Partitioned tunnel back break detection method and system

Abstract

The invention relates to the technical field of tunnel construction engineering, in particular to a partitioned tunnel back break detection method and system, and the method comprises the steps: collecting to-be-detected tunnel point cloud data, carrying out the preprocessing of the data, obtaining an actual tunnel point cloud set, intercepting a preset tunnel in a construction range, and obtaining an expected tunnel point cloud set; partitioning the actual tunnel point cloud set and the expected tunnel point cloud set based on a preset partitioning method; and comparing the actual tunnel point cloud set with the expected tunnel point cloud set in any partition to obtain an over-excavation and under-excavation result. Compared with the prior art, the method has the advantage that the detection on the back break is more accurate when an extra-large tunnel construction surface is dealt with.

Description

Technical Field

[0001] The present invention relates to the technical field of tunnel construction engineering, and particularly relates to a sectional tunnel overbreak and underbreak detection method and system. Background Art

[0002] During the excavation and construction of tunnels, as an advanced measurement method, three-dimensional laser scanning technology has been widely used in the engineering field, especially playing a crucial role in tunnel construction. This technology emits laser beams and receives the signals reflected from the tunnel surface to form a high-precision three-dimensional point cloud model. The point cloud data can truly and detailedly reflect the actual shape of the tunnel and its surrounding environment, thereby providing comprehensive spatial information for the construction team. Based on these data, engineers can achieve precise control of the tunnel dimensions, avoid overbreak or underbreak, and ensure that the tunnel excavation progress meets the design requirements.

[0003] Although three-dimensional laser scanning technology provides many advantages in tunnel construction, there are still certain technical limitations during the excavation of extra-large cross-section tunnels. Extra-large cross-section tunnels usually adopt the CD method or the bench method for sectional construction, which results in a large and complex cross-sectional space. When the existing three-dimensional laser technology is used for overbreak and underbreak detection, it usually judges only by calculating the area of the entire tunnel cross-section. This method often appears too rough and not delicate enough when facing the complex geological environment of extra-large cross-sections. Especially in the local areas of large cross-sections, there may be relatively small but important overbreak or underbreak phenomena, affecting the accuracy of the detection. Summary of the Invention

[0004] In order to overcome the defect of inaccurate detection effect in the above-mentioned prior art, the present invention provides a sectional tunnel overbreak and underbreak detection method and system.

[0005] To achieve the above technical effects, the technical solution of the present invention is as follows:

[0006] The present invention provides a sectional tunnel overbreak and underbreak detection method, including the following steps:

[0007] Collect the point cloud data of the tunnel to be detected and perform preprocessing to obtain the actual tunnel point cloud set, and intercept the preset tunnel within the construction range to obtain the expected tunnel point cloud set;

[0008] Based on the preset zoning method, zone the actual tunnel point cloud set and the expected tunnel point cloud set respectively;

[0009] Compare the actual tunnel point cloud set and the expected tunnel point cloud set in any zone to obtain the overbreak and underbreak results.

[0010] As a preferred solution, the step of performing preprocessing to obtain the actual tunnel point cloud set includes:

[0011] Select a reference plane with the central axis of the tunnel as the normal vector;

[0012] Project the point cloud data onto the reference plane to obtain an actual tunnel point cloud set; the actual tunnel point cloud set includes the projection distance of the point cloud data.

[0013] As a preferred solution, the steps of comparing the actual tunnel point cloud set and the expected tunnel point cloud set in any partition to obtain the over-excavation and under-excavation results include:

[0014] Establish coordinate axes on the reference plane with the tunnel center point as the origin, and calculate the areas enclosed by the actual tunnel point cloud set and the expected tunnel point cloud set in any partition respectively, and calculate the difference to obtain the over-excavation and under-excavation results.

[0015] As a preferred solution, the method for constructing the area enclosed by the point cloud set in the current partition includes: adding the vertices of the partition to the point cloud set to form a closed figure.

[0016] As a preferred solution, the steps of the preset partitioning method include: selecting the partitioning method used during tunnel construction as the preset partitioning method.

[0017] As a preferred solution, the preset partitioning method includes the bench method or the CD method.

[0018] As a preferred solution, the steps of partitioning the actual tunnel point cloud set and the expected tunnel point cloud set respectively based on the preset partitioning method include: obtaining the boundaries of each block in the preset partitioning method, and partitioning the point cloud based on the boundaries.

[0019] The present invention also provides a partitioned tunnel over-excavation and under-excavation detection system, including:

[0020] Point cloud partitioning module: used to partition the point cloud set respectively based on the preset partitioning method;

[0021] Over-excavation and under-excavation solution module: used to compare the actual tunnel point cloud set and the expected tunnel point cloud set in any partition to obtain the over-excavation and under-excavation results.

[0022] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the partitioned tunnel over-excavation and under-excavation detection method as described in the present invention is implemented.

[0023] The present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the partitioned tunnel over-excavation and under-excavation detection method as described in the present invention is implemented.

[0024] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0025] The present invention divides according to construction requirements into multiple zones, calculates the over-excavation and under-excavation areas separately for each zone, which are independent of each other without interference, and obtains more refined data; the over-excavation and under-excavation amounts of each zone can also be managed more precisely by parts, realizing more refined overall construction management. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 It is a flowchart of a partitioned tunnel over-excavation and under-excavation detection method.

[0027] Figure 2 It is a schematic diagram of point cloud projection.

[0028] Figure 3 It is a schematic diagram of the block division of the actual tunnel point cloud set and the expected tunnel point cloud set.

[0029] Figure 4 It is an architecture diagram of a partitioned tunnel over-excavation and under-excavation detection system. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0030] The drawings are only for illustrative purposes and should not be construed as a limitation to the present invention;

[0031] For those skilled in the art, it is understandable that some well-known descriptions in the drawings may be omitted.

[0032] The technical solutions of the present invention will be further described below with reference to the drawings and embodiments.

[0033] Embodiment 1

[0034] This embodiment proposes a partitioned tunnel over-excavation and under-excavation detection method, as Figure 1 shown, which is a flowchart of the partitioned tunnel over-excavation and under-excavation detection method of this embodiment.

[0035] In the partitioned tunnel over-excavation and under-excavation detection method proposed in this embodiment, the following steps are included:

[0036] Collect the point cloud data of the tunnel to be detected and perform preprocessing to obtain the actual tunnel point cloud set, and intercept the preset tunnel within the construction range to obtain the expected tunnel point cloud set;

[0037] Based on the preset partitioning method, partition the actual tunnel point cloud set and the expected tunnel point cloud set respectively;

[0038] Compare the actual tunnel point cloud set and the expected tunnel point cloud set in any partition to obtain the over-excavation and under-excavation results.

[0039] In this embodiment, the present invention divides the tunnel section to be detected into multiple independent regions according to a preset zoning method, and each region is separately subjected to over-excavation and under-excavation detection, which can effectively avoid the problems of rough and inaccurate data that may be brought about by the overall section analysis in the traditional method. Through this zoned method, the actual tunnel point cloud set in each zone is compared with the expected tunnel point cloud set, and the over-excavation and under-excavation areas obtained are more accurate, which can reflect in detail each subtle difference in the tunnel construction process, thus ensuring the controllability of the construction progress and the reliability of the construction quality. In addition, the zoned tunnel over-excavation and under-excavation detection method of the present invention enables the over-excavation and under-excavation amounts of each zone to be separately and detailedly counted and analyzed. The detection results of each zone can be independently managed, which not only reduces the interference between adjacent regions but also facilitates subsequent sub-part management. Engineering managers can flexibly adjust the construction strategy according to the specific over-excavation and under-excavation conditions of each zone in order to better allocate resources and control the progress.

[0040] In an alternative embodiment, the step of performing preprocessing to obtain the actual tunnel point cloud set includes:

[0041] Select a reference plane with the central axis of the tunnel as the normal vector;

[0042] Project the point cloud data onto the reference plane to obtain the actual tunnel point cloud set, and the actual tunnel point cloud set includes the projection distance of the point cloud data.

[0043] As Figure 2 shown, it is a schematic diagram of point cloud projection.

[0044] Specifically, use a three-dimensional laser scanner to collect the point cloud data of the tunnel to be measured and perform denoising and thinning; assume that the mileage range of the obtained tunnel is (m min , m max ): The mileage m is the midpoint of the tunnel, Take the point o corresponding to the mileage m, take the point s corresponding to the mileage m min , and take the point e corresponding to the mileage m max . Take as the plane normal vector and o as the point in the plane to obtain the reference plane S o . Project the point cloud p onto the cross-section plane to obtain the projection p n , and its formula is as follows:

[0045]

[0046] The calculation formula for the mileage m p of the point p on the road is as follows:

[0047]

[0048] In this embodiment, by selecting a plane perpendicular to the road direction as the reference plane, all tunnel point cloud data is projected onto the same plane, converting the original 3D point cloud data into 2D plane for processing, which simplifies the data processing process and avoids cumbersome geometric calculations in three-dimensional space. By unifying all point cloud data onto the same plane, the amount of calculation and processing complexity are effectively reduced, thereby improving the processing efficiency. In addition, after projection onto the plane, the projection distances of all point cloud data intuitively reflect the actual positions of the tunnel point cloud.

[0049] In an alternative embodiment, the steps of the preset zoning method include: selecting the zoning method used during tunnel construction as the preset zoning method.

[0050] In this embodiment, by selecting the same zoning method as that used during tunnel construction as the preset zoning method, the consistency between data zoning and the actual construction process is ensured, which helps to achieve the stability of data zoning before and after, and avoids problems of data deviation or inconsistency caused by different zoning standards.

[0051] In an alternative embodiment, the preset zoning method includes the bench method or the CD method.

[0052] In this embodiment, the bench method or the CD method is used as the preset zoning method. During the construction of extra-large section tunnels, these two zoning methods can usually effectively cope with complex geological environments and construction difficulties. The bench method is a technical method commonly used for sectional construction. It divides the tunnel section into multiple "bench"-shaped areas, so that each construction stage can focus on excavating and supporting specific areas; the CD method is a zoning method based on the idea of "sectioning", which divides the tunnel section into multiple circular or fan-shaped areas, and each area can be excavated and supported separately. Through zoning, the tunnel section can be divided into multiple smaller areas, thereby refining the overbreak and underbreak detection and improving the detection accuracy and reliability. Within each zone, the calculation and detection of overbreak and underbreak can be more accurate, avoiding errors that may be caused by overall section analysis, and being able to more effectively reflect the overbreak and underbreak conditions of local areas, thereby improving the overall construction accuracy and quality control level.

[0053] In an alternative embodiment, the steps of performing zoning include: obtaining the boundaries of each block in the preset zoning method and zoning the point cloud based on the boundaries.

[0054] Specifically, taking the center point of the tunnel as the origin, coordinate axes are constructed on the reference plane. Let the boundary range of a single zone be {x min ,x max ,y min ,y max}, and the point cloud coordinates are (x, y). If the point cloud satisfies x min<x < x max and y min <y < y max Then divide the point cloud into this area.

[0055] In an alternative embodiment, the steps of comparing the actual tunnel point cloud set and the expected tunnel point cloud set in any partition to obtain the over - excavation and under - excavation results include:

[0056] Establish coordinate axes on the reference plane with the tunnel center point as the origin. In any partition, calculate the areas enclosed by the actual tunnel point cloud set and the expected tunnel point cloud set respectively in the current partition and calculate the difference to obtain the over - excavation and under - excavation results.

[0057] Specifically, sort the point cloud set in clockwise order. Let the tunnel center point be (Ro x , Ro y ). Taking the negative Y - axis direction as 0 degrees, clockwise take [0, 360). The angle of the point (x, y) is (450 - atan2(y, x) * 180 / π) mod 360, where

[0058] After sorting in clockwise order according to the angle size, obtain the actual tunnel point cloud set P s and the expected tunnel point cloud set P D .

[0059] As Figure 3 shown, it is a schematic diagram of the divided blocks of the actual tunnel point cloud set and the expected tunnel point cloud set. Among them, the solid line is the expected tunnel point cloud set, and the dotted line is the actual tunnel point cloud set.

[0060] In this embodiment, by calculating the areas enclosed by the actual tunnel point cloud set and the expected tunnel point cloud set in the reference plane in the current partition and calculating the difference, the over - excavation and under - excavation area can be obtained intuitively.

[0061] In this embodiment, by establishing coordinate axes on the reference plane with the tunnel center point as the origin and combining the method of clockwise sorting, comparing the actual tunnel point cloud set and the expected tunnel point cloud set can intuitively calculate the over - excavation and under - excavation area. In addition, sorting the point cloud set according to the angle order and calculating the difference can clearly reflect the over - excavation and under - excavation area in each partition, providing an intuitive and accurate calculation result.

[0062] In an alternative embodiment, the method for constructing the area enclosed by the point cloud set in the current partition includes: adding the vertices of the partition to the point cloud set to make the point cloud form a closed figure.

[0063] Specifically, the formula for calculating the difference in the area enclosed by the actual tunnel point cloud set P s and the expected tunnel point cloud set P D is as follows:

[0064]

[0065] Among them, S is the area of overbreak and underbreak, and n is the number of point clouds in the point cloud.

[0066] Multiplying the area of overbreak and underbreak by the tunnel length gives the volume of overbreak and underbreak.

[0067] In this embodiment, by adding the vertices of the partition to the point cloud set to form a closed figure, the point cloud data can accurately reflect the difference between the actual tunnel shape and the expected shape within each partition, thus providing a more accurate basis for calculating the area of overbreak and underbreak. In addition, by calculating the difference between the areas enclosed by the actual tunnel point cloud set and the expected tunnel point cloud set, the area of overbreak and underbreak can be obtained more accurately, and then multiplying by the tunnel length to get the volume of overbreak and underbreak. By calculating the area of overbreak and underbreak for each partition independently, the engineering team can carry out more refined monitoring and adjustment during the construction process, thus providing support and guarantee for the extremely large tunnel project under complex geological conditions.

[0068] Embodiment 2

[0069] This embodiment proposes a partitioned tunnel overbreak and underbreak detection system, which applies the partitioned tunnel overbreak and underbreak detection method proposed in Embodiment 1. As Figure 4 shown, it is the architecture diagram of the partitioned tunnel overbreak and underbreak detection system of this embodiment.

[0070] This embodiment proposes a partitioned tunnel overbreak and underbreak detection system, including:

[0071] Point cloud partitioning module: used to partition the point cloud set respectively based on a preset partitioning method;

[0072] Overbreak and underbreak solution module: used to compare the actual tunnel point cloud set and the expected tunnel point cloud set in any partition to obtain the overbreak and underbreak result.

[0073] It can be understood that the system of this embodiment corresponds to the method of Embodiment 1 above, and the optional items in Embodiment 1 above also apply to this embodiment, so they will not be repeated here.

[0074] Embodiment 3

[0075] This embodiment proposes a computer device, including a memory and a processor. Computer-readable instructions are stored in the memory. When the computer-readable instructions are executed by the processor, the processor executes the steps of the partitioned tunnel overbreak and underbreak detection method proposed in Embodiment 1.

[0076] Embodiment 4

[0077] This embodiment provides a storage medium, on which computer-readable instructions are stored. When the computer-readable instructions are executed by a processor, the steps of the partitioned tunnel overbreak and underbreak detection method proposed in Embodiment 1 are implemented.

[0078] The terms in the accompanying drawings are only for illustrative purposes and should not be construed as a limitation of this patent.

[0079] Obviously, the above embodiments of the present invention are merely examples for clearly illustrating the present invention, rather than limitations on the implementation manners of the present invention. For those of ordinary skill in the art, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to enumerate all the implementation manners here. Any modifications, equivalent replacements, and improvements made within the spirit and principle of the present invention shall be included in the protection scope of the claims of the present invention.

Claims

1. A method for detecting overbreak and underbreak in a partitioned tunnel, characterized in that Including the following steps: Collect the point cloud data of the tunnel to be detected and perform preprocessing to obtain the actual tunnel point cloud set, and intercept the preset tunnel within the construction range to obtain the expected tunnel point cloud set; Based on the preset zoning method, zone the actual tunnel point cloud set and the expected tunnel point cloud set respectively; Compare the actual tunnel point cloud set and the expected tunnel point cloud set in any zone to obtain the overbreak and underbreak results.

2. The sectional tunnel overbreak and underbreak detection method according to claim 1, wherein The step of performing preprocessing to obtain the actual tunnel point cloud set includes: Select the reference plane with the central axis of the tunnel as the normal vector; Project the point cloud data onto the reference plane to obtain the actual tunnel point cloud set; the actual tunnel point cloud set includes the projection distance of the point cloud data.

3. The sectional tunnel overbreak and underbreak detection method according to claim 2, wherein, The step of comparing the actual tunnel point cloud set and the expected tunnel point cloud set in any zone to obtain the overbreak and underbreak results includes: Establish a coordinate axis on the reference plane with the tunnel center point as the origin, calculate the areas enclosed by the actual tunnel point cloud set and the expected tunnel point cloud set in any zone respectively, and calculate the difference to obtain the overbreak and underbreak results.

4. A method for detecting overbreak and underbreak of a partitioned tunnel according to claim 3, characterized in that, The method for constructing the area enclosed by the point cloud set in the current zone includes: adding the vertices of the zone to the point cloud set to form a closed figure.

5. A method for detecting overbreak and underbreak in a partitioned tunnel according to any one of claims 1 to 4, characterized in that, The steps of the preset zoning method include: selecting the zoning method used during tunnel construction as the preset zoning method.

6. A method for detecting overbreak and underbreak in a partitioned tunnel according to claim 5, characterized in that, The preset zoning method includes the bench method or the CD method.

7. A method for detecting overbreak and underbreak in a partitioned tunnel according to claim 5, characterized in that, The step of zoning the actual tunnel point cloud set and the expected tunnel point cloud set respectively based on the preset zoning method includes: obtaining the boundaries of each block in the preset zoning method, and zoning the point cloud based on the boundaries.

8. A partitioned tunnel overbreak and underbreak detection system, applied to the partitioned tunnel overbreak and underbreak detection method according to any one of claims 1 to 7, characterized in that, The system includes: Point cloud zoning module: used to zone the point cloud set respectively based on the preset zoning method; Overbreak and underbreak solving module: used to compare the actual tunnel point cloud set and the expected tunnel point cloud set in any zone to obtain the overbreak and underbreak results.

9. An electronic device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the zoned tunnel overbreak and underbreak detection method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the zoned tunnel overbreak and underbreak detection method according to any one of claims 1 to 7.

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