, the curvature, and the distance between the corresponding points.

6. The determination method according to claim 1, characterized in that: In step S40, the following steps are also included: S45: Determine a point of the actual three-dimensional point cloud model and adjacent points of the corresponding point on the ideal three-dimensional point cloud model within a predetermined range; S46: determining, according to the adjacent points, a first plane of a point of the actual three-dimensional point cloud model and its adjacent points and a second plane of a point on the ideal three-dimensional point cloud model and its adjacent points corresponding thereto; S47: Determine a local normal vector of the plane according to the first plane and the second plane determined in step S46; S48: Determine a cylinder of the actual three-dimensional point cloud model according to the first plane and the local normal vector; S49: Determine the difference in average distance between the points of the actual three-dimensional point cloud model and the points on the ideal three-dimensional point cloud model within the cylinder.

7. The determination method according to claim 1, characterized in that: In the step S60, the following steps are also included: S61: determining, according to the actual sub-three-dimensional point cloud model, a circle or an ellipse where points of the actual sub-three-dimensional point cloud model are located; S62: Determine the center of the circle or the center of the ellipse; S63: Determine the central axis of the ideal three-dimensional point cloud model; S64: Determine a distance between the center of the circle or the center and the central axis according to the center of the circle, the center and the central axis; S65: Determine the offset according to the distance determined in step S64.

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