Peeling and flaking identification device, method, and program

Abstract

The present invention provides a peeling and flaking identification device, a method, and a program that make it possible to identify a peeling and flaking part of a surface of concrete or the like of a building. A processor of a peeling and flaking identification device according to the present invention acquires three-dimensional measurement data of a surface of a building, measured for each inspection by a three-dimensional measurement device such as a LiDAR (step S10). The processor acquires difference data of the same measurement point on the surface of the building on the basis of a plurality of items of the three-dimensional measurement data measured for each inspection (step S20). The processor identifies a peeling and flaking part of the surface of the building on the basis of a feature of a time-series change in the acquired difference data (step S30). For example, when the time-series change in the difference data turns from positive to negative or decreases beyond a threshold value, the change part of the difference data is identified as the peeling and flaking part of the surface of the building.

Description

Peeling and peeling identification device, method, and program

[0001] The present invention relates to a peeling and flaking identification device, method, and program, and more particularly to a technique for identifying peeling and flaking portions on the surface of concrete or the like of a building.

[0002] Traditionally, inspections of structures such as tunnels and bridges have typically been carried out by inspectors patrolling the site, and during these inspections, inspectors may find areas of peeling or debris (concrete pieces) on the surface of the structure.

[0003] However, because patrols are man-dependent and cannot always be seen during daylight hours, peeling may be overlooked. To avoid overlooking the problem, the number of patrols is increased and multiple people are required to monitor, but this requires time and money and is not very accurate.

[0004] In recent years, new technologies described in Patent Documents 1-3 and the like have been developed and introduced into infrastructure inspection, and digital transformation (DX) of human-dependent inspections is expected.

[0005] The spalling prediction and diagnosis method described in Patent Document 1 takes an infrared thermal image of the surface of a concrete structure using an infrared camera, and simultaneously measures the outside air temperature near the surface.Based on the infrared thermal image and the outside air temperature, it calculates the temperature difference at the spalling section, which is the temperature difference between the healthy part and the spalled part, and the measured temperature environment, which is the difference between the surface temperature of the healthy part and the outside air temperature.It calculates a temperature environment coefficient as the ratio of the calculated temperature difference at the spalled part to the calculated measured temperature environment, and quantitatively evaluates the risk of the cover concrete (concrete from the steel bar surface to the concrete surface) spalling based on the temperature environment coefficient.

[0006] The inspection method described in Patent Document 2 involves striking an object to be inspected with an inspection hammer device, and determining the state of the object to be inspected based on time history data of sound pressure generated by the striking.

[0007] The non-destructive inspection method for concrete structures described in Patent Document 3 involves contacting an ultrasonic transmitter and receiver with the submerged portion of a concrete structure that is partially or completely submerged, irradiating shear ultrasonic waves from the transmitter into the concrete structure while detecting resonant vibrations of the concrete structure with the receiver, and determining backside damage and / or internal damage to the concrete structure based on the waveform detected by the receiver.

[0008] JP 2016-006398 A JP 2020-098098 A JP 2006-105680 A

[0009] However, none of the techniques described in Patent Documents 1 to 3 identify peeling and flaking areas on the surface of concrete, etc. of a building. In particular, the technique described in Patent Document 1 is a method for quantitatively evaluating the risk of cover concrete peeling, and is not a technique for actually identifying areas where cover concrete has peeled and flaked.

[0010] One embodiment of the technique of the present disclosure provides a peeling and flaking identification device, method, and program that can identify peeling and flaking portions on the surface of concrete or the like of a building.

[0011] The invention of the first aspect is a peeling and delaminating identification device that includes a processor, a program to be executed by the processor, and a memory that stores three-dimensional measurement data of the surface of a structure measured by a measuring device each time the structure is inspected, wherein the processor acquires multiple three-dimensional measurement data of the surface of the structure measured each time the inspection is performed, acquires difference data for the same measurement point on the surface of the structure based on the multiple three-dimensional measurement data, and identifies peeling and delaminating portions on the surface of the structure based on characteristics of changes in the difference data.

[0012] According to a first aspect of the present invention, multiple pieces of 3D measurement data of the surface of a building measured at each inspection are obtained, and difference data for the same measurement point on the surface of the building is obtained based on the multiple pieces of 3D measurement data. Peeling and delamination on the surface of the building are then identified based on the characteristics of the chronological changes in the difference data. Peeling and delamination on the surface of a building occurs when the surface gradually increases in volume (floating) and then falls off completely, and this change makes it possible to identify the peeling and delamination on the surface of the building.

[0013] In the second aspect of the peeling and delaminating identification device of the present invention, in the first aspect, it is preferable that the processor identifies the change in the differential data as a peeling and delaminating portion on the surface of the building when the change in the differential data turns negative, when the change in the differential data turns from positive to negative, or when the change in the differential data decreases by exceeding a threshold value.

[0014] In the third aspect of the present invention, in the first or second aspect, the processor preferably detects raised portions and depressed portions on the surface of a structure based on changes in the difference data, and when raised portions and depressed portions on the same part of the surface of the structure are detected in chronological order of inspection, identifies the depressed portion as a peeled or fallen portion on the surface of the structure. The raised portion is a candidate portion for a peeled or fallen portion, and when the raised portion changes to a depressed portion, the depressed portion can be identified as a peeled or fallen portion.

[0015] In the fourth aspect of the peeling and delaminating identification device of the present invention, in any of the first to third aspects, the processor preferably determines whether the changed portion of the differential data is a crack or not, and if it determines that it is not a crack, identifies the changed portion as a peeling and delaminating portion on the surface of the building.

[0016] In the peeling and delaminating identification device of the fifth aspect of the present invention, in any of the first to fourth aspects, it is preferable that the processor measures the width and height of the changed portion of the differential data, and if the shorter of the width or height exceeds a second threshold value, identifies the changed portion as a peeling and delaminating portion on the surface of the building.

[0017] In the peeling and delaminating identification device of the sixth aspect of the present invention, in any of the first to fourth aspects, it is preferable that the processor measures the area of ​​the changed portion of the differential data, and if the area exceeds a third threshold, identifies the changed portion as a peeling and delaminating portion on the surface of the building.

[0018] In a seventh aspect of the present invention, in any one of the first to sixth aspects, the processor acquires an image of the structure captured by the imaging device, detects cracks in the structure based on the captured image, and determines whether a change in the difference data represents a peeled or peeled portion on the surface of the structure or a crack based on the crack detection result, because detecting cracks based on the captured image is preferable to detecting cracks from three-dimensional measurement data.

[0019] In the peeling and delaminating portion identifying device according to an eighth aspect of the present invention, in any one of the first to seventh aspects, the processor preferably displays the identified peeling and delaminating portion in an identifiable manner on a screen of a display that displays three-dimensional measurement data, design surface data of the building, or an image of the building captured by an imaging device, allowing a user (inspector) to confirm on the screen of the display where the peeling and delaminating portion exists on the building.

[0020] A ninth aspect of the present invention provides a peeling and falling off identifying device according to any one of the first to eighth aspects, wherein the measurement device includes a LiDAR or a stereo camera.

[0021] A tenth aspect of the present invention provides a peeling and delamination identifying device according to the ninth aspect, wherein the LiDAR measures three-dimensional measurement data using a frequency modulated continuous wave (FMCW) method, which makes it possible to detect surface characteristics of a building that cannot be confirmed visually.

[0022] In the peeling and falling apart identifying device according to an eleventh aspect of the present invention, in any one of the first to tenth aspects, it is preferable that the material of the surface of the building includes concrete or a concrete repair material.

[0023] The invention of the twelfth aspect is a peeling and flaking identification method in which a processor identifies peeling and flaking on the surface of a building, the method including the steps of acquiring multiple three-dimensional measurement data of the surface of the building measured by a measuring device for each inspection, acquiring difference data for the same measurement point on the surface of the building based on the multiple three-dimensional measurement data, and identifying peeling and flaking portions on the surface of the building based on characteristics of changes in the difference data.

[0024] In the peeling and delaminating identification method according to the thirteenth aspect of the present invention, in the twelfth aspect, it is preferable that the processor identifies the change in the differential data as a peeling and delaminating part on the surface of the building when the change in the differential data turns negative, when the change in the differential data turns from positive to negative, or when the change in the differential data decreases by exceeding a threshold value.

[0025] A method for identifying peeling and delamination according to a fourteenth aspect of the present invention is preferably such that, in the twelfth or thirteenth aspect, a processor detects raised and depressed portions on the surface of a structure based on changes in differential data, and, when raised and depressed portions on the same part of the surface of the structure are detected in chronological order of inspection, identifies the depressed portions as peeling and delamination portions on the surface of the structure.

[0026] The invention of the fifteenth aspect is a peeling and flaking identification program that identifies peeling and flaking on the surface of a building, and causes a computer to execute the following functions: a function to acquire multiple three-dimensional measurement data of the surface of the building measured by a measuring device for each inspection; a function to acquire difference data for the same measurement point on the surface of the building based on the multiple three-dimensional measurement data; and a function to identify peeling and flaking parts on the surface of the building based on the characteristics of changes in the difference data.

[0027] According to the present invention, peeled and fallen portions on the surface of concrete or the like of a building can be identified with high accuracy.

[0028] FIG. 1 is a graph showing the relationship between the elapsed time after construction of a building and the surface displacement and peeling / fracture of the building, and a diagram showing an example of a cross-section of a building at each inspection. FIG. 2 is a schematic diagram of a building inspection system including a peeling / fracture identifying device according to the present invention. FIG. 3 is an external view of an embodiment of a three-dimensional measuring device including an FMCW-type LiDAR. FIG. 4 is a diagram showing an embodiment of measuring the three-dimensional shape of a building's surface using a stereo camera. FIG. 5 is a cross-sectional view of the vicinity of a building's surface showing an example of a mechanism by which the building's surface peels. FIG. 6 is a cross-sectional view of the vicinity of a building's surface showing another example of a mechanism by which the building's surface peels. FIG. 7 is a block diagram showing an embodiment of the hardware configuration of a peeling / fracture identifying device according to the present invention. FIG. 8 is a diagram showing an example of a method for detecting recessed portions that are candidates for peeled / fracture portions on the surface of a building. FIG. 9 is a diagram showing another example of a method for detecting recessed portions that are candidates for peeled / fracture portions on the surface of a building. FIG. 10 is a captured image of a building including peeled / fracture portions and cracked portions. FIG. 11 is a diagram showing an example of the surface texture of a building based on a large number of measurement points (measurement points distributed two-dimensionally) measured by a three-dimensional measuring device. FIG. 12 is a diagram showing another example of the surface texture of a building based on a large number of measurement points measured by a three-dimensional measuring device. FIG. 13 is a diagram showing an example of a surface texture image of a building displayed on a display. FIG. 14 is a graph showing a first example of the amount of protrusion that changes over time on the surface of a building. FIG. 15 is a graph showing a second example of the amount of protrusion that changes over time on the surface of a building. FIG. 16 is a graph showing a third example of the amount of protrusion that changes over time on the surface of a building. FIG. 17 is a graph showing the rate of change in the amount of lift that changes over time on the surface of a building. FIG. 18 is a diagram showing an example of a screen of a display on which peeled and flaked portions of the surface of a building are displayed. FIG. 19 is a flowchart showing an embodiment of a peeling and flaking identification method according to the present invention.

[0029] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Preferred embodiments of a peeling and peeling identifying device, method, and program according to the present invention will now be described with reference to the accompanying drawings.

[0030] [Outline of the Invention] FIG. 1 is a graph showing the relationship between the time elapsed after construction of a building and the surface displacement and peeling / falling of the building, and a diagram showing an example of a cross section of the building at each inspection time.

[0031] In Figure 1, the displacement of the structure's surface is measured at the start of inspection of the structure (the start of measurement during construction) t1, and at each subsequent inspection point (t2, t3, t4, t5, ...). By comparing the displacements at the same position on the structure's surface, it is possible to observe areas where the surface rises over time since the construction of the structure.

[0032] In the example shown in Figure 1, the building is in a normal state (A) at the start of measurement time t1, but at the inspection time t2, the surface has slightly bulged due to deterioration of the building (cracks (B)). At this stage, the bulge is not noticeable by visual inspection. Note that "cracks" are often caused by corrosion and thickening of the steel (reinforcing bars) inside the building.

[0033] At the initial stage of lifting (C) shown at inspection time t3, as corrosion of the reinforcing bars progresses, cracks also progress, causing the surface of the building to swell (lifting occurs).

[0034] At the final stage of the lifting (D) shown at inspection time t4, the "cracks" have progressed further, reaching the surface of the building, and the "lifting" has become even larger.

[0035] The inspection time point t5 indicates the time point when the concrete cover (concrete from the rebar surface to the concrete surface) falls ((E) Peeling / Falling).

[0036] In the example shown in Figure 1, the displacement (amount of rise) of the surface of the building measured at each inspection gradually increases, and the cover concrete begins to peel and fall off.

[0037] Regardless of the cause, spalling causes abnormalities on the concrete surface, and highly accurate surface displacement measurement makes it possible to detect even the slightest spalling without missing it.

[0038] Therefore, the present invention acquires 3D measurement data indicating the surface displacement of a structure measured at each inspection of the structure, then acquires difference data for the same measurement point on the structure's surface based on the multiple 3D measurement data acquired at each inspection of the structure, and identifies peeled and delaminated areas on the structure's surface based on characteristics of changes in the difference data that are specific to the peeled and delaminated areas.

[0039] [General Configuration of Inspection System] FIG. 2 is a schematic diagram of a building inspection system including a peeling and falling off identifying device according to the present invention.

[0040] The inspection system shown in FIG. 2 is a system for inspecting railway tunnels, and includes a three-dimensional measuring device 10, a data processing device 14, and a power supply device 16.

[0041] The three-dimensional measuring device 10 is mounted on a tripod 12, but may also be mounted on a carriage 18 that travels on a railroad track.

[0042] In this example, the three-dimensional measuring device 10 is a LiDAR (Light Detection And Ranging), and in particular, a FMCW (Frequency Modulated Continuous Wave) LiDAR that can measure distances on the order of several hundred μm, but the present invention is not limited to using distance data (three-dimensional measurement data) measured by an FMCW LiDAR.

[0043] [Three-dimensional Measuring Apparatus] FIG. 3 is an external view of one embodiment of a three-dimensional measuring apparatus including an FMCW LiDAR.

[0044] In FIG. 3, the three-dimensional measuring device 10 is mounted on a carriage 18 that travels on the railroad tracks as shown in FIG. 2, and measures the distance to the surface of a tunnel, which is a railway structure.

[0045] In addition to the three-dimensional measuring device 10, the carriage 18 is also equipped with a data processing device 14 and a power supply device 16. The power supply device 16 supplies power to the three-dimensional measuring device 10 and the data processing device 14.

[0046] The three-dimensional measuring device 10 measures the distance to a tunnel wall (surface) 20 to obtain three-dimensional measurement data indicating the shape of the tunnel wall 20 .

[0047] In the example shown in Fig. 3, the three-dimensional measuring device 10 scans the wall surface 20 shown in Fig. 3 in the left-right direction (main scanning direction) with an FMCW laser beam at high speed, while also moving the scanning line up and down (sub-scanning direction) across the wall surface 20. This measures the distance from the measurement head of the three-dimensional measuring device 10 to multiple measurement points on each scanning line of the laser beam. Then, three-dimensional data in a polar coordinate system consisting of the irradiation direction of the laser beam and the measured distance is converted into three-dimensional data in a Cartesian coordinate system, thereby obtaining three-dimensional measurement data that indicates the shape of the wall surface 20. In this example, three-dimensional measurement data (point cloud data) of multiple measurement points is obtained as the three-dimensional measurement data.

[0048] The three-dimensional measuring device 10 is considered to measure the uneven shape of the minute wall surface 20 under the following conditions: Measurement accuracy: 50 μm Measurement distance: 2 to 7 m Measurement speed: 10 m for area 2 / sec (laser light speed is equivalent to 4000 rpm)

[0049] Furthermore, the three-dimensional measuring device 10 acquires three-dimensional data of the wall surface 20 at regular intervals while the carriage 18 is moving, and it is preferable to acquire the three-dimensional data so that the measurement areas of the three-dimensional data acquired at each interval partially overlap, in order to synthesize the three-dimensional data acquired at each interval into a panoramic image.

[0050] The three-dimensional measuring device 10 can achieve the above measurement accuracy by using an FMCW LiDAR, but the conditions such as the measurement accuracy of the three-dimensional measurement data required in the present invention are not limited to the above example, and various three-dimensional measuring devices can be applied, not just FMCW LiDAR.

[0051] For example, instead of the FMCW LiDAR, a TOF (Time of Flight) LiDAR can be used, which measures the time of flight of pulsed projected light to measure the distance to the wall surface 20. Also, the three-dimensional shape of the wall surface 20 can be measured using a stereo camera.

[0052] FIG. 4 is a diagram showing an embodiment in which the three-dimensional shape of the surface of a building is measured using a stereo camera.

[0053] The stereo camera shown in FIG. 4 is composed of a left camera 30L and a right camera 30R, and measures the distance to the wall surface 20 of the photographing target by triangulation.

[0054] Other three-dimensional measuring devices that can be used to measure the distance to the wall surface 20 (i.e., three-dimensional measurement data of the wall surface) include the laser radar three-dimensional shape measuring device described in Japanese Patent Laid-Open No. 9-297014, the imaging device described in Japanese Patent Laid-Open No. 2021-2016-31249, a measuring device using a light-cutting method using a slit laser light projector, an FM laser radar type distance measuring device described in Japanese Patent No. 3194586, and an optical rangefinder described in Japanese Patent No. 3583906.

[0055] The three-dimensional shape of the tunnel wall surface 20 is measured by the three-dimensional measuring device 10 at the start of measurement (construction) of the tunnel and at the time of periodic inspection after construction. The three-dimensional measurement data of the measured wall surface is stored in a storage device within the data processing device 14 or an external storage device at the start of measurement and at the time of periodic inspection.

[0056] [Mechanism of Peeling of Surface Material of Building] FIG. 5 is a cross-sectional view of the vicinity of the surface of a building, showing an example of the mechanism by which the surface of a building peels off.

[0057] "(A) Normal state" in Figure 5 refers to a normal state such as during construction of a building. The surface in this state is the reference plane. In Figure 5, 40 denotes steel material (reinforcing bars).

[0058] The "(B) Cracks," "(C) Early stage of lifting / steel fracture," "(D) Final stage of lifting," and "(C) Peeling" in Figure 5 are caused by corrosion of the reinforcing bars 40 (e.g., salt damage or water leakage), and occur over time since the tunnel was constructed.

[0059] After "(C) Early stage of lifting / steel fracture" in Figure 5, the surface of the building gradually becomes higher than the reference level ("lifting" occurs), leading to the peeling of the cover concrete.

[0060] FIG. 6 is a cross-sectional view of the vicinity of the surface of a building, showing another example of the mechanism by which the surface of the building peels off.

[0061] "(A) Normal state" in Figure 6 refers to a normal state, such as during construction of a building. The surface in this state is taken as the reference surface. In Figure 6, 50 denotes reactive aggregate, and 60 denotes steel.

[0062] The "(B) Cracks," "(C) Early stage of lifting / steel fracture," "(D) Final stage of lifting," and "(C) Peeling" in Figure 5 are caused by deterioration of the concrete strength (e.g., alkali reaction of reactive aggregate 50), and occur over time since construction.

[0063] After "(C) Initial stage of lifting / steel fracture" in Figure 6, the surface of the building gradually becomes higher than the reference level ("lifting" occurs), leading to the peeling of the cover concrete from the surface of the steel 60 to the surface.

[0064] As shown in Figures 5 and 6, if the surface of a building changes over time and "lifting" occurs, "peeling" will occur in the future. This applies regardless of the cause of the "lifting." In other words, it does not matter whether there is reinforcing bars, their material, or shape, or the material and shape of the concrete, how the reinforcing bars are inserted into the concrete, the construction method, or the cause of corrosion (neutralization, frost damage, poor construction, etc.).

[0065] [Hardware Configuration of Peeling and Falling Identifying Device] FIG. 7 is a block diagram showing an embodiment of the hardware configuration of a peeling and falling identifying device according to the present invention.

[0066] 7 is configured, for example, by a personal computer, a workstation, or the like, and includes a processor 110, a memory 120, a display 130, an input / output interface 140, and an operation unit 150. This peeling and peeling identifying device 100 can be incorporated as one function of the data processing device 14 shown in FIG.

[0067] The processor 110 is composed of a CPU (Central Processing Unit) and the like, and controls each part of the peeling and delamination identification device 100, and executes a peeling and delamination identification program to perform various processes for identifying peeling and delamination parts on the surface of the building. Details of the various processes performed by the processor 110 will be described later.

[0068] The memory 120 includes a flash memory, a read-only memory (ROM), a random access memory (RAM), a hard disk drive, etc. The flash memory, ROM, or hard disk drive is a non-volatile memory that stores an operating system, various programs including the peeling and flake identification program according to the present invention, etc. Furthermore, the non-volatile memory (storage device) such as the flash memory or hard disk drive can store the 3D measurement data of the surface of the structure measured by the 3D measurement device 10 at the start of measurement of the structure and during periodic inspections, along with the measurement time.

[0069] The RAM functions as a working area for processing by the processor 110. It also temporarily stores various programs stored in flash memory or the like, and three-dimensional measurement data of the surface of a building. Note that the processor 110 may have part of the memory 120 (RAM) built in.

[0070] The display 130 not only displays a screen for operating the peeling and peeling identifying device 100, but also displays the design surface data of the building read from the memory 120, or an image (including a panoramic composite image) of the building taken by one of the stereo cameras shown in Figure 4 or another imaging device (not shown), and further displays the peeling and peeling parts identified by the peeling and peeling identifying device 100 in an identifiable manner on the surface data or the image.

[0071] The input / output interface 140 includes a connection unit connectable to an external device, a communication unit connectable to a network, etc. As the connection unit connectable to an external device, a Universal Serial Bus (USB), a High-Definition Multimedia Interface (HDMI) (HDMI is a registered trademark), etc. can be applied.

[0072] The peeling and delamination identifying device 100 can be configured as a device independent of the data processing device 14. In this case, the processor 110 can acquire three-dimensional measurement data of the surface of the structure from the data processing device 14 via the input / output interface 140, or, if the three-dimensional measurement data is stored in the cloud, acquire the three-dimensional measurement data of the surface of the structure from the cloud via the input / output interface 140. The processor 110 can also store the three-dimensional measurement data acquired in this way in the memory 120.

[0073] The operation unit 150 includes a pointing device such as a mouse, a keyboard, and the like, and functions as part of a GUI (Graphical User Interface) that uses the display screen of the display device 130 and accepts instruction inputs by user operation.

[0074] FIG. 8 is a diagram showing an example of a method for detecting recessed portions that are candidates for peeled and fallen portions on the surface of a building.

[0075] FIG. 8A is a diagram showing the surface of a building and the scanning line of the laser light that scans the surface.

[0076] The three-dimensional measuring device 10 acquires three-dimensional measurement data (point cloud data) of a large number of measurement points on a scanning line of a laser beam.

[0077] The processor 110 compares the 3D measurement data of the structure's surface with reference surface data that indicates a reference surface, and detects protrusions, depressions, etc. on the structure's surface. That is, by subtracting the reference surface data from the 3D measurement data, height (convex / concave) data of the structure's surface on the scanning line of the laser light is calculated.

[0078] FIG. 8B is a waveform diagram showing the height of the surface of a building obtained from point cloud data on a scanning line.

[0079] As shown in Figure 8(B), the areas where the height data is negative (areas lower than the reference surface) are depressions, and are candidates for peeling and falling areas. The reference surface data indicating the reference surface can be defined in various ways, but it can be surface data obtained by averaging the unevenness of the surface of the building indicated by the three-dimensional measurement data, or surface data in the design of the building.

[0080] The processor 110 preferably compares the depressions detected as described above with a first threshold value (Th1) to determine whether the depressions exceed the first threshold value (Th1), and designates depressions that exceed the first threshold value (Th1) as candidates for peeled and fallen portions, while excluding other depressions from the candidates for peeled and fallen portions. This is because slight irregularities (depressions) exist on the surface of the building from the time of construction, and such depressions are to be excluded.

[0081] FIG. 9 is a diagram showing another example of a method for detecting recessed portions that are candidates for peeled and fallen portions on the surface of a building.

[0082] FIG. 9A is a diagram showing the surface of a building and the scanning line of the laser light that scans the surface, similar to FIG. 8A.

[0083] The three-dimensional measurement device 10 acquires three-dimensional measurement data of a large number of measurement points on the scanning line of the laser light. The memory 120 stores the three-dimensional measurement data of the surface of the structure measured by the three-dimensional measurement device 10 for each inspection of the structure.

[0084] Fig. 9(B) is a waveform diagram showing the height (h1) of the surface of the structure at a certain inspection time T1. The height (h1) of the surface of the structure shown in Fig. 9(B) is acquired based on the three-dimensional measurement data on the scanning line shown in Fig. 9(A) measured at the inspection time T1.

[0085] Fig. 9(C) is a waveform diagram showing the height (h2) of the surface of the structure at inspection time T2, which is later than inspection time T1. The height (h2) of the surface of the structure shown in Fig. 9(C) is obtained based on the three-dimensional measurement data on the scanning line shown in Fig. 9(A) measured at inspection time T2.

[0086] Figure 9 (D) is a waveform diagram showing the difference (h1-h2) at the same measurement point on the surface of a building, obtained by subtracting the height (h2) of the surface of the building at inspection time T2 shown in Figure 9 (C) from the height (h1) of the surface of the building at inspection time T1 shown in Figure 9 (B).

[0087] If the difference (h1-h2) is positive, the surface of the structure has become lower (depressed) by that difference (h1-h2) during the period from inspection time T1 to inspection time T2. Conversely, if the difference (h1-h2) is negative, the surface of the structure has become higher (risen) by that difference (h1-h2) during the period from inspection time T1 to inspection time T2.

[0088] The processor 110 can detect raised and depressed portions on the surface of the structure by obtaining difference data for the same measurement point on the surface of the structure based on multiple pieces of 3D measurement data measured during each inspection. In this example, depressed portions on the surface of the structure can be detected from positive difference data, and raised portions on the surface of the structure can be detected from negative difference data. Furthermore, among the different 3D measurement data during inspections used to obtain difference data, the 3D measurement data from earlier in the inspection serves as reference surface data for the 3D measurement data from later in the inspection.

[0089] Next, the processor 110 determines whether the depression in the surface of the building detected as described above is a "crack."

[0090] FIG. 10 is a captured image of a building including peeled and fallen portions and cracked portions.

[0091] The peeled and fallen portion shown in Fig. 10 includes a cracked portion. In addition, the captured image shown in Fig. 10 also includes a single cracked portion that is not included in the peeled and fallen portion.

[0092] FIG. 11 is a diagram showing an example of the surface texture of a building based on a large number of measurement points (measurement points distributed two-dimensionally) measured by a three-dimensional measuring device.

[0093] In Figure 11, of the measurement points shown in the point cloud, measurement points whose height data exceeds the first threshold (Th1) are shown with white circles, and measurement points whose height data is equal to or less than the first threshold (Th1) are shown with black circles.

[0094] In Figure 11, the measurement point indicated by the 7x1 white circle in the center corresponds to the "crack," and the measurement point indicated by the 8x4 white circle to the left of it corresponds to the "peeled and peeled portion." Note that the depression corresponding to this "peeled and peeled portion" contains the "crack."

[0095] The processor 110 determines whether the recessed portion is a "crack" or not by one or more of the following methods.

[0096] (1) The width and height of the depression are measured, and if the shorter of the width and height exceeds a second threshold value (Th2), the depression is determined not to be a "crack."

[0097] The processor 110 detects recessed portions exceeding the first threshold value (Th1) from height data of a large number of measurement points (measurement points distributed two-dimensionally) on a plurality of scanning lines by the measurement head of the three-dimensional measuring device 10. In the example shown in Fig. 11, the measurement points indicated by white circles exceed the first threshold value (Th1) as described above.

[0098] The processor 110 measures the width and height of a rectangle inscribed in a "depression" that exceeds a first threshold (Th1), and if the shorter of the width or height exceeds a second threshold (Th2), it determines that the depression is not a "crack."

[0099] 11, the shorter width of the depression indicated by the 7 × 1 white circle measurement points corresponds to one measurement point, and is less than the second threshold value (Th2), so the depression is determined to be a "crack." The spacing between adjacent measurement points can be determined in advance based on the measurement distance to the surface of the structure, the scanning speed of the three-dimensional measurement device 10, etc.

[0100] On the other hand, the shorter width of the depression indicated by the 8 x 4 white circle measurement points is a width equivalent to four measurement points, and if the second threshold (Th2) is taken as a width equivalent to three measurement points, then this exceeds the second threshold (Th2), and therefore the depression is determined not to be a "crack." Note that although the depression indicated by the 8 x 4 white circle measurement points includes a crack, this does not hinder the identification of a "peeling or peeling portion" in a later stage.

[0101] FIG. 12 is a diagram showing another example of the surface texture of a building based on two-dimensional measurement points obtained by a three-dimensional measuring device.

[0102] 12, the processor 110 measures the width (W) and height (H) of a depression (a rectangle inscribed in a group of points indicated by a white circle) that exceeds the first threshold (Th1). In the example shown in FIG. 12, the width (W) corresponds to the width of 12 measurement points, and the height (H) corresponds to the width of 10 measurement points.

[0103] If the shorter of the width (W) and the height (H) (in the example of Figure 11, the height (H)) exceeds the second threshold (Th2), the processor 110 determines that the depression is not a "crack."

[0104] (2) The area of ​​the depression is measured, and if the area exceeds a third threshold (Th3), the depression is determined not to be a "crack."

[0105] The processor 110 detects a depression that exceeds the first threshold (Th1) in the same manner as above, and if the area of ​​the detected depression (corresponding to the number of points in the depression) exceeds the third threshold (Th3), it determines that the depression is not a "crack."

[0106] (3) An image of the building captured by the imaging device is acquired, and image processing is performed to detect "cracks" based on the captured image, and based on the crack detection results, it is determined whether the depression is a "crack."

[0107] The processor 110 acquires images of the building captured by the imaging device and detects cracks in the building based on the captured images. Based on the crack detection results, it determines whether or not a depression is a crack. Note that methods for detecting "cracks" from captured images are well known, and cracks can be detected more accurately by using captured images with a higher resolution than 3D measurement data.

[0108] <Method for Identifying Peeled and Fallen Portions> FIG. 13 is a diagram showing an example of a surface property image of a building displayed on a display.

[0109] The surface texture image shown in Fig. 13 is an image composed of multiple points uniformly distributed on the surface of a building. Each point in this image is composed of brightness data or color data that varies in brightness or color depending on the magnitude of the protrusion at the corresponding measurement point.

[0110] Therefore, the surface property image displayed on the display 130 is an image composed of multiple points uniformly distributed on the surface of the building, and each point has an area (point area) with different brightness or color depending on the height of its position.

[0111] 13, the images of the points included in the frames A1 to A4 have different brightness or color compared to the other regions, which allows the user to recognize that the regions included in the frames A1 to A4 are higher protruding regions or lower recessed regions compared to the other regions.

[0112] Here, a case will be described in which the user inputs, via the operation unit 150, any position (in this example, the position of a point) on the surface texture image displayed on the display 130 as a point of interest.

[0113] In the embodiment shown in Figure 13, the surface property image displayed on the display 130 is an image composed of multiple points uniformly distributed on the surface of the building, but is not limited to this and can be, for example, a heat map, a grayscale image, or a contour map according to the height of the surface of the building.

[0114] When the processor 110 receives a user input specifying a position on the surface texture image displayed on the display 130 as a point of interest, the processor 110 creates a graph corresponding to the received point of interest.

[0115] <Generation and display of graphs> The processor 110 acquires height data (amount of rise, etc.) based on the three-dimensional measurement data of the structure measured at the start of measurement of the structure and during regular inspections, at the position of the point of interest for which user input has been accepted.

[0116] Next, the processor 110 predicts the future amount of rise at the point of interest based on the inspection period and the amount of rise at each inspection, and creates a graph showing the change in the actually measured amount of rise at the point of interest over time and the predicted change in the amount of rise at the point of interest over time.

[0117] FIG. 14 is a graph showing a first example of the amount of rise of a building that changes over time.

[0118] In graph a1 in Figure 14, when the position of any point within frame A1 in Figure 13 is input by the user as a point of interest, processor 110 plots points indicating the amount of bulge on the surface corresponding to the point of interest at the start of measurement (year 0) and the amount of bulge on the surface at the time of regular inspections after 2, 4, 6, and 8 years have passed, and by connecting the plotted points, creates a graph (shown by a solid line) showing the change over time in the amount of bulge on the surface at the point of interest that has actually been measured.It also predicts the amount of bulge in the future from the amount of bulge on the surface corresponding to the point of interest at the start of measurement and the amount of bulge on the surface at each inspection, and creates a graph (shown by a dotted line) showing the change over time in the predicted amount of bulge.

[0119] The graph shown by the solid line can be, for example, an Nth-order spline curve that smoothly connects the (N+1) discrete points when each plotted point is (N+1) discrete points, and the graph shown by the dotted line can be a graph on that spline curve.

[0120] After creating the graph, the processor 110 outputs the created graph to the display 130 .

[0121] Figure 14 shows four graphs a1 to a4, but if the user inputs the position of any point within frame A1 in Figure 13 as a point of interest, only graph a1 will be displayed on the display 130.

[0122] FIG. 15 is a graph showing a second example of the amount of swelling that changes over time on the surface of a building.

[0123] The graph shown in FIG. 15 differs from the graph shown in FIG. 14 in that information on the surface texture at the time of the periodic inspection after 10 years has been added.

[0124] According to graphs a2 to a4 in Figure 15, the amount of bulge at the time of the 10-year regular inspection matches the amount of bulge on the graph (predicted graph) shown in Figure 14, but the amount of bulge shown in graph a1 is negative (depression). In other words, the amount of bulge on the surface of the building monotonically increases up to the eighth year after the construction of the building (see Figure 14), but at the time of the 10-year inspection, there are areas where the "bulge" has turned into a "depression."

[0125] FIG. 16 is a graph showing a third example of the amount of swelling that changes over time on the surface of a building.

[0126] The graph shown in FIG. 16 differs from the graph shown in FIG. 14 in that information on the surface texture at the time of the regular inspection after 10 years has been passed has been added, and also differs from the graph shown in FIG. 15 in the change in graph a1 after 10 years.

[0127] That is, according to the graph a1 shown in FIG. 16, the amount of swelling at the time of the periodic inspection in the 10th year has turned negative, but it is different in that it has not become a recessed portion.

[0128] FIG. 17 is a graph showing the rate of change in the amount of lift that changes over time on the surface of a building.

[0129] Here, the "amount of float" can be calculated by subtracting the amount of float measured at the start of measurement at the same position from the amount of float measured at each inspection, and the vertical axis of the graph shown in Figure 17 indicates the rate of change of the "amount of float."

[0130] According to the graph shown in Figure 17, the rate of change in the "amount of lift" at the measurement points within box A1 shown in Figure 13 turned negative from the 8th year inspection to the 10th year inspection. The higher the rate of change in the "amount of lift," the higher the risk of peeling and falling. Figure 17 also shows the peeling risk threshold.

[0131] When the processor 110 receives a user input specifying a point of interest on the surface texture image displayed on the display 130, it can create a graph showing the change over time in the amount of protrusion on the surface of the structure shown in Figures 14 to 16, or a graph showing the rate of change over time in the amount of lift on the surface of the structure shown in Figure 17, and display the created graph on the display 130. The graph in Figure 17 makes it easy to grasp whether the rate of change in the "amount of lift" is increasing or decreasing.

[0132] The user can recognize the peeled and fallen portions from the change in the graph displayed on the display 130.

[0133] In addition, the processor 110 can create and display the graphs shown in Figures 14 to 17, or can automatically identify peeled and fallen areas from the characteristics of changes in the surface properties of the building without creating and displaying the graphs.

[0134] That is, the processor 110 acquires multiple pieces of 3D measurement data of the structure surface measured for each inspection from the memory 120, etc., and acquires difference data for the same measurement point on the structure surface based on these 3D measurement data. Then, based on the characteristics of changes in the difference data, it identifies peeled and flaked areas on the structure surface.

[0135] As shown in the graphs of Figures 15 to 17, when the change in the differential data turns negative, when the change in the differential data turns from positive to negative, or when the change in the differential data decreases (for example, when it decreases beyond a "threshold value"), the processor 110 can identify such a change in the differential data as a peeling or flaking portion on the surface of the building.

[0136] Furthermore, the processor 110 detects raised and depressed portions on the surface of the structure based on changes in the difference data, and when raised and depressed portions on the same part of the surface of the structure are detected in chronological order of inspection, the depressed portion can be identified as a peeled or flaked portion on the surface of the structure, because it is believed that the raised portion has peeled or flaked.

[0137] Furthermore, for a candidate for a "peeling or peeling portion" that has been determined not to be a "crack" based on the size or area of ​​the changed portion of the differential data or image processing of the captured image, if the characteristics of the change in the differential data over time indicate "peeling or peeling," the processor 110 can identify the candidate for a "peeling or peeling portion" as a "peeling or peeling portion," thereby enabling the "peeling or peeling portion" to be identified more accurately.

[0138] <Display of Peeling and Falling Off Portions> When the processor 110 identifies peeling and falling off portions on the surface of the building, the processor 110 displays the identified peeling and falling off portions on the screen of the display 130 so that the user can check them.

[0139] The processor 110 can display on the display 130 the measured three-dimensional measurement data, the design surface data of the building, or an image of the building captured by an imaging device, but it is preferable to display the identified peeled and flaked parts in an identifiable manner on the screen of the display 130 that displays these data or captured images.

[0140] FIG. 18 is a diagram showing an example of a screen of a display device on which peeled and fallen parts and the like are displayed.

[0141] On the screen of the display 130 shown in FIG. 18, the peeled and fallen portion (H) and the cracked portions (C1 to C5) are displayed superimposed on the captured image of the surface of the building.

[0142] The peeled and flaked portions (H) are displayed in a different brightness or color from the captured image of the surface of the building in the background, so that they can be easily identified by the user. The detected crack portions (C1 to C5) are also highlighted on the screen of the display 130, but the detection of the crack portions (C1 to C5) and the highlighting of the crack portions (C1 to C5) are not necessarily required. The captured image displayed on the display 130 may also be a panoramic image created by combining multiple captured images.

[0143] [Method for Identifying Peeling and Falling Off] FIG. 19 is a flowchart showing an embodiment of a method for identifying peeling and falling off according to the present invention.

[0144] The peeling / flake identifying method shown in FIG. 19 is a method performed by the processor 110 of the peeling / flake identifying device 100 shown in FIG.

[0145] 19, the processor 110 acquires the three-dimensional measurement data measured by the three-dimensional measurement device 10 (see FIG. 3) for each inspection of the building (step S10). The processor 110 may acquire the three-dimensional measurement data from the storage device of the data processing device 14, the cloud, etc., or from the memory 120 of the peeling and delamination identifying device 100.

[0146] The processor 110 acquires differential data for the same measurement point on the surface of the structure based on the multiple pieces of three-dimensional measurement data measured for each inspection (step S20).

[0147] Next, processor 110 identifies peeled or flaked portions on the surface of the structure based on the characteristics of the change in the difference data acquired in step S20 (step S30). For example, processor 110 can identify a change in the difference data as a peeled or flaked portion on the surface of the structure if the change in the difference data turns negative, if the change in the difference data turns from positive to negative, or if the change in the difference data decreases beyond a threshold. Furthermore, processor 110 can detect raised and depressed portions on the surface of the structure based on the change in the difference data, and if raised and depressed portions on the same portion of the surface of the structure are detected in chronological order of inspection, the depressed portion can be identified as a peeled or flaked portion on the surface of the structure.

[0148] In step S40, it is determined whether or not a peeled or peeled portion was identified in step S30. If the peeled or peeled portion could not be identified (if "No"), this process is terminated, and if the peeled or peeled portion was identified (if "Yes"), the process proceeds to step S50, where the peeled or peeled portion is notified.

[0149] For example, the processor 110 displays the identified peeled and fallen portions (H) in an identifiable manner on the screen of the display 130 that displays the surface of the building (see FIG. 13 ), allowing the inspector to easily identify the peeled and fallen portions on the surface of the concrete or the like of the building.

[0150] [Others] The structure in this embodiment is a tunnel, but is not limited to this and may be any structure that is inspected, such as a bridge or a dam. The surface material of the structure includes reinforced concrete, concrete, and concrete repair materials such as mortar.

[0151] In this embodiment, the hardware structure of a processing unit that executes various processes, such as a CPU (Central Processing Unit), is various processors as shown below. The various processors include a CPU, which is a general-purpose processor that executes software (programs) to function as various processing units, a programmable logic device (PLD), such as an FPGA (Field Programmable Gate Array), whose circuit configuration can be changed after manufacture, and a dedicated electrical circuit, such as an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing specific processes.

[0152] A single processing unit may be configured with one of these various processors, or may be configured with two or more processors of the same or different types (e.g., multiple FPGAs, or a combination of a CPU and an FPGA). Multiple processing units may also be configured with a single processor. Examples of multiple processing units configured with a single processor include: a first configuration, as typified by client or server computers, in which a single processor is configured with a combination of one or more CPUs and software, and this processor functions as multiple processing units; and a second configuration, as typified by system-on-chip (SoC), in which a processor is used to realize the functions of an entire system including multiple processing units on a single IC (Integrated Circuit) chip. In this way, the various processing units are configured with one or more of the above-mentioned various processors as a hardware structure.

[0153] Furthermore, the hardware structure of these various processors is, more specifically, an electric circuit made up of a combination of circuit elements such as semiconductor elements.

[0154] Furthermore, the present invention includes a peeling and peeling identification program that, when installed on a computer, causes the computer to function as the peeling and peeling identification device of the present invention, and a non-volatile storage medium on which this peeling and peeling identification program is recorded.

[0155] Furthermore, it goes without saying that the present invention is not limited to the above-described embodiment, and various modifications are possible within the scope of the present invention.

[0156] REFERENCE SIGNS LIST 10...3D measuring device 12...Tripod 14...Data processing device 16...Power supply device 18...Cart 20...Wall surface 30L...Left camera 30R...Right camera 40...Reinforcing bar 50...Reactive aggregate 60...Steel material 100...Skinning and peeling identification device 110...Processor 120...Memory 130...Display 140...Input / output interface 150...Operation unit S10 to S50...Steps

Claims

1. A peeling and delamination identification device comprising a processor, a program to be executed by the processor, and a memory for storing three-dimensional measurement data of the surface of a structure measured by a measuring device for each inspection of the structure, wherein the processor: acquires multiple pieces of three-dimensional measurement data of the surface of the structure measured for each inspection; acquires difference data for the same measurement point on the surface of the structure based on the multiple pieces of three-dimensional measurement data; and identifies peeling and delamination areas on the surface of the structure based on characteristics of changes in the difference data.

2. The peeling and peeling identification device of claim 1, wherein the processor identifies the change in the difference data as a peeling and peeling portion of the surface of the structure when the change in the difference data turns negative, when the change in the difference data turns from positive to negative, or when the change in the difference data decreases beyond a threshold value.

3. The peeling and flaking identification device described in claim 1, wherein the processor detects raised and depressed portions on the surface of the structure based on changes in the difference data, and when the processor detects the raised and depressed portions on the same part of the surface of the structure in chronological order of the inspection, identifies the depressed portion as a peeled or flaked portion on the surface of the structure.

4. The peeling and peeling identification device according to claim 1, wherein the processor determines whether the changed portion of the difference data is a crack or not, and if it determines that it is not a crack, identifies the changed portion as a peeling and peeling portion on the surface of the building structure.

5. The peeling and peeling identification device as described in claim 1, wherein the processor measures the width and height of the changed portion of the difference data, and if the shorter of the width or height exceeds a second threshold value, identifies the changed portion as a peeling and peeling portion of the surface of the building structure.

6. The peeling and peeling identification device according to claim 1, wherein the processor measures an area of ​​a changed portion of the difference data, and if the area exceeds a third threshold value, identifies the changed portion as a peeling and peeling portion of the surface of the building structure.

7. The peeling and flaking identification device as described in claim 1, wherein the processor acquires an image of the structure captured by an imaging device, detects cracks in the structure based on the image, and determines whether a change in the difference data is a peeling or flaking part on the surface of the structure or a crack based on the crack detection result.

8. The peeling and peeling identification device described in claim 1, wherein the processor causes the identified peeling and peeling parts to be identifiable on a screen of a display that displays the three-dimensional measurement data, the design surface data of the building, or an image of the building captured by an imaging device.

9. The peeling and falling identification device according to claim 1, wherein the measurement device includes a LiDAR or a stereo camera.

10. The peeling and falling off identification device according to claim 9, wherein the LiDAR measures the three-dimensional measurement data using a Frequency Modulated Continuous Wave (FMCW) method.

11. The peeling and falling off identification device according to claim 1, wherein the material of the surface of the building includes concrete or a concrete repair material.

12. A peeling and spalling identification method in which a processor identifies peeling and spalling on the surface of a structure, the method including the steps of: acquiring multiple three-dimensional measurement data of the surface of the structure measured by a measuring device for each inspection; acquiring difference data for the same measurement point on the surface of the structure based on the multiple three-dimensional measurement data; and identifying peeling and spalling portions on the surface of the structure based on characteristics of changes in the difference data.

13. A peeling and flaking identification method as described in claim 12, wherein the processor identifies the change in the difference data as a peeling and flaking portion of the surface of the building structure when the change in the difference data turns negative, when the change in the difference data turns from positive to negative, or when the change in the difference data decreases beyond a threshold value.

14. A peeling / flake identification method as described in claim 12, wherein the processor detects raised and depressed portions on the surface of the structure based on changes in the difference data, and, when the processor detects the raised and depressed portions on the same part of the surface of the structure in chronological order of the inspection, identifies the depressed portion as a peeled / flaked portion on the surface of the structure.

15. A peeling and flaking identification program for identifying peeling and flaking on the surface of a structure, the program causing a computer to execute the following functions: acquiring multiple three-dimensional measurement data of the surface of the structure measured by a measuring device for each inspection; acquiring difference data for the same measurement point on the surface of the structure based on the multiple three-dimensional measurement data; and identifying peeling and flaking areas on the surface of the structure based on characteristics of changes in the difference data.

16. A non-transitory computer-readable recording medium having the program according to claim 15 recorded thereon.

Images