Analysis device, analysis method, and program

Abstract

To determine small displacements in millimeters on an inner surface of a structure from point cloud data at two points in time in an interior space of the structure.SOLUTION: An analysis device (1) comprises a point cloud data measurement unit (11) that acquires point cloud data of an internal space of a structure, a mesh data creation unit (12) that creates a three-dimensional model of an inner surface of the structure, a coordinate conversion unit (13) that aligns coordinates between all mesh nodes and point cloud data at each time, a displacement vector calculation unit (14) that calculates a displacement vector in which the three-dimensional model is divided into local regions containing the converted point cloud data and one mesh node, the coordinates of the nodes in each area are starting points, and the coordinates of each converted point cloud data associated with each area are ending points, and a displacement analysis unit (15) that calculates the difference between the displacement vector at the first time and the displacement vector at the second time as the displacement of each node.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present disclosure relates to an analysis apparatus, an analysis method, and a program for analyzing displacement of the inner surface of a structure using point cloud data of the internal space of the structure.

Background Art

[0002] Conventionally, when a large external force (such as an earthquake, groundwater level, ground movement, large-scale construction near a tunnel, etc.) acts on a tunnel (structure), the displacement of the internal space of the tunnel has been measured to quantitatively grasp the degree of distortion of the tunnel as a structure. However, conventionally, the displacement of the internal space of a tunnel has been measured locally, and in order to capture the distortion of the internal space of the tunnel in a three-dimensionally continuous range, many measuring devices are required, and the cost of the devices is also high. In addition, there has been no technology for analyzing the displacement of the internal space using three-dimensional point cloud data that can efficiently measure the structure of the internal space of the tunnel and evaluating the stress applied to the tunnel structure.

[0003] Non-Patent Document 1 describes a displacement amount analysis technique using an ICP (Iterative Closest Point) algorithm or the like that specifically and quantitatively represents the deformation of the seabed topography.

[0004] Non-Patent Document 2 describes a technique for acquiring three-dimensional point cloud data for a collapsed area of a steep slope facing a river and performing fluctuation analysis using an ICP algorithm or the like.

[0005] In the conventional slope fluctuation evaluation technique at two time points, the point cloud data at the two time points are superimposed by the ICP algorithm, and the vector connecting the corresponding point cloud data is regarded as the displacement. In addition, for efficiency improvement of the analysis, the displacement amount is calculated for each square mesh.

Prior Art Documents

Non-Patent Documents

[0006]

Non-Patent Document 1

Non-Patent Document 2

Summary of the Invention

Problems to be Solved by the Invention

[0007] However, there is no case where the displacement of a tunnel is analyzed using a method of calculating the displacement amount from point cloud data at two points. In the evaluation of slope movement other than tunnels, the displacement amount is calculated from point cloud data at two points, but since the displacement is in meters, the error in displacement is on the order of several tens of centimeters. On the other hand, there is no method for meshing the internal space of a tunnel and calculating displacement for analyzing small displacements in the order of millimeters on the surface like a tunnel. Furthermore, in the conventional stress evaluation by FEM (Finite Element Method) analysis, there is a problem that uncertainties and variations in the physical properties of the ground around the tunnel and tunnel members cannot be considered.

[0008] In view of such circumstances, an object of the present disclosure is to provide an analysis device, an analysis method, and a program that enable obtaining, in a planar manner, small displacements in the order of millimeters on the inner surface of a structure from point cloud data at two points of the internal space of the structure.

Means for Solving the Problems

[0009] To solve the above problems, an analysis device according to the present embodiment is an analysis device that analyzes the displacement of the inner surface of a structure using point cloud data of the internal space of the structure, and includes a point cloud data measurement unit that acquires point cloud data of the internal space of the structure at each of a first time and a second time, a mesh data creation unit that inputs design data of the structure and creates a three-dimensional model of the inner surface of the structure, a coordinate conversion unit that meshes the three-dimensional model and performs coordinate alignment between all mesh nodes and the point cloud data at each time, a displacement vector calculation unit that divides the three-dimensional model into local regions each including the transformed point cloud data at each time and one mesh node, and calculates, as a displacement vector of the mesh nodes in each region at each time, a first vector having the coordinates of the mesh nodes in each region as a starting point and the coordinates of the transformed point cloud data associated with each region as an end point, and a displacement analysis unit that calculates the difference between the displacement vector at the first time and the displacement vector at the second time as the displacement of each mesh node. It is provided with.

[0010] To solve the above problems, an analysis method according to the present embodiment is an analysis method that analyzes the displacement of the inner surface of a structure using point cloud data of the internal space of the structure, and includes steps of acquiring, by an analysis device, point cloud data of the internal space of the structure at each of a first time and a second time, inputting design data of the structure and creating a three-dimensional model of the inner surface of the structure, meshing the three-dimensional model and performing coordinate alignment between all mesh nodes and the point cloud data at each time, dividing the three-dimensional model into local regions each including the transformed point cloud data at each time and one mesh node, and calculating, as a displacement vector of the mesh nodes in each region at each time, a first vector having the coordinates of the mesh nodes in each region as a starting point and the coordinates of the transformed point cloud data associated with each region as an end point, and calculating the difference between the displacement vector at the first time and the displacement vector at the second time as the displacement of each mesh node.

[0011] To solve the above problems, the program according to this embodiment causes a computer to function as the above analysis device.

Effect of the Invention

[0012] According to the present disclosure, it becomes possible to obtain a small displacement in millimeters on the inner surface of a structure in a planar manner from the point cloud data of the internal space of the structure at two points in time.

Brief Description of the Drawings

[0013]

Figure 1

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Figure 8

Mode for Carrying Out the Invention

[0014] Hereinafter, embodiments for carrying out the present invention will be described in detail with reference to the drawings. The present invention is not limited to the following embodiments, and can be implemented with various modifications within the scope of the gist thereof.

[0015] FIG. 1 is a block diagram showing a configuration example of the analysis device 1 according to the present embodiment. As shown in FIG. 1, the analysis device 1 includes a point cloud data measurement unit 11, a mesh data creation unit 12, a coordinate conversion unit 13, a displacement vector calculation unit 14, and a displacement analysis unit 15. The analysis device 1 analyzes the displacement of the inner surface of the structure using the point cloud data P of the internal space of the structure. In the present embodiment, the structure will be described by taking a tunnel as an example.

[0016] The control arithmetic circuit 20 (controller 20) is constituted by the mesh data creation unit 12, the coordinate conversion unit 13, the displacement vector calculation unit 14, and the displacement analysis unit 15 included in the analysis device 1. The control arithmetic circuit 20 may be constituted by dedicated hardware such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field-Programmable Gate Array), or may be constituted by a processor, or may be constituted including both.

[0017] The point cloud data measurement unit 11 acquires the point cloud data P (P0, P1) of the internal space of the structure (tunnel) at each of the first time and the second time using a laser scanner. The point cloud data measurement unit 11 deletes the point cloud data of the internal equipment in the tunnel other than the tunnel main body from the acquired two-point data, that is, the point cloud data P0 of the internal space of the tunnel at the first time and the point cloud data P1 of the internal space of the tunnel at the second time, and outputs the point cloud data P0 and P1 after deletion (after correction) to the coordinate conversion unit 13.

[0018] The mesh data creation unit 12 inputs the design data d_data of the structure (tunnel) and creates a three-dimensional model 3Dm of the inner surface of the structure (tunnel). The mesh data creation unit 12 meshes the three-dimensional model 3Dm into a first mesh size. The first mesh size is, for example, a square mesh size of 20 cm × 20 cm. The mesh data creation unit 12 outputs the three-dimensional model 3Dm to the coordinate conversion unit 13 and the displacement vector calculation unit 14.

[0019] The coordinate transformation unit 13 meshes the 3D model 3Dm into the second mesh size, and performs coordinate alignment by coordinate transformation T between all the mesh nodes Q of the meshed 3D model 3Dm and the point cloud data P(P0, P1) at each time. FIG. 2 is a schematic diagram for explaining the alignment of the point cloud data P0 at the first time. FIG. 3 is a schematic diagram for explaining the alignment of the point cloud data P1 at the second time. As shown in FIGS. 2 and 3, the coordinate transformation unit 13 performs coordinate transformation T on the coordinates (x, y, z) of the point cloud data P(P0, P1) at each time in order to perform alignment between the point cloud data P(P0, P1) at each time and all the mesh nodes Q of the 3D model 3Dm meshed into the second mesh size, and obtains the coordinates (x', y', z') of the transformed point cloud data P'(P0', P1'). As shown in FIGS. 2 and 3, the second mesh size is, for example, a square mesh size of 5 cm × 5 cm. The coordinate transformation unit 13 outputs the transformed point cloud data P'(P0', P1') to the displacement vector calculation unit 14.

[0020] The coordinate transformation unit 13 may perform the coordinate transformation T using the ICP algorithm between the point cloud data P0 at the first time and all the mesh nodes Q. Similarly, the coordinate transformation unit 13 may perform the coordinate transformation T using the ICP algorithm between the point cloud data P1 at the second time and all the mesh nodes Q.

[0021] The ICP algorithm is one of the alignment algorithms for synthesizing point clouds by estimating the positional relationship between 3D point clouds captured from different positions. When two 3D point cloud data captured from different positions are given, the ICP algorithm estimates and obtains a rotation matrix and a translation matrix for aligning one point cloud data with the other point cloud data.

[0022] The coordinate transformation T by the ICP algorithm is performed according to the following formula (1). The coordinate transformation T performs a single translation and then a single rotational movement on the coordinates (x, y, z) of the point cloud data P, and the coordinates (x', y', z') of the point cloud data P' after the coordinate transformation are obtained. In formula (1), the matrix on the left side of the right side is a rotation matrix, and the matrix in the middle of the right side is a translation matrix.

Number

[0023] The displacement vector calculation unit 14 meshes the three-dimensional model 3Dm into a third mesh size, and divides it into a local area V that includes the transformed point cloud data P' at each time (P0' ik , P1' ik ) and a single mesh node Q ik . For each area V i , with the coordinates q i of the mesh node Q i in the area as the starting point, and the coordinates p' i of each transformed point cloud data P' i associated with each area V i as the ending point, the first vector is calculated as the displacement vector d ik of the mesh node Q ik in each area V i at each time. i i

[0024] Figure 4 is a schematic diagram for explaining the calculation method of the displacement vector d i at the first time. Also, Figure 5 is a schematic diagram for explaining the calculation method of the displacement vector d i at the second time. In Figures 4 and 5, P0' is the transformed point cloud data P' at the first time, P1' is the transformed point cloud data P' at the first time, i is the number of each mesh node of the meshed three-dimensional model 3Dm, k is the number of the point cloud data P' (P0', P1') included in each area V i centered on each mesh node Q i , and P irepresent the centroids of the point group data P’(P0’, P1’) to be described later respectively. The third mesh size is set to a size sufficient to capture the stress distribution obtained by dividing one side of the internal space of the tunnel. For example, when capturing the stress distribution obtained by dividing one side of the internal space of the tunnel into 12 parts, the third mesh size is set to 20 cm × 20 cm. Based on such a third mesh size, the mesh node Q i centers a 20 cm × 20 cm × 24 cm region as the local region V i . The displacement vector calculation unit 14 outputs the displacement vector d i of the mesh node Q i in each region V i at each calculated time to the displacement analysis unit 15. When there are multiple pieces of transformed point group data P’ i associated with each region V ik , the number of displacement vectors d i of the mesh node Qi becomes multiple.

[0025] However, when there are multiple pieces of transformed point group data P’ i associated with each region V ik , calculating the displacement vector d i for all the point group data P’ i contained in the region V ik centered on each mesh node Q i causes an increase in the computational complexity of displacement calculation. Therefore, the displacement vector calculation unit 14 obtains the centroid P ik (P0’ ik , P1’ ik ) of the transformed point group data P’ i , and uses the coordinate q i of the mesh node Q i in each region V i as the starting point, and the coordinate p i of the centroid P i associated with each region V i as the ending point to calculate the second vector as the displacement vector d i of the mesh node Q i in each region at each time. This makes it possible to reduce the computational complexity of displacement calculation. The coordinate p of the centroid of the point group data P’ ik ​i is calculated from the following formula (2). In formula (2), i represents the number of the mesh node, k represents the number of each point group data included in each region, N i represents the number of point group data in each region, p ik represents the region V i each point group data P’ ik (P0’ ik , P1’ ik ) represents the coordinates respectively.

Number

[0026] The displacement vector calculation unit 14 uses the coordinates q i of the mesh node Q i in each region V i as the starting point, and the coordinates p i of the centroid P ik of the transformed point group data P’ i associated with each region V i as the ending point to calculate the second vector as the displacement vector d i of the mesh node Q i in each region V i at each time. The displacement vector d i with the coordinates q i of the mesh node Q ik as the starting point and the coordinates p i of the centroid P i of the transformed point group data P’ i as the ending point is calculated from the following formula (3). In formula (3), p i represents the centroid coordinates of the point group data, and q i represents the coordinates of the mesh node Q i respectively.

Number

[0027] Further, the displacement vector calculation unit 14 calculates the displacement in the normal direction of the tunnel inner surface (mesh surface) in order to capture the degree of stress caused by the deformation, as the deformation of the tunnel inner surface at the first time and the second time is a deformation in which the displacement in the tangential direction is sufficiently smaller than the displacement in the normal direction of the mesh.

[0028] The displacement vector calculation unit 14 calculates the normal direction component of the displacement vector d i in each region V i and obtains a normal vector having the normal direction component, and sets the displacement vector d i of the mesh node Q i in each region V at each time to the normal vector. It may be calculated as (d0 in , d1 in ). The displacement vector d0 in at the first time (the normal vector having the normal direction component) is calculated from the following (Equation) 4. The displacement vector d1 in at the second time (the normal vector having the normal direction component) is calculated from the following (Equation) 5. In Equation (4) and Equation (5), n in represents a unit vector in the normal direction of the mesh, d0 i represents the displacement vector in the normal direction of the mesh at the first time, and d1 in represents the displacement vector in the normal direction of the mesh at the second time. The displacement vector calculation unit 14 calculates the displacement vectors d0 in and d1 in at each time for all regions V in and repeats the calculation. i

Equation

[0029] The displacement analysis unit 15 calculates the difference between the displacement vector d0 in at the first time and the displacement vector d1 in at the second time as the displacement dR i of each mesh node Q iIt is calculated as follows. FIG. 6 is a schematic diagram for explaining the displacement of each mesh node. For example, each mesh node Q shown in FIG. 6 i The displacement dR i is expressed as a vector starting from the coordinate of the end point of the displacement vector d in (d0 in ) at the first time shown in FIG. 4 and ending at the coordinate of the end point of the displacement vector d in (d1 in ) at the second time shown in FIG. 5. The displacement dR of each mesh node Q i is calculated by the following formula (6). The displacement analysis unit 15 calculates the displacement dR of each mesh node Q i repeatedly for all regions V i The displacement dR of i is calculated repeatedly for all regions V i .

Equation

[0030] FIG. 7 is a flowchart showing an example of the analysis method executed by the analysis apparatus 1 according to the present embodiment.

[0031] In step S101, the point cloud data measurement unit 11 acquires the point cloud data P (P0, P1) of the internal space of the tunnel at each of the first time and the second time using a laser scanner.

[0032] In step S102, the point cloud data measurement unit 11 corrects the acquired point cloud data P. Specifically, the point cloud data measurement unit 11 corrects the point cloud data P to the point cloud data P from which the point cloud data of the tunnel internal equipment other than the tunnel main body included in the point cloud data P is deleted.

[0033] In step S103, the mesh data creation unit 12 inputs the design data d_data of the tunnel and creates a three-dimensional model 3Dm of the inner surface of the tunnel meshed into the first mesh size.

[0034] In step S104, the coordinate conversion unit 13 performs coordinate alignment by coordinate conversion between the point cloud data P at each time and all the mesh nodes of the three-dimensional model 3Dm meshed into the second mesh size.

[0035] In step S105, the displacement vector calculation unit 14 meshes the three-dimensional model 3Dm with the third mesh size and divides it into local regions each containing the transformed point cloud data (which may include a plurality of point cloud data) at each time and one mesh node.

[0036] In step S106, the displacement vector calculation unit 14 uses the coordinates q i of the mesh node Q i in each region V i as the starting point, and calculates, for each time, a first vector (a plurality of vectors targeting a plurality of point cloud data may be calculated) with the coordinates p’ i of each transformed point cloud data P’ ik associated with each region V ik as the ending point, as the displacement vector d i of the mesh node Q i in each region V i at each time.

[0037] In step S107, the displacement analysis unit 15 calculates the difference between the displacement vector d0 in at the first time and the displacement vector d1 in at the second time as the displacement dR i of each mesh node Q i at each time.

[0038] According to the analysis device 1 according to the present disclosure, it is possible to obtain the small displacements in millimeter units of the inner surface of the structure (tunnel) in a planar manner from the point cloud data at two time points of the internal space of the structure (tunnel).

[0039] In addition, in order to operate the above-described analysis device 1, it is also possible to use a computer capable of executing program instructions. FIG. 8 is a block diagram showing a schematic configuration of a computer that functions as the analysis device 1. Here, the computer 100 may be a general-purpose computer, a dedicated computer, a workstation, a PC (Personal Computer), an electronic notebook, or the like. The program instructions may be program codes, code segments, etc. for executing necessary tasks.

[0040] As shown in FIG. 8, the computer 100 includes a processor 110, a ROM (Read Only Memory) 120, a RAM (Random Access Memory) 130, and a storage 140 as storage units, an input unit 150, an output unit 160, and a communication interface (I / F) 170. Each component is connected so as to be communicable with each other via a bus 180.

[0041] The ROM 120 stores various programs and various data. The RAM 130 temporarily stores a program or data as a work area. The storage 140 is composed of an HDD (Hard Disk Drive) or an SSD (Solid State Drive) and stores various programs and various data including an operating system. In the present disclosure, the program according to the present disclosure is stored in the ROM 120 or the storage 140.

[0042] The processor 110 is specifically a CPU (Central Processing Unit), MPU (Micro Processing Unit), GPU (Graphics Processing Unit), DSP (Digital Signal Processor), SoC (System on a Chip), etc., and may be composed of a plurality of processors of the same type or different types. The processor 110 reads a program from the ROM 120 or the storage 140, and executes the program using the RAM 130 as a working area, thereby controlling each of the above components and performing various arithmetic processes. Note that at least a part of these processing contents may be realized by hardware.

[0043] The program may be recorded on a recording medium readable by the analysis device 1. By using such a recording medium, it is possible to install the program in the analysis device 1. Here, the recording medium on which the program is recorded may be a non-transitory recording medium. The non-transitory recording medium is not particularly limited, and may be, for example, a CD-ROM, a DVD-ROM, a USB (Universal Serial Bus) memory, or the like. Further, this program may be in a form downloaded from an external device via a network.

[0044] Regarding the above embodiments, the following additional remarks are further disclosed.

[0045] (Additional Clause 1) An analysis device that analyzes the displacement of the inner surface of a structure using the point cloud data of the internal space of the structure, A laser scanner that acquires the point cloud data of the internal space of the structure at each of the first time and the second time, Input the design data of the structure, create a three-dimensional model of the inner surface of the structure, mesh the three-dimensional model, align the coordinates between all mesh nodes and the point cloud data at each time point, divide the three-dimensional model into local regions each containing the transformed point cloud data at each time point and one mesh node, calculate a first vector with the coordinates of the mesh nodes in each region as the starting point and the coordinates of the transformed point cloud data corresponding to each region as the ending point as the displacement vector of the mesh nodes in each region at each time point, and calculate the difference between the displacement vector at the first time point and the displacement vector at the second time point as the displacement of each mesh node, and an analysis device comprising a controller. (Additional item 2) The controller according to claim 1, wherein a second vector with the coordinates of the mesh nodes in each region as the starting point and the coordinates of the centroid of the transformed point cloud data corresponding to each region as the ending point is calculated as the displacement vector of the mesh nodes in each region at each time point. (Additional item 3) The controller according to claim 1 or 2, wherein the normal direction component of the displacement vector in each region is obtained, and a normal vector having the normal direction component is calculated as the displacement vector of the mesh nodes in each region at each time point. (Additional item 4) An analysis method for analyzing the displacement of the inner surface of a structure using point cloud data of the internal space of the structure, comprising: by an analysis device, Acquire point cloud data of the internal space of the structure at each of the first time and the second time, input the design data of the structure, create a three-dimensional model of the inner surface of the structure, mesh the three-dimensional model, perform coordinate alignment between all mesh nodes and the point cloud data at each time, divide the three-dimensional model into local regions each containing the transformed point cloud data at each time and one mesh node, calculate, as the displacement vector of the mesh nodes in each region, a first vector with the coordinates of the mesh nodes in each region as the starting point and the coordinates of the transformed point cloud data associated with each region as the ending point, and calculate the difference between the displacement vector at the first time and the displacement vector at the second time as the displacement of each mesh node. (Supplementary Claim 5) A non-transitory storage medium storing a program executable by a computer, the non-transitory storage medium storing a program that causes the computer to function as the analysis device according to any one of claims 1 to 3.

[0046] Although the above-described embodiments have been described as representative examples, it is obvious to those skilled in the art that many changes and substitutions can be made within the spirit and scope of the present disclosure. Therefore, the present invention should not be construed as being limited by the above-described embodiments, and various modifications or changes are possible without departing from the scope of the claims. For example, it is possible to combine a plurality of constituent blocks described in the configuration diagrams of the embodiments into one, or to divide one constituent block.

Explanation of Reference Numerals

[0047] 1 Analysis device 11 Point cloud data measurement unit (laser scanner) 12 Mesh data creation unit 13 Coordinate transformation unit 14 Displacement vector calculation unit 15 Displacement analysis unit 20 Control arithmetic circuit (controller) 100 Computer 110 Processor 120 ROM 130 RAM 140 Storage 150 Input section 160 Output section 170 Communication interface (I / F) 180 Bus

Claims

1. An analysis device for analyzing the displacement of the inner surface of a structure using point cloud data of the internal space of the structure, comprising: a point cloud data measurement unit that acquires point cloud data of the internal space of the structure at each of a first time and a second time; a mesh data creation unit that inputs design data of the structure and creates a three-dimensional model of the inner surface of the structure; a coordinate conversion unit that meshes the three-dimensional model and performs coordinate alignment between all mesh nodes and the point cloud data at each of the times; a displacement vector calculation unit that divides the three-dimensional model into local regions each including the transformed point cloud data at each of the times and one mesh node, and calculates, as displacement vectors of the mesh nodes in each region at each of the times, first vectors having the coordinates of the mesh nodes in each region as starting points and the coordinates of the transformed point cloud data associated with each region as end points; a displacement analysis unit that calculates the difference between the displacement vectors at the first time and the displacement vectors at the second time as the displacement of each mesh node; and an analysis device comprising the same.

2. The analysis device according to claim 1, wherein the displacement vector calculation unit calculates, as displacement vectors of the mesh nodes in each region at each of the times, second vectors having the coordinates of the mesh nodes in each region as starting points and the coordinates of the centroids of the transformed point cloud data associated with each region as end points.

3. The analysis device according to claim 1 or 2, wherein the displacement vector calculation unit obtains a normal direction component of the displacement vector in each region and calculates, as displacement vectors of the mesh nodes in each region at each of the times, normal vectors having the normal direction component.

4. An analysis method for analyzing the displacement of the inner surface of a structure using point cloud data of the internal space of the structure, comprising the steps of: by an analysis device, acquiring point cloud data of the internal space of the structure at each of a first time and a second time; inputting design data of the structure and creating a three-dimensional model of the inner surface of the structure; meshing the three-dimensional model and performing coordinate alignment between all mesh nodes and the point cloud data at each of the times; The step of dividing the three-dimensional model into local regions each including the point cloud data after conversion at each of the times and one mesh node, and calculating, as the displacement vector of the mesh node in each region, a first vector having the coordinates of the mesh node in each region as a starting point and the coordinates of each point cloud data after conversion associated with each region as an end point at each of the times; The step of calculating, as the displacement of each mesh node, the difference between the displacement vector at the first time and the displacement vector at the second time; An analysis method for executing the above.

5. A program for causing a computer to function as the analysis device according to Claim 1 or 2.

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