Three-dimensional measurement data processing device, method, and program

Abstract

Provided are a three-dimensional measurement data processing device, a method, and a program that make it possible to easily diagnose deterioration of a concrete structure. Three-dimensional measurement data obtained by three-dimensionally measuring a concrete structure is acquired. A floating region of the concrete structure is extracted on the basis of the three-dimensional measurement data. A physical quantity including at least the volume of the floating region is calculated on the basis of the three-dimensional measurement data. Information pertaining to the calculated physical quantity including at least the volume of the floating region is outputted to a display destination in association with information pertaining to the floating region.

Description

Three-dimensional measurement data processing device, method, and program

[0001] The present invention relates to a three-dimensional measurement data processing device, method, and program, and more particularly to a three-dimensional measurement data processing device, method, and program for processing three-dimensional measurement data obtained by three-dimensionally measuring a concrete structure.

[0002] Patent Document 1 discloses an evaluation system for evaluating the condition of a structure, which includes a detection means for detecting the condition of a structure based on measurement data obtained by measuring the structure, and an evaluation information generation means for generating evaluation information indicating an evaluation result of the condition of the structure based on the measurement data, wherein the measurement data includes surrounding data indicating physical quantities around the structure, the detection means detects signs of deformation of the structure based on the measurement data, and the evaluation information generation means generates evaluation information including data indicating signs of deformation of the structure.

[0003] Japanese Patent Publication No. 2023-030711

[0004] In order to properly maintain and manage concrete structures, it is necessary to periodically diagnose the deterioration of the concrete structures and to repair and reinforce them appropriately.

[0005] An object of one embodiment of the technique of the present disclosure is to provide a three-dimensional measurement data processing device, method, and program that can easily diagnose deterioration of a concrete structure.

[0006] (1) A three-dimensional measurement data processing device having a processor, the processor acquiring three-dimensional measurement data obtained by three-dimensionally measuring a concrete structure, extracting a floating area of ​​the concrete structure based on the three-dimensional measurement data, calculating physical quantities including at least the volume of the floating area based on the three-dimensional measurement data, and outputting information on the calculated physical quantities including at least the volume of the floating area to a display destination in association with information on the floating area.

[0007] (2) A three-dimensional measurement data processing device described in (1), in which the processor acquires time series data of physical quantities including at least the volume of the floating region, predicts future changes in the physical quantities including at least the volume of the floating region from the time series data of the physical quantities including at least the volume of the floating region, and outputs information on the predicted changes in the physical quantities including at least the volume of the floating region to a display destination in association with information on the floating region.

[0008] (3) A three-dimensional measurement data processing device described in (1) or (2), in which the processor calculates at least the volume of the floating area based on the three-dimensional measurement data, acquires information on the concrete structure in the floating area, infers the internal state of the floating area based on the information on the volume of the floating area and the information on the concrete structure in the floating area, associates the information on the inferred internal state with the information on the floating area and outputs it to a display destination.

[0009] (4) A three-dimensional measurement data processing device according to (3), in which the processor estimates the corrosion rate of the reinforcing steel bars present in the floating area as the internal state.

[0010] (5) A three-dimensional measurement data processing device according to (4), in which the processor estimates the corrosion rate of the reinforcing steel present in the floating area by utilizing the correlation between the volume of the floating area of ​​the concrete and the corrosion rate of the reinforcing steel.

[0011] (6) A three-dimensional measurement data processing device described in (4) or (5), in which the processor further estimates, as internal states, at least one of the amount of corrosion of the reinforcing bars and the volume of voids present in the floating area based on information on the corrosion rate of the reinforcing bars, information on the volume of the floating area, and information on the concrete structure in the floating area.

[0012] (7) A three-dimensional measurement data processing device described in any one of (3) to (6), wherein the information on the concrete structure in the floating area includes at least one of information on the reinforcing bars present in the floating area, information on damage, and information on the concrete.

[0013] (8) A three-dimensional measurement data processing device according to (7), in which the information on the reinforcing bars includes information on the density, length, surface area, and cross-sectional area of ​​the reinforcing bars.

[0014] (9) A three-dimensional measurement data processing device according to (7) or (8), wherein the damage information includes information on cracks, water leaks, and rust fluid.

[0015] (10) A three-dimensional measurement data processing device according to any one of (7) to (9), wherein the information on the concrete includes information on the cover thickness and the thickness of the concrete covering.

[0016] (11) A three-dimensional measurement data processing device described in any one of (3) to (10), in which the processor acquires time series data of the internal state of the floating area, predicts future changes in the internal state from the time series data of the internal state, associates information on the predicted changes in the internal state with information on the floating area, and outputs it to a display destination.

[0017] (12) A three-dimensional measurement data processing method, which acquires three-dimensional measurement data obtained by three-dimensionally measuring a concrete structure, extracts a floating area of ​​the concrete structure based on the three-dimensional measurement data, calculates a physical quantity including at least the volume of the floating area based on the three-dimensional measurement data, and outputs information on the calculated physical quantity including at least the volume of the floating area to a display destination in association with information on the floating area.

[0018] (13) A three-dimensional measurement data processing program that causes a computer to perform the following functions: acquiring three-dimensional measurement data obtained by three-dimensionally measuring a concrete structure; extracting a floating area of ​​the concrete structure based on the three-dimensional measurement data; calculating a physical quantity including at least the volume of the floating area based on the three-dimensional measurement data; and outputting information on the calculated physical quantity including at least the volume of the floating area to a display destination in association with information on the floating area.

[0019] According to the present invention, deterioration of a concrete structure can be easily diagnosed.

[0020] FIG. 1 is a block diagram showing an example of the hardware configuration of a deterioration diagnosis device; FIG. 2 is a block diagram of the main functions of the deterioration diagnosis device; FIG. 3 is a block diagram of the main functions of the floating area extraction unit; FIG. 4 is a conceptual diagram of height image generation; FIG. 5 is a diagram showing an example of an object; FIG. 6 is a diagram showing an example of a height image; FIG. 7 is a diagram showing an example of a binarized height image; FIG. 8 is a diagram showing an example of a height image with contour extraction; FIG. 9 is a diagram showing an example of a height image after filtering;

[0021] Preferred embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0022] First Embodiment Here, an example will be described in which the present invention is applied to a deterioration diagnosis device that diagnoses deterioration of a concrete structure based on the floating of concrete.

[0023] Concrete "floating" refers to the condition where the concrete near the surface is floating. Concrete floating refers to a condition where the concrete near the surface is losing its integrity with the concrete inside due to continuous cracks inside the concrete, etc.

[0024] The deterioration diagnosis device of this embodiment uses data obtained by three-dimensionally measuring a concrete structure (three-dimensional measurement data) to extract areas where lifting has occurred (lifted areas) and provide various information. Specifically, the area, height, and volume are calculated for each lifted area and displayed. The internal state of the lifted area is also estimated and displayed. Specifically, the corrosion rate, corrosion amount, and void volume of the rebar (steel) present in the lifted area are estimated and displayed. Furthermore, future fluctuations in the corrosion rate, corrosion amount, and void volume of the rebar are predicted and displayed. The deterioration diagnosis device of this embodiment is an example of a three-dimensional measurement data processing device.

[0025] [Hardware Configuration of Degradation Diagnostic Apparatus] FIG. 1 is a block diagram showing an example of the hardware configuration of a degradation diagnostic apparatus.

[0026] Degradation diagnosis device 100 has a configuration similar to that of a typical computer, including processor 101, main memory 102, auxiliary memory 103, operation unit 104, display unit 105, and interface (I / F) 106.

[0027] The processor 101 executes programs and functions as various processing units. As an example, in this embodiment, the processor 101 is configured as a CPU (Central Processing Unit). Various programs and data executed by the processor 101 are stored in the main memory unit 102 and / or the auxiliary memory unit 103. The term "program" is synonymous with "software."

[0028] The main memory unit 102 includes a RAM (Random Access Memory) and a ROM (Read Only Memory). The RAM is used as a work area for the processor 101. The ROM stores a basic input / output program and the like.

[0029] The auxiliary storage unit 103 is configured by, for example, a hard disk drive (HDD), a solid state drive (SSD), or the like.

[0030] The operation unit 104 is composed of, for example, a keyboard, a mouse, and the like.

[0031] The display unit 105 is configured by, for example, a liquid crystal display (LCD), an organic electroluminescence diode display (OLED display), or the like.

[0032] Interface section 106 includes various connection interfaces for connecting degradation diagnosis device 100 to external devices, networks, and the like.

[0033] [Functions of the Degradation Diagnostic Device] FIG. 2 is a block diagram of the main functions of the degradation diagnostic device.

[0034] 2, the degradation diagnosis device 100 of this embodiment has functions such as a data acquisition unit 110, a floating region extraction unit 120, a physical quantity calculation unit 130, an internal state estimation unit 140, a recording control unit 150, a fluctuation prediction unit 160, and an output control unit 170. The functions of each unit are realized by the processor 101 executing a predetermined program (degradation diagnosis program). The degradation diagnosis program is an example of a three-dimensional measurement data processing program.

[0035] [Data Acquisition Unit] The data acquisition unit 110 acquires three-dimensional measurement data of the concrete structure (object) to be diagnosed. As described above, this data is data obtained by three-dimensionally measuring the concrete structure and represents the three-dimensional shape of the surface. As an example, in this embodiment, three-dimensional measurement data is acquired by three-dimensionally measuring the object using photogrammetry. Photogrammetry is a method of obtaining geometric characteristics of an object from photographic images. For example, stereo photogrammetry can be used as a photogrammetry method to obtain three-dimensional coordinates of any point on the object. Note that photogrammetry itself is a well-known technology, and therefore a detailed description thereof will be omitted. The three-dimensional measurement method is not limited to this, and other methods can be used, such as a measurement method using a three-dimensional scanner such as a three-dimensional laser scanner or a LiDAR (Light Detection and Ranging) scanner, or a measurement method using a monocular camera with artificial intelligence (AI).

[0036] Based on an instruction from a user, the data acquisition unit 110 acquires three-dimensional measurement data of the object via the interface unit 106. At this time, information on the measurement date or measurement date and time is also acquired.

[0037] [Floating Region Extraction Unit] The floating region extraction unit 120 analyzes the three-dimensional measurement data acquired by the data acquisition unit 110, and extracts floating regions from the measured regions.

[0038] FIG. 3 is a block diagram showing the main functions of the floating region extraction unit.

[0039] As shown in FIG. 3, the floating region extraction unit 120 has functions such as a height image generation unit 121, a binarization processing unit 122, a contour extraction unit 123, and a filter processing unit 124.

[0040] [Height Image Generator] The height image generator 121 generates a height image from the three-dimensional measurement data acquired by the data acquisition unit 110. The height image is an image that represents the height from a reference plane for each pixel. Therefore, the pixel value of each pixel in the height image represents the height from the reference plane. FIG. 4 is a conceptual diagram of height image generation. As shown in FIG. 4, the difference between the measurement result and the reference plane is calculated for each pixel, and the height h at each pixel is calculated. ij Ask for.

[0041] Here, the reference surface may be a curved surface estimated from past measurement data, design data of the object (design drawings, etc.), or a three-dimensional measurement result.

[0042] Fig. 5 is a diagram showing an example of an object, and a three-dimensional model generated from images of the object captured from multiple viewpoints.

[0043] Fig. 6 is a diagram showing an example of a height image. Fig. 6 shows an example of a height image of the object shown in Fig. 5. Fig. 6 shows an example in which the height of each pixel is expressed by a shade (density) of color and visualized. In this embodiment, the height image is an example of a first image.

[0044] [Binarization Processing Unit] The binarization processing unit 122 performs binarization processing on the height image generated by the height image generation unit 121. For example, a value determined by measurement error, Otsu's binarization method, or the like can be used as the threshold value.

[0045] Fig. 7 is a diagram showing an example of a binarized height image Fig. 7 shows an example of a binarized height image of the height image shown in Fig. 6 .

[0046] [Contour Extraction Unit] The contour extraction unit 123 extracts contours from the binarized height image. The contour extraction unit 123 analyzes the binarized height image and extracts pixels that make up the contour. For example, the contour extraction unit 123 extracts pixels that make up the contour using a known contour tracking algorithm.

[0047] 8 is a diagram showing an example of a height image from which a contour has been extracted, in which a contour C has been extracted from the binarized height image shown in FIG.

[0048] By contour extraction, a contour C of an area having a height equal to or greater than a threshold is extracted from the height image. The area within the extracted contour C becomes a candidate for a raised area.

[0049] [Filter Processing Unit] The filter processing unit 124 performs filter processing on the height image from which the contours have been extracted, and extracts the floating area. The contours C extracted by the contour extraction unit 123 include things that are not floating, such as accessories and joints. For this reason, a filter is applied to the height image after contour extraction to remove contours other than floating. The filter applied is a filter that has the function of removing contours other than floating. The criteria for removal are the area inside the contour and the shape of the contour, etc. Regarding the area, for example, areas below a threshold are removed. The area is calculated using the number of pixels inside the contour. Regarding the shape, areas that include many straight lines are removed.

[0050] 9 is a diagram showing an example of a height image after filtering, in which the height image after contour extraction shown in FIG. 8 is subjected to filtering.

[0051] By performing the filtering process, contours C other than the floating area are removed from the image. Therefore, only the contours C of the floating area remain in the height image after the filtering process. In other words, the floating area is extracted.

[0052] [Physical Quantity Calculation Unit] The physical quantity calculation unit 130 calculates the physical quantity of each extracted uplifted region. The "physical quantity" is a quantity that indicates the size of the uplifted region, and is at least one of the area, height, and volume of the uplifted region. The physical quantity calculation unit 130 analyzes the height image to calculate the physical quantity of each uplifted region.

[0053] FIG. 10 is a block diagram of the main functions of the physical quantity calculation unit.

[0054] 10 , the physical quantity calculation unit 130 has functions of an area calculation unit 131, a height calculation unit 132, and a volume calculation unit 133. In this embodiment, the area, height, and volume are all calculated as the physical quantities of the floating region.

[0055] The area calculation unit 131 calculates the area of ​​the floating region. The area calculation unit 131 calculates the area ∫ of the contour extracted as the contour of the floating region. C ΔS is calculated as the area of ​​the floating region. More specifically, the area of ​​the floating region is calculated by adding up the areas ΔS of the pixels within the contour. The area of ​​a pixel is synonymous with the area of ​​the object corresponding to one pixel (one pixel).

[0056] The height calculation unit 132 calculates the height of the floating region. The height calculation unit 132 calculates the peak value max within the contour extracted as the contour of the floating region. C h ij , or average C h ij is calculated as the height of the floating area.

[0057] The volume calculation unit 133 calculates the volume of the floating region by calculating an integral value ∫ of the height within the contour extracted as the contour of the floating region. C h ij ΔS is calculated as the volume of the floating area. More specifically, the "height h" of the pixel in the contour is calculated as ij The volume of the floating area is calculated by adding up the area ΔS and the area ΔS.

[0058] [Internal State Estimation Unit] The internal state estimation unit 140 estimates the internal state of each extracted floating region. In this embodiment, the internal state estimation unit 140 estimates the corrosion rate of the rebars present in the floating region and the internal structure. The internal structure is the amount of corrosion of the rebars and the volume of voids in the floating region.

[0059] FIG. 11 is a block diagram of the main functions of the internal state estimation unit.

[0060] As shown in FIG. 11, the internal state estimation unit 140 has functions of an information acquisition unit 141, a measurement processing unit 142, a corrosion rate estimation unit 143, an internal configuration estimation unit 144, and the like.

[0061] The information acquisition unit 141 acquires various information necessary for estimating the internal state. The information necessary for estimating the internal state includes information on the floating region, information on the volume of the floating region, and information on the object in the floating region.

[0062] The information on the floated region is information on the floated region extracted by the floated region extraction unit 120 .

[0063] The information on the volume of the floating region is information on the volume of the floating region calculated by the physical quantity calculation unit 130 .

[0064] The information on the target object is information on the concrete structure to be diagnosed. The information on the concrete structure in the floating region includes information on the reinforcing bars in the floating region, information on damage, and information on the concrete.

[0065] The information on the rebar includes information on the density, length, thickness (diameter), surface area, and cross-sectional area of ​​the rebar. Here, the "length" of the rebar refers to the length of the rebar in the floating area. That is, the length of the portion of the rebar that exists in the floating area. FIG. 12 is a conceptual diagram of how the length of the rebar is derived. FIG. 12 shows an example in which two rebars Rb1 and Rb2 exist in a three-dimensionally measured area. One rebar, Rb1 (the upper rebar in FIG. 12 ), exists only in the floating area A, while the other rebar, Rb2 (the lower rebar in FIG. 12 ), exists in both the floating area A and the floating area B. The length of the rebar Rb1 across the floating area A is defined as La1. The length of the other rebar Rb2 across the floating area A is defined as La2, and the length of the rebar Rb2 across the floating area B is defined as Lb. The length of the rebar in the floating region A is the sum of the lengths La1 and La2 of the two rebars Rb1 and Rb2 that cross the floating region A. In other words, (La1 + La2) is the length of the rebar in the floating region A. Only rebar Rb2 crosses the floating region B. Therefore, the length of the rebar in the floating region B is the length Lb of rebar Rb2 that crosses the floating region B. In this way, the length of the rebar is the length of the part that exists in the floating region, and when multiple rebars exist in the floating region, it is the sum of the lengths that each rebar crosses the floating region. The same applies to the "surface area" of the rebar. In other words, the surface area of ​​the part that exists in the floating region is the surface area of ​​the rebar.

[0066] If the rebars used in the object are known from the design data of the object, the density is obtained from the design data, etc. If the design data of the object is not available, the density is given as a physical property value, for example. Alternatively, density information may be obtained by measuring in advance.

[0067] The same applies to the thickness and cross-sectional area of ​​rebars. If the rebars used in the object are known, information such as the cross-sectional area and thickness can be obtained from the object's design data. If the object's design data is not available, it can be obtained by measuring it in advance. In this case, for example, the shape can be approximated to a cylinder, the thickness can be measured, and the cross-sectional area can be calculated from the measured thickness.

[0068] The length of the rebar is calculated by acquiring information on the position of the rebar in the object and based on the acquired position information and information on the floating area. If the position information is known from the design data of the object, it is acquired from the design data of the object. If the design data of the object is not available, it is acquired, for example, by measuring in advance.

[0069] Regarding the surface area of ​​rebars, if the rebars used in the target object are known, information on the rebar's diameter or surface area per unit area is obtained from design data, etc., and calculations are made based on the obtained information on the rebar's diameter or surface area per unit area, and the length of the rebar in the floating area. If design data, etc. is not available, measurements are taken in advance. In this case, for example, the shape is approximated to a cylinder, the diameter is measured, and the surface area is calculated from the measured diameter.

[0070] The measurement processing unit 142 acquires information on the position of the rebar in the object, and calculates the length of the rebar in each floating area based on the acquired position information and floating area information. The measurement processing unit 142 also acquires information on the diameter and length of the rebar, and calculates the surface area of ​​the rebar in each floating area based on the acquired diameter and length information. In addition, it performs calculation processing for information necessary for estimating the internal state.

[0071] The position and thickness of the reinforcing bars can be measured by a known method, such as an electromagnetic wave radar method or an electromagnetic induction method.

[0072] Damage information includes information on cracks, water leaks, and rust fluid. For example, information on the results of a previously conducted inspection is acquired as damage information. Damage inspection results may be obtained visually or using image recognition. For damage information, information on the presence or absence of damage is acquired, for example. That is, information on the presence or absence of damage in the lifted area is acquired. Note that a configuration may be adopted in which more detailed information is acquired. For example, for cracks, in addition to the presence or absence of cracks, information on the width and length of the cracks may be acquired. For example, for water leaks and rust fluid, in addition to the presence or absence of cracks, information on the size (area) may be acquired.

[0073] Regarding the information on damage, information on the position of the damage on the object may be acquired, and the measurement processing unit 142 may automatically detect whether or not there is damage for each floating region.

[0074] Concrete information includes information on cover thickness and winding thickness. "Cover thickness" refers to the shortest distance from the surface of the rebar to the concrete surface in a concrete structure. "Wrapping thickness" refers to the thickness of the lining concrete in a tunnel structure. Wrapping thickness is also called lining thickness. When this information is known from the design data of the object, it is obtained from the design data of the object. When the design data of the object is not available, it is obtained, for example, by measuring in advance. Note that known methods can be used for measurement. For example, the electromagnetic wave radar method, the electromagnetic induction method, etc. can be used to measure cover thickness and winding thickness.

[0075] The information acquisition unit 141 acquires various pieces of information automatically or by user input. When acquiring various pieces of information by user input, the information acquisition unit 141 displays a predetermined input screen on the display unit 105 to accept the input of information.

[0076] The corrosion rate estimation unit 143 estimates the corrosion rate of the reinforcing bars present in the floating area.

[0077] Fig. 13 is a diagram illustrating an overview of reinforcing bar corrosion. In Fig. 13, (A) shows a cross section of reinforcing bar Rb before corrosion, and (B) shows a cross section of reinforcing bar Rb after corrosion.

[0078] When the reinforcing bar Rb corrodes, corrosion products Cp such as rust are produced. On the other hand, when the reinforcing bar Rb corrodes, its cross-sectional area decreases.

[0079] The "corrosion rate of rebar" can be defined as the ratio of the reduction in cross-sectional area of ​​the rebar to the cross-sectional area of ​​the rebar before corrosion. In other words, the "corrosion rate of rebar" can be expressed by the following formula: [Corrosion rate of rebar] = [Reduction in cross-sectional area of ​​rebar due to corrosion] / [Cross-sectional area of ​​rebar before corrosion]

[0080] From the perspective of volume, it can be defined as the ratio of the volume reduction to the volume of the rebar before corrosion. The "volume of the rebar" is calculated by multiplying the "cross-sectional area of ​​the rebar before corrosion" by the "length of the corroded rebar." Therefore, the "corrosion rate of the rebar" can be expressed in terms of volume by the following formula: [Corrosion rate of the rebar] = [Volume reduction of the rebar due to corrosion] / ([Cross-sectional area of ​​the rebar before corrosion] x [Length of the corroded rebar])

[0081] In terms of the weight of the rebar, the "corrosion rate of rebar" can be defined as the ratio of the weight loss to the weight of the rebar before corrosion. In other words, the "corrosion rate of rebar" can be expressed in terms of weight by the following formula: [Corrosion rate of rebar] = [Weight loss of rebar due to corrosion] / [Weight of rebar before corrosion]

[0082] Here, the "weight loss of rebar due to corrosion" is the difference between the "weight of rebar before corrosion" and the "weight of normal part of rebar after corrosion" ([weight loss of rebar due to corrosion] = [weight of rebar before corrosion] - [weight of normal part of rebar after corrosion]). Therefore, the "corrosion rate of rebar" can be expressed in terms of weight by the following formula: [corrosion rate of rebar] = ([weight of rebar before corrosion] - [weight of normal part of rebar after corrosion]) / [weight of rebar before corrosion]

[0083] One method for determining the degree of corrosion of rebars in concrete structures is to estimate the cross-sectional area reduction rate of the rebars through non-destructive testing (crack width and ultrasonic propagation velocity) (Ichiro Kuroda, "Method for Estimating the Cross-sectional Area Reduction Rate of Rebars and Flexural Strength Through Non-Destructive Testing of RC Beam Members with Multiple Corroded Rebars," Journal of Concrete Engineering, Vol. 27, pp. 43-55, 2016). This method utilizes the correlation between the quantities obtained through non-destructive testing and the cross-sectional area reduction rate of the rebars to estimate the cross-sectional area reduction rate of the rebars from the results of non-destructive testing.

[0084] The inventors of the present application have found that there is a correlation between the volume of the floating region and the corrosion rate of the reinforcing steel. In order to confirm this, a predetermined electrolytic corrosion test was carried out.

[0085] FIG. 14 is a diagram showing an outline of the electrolytic corrosion test.

[0086] The electrolytic corrosion test is a method in which a constant current is passed through rebar to induce corrosion. By setting the cumulative current obtained by multiplying the electrolytic corrosion time by the applied current value, it is possible to quantitatively evaluate the corrosion rate and amount of corrosion of the rebar as the corrosion progresses.

[0087] While the rectangular column specimen Sp was immersed in salt water Sw, a constant current was passed from a current source through the reinforcing bars of the rectangular column specimen Sp to induce corrosion of the reinforcing bars, and the relationship between the corrosion rate and the volume of the floating area was confirmed.

[0088] Figure 15 shows the results of the electrolytic corrosion test. Figure 15 shows height images obtained by three-dimensionally measuring the surface of a rectangular columnar specimen. Figure 15 (A) shows a height image when the corrosion rate of the rebar is 0.5%. Figure 15 (B) shows a height image when the corrosion rate of the rebar is 3.0%.

[0089] As shown in Figure 15, it can be seen that the height of the surface rise increases as corrosion progresses (increasing corrosion rate). As mentioned above, the volume of the floating region is the integral value of the height within the floating region, so an increase in the height of the surface rise means an increase in the volume of the floating region. Therefore, it can be seen that there is a correlation between the corrosion rate and the volume of the floating region.

[0090] In this embodiment, the correlation between the volume of the floating area and the corrosion rate of the rebar is utilized to estimate the corrosion rate of the rebar present in the floating area from the volume of the floating area. For example, the relationship between the volume of the floating area and the corrosion rate of the rebar is derived in advance by an electrolytic corrosion test or the like, and the result is used to perform the estimation process.

[0091] The relationship between the volume of the floating area and the corrosion rate of the rebar varies depending on the cover thickness and winding thickness, etc., the length and thickness of the rebar, and the presence or absence of damage (cracks, water leakage, rust, etc.). Therefore, for a more accurate estimation, it is preferable to estimate the corrosion rate of the rebar using parameters such as the cover thickness, winding thickness, the length and thickness of the rebar, and the presence or absence of damage.

[0092] As an example, in this embodiment, the correlation between the volume of the floating area and the corrosion rate of the rebar is utilized to predict the corrosion rate of the rebar through simulation, and the simulation parameters used are information on the concrete in the floating area (cover thickness, winding thickness, etc.), information on the rebar (length, diameter, etc.), and information on damage (presence or absence of cracks, water leakage, rust, etc.).

[0093] The corrosion rate estimation unit 143 acquires the volume information of the lifted region and information on various parameters acquired by the information acquisition unit 141, and performs a simulation to estimate the corrosion rate of the reinforcing steel bars present in the lifted region. For example, FEM (Finite Element Method) analysis can be used for the simulation.

[0094] The internal structure estimation unit 144 estimates the internal structure of the floating region. In this embodiment, the internal structure estimation unit 144 estimates the "amount of corrosion of rebar" and "volume of voids" in the floating region as the internal structure of the floating region.

[0095] The "amount of corrosion of rebar" is expressed by the following formula: Amount of corrosion = [weight loss of rebar due to corrosion] / [surface area of ​​corroded rebar]

[0096] The "weight loss of rebar due to corrosion" is expressed as the product of the "volume loss of rebar due to corrosion" and the "density of rebar." In other words, it is expressed by the following formula: [Weight loss of rebar due to corrosion] = [Volume loss of rebar due to corrosion] x [Density of rebar]

[0097] Therefore, the "amount of corrosion of rebar" can be expressed by the following formula: [amount of corrosion of rebar] = ([volume reduction of rebar due to corrosion] x [density of rebar]) / [surface area of ​​corroded rebar]

[0098] As mentioned above, the "corrosion rate of rebar" can be expressed in terms of volume as follows: [Corrosion rate of rebar] = [Volume reduction of rebar due to corrosion] / ([Cross-sectional area of ​​rebar before corrosion] × [Length of corroded rebar]).

[0099] From the above formula, the "volume loss of rebar due to corrosion" can be calculated using the following formula: [Volume loss of rebar due to corrosion] = [Cross-sectional area of ​​rebar before corrosion] x [Length of corroded rebar] x [Corrosion rate of rebar]

[0100] Therefore, the "amount of corrosion of rebar" can be expressed by the following formula: [amount of corrosion of rebar] = ([cross-sectional area of ​​rebar before corrosion] x [length of corroded rebar] x [corrosion rate of rebar] x [density of rebar]) / [surface area of ​​corroded rebar]

[0101] That is, the "amount of corrosion of rebar" can be calculated from the "cross-sectional area of ​​rebar before corrosion," "length of corroded rebar," "corrosion rate of rebar," "density of rebar," and "surface area of ​​corroded rebar." The "corrosion rate of rebar" is estimated by the corrosion rate estimation unit 143. Other information is acquired by the information acquisition unit 141. The internal configuration estimation unit 144 acquires each piece of information and calculates the "amount of corrosion of rebar" in the floating area using the above formula.

[0102] The "volume of the void" is estimated as follows: The "volume of the floating region" is considered to be the sum of the "volume of the void" and the "volume increase due to corrosion products," and the "volume of the void" is calculated from the "volume of the floating region" and the "volume increase due to corrosion products."

[0103] The "volume increase due to corrosion products" is the difference between the "volume of corrosion products" and the "volume decrease of rebar due to corrosion" (see Figure 13), and is expressed by the following formula: [Volume increase due to corrosion products] = [volume of corrosion products] - [volume decrease of rebar due to corrosion]

[0104] Therefore, the "volume of the floating area" can be expressed by the following formula: [Volume of the floating area] = [Volume of the void] + ([Volume of corrosion products] - [Volume reduction of the rebar due to corrosion])

[0105] From the above formula, the "void volume" can be expressed by the following formula: [void volume] = [volume of floating area] - ([volume of corrosion products] - [volume reduction of rebar due to corrosion])

[0106] The "volume of corrosion products" is expressed as the product of the "volume reduction of rebar due to corrosion" and the "expansion coefficient due to corrosion." In other words, it is expressed by the following formula: [volume of corrosion products] = [volume reduction of rebar due to corrosion] x [expansion coefficient due to corrosion]

[0107] Therefore, the "void volume" is expressed by the following formula: [void volume] = [volume of the floating area] - [([expansion coefficient due to corrosion] - 1) x [volume reduction of the rebar due to corrosion]]

[0108] In this way, the "volume of the void" is calculated from the "volume of the floating region," the "expansion coefficient due to corrosion," and the "volume reduction of the reinforcing bar due to corrosion."

[0109] Here, the "volume of the lifted region" is calculated from the results of three-dimensional measurement. The "volume reduction of the rebar due to corrosion" is calculated from the "cross-sectional area of ​​the rebar before corrosion," "length of the corroded rebar," and "corrosion rate of the rebar," as described above. The "expansion coefficient due to corrosion" is, for example, an experimental value used as a constant. Generally, the expansion coefficient due to corrosion of rebar used in concrete structures is 2 to 2.5 times. If the type of rebar used is known from the design data of the object, it is preferable to assume or measure the composition of the corrosion product to obtain information on the expansion coefficient due to corrosion.

[0110] As described above, the internal state estimation unit 140 estimates the corrosion rate, corrosion amount, and void volume of the reinforcing bars present in the floating region as the internal state of the floating region.

[0111] [Recording Control Unit] The recording control unit 150 records the 3D measurement data of the object acquired by the data acquisition unit 110, information on the floating area extracted by the floating area extraction unit 120, information on the physical quantities (height, area, and volume) of the floating area calculated by the physical quantity calculation unit 130, and information on the internal state of the floating area (corrosion rate, corrosion amount, and void volume of the rebar) estimated by the internal state estimation unit 140 in the management database 180. Each piece of information is recorded in association with the 3D measurement data. Furthermore, the 3D measurement data, along with information on the measurement date or measurement date and time, is recorded in association with information on the object. The information on the object is, for example, identification information assigned individually to each object. Inspections of concrete structures are periodically conducted. Therefore, various data related to the floating area are accumulated in the management database 180 through repeated inspections. The management database 180 is generated, for example, in the auxiliary storage unit 103.

[0112] Fluctuation Prediction Unit The fluctuation prediction unit 160 predicts future changes in the physical quantity of the floated region and future changes in the internal state of the floated region.

[0113] As described above, by repeatedly carrying out inspections, various data relating to the floating area are accumulated in the management database 180.

[0114] The fluctuation prediction unit 160 acquires time-series data on the physical quantities of the floating region from the management database 180 and predicts future changes in the physical quantities from the acquired time-series data on the physical quantities. As described above, in this embodiment, the height, area, and volume of the floating region are measured as the physical quantities of the floating region. Therefore, in this embodiment, future changes in the height, area, and volume of the floating region are predicted from the time-series data on the height, area, and volume of the floating region.

[0115] The fluctuation prediction unit 160 also acquires time-series data on the internal state of the floating region from the management database 180 and predicts future changes in the internal state based on the acquired time-series data on the internal state. As described above, in this embodiment, the corrosion rate, corrosion amount, and void volume of the reinforcing bars present in the floating region are estimated as the internal state of the floating region. Therefore, in this embodiment, future changes in the corrosion rate, corrosion amount, and void volume of the reinforcing bars are predicted based on the time-series data on the corrosion rate, corrosion amount, and void volume of the reinforcing bars present in the floating region.

[0116] The fluctuation prediction unit 160 predicts future changes in the height, area, and volume of the lifted region through time series analysis. The fluctuation prediction unit 160 also predicts future changes in the corrosion rate and corrosion amount of the reinforcing bars and the volume of the voids through time series analysis.

[0117] For time series analysis, a classical statistical model such as an autoregressive model can be used. Alternatively, a forecasting method using artificial intelligence (AI) can be used. That is, a trained model that has been machine-learned to predict future changes from time series data can be used for forecasting. A neural network such as LSTM (Long Short Term Memory) can be used to build the model.

[0118] [Output Control Unit] The output control unit 170 outputs to the display unit 105, in a predetermined format, information on the float region extracted by the float region extraction unit 120, information on the physical quantities of the float region calculated by the physical quantity calculation unit 130, information on the internal state of the float region estimated by the internal state estimation unit 140, and information on future changes in the physical quantities and internal state of the float region predicted by the fluctuation prediction unit 160.

[0119] FIG. 16 is a diagram showing an example of a screen display.

[0120] FIG. 16 shows an example of outputting information about a floating area and information about the physical quantities of the floating area. As shown in FIG. 16, a binarized and filtered height image IM is displayed, and information about the floating area and information about the physical quantities of the floating area are superimposed on the height image IM. The information about the floating area is displayed by displaying the outline C of the extracted floating area. The physical quantity information IF is displayed adjacent to the corresponding floating area. In other words, it is displayed near the floating area from which it was calculated so that it is possible to distinguish which floating area's physical quantity is being displayed. The example shown in FIG. 16 shows an example of displaying information about height and area as the physical quantities of the floating area. As shown in FIG. 16, the height and area information is displayed, for example, in the format of "height / area."

[0121] FIG. 17 is a diagram showing an example of displaying information on the volume and internal state of a floating region.

[0122] Figure 17 shows an example of a graph displaying the volume of the lifted area, the corrosion rate, the amount of corrosion, and the volume of the voids along with past measurement data. The horizontal axis of the graph shows the corrosion rate, and the vertical axis shows the volume of the lifted area. A regression line is calculated from the measured values ​​of the volume of the lifted area and displayed on the graph. The amount of corrosion and the volume of the voids are also displayed in different colors. In the example shown in Figure 17, "Rebar corrosion" shows the amount of corrosion of the rebar, and "Voids" shows the volume of the voids.

[0123] By displaying the data in a graph, changes in the volume of the float and changes in its internal state can be easily understood, and future fluctuations can be predicted.

[0124] FIG. 18 is a diagram showing an example of a screen display of information on the volume and internal state of a floating region.

[0125] For example, when one of the floated regions is selected on a screen that displays information about the floated regions and their physical quantities, a menu is displayed. When "Display of volume and internal state information" is selected from the menu, a graph showing information about the volume and internal state of the selected floated region is displayed as a pop-up on the screen, as shown in Fig. 18. The floated region is selected, for example, by using a cursor Ca displayed on the screen. The menu is displayed, for example, by operating a mouse. For example, the menu is displayed by moving the cursor Ca within the outline of the target floated region and right-clicking.

[0126] FIG. 19 is a diagram showing an example of a display of the predicted results of future changes in the corrosion rate of reinforcing bars.

[0127] Fig. 19 shows an example of a graph displaying future changes in the corrosion rate of rebar. The horizontal axis of the graph represents time, and the vertical axis represents the corrosion rate. In the example shown in Fig. 19, the predicted corrosion rate is displayed along with past corrosion rate measurement results (estimated values). In addition, a regression curve including the prediction is displayed.

[0128] FIG. 20 is a diagram showing an example of a screen display of the predicted results of future changes in the corrosion rate of reinforcing bars.

[0129] For example, when one of the floating areas is selected on a screen that displays information about the floating areas and their physical quantities, a menu is displayed. When "Display of fluctuation forecast" is selected from the menu, a graph showing future changes in the corrosion rate of rebar for the selected floating area is displayed, as shown in Figure 20.

[0130] [Operation of Degradation Diagnostic Device] FIG. 21 is a flowchart showing the flow of degradation diagnosis processing by the degradation diagnostic device.

[0131] First, three-dimensional measurement data obtained by three-dimensionally measuring an object is acquired (step S1).

[0132] Next, the floating region is extracted based on the acquired three-dimensional measurement data (step S2). In this embodiment, a height image is generated from the three-dimensional measurement data, and the floating region is extracted based on the generated height image. More specifically, the height image is binarized, and contours are extracted from the binarized height image, followed by filtering to extract the floating region.

[0133] Next, the physical quantities of each extracted floating region are calculated (step S3). In this embodiment, the height, area, and volume of the floating region are calculated as the physical quantities.

[0134] After calculating the physical quantities, information on the calculated physical quantities is output to the display destination together with information on the floating regions (step S4). That is, it is output to the display unit 105. It is not necessary to output all of the calculated physical quantity information; only information on some of the physical quantities may be output. In this embodiment, information on height and area is output. Information on the floating regions is displayed, for example, by showing the outline of the extracted floating region on the binarized height image (see FIG. 16). Furthermore, information on the physical quantities of each floating region is displayed adjacent to the corresponding floating region.

[0135] Next, the internal state of each floating area is estimated (step S5). That is, for each floating area, the corrosion rate of the rebar, the amount of corrosion, and the volume of the void are estimated. The corrosion rate of the rebar is estimated based on the volume of the floating area. The amount of corrosion of the rebar and the volume of the void are estimated based on the corrosion rate.

[0136] After the internal state is estimated, it is determined whether or not there is an instruction from the user to output the internal state (step S6). If there is an instruction to output, the estimation result of the internal state is output to the display destination (step S7). That is, it is output to the display unit 105.

[0137] Thereafter, it is determined whether or not the user has issued an instruction to output the internal state of the fluctuation prediction (step S8). If an output instruction has been issued, the fluctuation prediction process is carried out (step S9), and the result is output to the display destination (step S10). As an example, in this embodiment, future changes in the corrosion rate are predicted, and the result is output to the display unit 105.

[0138] As described above, the deterioration diagnosis device 100 of this embodiment can non-destructively extract a floating region from three-dimensional measurement data of an object, and can non-destructively measure the physical quantities (height, area, and volume) of the extracted floating region and display them together with information about the floating region, thereby facilitating the deterioration diagnosis of the object.

[0139] Furthermore, the deterioration diagnosis device 100 of this embodiment can estimate the internal state of the floating area (the corrosion rate of the rebars present in the floating area, the amount of corrosion, and the volume of the voids), and can display the estimation results together with the information about the floating area, thereby further facilitating the deterioration diagnosis of the object.

[0140] Furthermore, the deterioration diagnosis device 100 of this embodiment can predict future changes in the lifted area (changes in physical quantities and changes in internal conditions) from data accumulated through repeated measurements, and can display the prediction results together with information about the lifted area, thereby facilitating repair and reinforcement planning.

[0141] [Variations] [Output format of physical quantities of floating region] In the above embodiment, the physical quantities of the floating region are output in a format in which the height and area are displayed separately from the volume, but the output format of the physical quantities is not limited to this.

[0142] FIG. 22 is a diagram showing another example of an output form of a physical quantity.

[0143] Fig. 22 shows an example of displaying all measured physical quantities. As shown in Fig. 22, all measured physical quantities are displayed adjacent to the corresponding floating areas. In the example shown in Fig. 22, all three measured physical quantities are displayed as "height / area / volume".

[0144] In addition, information on the estimated internal condition, i.e., the corrosion rate, corrosion amount, and void volume of the reinforcing bar, may also be displayed. Furthermore, as information on the internal condition, only part of the estimated corrosion rate, corrosion amount, and void volume of the reinforcing bar may be displayed. For example, only the corrosion rate information may be displayed.

[0145] [Output Format of Internal State of Floating Region] In the above embodiment, a graph showing the relationship between the corrosion rate of the rebar and the volume of the floating region is generated and displayed as information indicating the internal state of the floating region, but the output format of the internal state information is not limited to this. Any format is sufficient as long as it at least shows the floating region and the internal state information estimated from the floating region. Furthermore, the output does not necessarily have to be in the form of a graph or the like, and may simply display estimated numerical values, etc. For example, the estimated corrosion rate, corrosion amount, and void volume of the rebar may be displayed adjacent to the corresponding floating region. Alternatively, only some of this information may be displayed.

[0146] [Output Format of Fluctuation Prediction] In the above embodiment, the predicted results of future changes in the lifted area are output in a graph format, but the output format of the predicted results is not limited to this. For example, the output format may be such that only the predicted numerical values ​​are displayed.

[0147] In the above embodiment, the case where the predicted results of future changes in the corrosion rate of reinforcing bars are output has been described as an example, but it is preferable to output other items in the same way. That is, it is preferable to output the predicted results of future changes in the physical quantities of the lifted areas, and the predicted results of future changes in the amount of corrosion of reinforcing bars and the volume of voids. In this case, as with the predicted results of the corrosion rate, by displaying them in a graph format, it is possible to easily grasp how they change.

[0148] [Other output formats] (1) Superimposed display on on-site photographs, etc. Information on the floating area may be superimposed on an image of the object or a three-dimensional model of the object, and the extraction results of the floating area may be output.

[0149] FIG. 23 is a diagram showing an example of superimposed display on a three-dimensional model.

[0150] Fig. 23 shows an example in which the outline C of the floating region is superimposed on a three-dimensional model. Fig. 23 also shows an example in which information on the measurement results of the physical quantities of the floating region is displayed together with information on the floating region. In particular, Fig. 23 shows an example in which information on the measurement results of the height and area is displayed as information on the measurement results of the physical quantities of the floating region.

[0151] In this way, by superimposing information about the floating area on a three-dimensional model of the object, it is possible to easily grasp the position of the floating area at the actual site.

[0152] In this example, information about the floating region is superimposed on a three-dimensional model of the object, but the same effect can be achieved by superimposing the information on an image of the object. The image of the object is an example of a second image. The image includes images of the object taken in separate images and then combined into a panoramic image. The three-dimensional model can be generated using a known method such as photogrammetry.

[0153] An image obtained by photographing the object or an image in which information about the floating region is superimposed on a three-dimensional model of the object is an example of a third image.

[0154] (2) Warning Display A configuration may be adopted in which a warning or notification is given to the user when the measured physical quantity of the floating region exceeds a threshold value.

[0155] FIG. 24 is a diagram showing an example of a warning display.

[0156] Fig. 24 shows an example of a warning display when an extracted floating area is superimposed on a three-dimensional model. In this case, the floating area to be warned is highlighted as shown in Fig. 24. Fig. 24 also shows an example of a case where the outline of the floating area to be warned is highlighted by displaying it in a predetermined color (for example, red). Fig. 24 also shows an example of a case where the area exceeds a threshold. In this case, the numerical value indicating the area is enlarged and displayed to highlight it. This allows the user to check the items that exceed the threshold from the display.

[0157] In this example, the floating area of ​​the warning target is highlighted by being displayed in a predetermined color, but the highlighting method is not limited to this. Other configurations include highlighting by changing the color of the outline or by flashing the outline. Furthermore, when physical quantities and / or internal state information are also displayed, the physical quantities and / or internal state information may be highlighted by changing the display color or by flashing the display. In this case, only items exceeding the threshold may be highlighted. This allows items exceeding the threshold to be identified from the display.

[0158] When this configuration is adopted, the degradation diagnosis processing device is provided with the function of a judgment processing unit. The judgment processing unit performs processing to determine whether or not the measured physical quantity, the numerical value of the internal state, etc. exceed a threshold value. The judgment may be configured to determine whether or not the measured physical quantity itself exceeds a threshold value, or whether or not the amount of change in the measured physical quantity exceeds a threshold value. Also, a configuration may be used in which a combination of multiple judgment items is used to determine whether or not a warning is required. Also, the mode of highlighting may be changed depending on the degree of degradation. For example, a configuration may be used in which multiple threshold values ​​are set and the mode of highlighting is changed in stages.

[0159] Furthermore, Figure 24 shows an example of a warning display when a floating area is superimposed on a three-dimensional model, but a warning can also be displayed using a similar method when a floating area is displayed on a height image, etc.

[0160] [Device Configuration] In the above embodiment, the floating area extraction process, physical quantity calculation process, internal situation estimation process, and variation prediction process are performed by one device (computer), but each process can also be performed by multiple devices in a distributed manner. For example, the overall device can be configured with a device that performs the floating area extraction process and physical quantity calculation process, and a device that performs the internal situation estimation process and variation prediction process. In this case, each device works together to perform each process.

[0161] Alternatively, a so-called client-server model may be adopted, with the server providing the various functions of the degradation diagnosis device. In this case, the server functions may be realized by a so-called cloud computer.

[0162] [Hardware Configuration] In this embodiment, each process is executed by a computer. The computer may execute these processes using a processor, a program, or a combination thereof. The computer may be a general-purpose computer, a computer for a specific purpose, a system such as a workstation, or other hardware element capable of executing a program.

[0163] The processor may be composed of one or more pieces of hardware, and the type of hardware is not limited. For example, the processor may be composed of hardware such as a programmable logic device such as a CPU (Central Processing Unit), an MPU (Micro Processing Unit), or an FPGA (Field Programmable Gate Array), a dedicated circuit for executing specific processes such as an ASIC (Application Specific Integrated Circuit), a GPU (Graphic Processing Unit), or an NPU (Neural Processing Unit). The processor also has various units or means for executing various processes in this embodiment. The type of hardware may also be a combination of different types of hardware. When multiple pieces of hardware are configured to execute one or more processes of a certain processor, the multiple pieces of hardware may exist in devices physically separated from each other or in the same device. In any of the embodiments, the order of each process performed by the processor is not limited to the order described above and may be changed as appropriate. The hardware may be composed of an electrical circuit (circuitry) combining circuit elements such as semiconductor devices.

[0164] Furthermore, the present embodiment may be implemented by hardware, software, firmware, microcode, or a combination thereof. Software, firmware, and microcode are configured by a program. Furthermore, a program may be, for example, a group of program modules, each function of which may be implemented by a processor configured to execute the respective function. The program may be, for example, a program code and / or multiple code segments stored in one or more non-transitory computer-readable media (e.g., storage media and other storages). The program may be stored in multiple non-transitory computer-readable media that reside in physically separate devices. The program code or code segment may represent a procedure, a function, a subprogram, a routine, a subroutine, a module, a software package, a class, or any combination of instructions, data structures, or program statements. The program code or code segment may be connected to another code segment or a hardware circuit by sending or receiving information, data, arguments, parameters, or memory contents.

[0165] [Supplementary Note] The following supplementary note is further disclosed regarding the above-described embodiment.

[0166] [Supplementary Note 1] A three-dimensional measurement data processing device having a processor, which acquires three-dimensional measurement data obtained by three-dimensionally measuring a concrete structure, extracts a floating area of ​​the concrete structure based on the three-dimensional measurement data, calculates a physical quantity of the floating area based on the three-dimensional measurement data, acquires time-series data of the physical quantity of the floating area, predicts future changes in the physical quantity of the floating area from the time-series data of the physical quantity of the floating area, and outputs information on the predicted changes in the physical quantity of the floating area to a display destination in association with information on the floating area.

[0167] [Supplementary Note 2] The three-dimensional measurement data processing device according to Supplementary Note 1, wherein the processor calculates at least one of an area, a height, and a volume of the floating region as the physical quantity.

[0168] [Supplementary Note 3] The three-dimensional measurement data processing device described in Supplementary Note 1 or 2, wherein the processor calculates at least the volume of the floating region based on the three-dimensional measurement data, acquires information about the concrete structure in the floating region, infers the internal state of the floating region based on the information about the volume of the floating region and the information about the concrete structure in the floating region, and outputs the inferred information about the internal state to the display destination in association with the information about the floating region.

[0169] [Supplementary Note 4] The three-dimensional measurement data processing device according to Supplementary Note 3, wherein the processor estimates, as the internal state, a corrosion rate of reinforcing steel bars present in the floating area.

[0170] [Supplementary Note 5] The three-dimensional measurement data processing device according to Supplementary Note 4, wherein the processor estimates the corrosion rate of the reinforcing steel present in the floating area of ​​the concrete by utilizing a correlation between the volume of the floating area of ​​the concrete and the corrosion rate of the reinforcing steel.

[0171] [Supplementary Note 6] The three-dimensional measurement data processing device described in Supplementary Note 4 or 5, wherein the processor estimates at least one of the amount of corrosion of the reinforcing steel bars and the volume of voids present in the floating area based on the information on the corrosion rate of the reinforcing steel bars, the information on the volume of the floating area, and the information on the concrete structure in the floating area as the internal state.

[0172] [Supplementary Note 7] The 3D measurement data processing device according to any one of Supplementary Notes 3 to 6, wherein the information on the concrete structure in the floating region includes at least one of information on rebar present in the floating region, information on damage, and information on the concrete.

[0173] [Supplementary Note 8] The three-dimensional measurement data processing device according to Supplementary Note 7, wherein the information on the reinforcing bars includes information on the density, length, surface area, and cross-sectional area of ​​the reinforcing bars.

[0174] [Supplementary Note 9] The three-dimensional measurement data processing device according to Supplementary Note 7 or 8, wherein the damage information includes information on cracks, water leaks, and rust fluid.

[0175] [Supplementary Note 10] The three-dimensional measurement data processing device according to any one of Supplementary Notes 7 to 9, wherein the information on the concrete includes information on cover thickness and concrete layer thickness.

[0176] [Supplementary Note 11] The three-dimensional measurement data processing device according to any one of Supplementary Notes 3 to 10, wherein the processor acquires time-series data of the internal state of the floating region, predicts future changes in the internal state from the time-series data of the internal state, and outputs information on the predicted changes in the internal state to the display destination in association with information on the floating region.

[0177] [Supplementary Note 12] The three-dimensional measurement data processing device according to any one of Supplementary Notes 1 to 11, wherein the processor generates a first image indicating a difference from a reference surface for each pixel based on the three-dimensional measurement data, and extracts the floating region based on the first image.

[0178] [Supplementary Note 13] The three-dimensional measurement data processing device according to Supplementary Note 12, wherein the processor: binarizes the first image to extract contours; and applies a filter to the first image from which contours have been extracted, which removes contours other than those of the raised area, to extract the raised area.

[0179] [Supplementary Note 14] The three-dimensional measurement data processing device according to any one of Supplementary Notes 1 to 13, wherein the processor highlights the lifted region in which the physical quantity and / or a change in the physical quantity exceeds a threshold.

[0180] [Supplementary Note 15] The three-dimensional measurement data processing device according to Supplementary Note 4, wherein the processor highlights the lifted region where the corrosion rate of the reinforcing bar and / or the amount of change in the corrosion rate of the reinforcing bar exceeds a threshold.

[0181] [Supplementary Note 16] The three-dimensional measurement data processing device according to any one of Supplementary Notes 1 to 15, wherein the processor acquires a second image of the concrete structure or a three-dimensional model representing the concrete structure, generates a third image in which information about the floating region is superimposed on the second image or the three-dimensional model, and outputs the third image to a display destination.

[0182] [Supplementary Note 17] A three-dimensional measurement data processing method comprising: acquiring three-dimensional measurement data obtained by three-dimensionally measuring a concrete structure; extracting a floating area of ​​the concrete structure based on the three-dimensional measurement data; calculating a physical quantity of the floating area based on the three-dimensional measurement data; acquiring time-series data of the physical quantity of the floating area; predicting future changes in the physical quantity of the floating area from the time-series data of the physical quantity of the floating area; and outputting information on the predicted changes in the physical quantity of the floating area to a display destination in association with information on the floating area.

[0183] [Supplementary Note 18] A three-dimensional measurement data processing program that causes a computer to realize the following functions: a function to acquire three-dimensional measurement data obtained by three-dimensionally measuring a concrete structure; a function to extract a floating area of ​​the concrete structure based on the three-dimensional measurement data; a function to calculate a physical quantity of the floating area based on the three-dimensional measurement data; a function to acquire time-series data of the physical quantity of the floating area; a function to predict future changes in the physical quantity of the floating area from the time-series data of the physical quantity of the floating area; and a function to output information on the predicted changes in the physical quantity of the floating area to a display destination in association with information on the floating area.

[0184] REFERENCE SIGNS LIST 100 Deterioration diagnosis device 101 Processor 102 Main memory unit 103 Auxiliary memory unit 104 Operation unit 105 Display unit 106 Interface unit 110 Data acquisition unit 120 Area extraction unit 121 Height image generation unit 122 Binarization processing unit 123 Contour extraction unit 124 Filter processing unit 130 Physical quantity calculation unit 131 Area calculation unit 132 Height calculation unit 133 Volume calculation unit 140 Internal state estimation unit 141 Information acquisition unit 142 Measurement processing unit 143 Corrosion rate estimation unit 144 Internal configuration estimation unit 150 Recording control unit 160 Fluctuation prediction unit 170 Output control unit 180 Management database A Floating area B Floating area C Contour of floating area Ca Cursor IF Information on physical quantity of floating area IM Height image Rb Reinforcing bar Rb1 Reinforcement bar Rb2 Reinforcement bar Sp Square column specimen Sw Salt water

Claims

1. A three-dimensional measurement data processing device having a processor, which acquires three-dimensional measurement data obtained by three-dimensionally measuring a concrete structure, extracts a floating area of ​​the concrete structure based on the three-dimensional measurement data, calculates physical quantities including at least the volume of the floating area based on the three-dimensional measurement data, and outputs information on the calculated physical quantities including at least the volume of the floating area to a display destination in association with information on the floating area.

2. The three-dimensional measurement data processing device according to claim 1, wherein the processor acquires time-series data of physical quantities including at least the volume of the floating region, predicts future changes in the physical quantities including at least the volume of the floating region from the time-series data of the physical quantities including at least the volume of the floating region, and outputs information on the predicted changes in the physical quantities including at least the volume of the floating region to the display destination in association with information on the floating region.

3. A three-dimensional measurement data processing device as described in claim 1, wherein the processor calculates at least the volume of the floating region based on the three-dimensional measurement data, acquires information about the concrete structure in the floating region, infers the internal state of the floating region based on the information about the volume of the floating region and the information about the concrete structure in the floating region, and outputs the inferred information about the internal state to the display destination in association with the information about the floating region.

4. The three-dimensional measurement data processing device according to claim 3, wherein the processor estimates the corrosion rate of reinforcing steel present in the floating area as the internal state.

5. The three-dimensional measurement data processing device according to claim 4, wherein the processor estimates the corrosion rate of the reinforcing steel present in the floating area by utilizing the correlation between the volume of the floating area of ​​concrete and the corrosion rate of the reinforcing steel.

6. The three-dimensional measurement data processing device of claim 4, wherein the processor further estimates, as the internal state, at least one of the amount of corrosion of the reinforcing steel bars and the volume of voids present in the floating area based on information on the corrosion rate of the reinforcing steel bars, information on the volume of the floating area, and information on the concrete structure in the floating area.

7. The three-dimensional measurement data processing device according to claim 3, wherein the information on the concrete structure in the floating area includes at least one of information on reinforcing bars present in the floating area, information on damage, and information on the concrete.

8. The three-dimensional measurement data processing device according to claim 7, wherein the information on the reinforcing bars includes information on the density, length, surface area, and cross-sectional area of ​​the reinforcing bars.

9. The three-dimensional measurement data processing device according to claim 7, wherein the damage information includes information on cracks, water leaks, and rust.

10. The three-dimensional measurement data processing device according to claim 7, wherein the concrete information includes information on cover thickness and concrete roll thickness.

11. A three-dimensional measurement data processing device according to claim 3, wherein the processor acquires time series data of the internal state of the floating region, predicts future changes in the internal state from the time series data of the internal state, and outputs information on the predicted changes in the internal state to the display destination in association with information on the floating region.

12. A three-dimensional measurement data processing method comprising: acquiring three-dimensional measurement data obtained by three-dimensionally measuring a concrete structure; extracting a floating area of ​​the concrete structure based on the three-dimensional measurement data; calculating a physical quantity including at least the volume of the floating area based on the three-dimensional measurement data; and outputting information on the calculated physical quantity including at least the volume of the floating area to a display destination in association with information on the floating area.

13. A three-dimensional measurement data processing program that causes a computer to perform the following functions: acquire three-dimensional measurement data obtained by three-dimensionally measuring a concrete structure; extract a floating area of ​​the concrete structure based on the three-dimensional measurement data; calculate a physical quantity including at least the volume of the floating area based on the three-dimensional measurement data; and output information on the calculated physical quantity including at least the volume of the floating area to a display destination in association with information on the floating area.

14. A non-transitory computer-readable recording medium on which the program according to claim 13 is recorded.

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