Tunnel displacement measurement method and tunnel displacement measurement system

Abstract

To provide a method, a device and a system capable of measuring the displacement of the inner space of a tunnel at high speed.SOLUTION: 1) In the initial measurement step, the unevenness feature of the target 100a to 100e is acquired. In addition, the point cloud of the inner surface of the tunnel including the target 100a to 100e is obtained as the first point cloud, and the unevenness feature is extracted from the first point cloud to obtain the first position information of the target 100a to 100e. In the displacement measurement step (2) performed after a predetermined time elapses, a search region including a position specified based on the first positional information and having a larger area than the targets 100a to 100e is set, point cloud of the search region is acquired, and the targets 100a to 100e are extracted from the point cloud of the search region based on the unevenness feature information to acquire the second positional information. Then, the displacement of the inner space of the tunnel is measured based on the difference between the first position information and the second position information.SELECTED DRAWING: Figure 17

Description

[Technical Field]

[0001] The present invention relates to a technique for measuring the subsidence of the top of a tunnel and the displacement of the inner shape of the tunnel during tunnel excavation work. [Background technology]

[0002] In tunnel excavation using the NATM (New Austrian Tunneling Method) method, explosives are used to blast the tunnel face, and after the generated debris is removed, impact testing, support work, primary lining work, and rock bolt installation are carried out. This type of construction work is repeated at intervals of about 1.5 m to advance the tunnel. During tunnel excavation work, displacement measurements (A-measurement) of the natural ground, support members, etc. are periodically carried out to ensure the safety and quality of the work. In A-measurement, internal displacement measurements are carried out to understand the behavior of the surrounding natural ground and the deformation mode of the support, confirm the safety of the construction and the adequacy of the support, and consider the timing of pouring the lining. Conventionally, A-measurement has been carried out by setting control cross sections at specified intervals and measuring the coordinates of targets set on the top or side walls of the tunnel at the control cross sections using a distance measuring device such as a total station (see, for example, Patent Document 1).

[0003] A measurement system uses a 3D laser scanner to measure the shape of a tunnel wall, with the aim of measuring the displacement of the tunnel wall, since the displacement of the surrounding wall can be predicted based on the displacement at the location where a target is installed. For example, Patent Document 2 discloses a method for measuring displacement inside a tunnel, in which multiple targets are installed on the tunnel wall, the shape of the tunnel wall including the targets is measured using a 3D laser scanner, and the cross-sectional shape data of the tunnel at the same location is compared based on the coordinates of the targets to track the displacement of the tunnel (see Patent Document 2). However, installing multiple targets on the tunnel wall has problems such as complicated installation work and high target costs.

[0004] Therefore, a technology is known that can measure tunnel interior displacement without using a target by using scan data from a 3D laser scanner to determine interior displacement at countless points (see Patent Document 3). This method is said to enable easy and efficient measurement of interior displacement, as it does not require the work of attaching a target to the measurement cross section. However, the tunnel interior displacement measurement method of Patent Document 3 has a problem in that it is difficult to process at high speed because it determines interior displacement at countless points measured by a 3D laser scanner. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] Japanese Patent Application Laid-Open No. 2004-170164 [Patent Document 2] Japanese Patent Application Laid-Open No. 2014-002027 [Patent Document 3] Japanese Patent Application Laid-Open No. 2012-058167 Summary of the Invention [Problem to be solved by the invention]

[0006] In view of the above, an object of the present invention is to provide a method, an apparatus, and a system that can measure the displacement inside a tunnel at high speed. [Means for solving the problem]

[0007] After extensive research, the inventors discovered that, rather than using a 3D laser scanner to perform surface measurements, simple and fast displacement measurement is possible by applying point cloud data obtained by a 3D laser scanner to point measurement technology.

[0008] In other words, the tunnel displacement measurement method of the present invention is a method of setting a target and measuring the displacement of the interior of a tunnel over time using point cloud data of the tunnel's inner surface acquired by a 3D laser scanner, and is characterized by comprising 1) an initial measurement step and 2) a displacement measurement step, wherein the 1) initial measurement step includes acquiring unevenness feature data that are the unevenness features of the target, acquiring point cloud data of the tunnel's inner surface including the target as first point cloud data, extracting the unevenness feature data from the first point cloud data to obtain first position information of the target, and the 2) displacement measurement step, which is carried out after a predetermined time has elapsed, includes setting a search area that is larger in area than the target and includes a position identified based on the first position information, acquiring point cloud data of the search area, extracting the target from the point cloud data of the search area based on the unevenness feature data to obtain second position information, and measuring the displacement of the interior of the tunnel based on the difference between the first position information and the second position information. Alternatively, 1) the initial measurement step includes acquiring point cloud data of the inner surface of the tunnel as first point cloud data, cutting out a predetermined area of ​​the inner surface of the tunnel as a target from the first point cloud data, extracting unevenness feature data that is the unevenness feature of the target, and registering first position information of the target and the unevenness feature data, and is carried out after a predetermined time has elapsed.2) The displacement measurement step includes setting a search area that includes a position identified based on the first position information and has a larger area than the target, acquiring point cloud data of the search area, extracting a target from the point cloud data of the search area based on the unevenness feature data to acquire second position information, and measuring the displacement inside the tunnel based on the difference between the first position information and the second position information.

[0009] In this way, by limiting the comparison target to the target range rather than using all of the acquired point cloud data for displacement measurement, rapid processing can be achieved.

[0010] The 1) initial measurement step and the 2) displacement measurement step each include the following steps.

[0011] 1) Initial measurement step 1-A) Scanner coordinate acquisition step to acquire the position coordinates of the 3D laser scanner. 1-B) A first point cloud data acquisition step of acquiring point cloud data of the sprayed concrete surface inside the tunnel as first point cloud data. 1-C) A pseudo target setting step in which at least three regions are cut out from the first point cloud data and set as pseudo targets. 1-D) A first unevenness feature data extraction step of extracting unevenness features based on the plane of the pseudo target as first unevenness feature data. 1-E) A first registration step of registering the position coordinates of the pseudo target, which is the first position information, and the first unevenness feature data in association with the position coordinates of the three-dimensional laser scanner.

[0012] 2) Displacement measurement step 2-A) A second point cloud data acquisition step of acquiring point cloud data of the sprayed concrete surface as second point cloud data. 2-B) A search area setting step for setting a search area from the second point cloud data based on the position coordinates of the pseudo target. 2-C) A second unevenness feature data extraction step of extracting unevenness features based on the plane of the pseudo target from the search region as second unevenness feature data. 2-D) A pseudo target identification step of identifying the position coordinates of a pseudo target, which is second position information, based on the similarity between the concave-convex feature of the first concave-convex feature data and the partial concave-convex feature of the second concave-convex feature data. 2-E) A second registration step in which the position coordinates of the identified pseudo target are registered in relation to the position coordinates of the 3D laser scanner. 2-F) A displacement measurement step for measuring the displacement inside the tunnel based on the changes in the position coordinates of the pseudo targets set in the initial measurement step and the pseudo targets identified in the displacement measurement step.

[0013] By using a pseudo target, it is possible to measure the displacement of the tunnel's inner shape inexpensively, easily, and with high accuracy without using an existing target (prism). Generally, for measurements of crown settlement and interior displacement, targets are set up every 10 to 30 meters, and measurements are taken as frequently as twice a day, or as frequently as once a week. When a new pseudo target is set up, 1) the initial measurement step is carried out at the location where the new pseudo target is to be set up, and 2) the displacement measurement step is carried out at locations where initial measurements have already been completed. By carrying out measurements in this manner repeatedly, the shape displacement of the tunnel interior can be measured accurately.

[0014] 1-A) The scanner coordinate acquisition step can use a wide variety of methods to acquire the position coordinates of the 3D laser scanner inside the tunnel. For example, the position coordinates of the 3D laser scanner can be acquired using a laser scanner target attached to a point whose position coordinates are known. If the 3D laser scanner has a surveying instrument function, absolute coordinates or tunnel coordinates can be acquired using that function. The acquired position coordinates can be absolute coordinates (global coordinates) or tunnel coordinates (local coordinates).

[0015] Instead of regarding all of the point cloud data acquired in 1-B) first point cloud data acquisition step as countless targets, 1-C) pseudo target setting step cuts out three or more areas from the point cloud data and sets them as pseudo targets, thereby limiting the locations where displacement is measured and improving the processing speed of displacement measurement. In order to improve the processing speed while maintaining the measurement accuracy, it is preferable that the cut-out areas be three to five locations per measurement cross section. Because the sprayed concrete surface inside the tunnel has minute irregularities, it is possible to extract unique areas from point cloud data. Here, "sprayed concrete surface inside the tunnel" refers to the areas where concrete was sprayed onto the tunnel wall and shoring after blasting. The term "sprayed concrete surface" does not have a strict meaning, and is intended to include areas where the concrete was not sufficiently sprayed. Therefore, it also includes rock bolts that were fixed after the concrete was sprayed. A LiDAR (Light Detection and Ranging) scanner is preferably used as the 3D laser scanner. Each area used as a pseudo target is cut out in a predetermined shape, such as a polygonal shape like a square, a circle, or an ellipse, for example, a roughly square shape measuring 150 mm in length and width.

[0016] 1-E) The position coordinates of the pseudo target registered in the first registration step are preferably the first point cloud data included in the pseudo target, but may also be the center of gravity, normal line, or plane data, which will be described later.

[0017] In the tunnel displacement measurement method of the present invention, the 1-C) pseudo target setting step preferably includes a first extraction step of extracting an area, a first centroid calculation step of calculating the center of gravity of the pseudo target based on point cloud data included in the extracted area, a first normal calculation step of calculating the normal of the pseudo target based on the point cloud data and the centroid, and a first planarization step of converting the pseudo target into planar data based on the centroid and the normal. The normal can be calculated using a known method for processing point cloud data, for example, as a line segment passing through the centroid coordinates from the eigenvector of the covariance matrix of the point cloud data. By calculating the centroid and normal and performing planarization processing rather than using the point cloud data as a comparison target, feature data extraction becomes easier, enabling high-speed and high-accuracy identification of the pseudo target and displacement measurement.

[0018] In the tunnel displacement measurement method of the present invention, 1-D) the first unevenness feature data extraction step preferably calculates cross-sectional data from the relative positions of each point in the normal direction for at least one cross section in the planar data. Calculating the cross-sectional data makes it easier to compare the unevenness feature data. It is preferable to calculate a plurality of cross-sectional data, more preferably a plurality of cross-sectional data with different orientations.

[0019] In the tunnel displacement measurement method of the present invention, the 2-B) search area setting step preferably includes a second cutting out step of cutting out the search area from the second point cloud data based on the position coordinates of the pseudo target set in the initial measurement step, a second centroid calculation step of calculating the centroid of the search area based on the second point cloud data included in the cut-out search area, a second normal calculation step of calculating a normal to the search area based on the second point cloud data and the centroid, and a second planarization step of converting the search area into planar data based on the centroid and the normal. By including these steps, it becomes easier to identify the pseudo target.

[0020] In the tunnel displacement measurement method of the present invention, it is preferable that the second unevenness feature data extraction step (2-C) calculates cross-sectional data from the relative positions of each point in the normal direction for at least one cross section in the planar data. This makes it easy to identify false targets by comparing the first unevenness feature data with the second unevenness feature data.

[0021] In the tunnel displacement measurement method of the present invention, it is preferable that the 2-D) pseudo target identification step compares the cross-sectional data calculated in the 1-D) first unevenness feature data extraction step with the cross-sectional data calculated in the 2-C) second unevenness feature data extraction step to identify a pseudo target based on the similarity in the relative positions of each point in the normal direction.

[0022] In the tunnel displacement measuring method of the present invention, the second cutting-out step may be 1) cutting out a region having an area of ​​approximately four times or less the area of ​​the false target set in the initial measurement step, with the position coordinates of the false target set in the initial measurement step as the center. In the second extraction step, a search area is extracted from the second point cloud data based on the position coordinates of the pseudo target registered in the first registration step, but since there is a possibility that the pseudo target will move or change in shape after the initial measurement, it is necessary to provide a predetermined margin when extracting the area. Therefore, by setting the length and width of the pseudo target to approximately double and extracting an area with an area of ​​approximately four times or less, it is possible to prevent the pseudo target from becoming unidentifiable due to movement or change in shape of the pseudo target.

[0023] In the tunnel displacement measurement method of the present invention, the change in the position coordinates of the pseudo target in the displacement measurement step 2-F is preferably a change in the position coordinates of the first point cloud data and the second point cloud data contained in the pseudo target. The change in position coordinates refers to a change in the three-dimensional position coordinates of each point. By comparing only the point cloud data contained in the pseudo target rather than all of the acquired point cloud data, high-speed and high-precision displacement measurement can be achieved. Furthermore, the displacement of the tunnel's internal shape may be measured based on changes in the center of gravity, normal, and plane data, or the displacement may be measured based on changes in the first unevenness feature data and the second unevenness feature data.

[0024] In the tunnel displacement measuring method of the present invention, the position coordinates of the pseudo target may be absolute coordinates or tunnel coordinates.

[0025] In the tunnel displacement measurement method of the present invention, pseudo targets are preferably set in at least one of the following areas: positions where measurement lines A, B, and C can be measured, and positions where measurement line D can be measured, during tunnel excavation work using the NATM (New Austrian Tunneling Method) method, based on the position or shape of the tunnel interior, supports, or rock bolts. Setting pseudo targets in such areas makes it easy to perform measurement A. The setting may be performed automatically based on the position or shape of the tunnel interior, supports, or rock bolts, or manual setting may be accepted. Furthermore, pseudo targets may also be set in areas other than these areas, for example, by detecting automatically or visually by an operator, areas where the tunnel interior surface has significant unevenness.

[0026] It is also desirable that the target be a fixing plate for a rock bolt installed on the inner surface of the tunnel. It is also desirable that the target be a steel support installed on the inner surface of the tunnel. This eliminates the need to install a dedicated target for measurement. Furthermore, by having protrusions installed at multiple locations in the vertical direction, the target can accurately determine horizontal and vertical displacements as changes in position coordinates due to the characteristic uneven shape caused by the protrusions on the surface of the target. This makes it possible to measure the displacement of the tunnel's interior shape inexpensively, simply, and with high accuracy. In other words, the target can be any metal object installed on the inner surface of the tunnel and exposed to the inner surface of the tunnel. It is preferable that the exposed part of the metal object has an uneven shape.

[0027] 1) In the initial measurement step, the imaging results of the target are input to the tunnel displacement measurement device that executes the initial measurement step and the displacement measurement step in order to obtain the unevenness feature data of the target.

[0028] The tunnel displacement measurement device of the present invention is a device that uses point cloud data of the tunnel's inner surface acquired by a 3D laser scanner to set a target and measure the displacement of the tunnel's interior over time, and is characterized in that it comprises an initial measurement unit and a displacement measurement unit, and the initial measurement unit acquires unevenness feature data that is the unevenness features of the target, acquires point cloud data of the tunnel's inner surface including the target as first point cloud data, extracts the unevenness feature data from the first point cloud data, and obtains first position information of the target, the displacement measurement unit sets a search area that is larger in area than the target and includes a position identified based on the first position information, acquires point cloud data of the search area, extracts the target from the point cloud data of the search area based on the unevenness feature data, and obtains second position information, and measures the displacement of the tunnel's interior based on the difference between the first position information and the second position information. The initial measurement unit receives input of the imaging results of the target in order to acquire unevenness feature data of the target.

[0029] Alternatively, the initial measurement unit acquires point cloud data of the inner surface of the tunnel as first point cloud data, cuts out a predetermined area of ​​the inner surface of the tunnel as a target from the first point cloud data, extracts unevenness feature data that is the unevenness features of the target, and registers first position information and the unevenness feature data of the target; the displacement measurement unit sets a search area that includes a position identified based on the first position information and is larger in area than the target, acquires point cloud data of the search area, extracts the target from the point cloud data of the search area based on the unevenness feature data, and acquires second position information; and measures the displacement inside the tunnel based on the difference between the first position information and the second position information. The initial measurement unit and the displacement measurement unit each include the following means.

[0030] 1) The initial measurement part 1-a) A scanner coordinate acquisition means for acquiring the position coordinates of a three-dimensional laser scanner. 1-b) A first point cloud data acquisition means for acquiring point cloud data of the surface of the sprayed concrete inside the tunnel as first point cloud data. 1-c) A pseudo target setting means for cutting out at least three regions from the first point cloud data and setting them as pseudo targets. 1-d) A first unevenness feature data extracting means for extracting unevenness features based on the plane of the pseudo target as first unevenness feature data. 1-e) A first registration means for registering the position coordinates of the pseudo target, which is the first position information, and the first unevenness feature data in association with the position coordinates of the three-dimensional laser scanner. 2) Displacement measurement section 2-a) A second point cloud data acquisition means for acquiring point cloud data of the sprayed concrete surface as second point cloud data. 2-b) A search area setting means for setting a search area from the second point cloud data based on the position coordinates of the pseudo target. 2-c) A second unevenness feature data extraction means for extracting unevenness features based on the plane of the pseudo target from the search region as second unevenness feature data. 2-d) A pseudo target identification means for identifying the position coordinates of a pseudo target, which is second position information, based on the similarity between the unevenness features of the first unevenness feature data and the partial unevenness features of the second unevenness feature data. 2-e) A second registration means for registering the position coordinates of the identified pseudo target in relation to the position coordinates of the three-dimensional laser scanner. 2-f) A displacement measurement means for measuring the displacement inside the tunnel based on changes in the position coordinates of the pseudo target set in the initial measurement means and the pseudo target identified in the displacement measurement means.

[0031] The tunnel displacement measurement system of the present invention comprises a tunnel displacement measurement device and a metal target that is installed on the inner surface of the tunnel and exposed on the inner surface of the tunnel. If the tunnel is constructed using the NATM method, the target is a rock bolt anchor plate or a steel support. If the tunnel is constructed using the shield method, the target is a gripping metal or joint metal installed on the inner surface of a tunnel segment piece. [Effects of the Invention]

[0032] The tunnel displacement measurement method, device, and system of the present invention have the advantage of being able to measure the displacement inside a tunnel at high speed. [Brief explanation of the drawings]

[0033] [Figure 1] Functional block diagram of the tunnel displacement measurement device [Figure 2] Image of the tunnel displacement measurement device [Figure 3] Schematic flow diagram of tunnel displacement measurement method [Figure 4] Diagram of the initial measurement step and displacement measurement step (1) [Figure 5] Diagram of the initial measurement step and displacement measurement step (2) [Figure 6] Initial measurement flow chart [Figure 7] Image of the placement of pseudo targets [Figure 8] Pseudo target setting flow chart [Figure 9] Illustration of pseudo target setting steps [Figure 10] Image of pseudo target and feature data [Figure 11] Image of feature data extraction [Figure 12] Displacement measurement flow chart [Figure 13] Search area setting flow chart [Figure 14] Search area setting image [Figure 15] Illustration of the pseudo-target identification step (1) [Figure 16] Illustration of the pseudo target identification step (2) [Figure 17] Image of the tunnel displacement measurement system configuration [Figure 18] Image of a rock bolt plate [Figure 19] Target image [Figure 20] Schematic diagram of the relationship between the number of protrusions and measurement accuracy [Figure 21]Image of the protrusion [Figure 22] Image of the tunnel displacement measurement system configuration [Figure 23] Image of the protrusions of the steel support DETAILED DESCRIPTION OF THE INVENTION

[0034] An example of an embodiment of the present invention will be described in detail below with reference to the drawings. Note that the scope of the present invention is not limited to the following examples and illustrated examples, and many modifications and variations are possible. [Example]

[0035] FIG. 1 shows a functional block diagram of a tunnel displacement measurement device. FIG. 2 shows a configuration image of the tunnel displacement measurement device. As shown in FIG. 1, the tunnel displacement measurement device 1 comprises an initial measurement unit 2 and a displacement measurement unit 3. The initial measurement unit 2 comprises a scanner coordinate acquisition means 21, a first point cloud data acquisition means 22, a pseudo target setting means 23, a first unevenness feature data extraction means 24, and a first registration means 26. The displacement measurement unit 3 comprises a second point cloud data acquisition means 32, a search area setting means 33, a second unevenness feature data extraction means 34, a pseudo target identification means 35, a second registration means 36, and a displacement measurement means 37. 2, the tunnel displacement measuring device 1 is composed of a LiDAR scanner 4, a computer 5, and scanner targets (11a to 11c), and the LiDAR scanner 4 and the computer 5 are connected by wire or wirelessly. The scanner targets (11a to 11c) are attached to points inside the tunnel 7 whose position coordinates are known. The scanner targets (11a to 11c) can be provided on the wall surface 72 of the tunnel 7, for example.

[0036] The scanner coordinate acquisition means 21 acquires the position coordinates of the 3D laser scanner. A LiDAR scanner 4 is used as the 3D laser scanner. In this embodiment, the scanner coordinate acquisition means 21 acquires the absolute coordinates of the LiDAR scanner 4 using scanner targets (11a to 11c). The first point cloud data acquisition means 22 acquires point cloud data of the sprayed concrete surface (tunnel inner surface) inside the tunnel using the 3D laser scanner. The pseudo target setting means 23 cuts out at least three predetermined areas from the first point cloud data and sets them as pseudo targets (targets). The first unevenness feature data extraction means 24 extracts first unevenness feature data from the pseudo targets. The first registration means 26 registers the position coordinates (first position information) of the pseudo targets and the first unevenness feature data in association with the position coordinates of the 3D laser scanner.

[0037] The second point cloud data acquisition means 32 acquires point cloud data of the sprayed concrete surface inside the tunnel using a 3D laser scanner. The search area setting means 33 sets a search area for a pseudo target (target) from the second point cloud data. The search area includes a position identified based on the position coordinates of the pseudo target (first position information) and is an area larger than the pseudo target. The second unevenness feature data extraction means 34 extracts second unevenness feature data from the point cloud data of the search area. The pseudo target identification means 35 extracts a pseudo target based on the similarity between the first unevenness feature data and the second unevenness feature data, and identifies and acquires its position coordinates (second position information). The second registration means 36 registers the position coordinates of the identified pseudo target in association with the position coordinates of the 3D laser scanner. The displacement measuring means 37 measures the displacement of the tunnel's internal shape based on the change in the position coordinates (the difference between the first position information and the second position information) of the pseudo target set in the initial measurement unit 2 and the pseudo target identified in the displacement measuring unit 3.

[0038] In this embodiment, the LiDAR scanner 4 includes a first point cloud data acquisition means 22 and a second point cloud data acquisition means 32, and the computer 5 includes a pseudo target setting means 23, a first unevenness feature data extraction means 24, a first registration means 26, a second point cloud data acquisition means 32, a search area setting means 33, a second unevenness feature data extraction means 34, a pseudo target identification means 35, a second registration means 36, and a displacement measurement means 37.

[0039] FIG. 3 shows a schematic flow diagram of the tunnel displacement measurement method. As shown in FIG. 3, the tunnel displacement measurement method of this embodiment first performs an initial measurement (step S01: initial measurement step), and then performs displacement measurement (step S02: displacement measurement step). Displacement measurement is performed once a week to twice a day. Specifically, it is determined based on the distance between the measurement position and the tunnel face and the displacement speed of the internal displacement. Displacement measurement is performed repeatedly, and when all displacement measurements are completed (step S03), the displacement measurement is completed. 4 and 5 are explanatory diagrams of the initial measurement step and the displacement measurement step. As shown in FIG. 4 or 5, when the initial measurement step (step S01) is performed for range R2, if the initial measurement step (step S01) has already been completed for range R1 shown in FIG. 5, the initial measurement step (step S01) is performed for range R2, and the displacement measurement step (step S02) is performed for range R1. After a predetermined time has elapsed, if a false target is to be set for a new range R3 as the tunnel excavation work progresses, the initial measurement step (step S01) is performed for range R3, and the displacement measurement step (step S02) is performed for the ranges (R1, R2) for which initial measurement has already been completed. In this way, displacement measurement can be performed repeatedly while increasing the number of false targets.

[0040] (Initial measurement steps) Fig. 6 shows a flow diagram of initial measurement. As shown in Fig. 6, first, the position coordinates of the 3D laser scanner are acquired (step S11: scanner coordinate acquisition step). As described above, in this embodiment, the absolute coordinates of the LiDAR scanner 4 are acquired using the scanner targets (11a to 11c). A three-dimensional laser scanner is used to acquire point cloud data of the sprayed concrete surface inside the tunnel (step S12: first point cloud data acquisition step). In this embodiment, the LiDAR scanner 4 is used to acquire point cloud data relating to the face 71 and wall surface 72 in front of the LiDAR scanner 4. Concrete is sprayed onto the wall surface 72. The range in which the point cloud data is acquired here is not limited to the range set as the pseudo target; for example, as shown in FIG. 5, if point cloud data can be acquired for a range R, point cloud data is acquired for the entire range R.

[0041] At least three regions are extracted from the point cloud data and set as pseudo targets (step S13: pseudo target setting step). In this embodiment, as shown in FIG. 2, five regions are extracted so as to include the measurement cross section 70, and set as pseudo targets (6a to 6e). FIG. 7 shows an image diagram of the arrangement of the pseudo targets. As shown in FIG. 7, the pseudo targets (6a, 6e) are set at positions where the D measurement line can be measured using the pseudo target 6a and the pseudo target 6e. In addition, the pseudo targets (6b to 6d) are set at positions where the A measurement line can be measured using the pseudo target 6b and the pseudo target 6c, the B measurement line can be measured using the pseudo target 6c and the pseudo target 6d, and the C measurement line can be measured using the pseudo target 6b and the pseudo target 6d.

[0042] Here, a method for setting a false target will be described. FIG. 8 shows a flow diagram for setting a false target. FIG. 9 is an explanatory diagram of the false target setting step, in which (1) shows area extraction, (2) shows calculation of the center of gravity, (3) shows calculation of normals, and (4) shows an image of planarization. As shown in FIG. 8, in the false target setting step (step S13), first, an area is extracted from the first point cloud data (step S131: first extraction step). FIG. 9(1) shows a point cloud 8 in the extracted area. Next, as shown in FIG. 9(2), the center of gravity G of the false target is calculated based on the point cloud data included in the extracted area (step S132: first center of gravity calculation step). The normal of the false target is calculated based on the point cloud data and the center of gravity (step S133: first normal calculation step). The normal can be calculated using a known method for processing point cloud data, for example, as a line segment passing through the center of gravity coordinates from the eigenvectors of the covariance matrix of the point cloud data. 9(3) illustrates the normal direction N. Finally, the pseudo target is converted into plane data based on the center of gravity and the normal (step S134: first planarization step). The planarized plane P is illustrated in FIG. 9(4).

[0043] Next, as shown in Fig. 6, first unevenness feature data is extracted from the pseudo target (step S14: first unevenness feature data extraction step). In the first unevenness feature data extraction step, cross-sectional data is calculated from the relative positions of each point in the normal direction N for at least one cross section in the plane data. FIG. 10 is an illustration of a false target and unevenness feature data, where (1) shows the false target set state and (2) shows the unevenness feature data extracted state. FIG. 11 is an illustration of the unevenness feature data extraction. As shown in FIG. 10(1), a false target 6 is set for a point cloud 80 acquired regarding a wall surface 72, and then, as shown in FIG. 11, multiple cross-sectional data are calculated. Specifically, in this embodiment, cross-sectional data relating to vertical cross-sections (C1-C3) of the false target 6 and cross-sectional data relating to horizontal cross-sections (C4-C6) are calculated. The vertical direction corresponds, for example, to the circumferential direction of the tunnel cross-section perpendicular to the tunnel axis direction, and the horizontal direction corresponds, for example, to the tunnel axis direction. Unlike this embodiment, more cross-sectional data may be calculated, or cross-sectional data in a diagonal direction may be calculated. The diagonal direction is a direction inclined relative to the vertical and horizontal directions.

[0044] The position coordinates of the pseudo target and the first unevenness feature data are registered in association with the position coordinates of the 3D laser scanner (step S15: first registration step). In this embodiment, the position coordinates of the pseudo target to be registered are the absolute coordinates of the point cloud 8 in the pseudo target (6a to 6e), the center of gravity, normal, and plane data based on the absolute coordinates of the LiDAR scanner 4, but it is also possible to register only the absolute coordinates of the point cloud 8 in the pseudo target (6a to 6e).

[0045] (Displacement measurement step) Fig. 12 shows a displacement measurement flow diagram. As shown in Fig. 12, a 3D laser scanner is used to acquire point cloud data of the surface of the sprayed concrete inside the tunnel (step S21: second point cloud data acquisition step). The method of acquiring the point cloud data is the same as the first point cloud data acquisition step (step S12).

[0046] Next, a search area for a pseudo target is set from the second point cloud data (step S22: search area setting step). Fig. 13 shows a search area setting flow diagram. Fig. 14 shows an image diagram of setting the search area 60, and Figs. 15 and 16 show explanatory diagrams of the pseudo target identification step. As shown in Figures 13 and 14(1), first, based on the position coordinates 60a of the pseudo target 6 set in the initial measurement step (step S01), a search area 60 is extracted from the second point cloud data 81 (step S221: second extraction step). Next, second point cloud data included in the cut-out search area 60 is acquired, and the center of gravity of the search area 60 is calculated based on the point cloud data (step S222: second center of gravity calculation step). Based on the second point cloud data and the center of gravity, a normal to the search area 60 is calculated (step S223: second normal calculation step). Based on the center of gravity and the normal, the search area 60 is made into planar data (step S224: second planarization step). This processing is similar to the pseudo target setting step shown in Figure 9. Figure 14(1) shows the state in which the search area 60 has been made into planar data.

[0047] Second unevenness feature data is extracted from the search area 60 (step S23: second unevenness feature data extraction step). In FIG. 14(2), the second unevenness feature data is extracted from the vertical cross section (C 10 ~C 30 ) and cross-sectional data for transverse sections (C 40 ~C 60 ) is an image in which cross-sectional data for As shown in FIG. 15(1), the false target 6 is extracted and its position coordinates are identified based on the similarity between the first unevenness feature data of the false target 6 and the second unevenness feature data of the search area 60 (step S24: false target identification step). In this embodiment, as shown in FIG. 15(2), the cross section C 20 and section C2, and section C 50It is determined that the similarity between the cross section C1 and the cross section C5 is high. Then, as shown in Fig. 16(1), from the position coordinates of the area (A1, A2) with high similarity, the false target 6 is extracted as shown in Fig. 16(2), and its position coordinates are identified and acquired.

[0048] The position coordinates of the identified pseudo target are registered in association with the position coordinates of the three-dimensional laser scanner (step S25: second registration step). The method of registering the coordinates is the same as the first registration step (step S15). Based on the changes in the position coordinates of the pseudo targets set in the initial measurement step and the pseudo targets identified in the displacement measurement step, the displacement of the tunnel's internal shape is measured (step S26: displacement measurement step). In this embodiment, the point cloud data 8 of the pseudo targets 6 shown in Figure 10(2) is compared with the point cloud data 8a of the pseudo targets 6 shown in Figure 16(2) to measure the displacement of the tunnel's internal shape. [Example]

[0049] In Example 1, point cloud data (pseudo targets) are used as targets, but the targets may be actual target members installed inside the tunnel. However, to eliminate the effort of installing targets, it is preferable that the targets are not dedicated to measurement, but are also used as other members that are normally installed inside the tunnel.

[0050] One example is the tunnel displacement measurement system 10 shown in Fig. 17, which includes a tunnel displacement measurement device 1a as well as targets 100a-100e installed on the wall surface 72 of the tunnel 7. The targets 100a-100e are installed at the same positions as the pseudo targets 6a-6e in each of ranges R1, R2, R3, ... (see Fig. 5) in the tunnel axial direction.

[0051] Furthermore, a LiDAR scanner 4 is provided along each of the wall surfaces 72 on both sides of the tunnel width direction, and each LiDAR scanner 4 acquires point cloud data of the wall surface 72 opposite to the wall surface 72 on which the LiDAR scanner 4 is installed. The tunnel width direction is a direction perpendicular to the tunnel axis direction on a plane. In Figure 17, the tunnel axis direction is indicated by symbol A, and the tunnel width direction is indicated by symbol B.

[0052] 18 is a diagram showing a target 100a. In this example, a plate for anchoring a rock bolt 200 is used as the target 100a. The rock bolt 200 is driven into the natural ground behind the wall surface 72 of the tunnel 7, and the plate for the rock bolt 200, i.e., the target 100a, is placed on the sprayed concrete on the wall surface 72. The end of the rock bolt 200 protrudes from the outer surface of the target 100a, and a nut 210 is tightened onto the protruding portion.

[0053] The target 100a is a plate-shaped metal object having protrusions 110 on its outer surface, giving it an uneven texture. The protrusions 110 are horizontally continuous ridges, arranged in parallel in multiple rows, one above the other, within the target 100a. More specifically, two rows of protrusions 110 are arranged on the top of the target 100a and two rows on the bottom, and a through-hole (not shown) for passing the end of the rock bolt 200 is provided between the two rows of protrusions 110 on the top and the two rows of protrusions 110 on the bottom. The cross section of the protrusions 110 is rectangular.

[0054] The other targets 100b to 100e have the same shape, and only the postures at the time of installation differ depending on the positions of the targets 100b to 100e. For example, the target 100c at the top of the tunnel 7 shown in Fig. 17 is placed with its plate surface in the horizontal direction, and the protrusions 110 are arranged in multiple rows at intervals in the tunnel width direction B.

[0055] The tunnel displacement measurement device 1a functions in substantially the same way as the tunnel displacement measurement device 1 described in Fig. 1. However, instead of the pseudo target setting means 23 and the first unevenness feature data extraction means 24, the initial measurement unit 2 includes an unevenness feature data acquisition means that accepts input of imaging results of targets 100a-100e captured in advance using a separate imaging device (not shown), such as a 3D laser scanner, and acquires unevenness feature data representing the unevenness features of the targets 100a-100e from the imaging results, and a position information acquisition means that extracts unevenness feature data from point cloud data (first point cloud data) of the tunnel inner surface including the targets 100a-100e and acquires the position coordinates (first position information) of the targets 100a-100e. The first registration means 26 registers the position information and unevenness feature data of the targets 100a-100e.

[0056] The displacement measurement unit 3 is provided with a target identification means, instead of the pseudo target identification means 35, that extracts targets 100a-100e from the point cloud data of the search area 60 and identifies and acquires their position coordinates (second position information). The search area 60 includes positions identified based on the position coordinates (first position information) of the targets 100a-100e acquired by the position information acquisition means, and is an area larger than the targets 100a-100e. The second registration means 36 and displacement measurement means 37 perform similar processing on the area of ​​the targets 100a-100e instead of the pseudo targets 6a-6e.

[0057] The initial measurement flow in this embodiment is basically the same as that described in FIG. 6. However, in this embodiment, the computer 5 accepts input of imaging results obtained by previously imaging the targets 100a-100e using a separate imaging device (not shown) and acquires in advance unevenness feature data of the targets 100a-100e from the imaging results. Then, instead of performing the pseudo target setting step (step S13) and the first unevenness feature data extraction step (step S14) of FIG. 6, unevenness feature data is extracted from the point cloud data of the tunnel inner surface including the targets 100a-100e acquired in the first point cloud data acquisition step (step S12) to acquire the position coordinates of the targets 100a-100e. Thereafter, in a first registration step (step S15), the position coordinates and unevenness feature data of the targets 100a-100e are registered.

[0058] Since the targets 100a to 100e have protrusions 110, in the unevenness feature data, the unevenness features due to the protrusions 110 appear in the vertical cross-sectional data (see symbols C1 to C3 in FIG. 11), and the height of the convex portions and the depth of the concave portions in the unevenness features appear in the horizontal cross-sectional data (see symbols C4 to C6 in FIG. 11). Note that it is desirable to select a cross section for calculating the cross-sectional data at a position that avoids the end of the lock bolt 200 and the nut 210.

[0059] The displacement measurement flow in this embodiment is basically the same as the flow in the first embodiment described with reference to FIG. 12. However, in this embodiment, instead of identifying the position coordinates of the pseudo targets 6a to 6e in the pseudo target identification step (step S24) of FIG. 12, the position coordinates (second position information) of the regions of the targets 100a to 100e are identified. In the target identification step, based on the similarity between the unevenness feature data of the targets 100a to 100e and the unevenness feature data of the search region 60, a region having the same unevenness feature as the targets 100a to 100e is extracted as the region of the targets 100a to 100e, and its position coordinates are identified and acquired. The target identification method may be the same template matching method as in the first embodiment, but is not limited thereto. Any known matching method may be applied as long as it searches for the unevenness feature due to the protrusions 110 of the targets 100a to 100e within the search region 60.

[0060] In this embodiment, the protrusions 110 are disposed on the outer surfaces of the targets 100a to 100e, thereby enabling accurate position identification for these targets 100a to 100e. That is, as shown in Fig. 19(a), if the surface of the target 100a were smooth, there would be no distinctive features in the shape of the interior of the tunnel including the target 100a, but when the protrusions 110 are formed on the target 100a as in this embodiment, distinctive irregularities occur in the shape of the interior of the tunnel including the target 100a, as shown by the solid line in Fig. 19(b).

[0061] In this embodiment, even when the target 100a is displaced horizontally or vertically in the tunnel width direction B, the horizontal and vertical positions of the target 100a after displacement along the tunnel width direction B can be accurately determined by determining the location of the unevenness feature. In particular, if the surface of the target 100a is smooth as shown in FIG. 19(a), even when the target 100a is displaced vertically as indicated by arrow a (the displaced target 100a is shown by a dashed line), the shape of the interior of the tunnel remains almost unchanged, making it difficult to determine the vertical displacement of the target 100a. In contrast, in this embodiment, as shown in FIG. 19(b), when the target 100a is displaced vertically, the position of the convex portion due to the protrusion 110 clearly changes, thereby making it easy to determine the vertical displacement of the target 100a.

[0062] In the second registration step (step S25) and the displacement measurement step (step S26), processing is performed on the areas of the targets 100a to 100e instead of the pseudo targets 6a to 6e. In the displacement measurement step (step S26), the vertical displacement of the targets 100a to 100e, i.e., the vertical displacement inside the tunnel, and the horizontal displacement of the targets 100a to 100e in the tunnel width direction B, i.e., the horizontal displacement inside the tunnel in the tunnel width direction B, can be calculated from the change in the position coordinates of the targets 100a to 100e (the difference between the first position information and the second position information).

[0063] In this way, in this embodiment, by using the plates of the rock bolt 200 as the targets 100a to 100e, there is no need to install a dedicated measurement target in the tunnel 7, simplifying the measurement work. Also, some dedicated measurement targets use prisms or mirrors, which may be damaged during blasting of the tunnel cutting edge, but the targets 100a to 100e (plates of the rock bolt 200) of this embodiment do not have this risk. Therefore, it is also possible to measure displacement immediately after blasting.

[0064] Furthermore, since the target 100a has protrusions 110 on its outer surface, the horizontal and vertical displacements of the area of ​​the target 100a can be measured with high accuracy due to the unevenness of the outer surface caused by the protrusions 110. This also applies to the other targets 100b to 100e.

[0065] Furthermore, because the protrusions 110 of target 100a are ridges arranged in multiple rows, vertically and horizontally, the vertical displacement of the area of ​​target 100a can be measured with greater accuracy. This is also true for targets 100b, 100d, and 100e. For target 100c at the top of tunnel 7, the protrusions 110 are arranged in multiple rows at intervals in the tunnel width direction B, allowing for more accurate measurement of horizontal displacement in the tunnel width direction B.

[0066] The shapes of the targets 100a to 100e are not limited to those described above. For example, in the example of FIG. 18, the targets 100a to 100e are provided with four protrusions 110, but the number of protrusions 110 is not particularly limited. However, in terms of accuracy, it is desirable to provide three or more protrusions 110. FIG. 20 shows a simple diagram of the results of the inventor's study on the relationship between the number of protrusions 110 and measurement accuracy, and the results showed that accuracy improved when there were three or more protrusions 110.

[0067] Furthermore, although the protrusions 110 of the target 100a are ridges that are continuous in the horizontal direction, the shape of the protrusions 110 is not limited to this. For example, as shown in target 100a' in Fig. 21, which is a modification of the target 100a in Fig. 18, the protrusions 110' may be provided discretely at intervals in the vertical and horizontal directions. However, if the protrusions 110 are continuous in the horizontal direction, it is easier to set a large number of vertical cross-sectional data (see symbols C1 to C3 in Fig. 11) in which the unevenness characteristics caused by the protrusions 110 appear, which contributes to improving measurement accuracy.

[0068] In addition, the protrusion height of the protrusions 110 can be freely set taking into consideration measurement accuracy and handling. For example, if the protrusion height of the protrusions 110 is increased, the convex portions will appear more clearly in the cross-sectional data, improving measurement accuracy, but the protrusions 110 will be more susceptible to damage during transportation and installation, and more space will be required for storage. It is also possible to change the pattern of the protrusions 110 for each target, making it possible to identify each target by that pattern.

[0069] Alternatively, as shown in the tunnel displacement measurement system 10a in Fig. 22, a steel support 73 (metalwork) installed inside the tunnel may be used as a substantial target member installed inside the tunnel as targets 100a-100e. In this case, similar to the above, a plate having a protrusion 110 may be attached to the outer surface of the steel support 73, and the area including the protrusion 110 of the steel support 73 may be used as targets 100a-100e, or, as shown in the target 100a in Fig. 23, the steel support 73 itself may have the protrusion 110 on its outer surface. In this case, the target 100a is also the area including the protrusion 110 of the steel support 73.

[0070] In this embodiment, five targets 100a to 100e are provided per measurement cross section 70, but some of them may be omitted. For example, 100b to 100d may be omitted, and measurements may be performed using the above-mentioned false targets at these positions. [Example]

[0071] The tunnel displacement measurement systems 10, 10a of Example 2 are displacement measurement systems mainly for mountain tunnels and tunnels constructed using the NATM method. Instead, in this example, an example of a displacement measurement system mainly for urban tunnels and tunnels constructed using the shield method will be described.

[0072] In shield tunnels (shield tunnels), the displacement inside the lining constructed by the shield tunneling method is measured. In shield tunnels, multiple segment pieces are connected in the tunnel circumferential direction to construct a ring-shaped lining, called a segment ring, in the excavated hole excavated by a shield tunneling machine. Furthermore, multiple segment rings are connected in the tunnel axial direction to construct a lining inside the excavated hole.

[0073] The outer surface (outside) of the segment piece faces the natural ground in the excavation hole, and the inner surface (inside) faces the interior space. The tunnel displacement measurement system of this embodiment measures the displacement of the inner peripheral surface of the segment using the tunnel displacement measurement device 1a described above. A gripping hardware that is gripped by the erector of the shield excavation machine is provided exposed on the inner surface (inside) of the segment piece. The gripping hardware has a recess into which the erector's gripping tool is inserted, and the gripping hardware itself has an uneven feature. In addition, adjacent segment pieces in the tunnel circumferential direction are connected in the tunnel circumferential direction via joint hardware provided at the tunnel circumferential end of each segment piece. The joint hardware also has an uneven feature like the gripping hardware.

[0074] In this embodiment, instead of the rock bolt anchoring plates and steel supports that are the target elements installed on the tunnel inner surface in embodiment 2, metal objects that are installed on the inner surface of the segment pieces and have uneven features on the parts exposed to the tunnel inner surface are used as target elements. For example, gripping metal objects and joint metal objects are metal objects that have uneven features. In embodiment 3, the displacement inside the tunnel can also be measured using the same tunnel displacement measurement method as in embodiment 2. [Industrial Applicability]

[0075] INDUSTRIAL APPLICABILITY The present invention is useful as a technique for measuring the subsidence of the tunnel crown and the displacement of the inner shape during tunnel excavation work. [Explanation of symbols]

[0076] 1,1a Tunnel displacement measuring device 2 Initial measurement section 3. Displacement measurement section 4. LiDAR Scanner 5. Computer 6,6a~6e Pseudo Target 7. Tunnel 8, 8a, 80, 81 Point cloud (data) 10,10a Tunnel displacement measurement system 11a~11c Scanner Targets 21 Scanner coordinate acquisition means 22 First point cloud data acquisition means 23 Pseudo-target setting method 24 First unevenness feature data extraction means 26 First registration method 32 Second point cloud data acquisition means 33 Search area setting means 34 Second unevenness feature data extraction means 35 False target identification method 36 Secondary registration method 37 Displacement measuring means 60 Search area 70 Measurement cross section 71 Face 72 Wall 100a~100e,100a' target 110,110' protrusion

Claims

1. A method for measuring the displacement of a tunnel interior over time by setting a target using point cloud data of the tunnel interior surface acquired by a 3D laser scanner, comprising: It consists of an initial measurement step and a displacement measurement step. 1) The initial measurement step is acquiring unevenness feature data that is unevenness features of the target; acquiring point cloud data of an inner surface of a tunnel including the target as first point cloud data, and extracting the unevenness feature data from the first point cloud data to acquire first position information of the target; 2) Displacement measurement step, which is carried out after a predetermined time has elapsed, setting a search area that includes a position identified based on the first position information and has an area larger than that of the target, acquiring point cloud data of the search area, and extracting the target from the point cloud data of the search area based on the unevenness feature data to acquire second position information; A tunnel displacement measurement method comprising: measuring a displacement inside the tunnel based on a difference between the first position information and the second position information.

2. A method for measuring the displacement of a tunnel interior over time by setting a target using point cloud data of the tunnel interior surface acquired by a 3D laser scanner, comprising: It consists of an initial measurement step and a displacement measurement step. 1) The initial measurement step is acquiring point cloud data of an inner surface of a tunnel as first point cloud data, and extracting a predetermined area of ​​the inner surface of the tunnel from the first point cloud data as the target; extracting unevenness feature data that is unevenness features of the target, and registering first position information of the target and the unevenness feature data; 2) Displacement measurement step, which is carried out after a predetermined time has elapsed, setting a search area that includes a position identified based on the first position information and has an area larger than that of the target, acquiring point cloud data of the search area, and extracting the target from the point cloud data of the search area based on the unevenness feature data to acquire second position information; A tunnel displacement measurement method comprising: measuring a displacement inside the tunnel based on a difference between the first position information and the second position information.

3. 1) The initial measurement step is a scanner coordinate acquisition step of acquiring position coordinates of a three-dimensional laser scanner; a first point cloud data acquisition step of acquiring point cloud data of a surface of the sprayed concrete inside the tunnel as first point cloud data; a pseudo target setting step of extracting at least three regions from the first point cloud data and setting them as pseudo targets that are the targets; a first unevenness feature data extraction step of extracting unevenness features based on a plane of the pseudo target as first unevenness feature data; a first registration step of registering the position coordinates of the pseudo target, which is the first position information, and first unevenness feature data in association with the position coordinates of the three-dimensional laser scanner; 2) The displacement measurement step is a second point cloud data acquisition step of acquiring point cloud data of the sprayed concrete surface as second point cloud data; a search area setting step of setting the search area from second point cloud data based on position coordinates of the pseudo target; a second unevenness feature data extraction step of extracting unevenness features based on the plane of the pseudo target from the search area as second unevenness feature data; a false target specifying step of specifying position coordinates of the false target, which is the second position information, based on a similarity between the unevenness features of the first unevenness feature data and the partial unevenness features of the second unevenness feature data; a second registration step of registering the position coordinates of the identified pseudo target in association with the position coordinates of the three-dimensional laser scanner; a displacement measurement step of measuring the displacement of the interior of the tunnel based on changes in the position coordinates of the pseudo target set in the initial measurement step and the pseudo target identified in the displacement measurement step; 3. The tunnel displacement measuring method according to claim 2, further comprising:

4. 2. The tunnel displacement measuring method according to claim 1, wherein the target is a fixing plate of a rock bolt provided on the inner surface of the tunnel.

5. 2. A tunnel displacement measuring method according to claim 1, wherein the target is a steel support provided on the inner surface of the tunnel.

6. 6. A tunnel displacement measuring method according to claim 4, wherein the target has protrusions provided at a plurality of positions in the vertical direction.

7. 1) In the initial measurement step, The tunnel displacement measurement method according to claim 1, characterized in that the imaging results of the target are input into a tunnel displacement measurement device that performs an initial measurement step and a displacement measurement step in order to obtain unevenness feature data of the target.

8. A device that uses point cloud data of the tunnel inner surface acquired by a 3D laser scanner to set a target and measure the displacement of the tunnel interior over time, It consists of an initial measurement section and a displacement measurement section. The initial measurement section is acquiring unevenness feature data that is unevenness features of the target; acquiring point cloud data of the tunnel inner surface including the target as first point cloud data, and extracting the unevenness feature data from the first point cloud data to acquire first position information of the target; The displacement measurement unit is setting a search area that includes a position identified based on the first position information and has an area larger than that of the target, acquiring point cloud data of the search area, and extracting the target from the point cloud data of the search area based on the unevenness feature data to acquire second position information; A tunnel displacement measuring device characterized in that it measures displacement inside a tunnel based on the difference between the first position information and the second position information.

9. A device that uses point cloud data of the tunnel inner surface acquired by a 3D laser scanner to set a target and measure the displacement of the tunnel interior over time, It consists of an initial measurement section and a displacement measurement section. The initial measurement section is acquiring point cloud data of an inner surface of a tunnel as first point cloud data, and extracting a predetermined area of ​​the inner surface of the tunnel from the first point cloud data as the target; extracting unevenness feature data that is unevenness features of the target, and registering first position information of the target and the unevenness feature data; The displacement measurement unit is setting a search area that includes a position identified based on the first position information and has an area larger than that of the target, acquiring point cloud data of the search area, and extracting the target from the point cloud data of the search area based on the unevenness feature data to acquire second position information; A tunnel displacement measuring device characterized in that it measures displacement inside a tunnel based on the difference between the first position information and the second position information.

10. The initial measurement section is 9. The tunnel displacement measuring device according to claim 8, further comprising: an input of an image of the target to acquire data on the unevenness characteristics of the target.

11. a tunnel displacement measuring device according to claim 8; a metal object provided on the inner surface of the tunnel and having a concave-convex feature used as the target; A tunnel displacement measurement system comprising:

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