Non-contact shotcrete rebound rate testing method and device

Abstract

This invention discloses a non-contact method for testing the rebound rate of shotcrete, specifically including the following steps: S1, scanning the tunnel wall of the section to be constructed before concrete spraying using a lidar to obtain a laser point cloud 1; S2, performing shotcrete construction and simultaneously preparing a density measurement specimen, measuring the density value ρ of the sprayed concrete based on the density measurement specimen; S3, scanning the tunnel wall of the section to be constructed after concrete spraying using a lidar to obtain a laser point cloud 2; S4, downsampling laser point clouds 1 and 2 to form laser point clouds 3 and 4; S5, modeling laser point clouds 3 and 4 respectively, the difference in volume between the two models is the volume v of the shotcrete attached to the tunnel wall, and then calculating the rebound rate of the shotcrete. This invention uses three-dimensional laser scanning technology for non-contact measurement, eliminating the need for laying a canvas for weighing; it calculates the rebound rate of shotcrete based on the concrete mass ratio rather than the concrete volume ratio, avoiding the influence of volume changes of the same mass of concrete before and after spraying.

Description

Technical Field

[0001] This invention belongs to the field of concrete spraying technology, and more specifically, this invention relates to a non-contact method and apparatus for testing the rebound rate of sprayed concrete. Background Technology

[0002] Shotcrete is a type of concrete that uses compressed air to spray a mixture of cement, sand, and gravel onto a target surface, where it quickly sets and hardens. It boasts numerous advantages, including high construction efficiency, simple process, excellent support and reinforcement effects, strong adaptability, and significant economic and technical benefits, making it a crucial tunnel support measure in tunnel engineering. However, shotcrete generally exhibits a high rebound rate during construction, leading to significant waste of raw materials, impacting construction progress, increasing the cost of waste concrete disposal, and raising environmental impact.

[0003] The paper "Determination of Rebound of Shotcrete in Tunnels Based on 3D Laser Scanning" uses a ground-based 3D laser scanning instrument to measure the volume V of concrete sprayed onto the tunnel. j , using V j The total volume V of shotcrete during construction 总 The ratio of the two values ​​is used as the rebound rate. This method has the following problems: (1) The volume of the same mass of concrete changes before and after construction, so the volume is difficult to represent the amount of concrete used; and the mixing plant usually weighs the raw materials to prepare concrete according to weight, making it difficult to obtain the V value. 总 (2) This method assumes that the volume of shotcrete on the excavation face between a certain mileage is equal to the sum of the areas of shotcrete on N cross sections. Therefore, when the cross section spacing is small, there are more point cloud cross sections to be processed, and the workload of the office work is large. When the cross section spacing is large, it cannot represent the true situation of shotcrete in the mileage section. Summary of the Invention

[0004] This invention provides a non-contact method for testing the rebound rate of shotcrete, aiming to improve the above-mentioned problems.

[0005] This invention is implemented as follows: a non-contact method for testing the rebound rate of shotcrete, the method specifically including the following steps:

[0006] S1. Obtain laser point cloud 1 by scanning the tunnel wall of the section to be constructed before concrete spraying using lidar;

[0007] S2 performs shotcrete construction and simultaneously prepares density measurement specimens. The density value ρ of the shotcrete is measured based on the density measurement specimens.

[0008] S3. Use lidar to scan the tunnel wall of the section to be constructed after concrete spraying to obtain a laser point cloud 2;

[0009] S4. After downsampling the laser point cloud 1 and laser point cloud 2, laser point cloud 3 and laser point cloud 4 are formed.

[0010] S5. Model laser point cloud 3 and laser point cloud 4 respectively. The difference in volume between the two models is the volume v of the shotcrete attached to the tunnel wall. Then calculate the rebound rate of the shotcrete.

[0011] Furthermore, the downsampling method for laser point cloud 1 is as follows:

[0012] 1) Project the coordinates in laser point cloud 1 to the world coordinate system and import the tunnel design outline into the world coordinate system;

[0013] 2) Read the coordinates of all points in the laser point cloud 1 in the world coordinate system, traverse and retrieve all points in the laser point cloud 1, and set each point P... i Project the image onto the tunnel design outline to obtain point P. i Projection point P on the tunnel design outline i The curve length x to the left arch foot of the tunnel i Point P i Tunnel mileage y i Point P i Minimum distance z to the tunnel design profile surface i ;

[0014] 3) Establish a spatial rectangular coordinate system and generate point P. i Mapping point Q i (x i ,y i ,z i ), traverse all points P i This ultimately forms the point cloud Q;

[0015] 4) Traverse all points Q in the point cloud Q i (x i ,y i ,z i Remove |z from the point cloud Q. i Points ≥ z0, where z0 is the set threshold;

[0016] 5) Thin the point cloud Q and store the remaining valid points in the array {Q}. i}

[0017] 6) Filter from laser point cloud 1 the points that match the array {Q} i Q at each point i Corresponding point P i Delete the remaining points and obtain the downsampled laser point cloud 1.

[0018] Furthermore, prior to step S1, the following is also included:

[0019] S1. Pre-construction of shotcrete: Prepare a small amount of concrete for trial transport and trial spraying before formal construction.

[0020] Furthermore, the specific preparation process of the density measurement specimen is as follows:

[0021] The concrete slab test mold is placed at an angle along the side wall of the tunnel section to be constructed. When the wet spraying machine is in a stable operating state, it is sprayed onto the concrete slab test mold to form a concrete specimen.

[0022] Furthermore, multiple large concrete slab test molds were prepared and placed at different positions along the tunnel sidewall of the section to be constructed.

[0023] Furthermore, the specific method for determining the density value ρ of the sprayed concrete is as follows:

[0024] The density of each concrete specimen is tested, and the average density of all concrete specimens is the density value of the sprayed concrete.

[0025] Furthermore, the specific formula for calculating the rebound rate k of shotcrete is as follows:

[0026]

[0027] Where m is the total mass of the concrete before spraying, ρ is the density of the concrete after spraying, and v is the volume of the sprayed concrete.

[0028] Furthermore, before step S0 and after step S1, the following steps are also included:

[0029] Concrete preparation and weighing were carried out, and the total mass of the concrete before leaving the station was recorded as m.

[0030] This invention is implemented as follows: a non-contact shotcrete rebound rate testing device, the device comprising:

[0031] A processor installed on a drone equipped with a lidar and communicating with the lidar;

[0032] Before concrete spraying, the drone is controlled to scan the tunnel wall of the section to be constructed along a set route to obtain laser point cloud 1. After concrete spraying, the drone is controlled to scan the tunnel wall of the construction section along a set route to obtain laser point cloud 2. Laser point cloud 1 and laser point cloud 2 are sent to the processor, which obtains the rebound rate of the sprayed concrete based on the above-mentioned non-contact shotcrete rebound rate test method.

[0033] The non-contact shotcrete rebound rate testing method provided by this invention has the following beneficial technical effects:

[0034] (1) The present invention uses three-dimensional laser scanning technology for non-contact measurement, eliminating the need to lay a canvas for weighing;

[0035] (2) The present invention calculates the rebound rate of shotcrete based on the mass ratio of concrete, rather than the volume ratio of concrete, thus avoiding the influence of volume change of the same mass of concrete before and after spraying.

[0036] (3) The new method for downsampling tunnel point clouds proposed in this invention first converts the measured point cloud P of the cylindrical tunnel into a new point cloud Q that is easy to process, according to the principle that the minimum distance from each point to the tunnel design outline remains unchanged. Then, the new point cloud Q is downsampled by the method of densifying irregular triangular mesh. Finally, redundant points and noise points are removed from the measured point cloud P according to the one-to-one mapping relationship, thereby improving the measurement accuracy of shotcrete volume and thus improving the calculation accuracy of shotcrete rebound rate. Attached Figure Description

[0037] Figure 1 A flowchart of a non-contact shotcrete rebound rate testing method provided in an embodiment of the present invention;

[0038] Figure 2 A schematic diagram of the projection process of each point in the laser point cloud onto the tunnel design outline provided in an embodiment of the present invention;

[0039] Figure 3 This is a three-dimensional schematic diagram of the projection process of each point in the laser point cloud onto the tunnel design outline, provided in an embodiment of the present invention. Detailed Implementation

[0040] The specific embodiments of the present invention will be further described in detail below with reference to the accompanying drawings, so as to help those skilled in the art to have a more complete, accurate and in-depth understanding of the inventive concept and technical solution of the present invention.

[0041] Figure 1 The flowchart below shows a non-contact shotcrete rebound rate testing method provided in this embodiment of the invention. The method specifically includes the following steps:

[0042] S1. Pre-construction of shotcrete: In order to reduce the quality error caused by concrete adhering to the transport tanker and wet spraying machine, a small amount of concrete is prepared for trial transport and trial spraying before formal construction to ensure that the concrete fully impregnates the inner wall of the construction equipment, thereby minimizing the loss of concrete adhering to the inner wall of the construction equipment.

[0043] S2. Concrete preparation and weighing: The total mass of concrete to be mixed at the batching plant before leaving the plant is recorded as m.

[0044] S3. Obtain laser point cloud 1 by scanning the tunnel wall of the section to be constructed before concrete spraying using lidar;

[0045] Before spraying, a drone equipped with a lidar module is used to perform a complete scan of the tunnel walls in the section to be constructed.

[0046] S4. Carry out shotcrete construction and prepare density measurement specimens at the same time. Measure the density value ρ of the shotcrete based on the density measurement specimens.

[0047] In this embodiment of the invention, the preparation process of the density measurement specimen is as follows:

[0048] Several large concrete slab test molds were placed at different positions along the tunnel sidewall of the section to be constructed. When the wet spraying machine was in a stable operating state, the concrete slab test molds were sprayed to form several concrete test specimens.

[0049] In this embodiment of the invention, the density of each concrete specimen is tested, and the average density of all concrete specimens is the density value ρ of the sprayed concrete.

[0050] S5. The laser point cloud 2 is obtained by scanning the tunnel wall of the section to be constructed after concrete spraying using lidar.

[0051] S6. After downsampling the laser point cloud 1 and laser point cloud 2, laser point cloud 3 and laser point cloud 4 are formed.

[0052] S7. Based on 3D reshaper, laser point cloud 3 and laser point cloud 4 are modeled respectively. The difference in volume between the two models is the volume v of the shotcrete attached to the tunnel wall, and then the rebound rate of the shotcrete is calculated.

[0053] In the embodiments of the invention, the formula for calculating the rebound rate of shotcrete is as follows:

[0054]

[0055] In this embodiment of the invention, laser point cloud 1 and laser point cloud 2 are downsampled using the same point cloud downsampling method. Taking laser point cloud 1 as an example, the point cloud downsampling method is described in detail as follows:

[0056] 1) Project the coordinates in laser point cloud 1 to the world coordinate system and import the tunnel design outline into the world coordinate system;

[0057] The world coordinate system is a coordinate system constructed based on a certain point in the tunnel; it can also be understood as the construction coordinate system.

[0058] 2) Read the coordinates of all points in the laser point cloud 1 in the world coordinate system, traverse and retrieve all points in the laser point cloud 1, and project each point onto the tunnel design outline. The i-th point P i The projection method is as follows:

[0059] Determine point P i Projection point P on the tunnel design outline i ′, obtain projection point P i The curve length x to the left arch foot of the tunnel i Determine point P i Tunnel mileage y i Point P i Minimum distance z to the tunnel design profile surface i Floor plan as follows Figure 2 As shown, the 3D diagram is as follows Figure 3 As shown;

[0060] 3) Establish a spatial rectangular coordinate system and generate point P. i Mapping point Q i , let Q i (x i ,y i ,z i ); Traverse all points P i This ultimately forms the point cloud Q;

[0061] 4) Traverse all points Q in the point cloud Q i (x i ,y i ,z i According to z i The statistical regularity determines the threshold z0, and |z is removed from the point cloud Q. i |≥z0 point.

[0062] 5) Thin the point cloud Q to remove noise and redundant points, retaining only the valid points related to the tunnel contour features, and store the valid points in the array {Q}. i}

[0063] The thinning method used is the LIDAR point cloud data thinning algorithm from the paper "LIDAR Point Cloud Data Thinning Algorithm Considering Terrain Features".

[0064] 6) Filter from laser point cloud 1 the points that match the array {Q} i Q at each point i Corresponding point P i Delete the remaining points to obtain the downsampled laser point cloud, i.e., laser point cloud 3.

[0065] The present invention also provides a non-contact shotcrete rebound rate testing device, the device comprising:

[0066] The processor located on the drone equipped with LiDAR and communicating with the LiDAR is...

[0067] Before concrete spraying, the drone is controlled to scan the tunnel wall of the section to be constructed along a set route to obtain laser point cloud 1. After concrete spraying, the drone is controlled to scan the tunnel wall of the construction section along a set route to obtain laser point cloud 2. Laser point cloud 1 and laser point cloud 2 are sent to the processor, which obtains the rebound rate of the sprayed concrete based on the above-mentioned non-contact shotcrete rebound rate test method.

[0068] The present invention has been described by way of example. Obviously, the specific implementation of the present invention is not limited to the above-described manner. Any non-substantial improvements made using the inventive concept and technical solution of the present invention, or the direct application of the inventive concept and technical solution of the present invention to other occasions without modification, are all within the protection scope of the present invention.

Claims

1. A non-contact method of testing the rebound of sprayed concrete, characterized in that, The method specifically comprises the following steps: S1, scanning the tunnel wall of the to-be-constructed section before concrete spraying by laser radar to obtain laser point cloud 1; S2, spraying concrete construction is carried out, and a density measurement sample is prepared, and the density value p of the sprayed concrete is measured based on the density measurement sample; S3, scanning the tunnel wall of the to-be-constructed section after concrete spraying by laser radar to obtain laser point cloud 2; S4, after point cloud downsampling of the laser point cloud 1 and the laser point cloud 2, laser point cloud 3 and laser point cloud 4 are formed; S5, modeling is respectively performed on the laser point cloud 3 and the laser point cloud 4, and the difference between the volumes of the two models is the volume v of the sprayed concrete attached to the tunnel wall, and then the rebound rate of the sprayed concrete is calculated; The downsampling method of the laser point cloud 1 is specifically as follows: 1) Projecting the coordinates in the laser point cloud 1 to a world coordinate system, and importing a tunnel design contour into the world coordinate; 2) Read the coordinates of all points in the laser point cloud 1 in the world coordinate system, traverse all points in the laser point cloud 1, and project each point P i to the tunnel design contour to obtain the projection point P i of the point P i on the tunnel design contour i , the curve length x of the projection point P i to the left spring of the tunnel i , the tunnel mileage y of the point P i , and the minimum distance z of the point P i to the tunnel design contour surface; 3) Establish a spatial rectangular coordinate system and generate point P. i Mapping point Q i (x i ,y i ,z i ), traverse all points P i This ultimately forms the point cloud Q; 4) iterate over all points Q of point cloud Q i (x i ,y i ,z i ), remove points with |z i |≥z0 from point cloud Q, z0 being a set threshold value; 5) thinning the point cloud Q, storing the remaining valid points in the array {Q i}; 6) from the laser point cloud 1, select the points Q i} corresponding to the array {Q i} points P i , delete the remaining points, and obtain the down-sampled laser point cloud 1.

2. The non-contact method of testing the rebound of sprayed concrete according to claim 1, characterized in that Before step S1, the method further comprises the following steps: S1, spraying concrete pre-construction: a small amount of concrete is prepared before formal construction to perform trial transportation and trial spraying.

3. The non-contact method of testing the rebound of sprayed concrete according to claim 1, wherein The preparation process of the density measurement sample is specifically as follows: The concrete large plate test mold is inclined and placed along the tunnel side wall of the to-be-constructed section, and when the wet spraying machine is in a stable operation state, spraying is performed on the concrete large plate test mold to form a concrete test piece.

4. The non-contact method of testing the rebound of sprayed concrete according to claim 3, characterized in that The concrete large plate test mold is multiple, and is inclined and placed at different positions along the tunnel side wall of the to-be-constructed section.

5. The non-contact method of testing the resiliency of sprayed concrete according to claim 4, characterized in that The method for determining the density value p of the sprayed concrete is specifically as follows: The density of each concrete test piece is tested, and the average density of all the concrete test pieces is the density value of the sprayed concrete.

6. The non-contact method of testing the rebound of sprayed concrete according to claim 1, wherein The calculation formula of the rebound rate k of the sprayed concrete is specifically as follows: Wherein, m is the total mass of the concrete before spraying, p is the density value of the sprayed concrete, and v is the volume of the sprayed concrete.

7. The non-contact method of testing the resiliency of sprayed concrete according to claim 1, wherein Before step S0 and after step S1, the method further comprises the following steps: Concrete preparation and weighing, and recording the total mass of the concrete before leaving as m.

8. A non-contact rebound testing device for shotcrete, characterized in that, The device comprises: A processor in communication connection with the laser radar carried by the unmanned aerial vehicle; Before the concrete spraying, the unmanned aerial vehicle is controlled to scan the tunnel wall of the to-be-constructed section along a set route to obtain the laser point cloud 1, and after the concrete spraying, the unmanned aerial vehicle is controlled to scan the tunnel wall of the to-be-constructed section along the set route to obtain the laser point cloud 2, and the laser point cloud 1 and the laser point cloud 2 are sent to the processor, and the processor obtains the rebound rate of the sprayed concrete based on the non-contact sprayed concrete rebound rate testing method in any one of claims 1 to 7.

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