Analysis device, analysis method, and program

Abstract

An analysis device (1) according to this invention comprises a 3D point cloud data input unit (12) for inputting point cloud data for the inside of a structure that has been measured using a laser scanner, a first analysis unit (13) for removing, from the point cloud data, point cloud data that is not for an object under structural evaluation, and a second analysis unit (14) for extracting point cloud data for a location necessary for structural evaluation.

Description

[Technical field]

[0001] The present disclosure relates to an analysis device, an analysis method, and a program for improving the accuracy of point cloud data. [Background technology]

[0002] Traditionally, point cloud data with 3D coordinate values ​​has been used to predict deterioration inside cable tunnels (dedicated conduit tunnels for communication cables, etc., particularly those with a pipe diameter that allows people to enter for installation, removal, and maintenance work). Point cloud data refers to a collection of points handled by a computer that contains basic positional information of X, Y, and Z, as well as color and other information. Traditionally, the following three methods have been used to obtain the positional coordinates of point cloud data.

[0003] In the first method, a laser scanner outputs acquired data as colored point cloud data, and the position of the point cloud data is automatically corrected by SLAM (Simultaneous Localization and Mapping). Point cloud data is acquired by reading information that is reflected when a laser beam emitted from a laser scanner hits an object. For example, Non-Patent Document 1 describes an efficient method for inspecting concrete structures using three-dimensional point cloud data, and Non-Patent Document 2 describes the catalog specifications of a compact and highly accurate laser scanner.

[0004] The second method is to generate position coordinates from images captured by a stereo camera using SFM (Structure from Motion) technology. In order to generate high-density point cloud data, "MVS (Multi-View Stereo)" technology, which is a concept of SFM technology, may be used.

[0005] The third method is to obtain absolute position coordinates inside the tunnel by combining a plan view and an internal structure view of the tunnel. [Prior art documents] [Non-patent literature]

[0006] [Non-Patent Document 1] Makoto Kameoka and 5 others, "Inspection of Concrete Structures Using Point Cloud Data", 75th Annual Academic Lecture Meeting of the Japan Society of Civil Engineers, 2020, VI-270 [Non-Patent Document 2] FARO Focus Laser Scanner catalog, [online], [searched May 10, 2021], Internet<URL:https: / / www.faro.com / ja-JP / Resource-Library / Tech-Sheet / techsheet-faro-focus-laser-scanner> Summary of the Invention [Problem to be solved by the invention]

[0007] However, in order to predict deterioration through structural evaluation of the tunnel, it is necessary to minimize errors in the positional information of the point cloud data inside the tunnel and to carry out FEM (Finite Element Method) analysis, etc. For example, the allowable amount of displacement itself is 1 / 500 of the tunnel diameter, and for a diameter of 3m, an allowable amount of about 6mm is required. Since earth pressure is already applied and the remaining allowable displacement is only a few mm, displacement measurement in millimeters is necessary, but even with the highest accuracy of a point cloud scanner, the diameter displacement can only be measured with an accuracy of ±2mm.

[0008] Furthermore, there are some inconsistencies in the relative position information of the plan, longitudinal section and internal structure drawings of the cable tunnel, and there are some parts of the plan, longitudinal section and internal structure drawings that do not match the on-site structure, making it difficult to perform a structural evaluation using drawing position information obtained by combining the plan and internal structure drawings of the cable tunnel.

[0009] On the other hand, the positional information of point cloud data obtained by high-precision laser scanners is highly accurate (maximum accuracy of ±1.0 mm), but most measurements are taken while the scanner is stationary, so measuring wide areas and long sections such as tunnels takes time and is expensive.

[0010] In view of the above circumstances, an object of the present invention is to establish a technique for improving the accuracy of point cloud data for structural evaluation in the analysis of internal images and point cloud data of a structure. [Means for solving the problem]

[0011] In order to solve the above problems, an analysis device according to one embodiment is an analysis device that generates point cloud data of a structural evaluation object, and includes a 3D point cloud data input unit that inputs point cloud data of a structural evaluation object area measured by a laser scanner, a first analysis unit that removes point cloud data other than that of the structural evaluation object from the point cloud data, and a second analysis unit that extracts point cloud data of locations necessary for structural evaluation from the point cloud data removed by the first analysis unit.

[0012] In order to solve the above problems, an analysis method according to one embodiment is an analysis method in an analysis device that generates point cloud data of a structural evaluation object, and includes an input step of inputting point cloud data of a structural evaluation object area measured by a laser scanner by the analysis device, a removal step of removing point cloud data other than that of the structural evaluation object from the point cloud data, and a step of extracting point cloud data of locations necessary for structural evaluation from the point cloud data removed by the removal step.

[0013] In order to solve the above problem, a program according to one embodiment causes a computer to function as the above analysis device. Effect of the Invention

[0014] According to the present disclosure, it is possible to improve the accuracy of point cloud data for structural evaluation. [Brief description of the drawings]

[0015] [Figure 1] 1 is a block diagram showing an example of the configuration of an analysis device according to an embodiment. [Figure 2A] FIG. 11 is a schematic diagram for identifying a point cloud data region to be removed other than a structural evaluation target object. [Figure 2B] 11 is a schematic diagram showing a criterion for identifying a point cloud data surface to be removed other than a structural evaluation target object. FIG. [Diagram 3] 1 is a schematic diagram for explaining a method for extracting point cloud data of a portion required for structural analysis. FIG. [Figure 4] 1 is a flowchart illustrating an example of an analysis method executed by an analysis device according to an embodiment. [Diagram 5] FIG. 2 is a block diagram showing a schematic configuration of a computer functioning as an analysis device. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0016] An analysis device according to an embodiment will be described in detail below. The present invention is not limited to the following embodiment, and various modifications can be made within the scope of the present invention.

[0017] 1, an analysis device 1 according to an embodiment includes a structural evaluation necessity determination unit 11, a 3D point cloud data input unit 12, a first analysis unit 13, and a second analysis unit 14. The analysis device 1 generates point cloud data of a structural evaluation object.

[0018] The structural evaluation necessity determination unit 11 determines whether or not the structure is a structural evaluation target area that requires structural evaluation based on the cross-sectional linear data of the structure. The structural evaluation target area is a portion where stress is applied due to vibration over time, such as a shaft-tunnel connection or a building-tunnel connection. For example, the structural evaluation necessity determination unit 11 uses cross-sectional linear data described in any one of the plan, longitudinal section, and internal structure drawings of the structure to select a portion where the shape has changed compared to other portions as the structural evaluation target area. The structural evaluation necessity determination unit 11 outputs the determination result to the 3D point cloud data input unit 12. The structural evaluation necessity determination unit 11 may determine whether or not structural evaluation is required manually by having an operator look around the positions for structural evaluation, or may be realized by hardware as a functional unit that automatically determines whether or not structural evaluation is required by reading data that can recognize the location on the drawing of the tunnel. In this embodiment, the structural evaluation target area will be described below as the tunnel internal structure, but the structural evaluation target area is not limited to this.

[0019] When the structural evaluation necessity determination unit 11 determines that a structure is a structural evaluation target area, the 3D point cloud data input unit 12 inputs point cloud data (3D point cloud data) of the structural evaluation target area measured by the laser scanner 15, and outputs the point cloud data to the first analysis unit 13.

[0020] The first analysis unit 13 removes point cloud data other than that of the structural evaluation object from the 3D point cloud data, and outputs the point cloud data from which the point cloud data other than that of the structural evaluation object has been removed to the second analysis unit. A method for removing point cloud data other than that of the deterioration prediction object will be described in detail below with reference to Figures 2A and 2B.

[0021] When removing point cloud data other than that of the structural evaluation object, the first analysis unit 13 identifies ancillary objects other than the structural evaluation object and removes the point cloud data of the ancillary objects. When the structural evaluation object area is the internal structure of a tunnel, the ancillary objects are metal fittings, cables, and the like installed inside the tunnel.

[0022] For example, the first analysis unit 13 identifies a point cloud data surface where the length of the normal between the 2D internal cross section of the structure and the point cloud data surface is equal to or longer than a certain length, and removes the area obtained by extending the identified point cloud data surface in the traveling direction of the structure. This process will be described with reference to Fig. 2. In Fig. 2, the structure evaluation target area will be described below as the internal structure of a tunnel, but the deterioration prediction target is not limited to this.

[0023] Fig. 2A is a schematic diagram of identifying a point cloud data area to be removed other than the object to be structurally evaluated. In Fig. 2A, the solid lines indicate the 2D internal cross section 21 of the tunnel and the area 21' obtained by extending the internal cross section 21 in the tunnel travel direction, the dashed lines indicate the 2D point cloud data surface 22 generated by the laser scanner and the area 22' obtained by extending the point cloud data surface 22 in the tunnel travel direction, the dashed and dotted lines indicate the 2D point cloud data surface 23 to be removed and the point cloud data area 23' to be removed obtained by extending the point cloud data surface 23 to be removed in the tunnel travel direction, and the black circles and triangles indicate accessories (black circles indicate cables, triangles indicate metal fittings).

[0024] Fig. 2B is a schematic diagram showing a criterion for identifying a point cloud data surface to be removed other than the structural evaluation object. Specifically, as shown in Fig. 2B, the first analysis unit 13 judges whether or not the length of a normal line L extending from the point cloud data surface 22 at a right angle to the 2D internal cross section 21 of the tunnel is equal to or longer than a certain length in the 2D internal cross section of the tunnel. If the length of the normal line L is equal to or longer than a certain length, the first analysis unit 13 judges that the 2D internal cross section 21 of the tunnel and the point cloud data surface 22 are largely separated from each other, and identifies a point cloud data surface 23 to be removed in the 2D internal cross section 21 of the tunnel as shown in Fig. 2A, extends the point cloud data surface 23 in the tunnel travel direction, and identifies a 3D point cloud data region 23' to be removed.

[0025] In addition, the first analysis unit 13 may estimate the cross-sectional linearity of the structural evaluation object that is hidden by accessories (such as the cable / metal fittings 20 shown in Figure 2B) installed inside the structural evaluation object area from the cross-sectional linearity of the 3D point cloud data, and remove the area where the estimated cross-sectional linearity is extended in the direction of travel of the structure.

[0026] The second analysis unit 14 is a functional unit that extracts, from the point cloud data removed by the first analysis unit 13, point cloud data of locations required for structural evaluation.

[0027] When extracting point cloud data of a portion required for structural evaluation, the second analysis unit 14 specifies a portion required for structural evaluation such as FEM analysis, etc. A specific extraction method will be described below.

[0028] Fig. 3 is a schematic diagram for explaining a method for extracting point cloud data of locations required for structural analysis when the shape of the 2D internal cross section of a tunnel is rectangular. In the figure, in order to facilitate the following explanation, the following positions are specified on the 2D internal cross section of the rectangular tunnel: corner 24, upper deck support 25, upper deck center 26, side wall upper support 29, side wall upper center 30, side wall lower support 31, lower deck support 27, and lower deck center 28.

[0029] A specific method of identifying the point cloud data surface to be extracted in 3D is as follows. First, the center point of three points that form an angle of 90 degrees between any three points of the tunnel 2D internal cross section on the tunnel internal image is identified as the vertex of the tunnel 2D internal cross section. Next, the second analysis unit 14 plots the above four vertices on the point cloud data acquired by the laser scanner, divides the tunnel 2D internal cross section surrounded by the four vertices into two in the deck direction, and extracts the point cloud data included in the area 32 (the 2D internal cross section divided into two in the deck direction) indicated by diagonal lines. The reason for limiting the point cloud data to the area 32 is that the data range to be input when performing FEM analysis, etc., is half in the deck direction. Next, the point cloud data is extended in the tunnel travel direction to identify the point cloud data area to be extracted in 3D, and the point cloud data of the part required for structural evaluation is extracted. That is, as shown in Figure 3, the second analysis unit 14 divides the 2D internal cross section of the rectangular tunnel (structure) into two in the deck direction by a line connecting the center 26 of the upper deck and the center 28 of the lower deck, and extends the 2D internal cross section in the direction of travel of the tunnel (structure), thereby identifying the 3D point cloud data area to be extracted and extracting the point cloud data contained in that area.

[0030] FIG. 4 is a flowchart showing an example of an analysis method executed by the analysis device 1 according to the first embodiment.

[0031] In step S101, the structural evaluation necessity determination unit 11 determines whether or not a tunnel (structure) falls within a structural evaluation target area requiring a structural evaluation.

[0032] When the structural evaluation necessity determination unit 11 determines that the tunnel falls within the structural evaluation target area, the analysis device 1 executes steps S102 to S105.

[0033] In step S102, the 3D point cloud data input unit inputs point cloud data (3D point cloud data) of the structure target area measured by the laser scanner 15.

[0034] In step S103, the first analysis unit 13 removes point cloud data other than that of the object to be structurally evaluated from the 3D point cloud data.

[0035] In step S104, the second analysis unit 14 extracts point cloud data of locations required for structural evaluation.

[0036] On the other hand, as shown in FIG. 4, if the structural evaluation necessity determination unit 11 determines in step S101 that the tunnel does not fall within the structural evaluation target area, the analysis device 1 executes steps S105 to S107.

[0037] In step S105, the internal image input unit 16 inputs an image of the inside of the tunnel captured by the camera.

[0038] In step S106, the 3D point cloud data generating unit 17 generates 3D point cloud data of the internal structure from each internal image on the photographing route.

[0039] In step S107, the defect data extraction unit 18 extracts data of defect positions from the generated 3D point cloud data. The defect data refers to position data of a portion where the shape of the tunnel is changed compared to other portions, such as a large bend.

[0040] According to the analysis device 1, the accuracy of point cloud data for structure evaluation can be improved.

[0041] The structural evaluation necessity determination unit 11, the 3D point cloud data input unit 12, the first analysis unit 13 and the second analysis unit 14 in the above-mentioned analysis device 1 constitute a part of a control unit (controller). The control and arithmetic circuit may be constituted by dedicated hardware such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field-Programmable Gate Array), may be constituted by a processor, or may be constituted by including both.

[0042] Also, a computer capable of executing program instructions can be used to function the above-mentioned analysis device 1. Fig. 5 is a block diagram showing a schematic configuration of a computer functioning 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 notepad, etc. The program instructions may be program code, code segments, etc. for performing necessary tasks.

[0043] 5, the computer 100 includes a processor 110, a memory unit including a ROM (Read Only Memory) 120, a RAM (Random Access Memory) 130, and a storage 140, an input unit 150, an output unit 160, and a communication interface (I / F) 170. Each component is connected to each other via a bus 180 so as to be able to communicate with each other.

[0044] The ROM 120 stores various programs and various data. The RAM 130 temporarily stores programs or data as a working area. The storage 140 is configured with a hard disk drive (HDD) or a solid state drive (SSD), and stores various programs including an operating system and various data. In the present disclosure, the programs related to the present disclosure are stored in the ROM 120 or the storage 140.

[0045] Specifically, the processor 110 is a CPU (Central Processing Unit), an MPU (Micro Processing Unit), a GPU (Graphics Processing Unit), a DSP (Digital Signal Processor), a SoC (System on a Chip), etc., and may be composed of multiple processors of the same 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 processing. At least a part of the processing contents may be realized by hardware.

[0046] The program may be recorded on a recording medium readable by the computer 100. By using such a recording medium, the program can be installed in the computer 100. 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, or a USB (Universal Serial Bus) memory. In addition, the program may be in a form that is downloaded from an external device via a network.

[0047] The following supplementary notes are further disclosed regarding the above embodiment.

[0048] (Additional note 1) A control unit for generating point cloud data of an analysis device for a structural evaluation object, the control unit inputting point cloud data of a structural evaluation target area measured by a laser scanner, removing point cloud data other than that of the structural evaluation target from the point cloud data, and extracting point cloud data of locations necessary for the structural evaluation from the point cloud data removed by the first analysis unit. An analysis device comprising: (Additional note 2) The control unit is The analysis device described in appendix 1 identifies a point cloud data surface where the length of the normal between the 2D internal cross section of the structure and the point cloud data surface is equal to or longer than a certain length, and removes an area extending from the identified point cloud data surface in the traveling direction of the structure. (Additional note 3) The control unit is The analysis device according to claim 1, further comprising: estimating a cross-sectional alignment of the object to be structurally evaluated that is hidden by an attachment installed inside the object to be structurally evaluated from the cross-sectional alignment of the point cloud data; and removing a region in which the estimated cross-sectional alignment is extended in a direction in which the object to be structurally evaluated is moving. (Additional note 4) The control unit is 4. The analysis device according to claim 1, which identifies locations required for structural evaluation such as FEM analysis and extracts point cloud data. (Additional note 5) The control unit is The analysis device described in appended claim 4, which divides a 2D internal cross section of a structure into two in the deck direction and extends the 2D internal cross section in the direction of progression of the structure to identify a 3D point cloud data area to be extracted and extract the point cloud data included in that area. (Additional note 6) An analysis method for an analysis device that generates point cloud data of a structural evaluation object, comprising: The analysis device An input step of inputting point cloud data of a structural evaluation target area measured by a laser scanner; a removing step of removing point cloud data other than that of the object to be structurally evaluated from the point cloud data; extracting point cloud data of a portion required for structural evaluation from the point cloud data removed by the removing step; Analysis methods including: (Additional note 7) A non-transitory storage medium storing a program executable by a computer, the non-transitory storage medium storing the program causing the computer to function as the analysis device described in any one of appended claims 1 to 5.

[0049] Although the above-mentioned embodiment has been described as a representative example, it is obvious to those skilled in the art that many modifications and substitutions can be made within the spirit and scope of the present disclosure. Therefore, the present invention should not be interpreted as being limited by the above-mentioned embodiment, and various modifications or changes can be made without departing from the scope of the claims. For example, it is possible to combine multiple building blocks shown in the configuration diagram of the embodiment into one, or to divide one building block. [Explanation of symbols]

[0050] 1 Analysis device 11 Structural Evaluation Necessity Judgment Division 12 3D point cloud data input section 13 1st analysis section 14 2nd analysis section 15 Laser Scanner 16 Internal image input section 17 3D point cloud data generation section 18 Bad Data Extraction Section 19 Camera 100 Computers 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 generating point cloud data of a structural evaluation object, comprising: a 3D point cloud data input unit for inputting point cloud data of a structural evaluation target area measured by a laser scanner; a first analysis unit that removes point cloud data other than that of the object to be structurally evaluated from the point cloud data; a second analysis unit that extracts point cloud data of a location required for structural evaluation from the point cloud data of the structural evaluation target area after the point cloud data of the structural evaluation target area has been removed by the first analysis unit; Equipped with The first analysis unit is an analysis device that estimates the cross-sectional line of the structural evaluation object that is hidden by accessories installed inside the structural evaluation object area from the cross-sectional line of the point cloud data, and removes the point cloud data inside the area obtained by extending the estimated cross-sectional line in the direction of travel of the structural evaluation object from the point cloud data of the structural evaluation object area.

2. The analysis device according to claim 1 , wherein the structural evaluation object is a tunnel internal structure where an operator performs an on-site inspection, and the structural evaluation target area is a structural evaluation target area of ​​the tunnel internal structure.

3. The analysis device according to claim 1 , wherein the second analysis unit identifies a location required for structural evaluation in an FEM analysis and extracts point cloud data.

4. The analysis device described in claim 3, wherein the second analysis unit identifies a 3D point cloud data area to be extracted by dividing a 2D internal cross-section of the structural evaluation object into two in the deck direction and extending the 2D internal cross-section in the direction of travel of the structural evaluation object, and extracts the point cloud data contained in the point cloud data area.

5. An analysis method for an analysis device that generates point cloud data of a structural evaluation object, comprising: The analysis device An input step of inputting point cloud data of a structural evaluation target area measured by a laser scanner; a removing step of removing point cloud data other than that of the object to be structurally evaluated from the point cloud data; a step of extracting point cloud data of a portion required for structural evaluation from the point cloud data of the structural evaluation target area after the point cloud data other than that of the structural evaluation object is removed by the removing step; Including, The removal step is an analysis method that executes a step of estimating the cross-sectional line of the structural evaluation object that is hidden by accessories installed inside the structural evaluation object area from the cross-sectional line of the point cloud data, and removing the point cloud data inside the area obtained by extending the estimated cross-sectional line in the direction of travel of the structural evaluation object from the point cloud data of the structural evaluation object area.

6. A program for causing a computer to function as the analysis device according to any one of claims 1 to 4.

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