JP2018017620A - State change detection apparatus, and state change detection program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a state change detection apparatus and a state change detection program which are capable of evaluating the occurrence state of a state change in an object to be detected effectively and quantitatively.SOLUTION: A lattice pattern 5A is formed on the surface of bridge girder where the occurrence of a state change is expected. On the basis of a photographed image of a region to be detected Awhere the lattice pattern 5A exists, displacement in the region to be detected Abefore/after the occurrence of the state change is calculated by a sampling moire method. A photographed image dividing part divides the photographed image of the region to be detected Ainto a plurality of regions Ato A, and a relative displacement calculating part calculates relative displacement for each of a plurality of the regions Ato A. A relative displacement difference calculating part calculates a difference of relative displacement between a plurality of the regions Ato A, and when the difference of the relative displacement exceeds a threshold value, a state change detection part detects that state change occurs between a plurality of the regions Ato A. The difference of the relative displacement is considered to be the width of the crack, and a visualized image generation part generates a contour diagram corresponding to the width of the crack.SELECTED DRAWING: Figure 5

Description

  The present invention relates to a deformation detection apparatus and a deformation detection program for detecting a deformation generated in a detection object by measuring a displacement of a characteristic pattern formed on the surface of the detection object.

  Strain and cracks generated in a concrete structure are a direct index for evaluating the load history and durability of the structure. Therefore, it is important to accurately grasp the state or signs of occurrence. It is very important in the maintenance of structures. In particular, in railway structures, there is a need for a technique for measuring fine strains and cracks with relatively high frequency and high accuracy generated by high-speed running of trains. The inspection of the position and width of a crack is currently performed mainly by attaching a visual or contact sensor.

  The conventional method for measuring the accumulated strain in the roadbed is to remove the asphalt concrete layer at the measurement location to expose the roadbed, and drive a pair of measuring rods into the roadbed at a predetermined interval, and this pair of measuring rods A pie-type displacement meter is attached to the protruding portion (see, for example, Patent Document 1). In such a conventional method for measuring accumulated strain in a roadbed, a pie-type displacement meter is connected to a data recorder, the initial value of displacement is recorded, measurement is started, and the measured displacement is divided by the measurement length. Strain is measured to predict deformations such as cracks in the roadbed.

  A conventional method for measuring displacement of an object is based on a step of photographing a predetermined area before and after applying a force of a grid pattern attached to the surface of the object with an optical camera, and an image taken by the optical camera. A step of calculating the phase distribution of moire fringes by the sampling moire method, a step of calculating the strain or stress distribution of the object based on the phase distribution, and the like (see, for example, Patent Document 2). In such a conventional method for measuring displacement of an object, sampling is performed at equal intervals on a captured image at least three times while changing the starting pixel, and the thinned image obtained by this sampling processing is complemented. Thus, moire fringes are generated, and the phase distribution of the moire fringes obtained by the phase shift method is calculated.

JP 2010-048595

JP 2009-264852 A

  For the inspection of the position and width of the crack, a technique for inspecting the crack more efficiently and quantitatively is required. Especially for PC (prestressed concrete) bridges and PRC (prestressed reinforced concrete) bridges, it is necessary to evaluate the soundness of the structure by measuring the state of cracks when passing through the train. Therefore, there is a need for a system that can efficiently acquire a wide range of crack distributions and quantitatively capture crack widths. There is also a need for a system that can efficiently and quantitatively evaluate the occurrence of cracks during concrete loading tests and fatigue tests. In recent years, many studies have been conducted on non-contact measurement of displacement and strain of concrete structures based on image analysis, etc., but it can be said that the verification of dynamic and highly accurate measurement of micro strains and cracks is sufficient. Absent.

  The subject of this invention is providing the deformation | transformation detection apparatus and deformation | transformation detection program which can evaluate efficiently and quantitatively about the generation | occurrence | production state of the deformation | transformation of a detection target object.

The present invention solves the above-mentioned problems by the solving means described below.
In addition, although the code | symbol corresponding to embodiment of this invention is attached | subjected and demonstrated, it is not limited to this embodiment.
The invention of claim 1 measures the displacement of the characteristic pattern (5A; 5B) formed on the surface of the detection object (3a) as shown in FIGS. Is a deformation detection device for detecting a deformation occurring in the detection object, and is a captured image dividing unit (11) that divides the captured image having the characteristic pattern into a plurality of regions (A _{11 to} A _MN ). ), A relative displacement calculation unit (12) for calculating the relative displacement of the plurality of regions, and a deformation detection unit for detecting a deformation occurring in the detection object based on the calculation result of the relative displacement calculation unit (14) is a deformation detection device (8).

  According to a second aspect of the present invention, in the deformation detection device according to the first aspect, as shown in FIGS. 5, 6, and 12, based on the calculation result of the relative displacement calculation unit, the adjacent regions are A relative displacement difference calculation unit (13) for calculating a difference between relative displacements is provided, wherein the deformation detection unit detects a deformation generated in the detection object based on the difference between the relative displacements. This is a deformation detection device.

  According to a third aspect of the present invention, in the deformation detection device according to the second aspect, the photographed image dividing unit subdivides the plurality of regions into finer regions based on a calculation result of the relative displacement difference calculating unit. The relative displacement difference calculation unit calculates a difference in relative displacement between the plurality of regions after subdivision, and the deformation detection unit detects the detection based on the difference in relative displacement after subdivision. A deformation detection device that detects a deformation generated in an object.

  According to a fourth aspect of the present invention, in the deformation detection device according to the second or third aspect, as shown in FIGS. 6 and 8, the deformation detection unit is configured such that the difference between the relative displacements is a threshold value ( When it exceeds (th), it is determined that a crack has occurred in the detection object, and when the difference in relative displacement is equal to or less than a threshold value, it is determined that no crack has occurred in the detection object. This is a deformation detection device.

  According to a fifth aspect of the present invention, in the deformation detection device according to any one of the second to fourth aspects, the deformation detection unit is configured to detect the detection object based on the difference in the relative displacement. The deformation detection device is characterized by detecting a width of a crack generated.

  According to a sixth aspect of the present invention, in the deformation detection device according to any one of the second to fifth aspects, as shown in FIGS. 4 and 8, the detection is performed based on the difference in the relative displacement. The deformation detection device includes a load estimation unit (15) that estimates a load acting on an object.

  A seventh aspect of the present invention is the deformation detection apparatus according to any one of the second to sixth aspects, wherein, as shown in FIG. 4, visualization for visualizing and displaying the difference of the relative displacements. The deformation detection apparatus includes a visualized image generation unit (16) that generates an image.

  The invention according to claim 8 is the deformation detection device according to any one of claims 1 to 7, wherein, as shown in FIGS. The deformation detection device is characterized by detecting a deformation generated in the detection target based on a detection result of the vibration detection device (5) for detecting the vibration of the detection target.

The invention of claim 9 measures the displacement of the characteristic pattern (5A; 5B) formed on the surface of the detection object (3a) as shown in FIGS. 1 to 6 and 9 to 13. Is a deformation detection program for detecting a deformation occurring in the detection object, and a captured image dividing procedure for dividing the captured image having the characteristic pattern into a plurality of regions (A _{11 to} A _MN ). (S150), a relative displacement calculation procedure (S160) for calculating the relative displacement of the plurality of regions, and a deformation that detects a deformation that occurs in the detection object based on the calculation result in the relative displacement calculation procedure. This is a deformation detection program for causing a computer to execute a detection procedure (S190).

  According to a tenth aspect of the present invention, in the deformation detection program according to the ninth aspect, as shown in FIGS. 5, 6, 9, and 12, the adjacent ones based on the calculation result in the relative displacement calculation procedure. A relative displacement difference calculation procedure (S170) for calculating a relative displacement difference between the regions, wherein the deformation detection procedure is a procedure for detecting a deformation generated in the detection object based on the relative displacement difference. It is a deformation detection program characterized by including.

  According to an eleventh aspect of the present invention, in the deformation detection program according to the ninth or tenth aspect, as shown in FIG. 9, the captured image dividing procedure is based on a calculation result in the relative displacement difference calculating procedure. Including a procedure of subdividing the plurality of regions into finer regions, and the relative displacement difference calculation procedure includes a procedure of calculating a relative displacement difference between the plurality of regions after the subdivision, and the deformation detection procedure Is a deformation detection program characterized by including a procedure for detecting a deformation occurring in the detection target object based on the difference of the relative displacements after subdivision.

  According to a twelfth aspect of the present invention, in the deformation detection program according to the tenth or eleventh aspect, as shown in FIGS. 6, 8, and 9, the deformation detection procedure includes a difference between the relative displacements. When the threshold value (th) is exceeded, it is determined that a crack has occurred in the detection object, and when the difference in relative displacement is not more than a threshold value, it is determined that no crack has occurred in the detection object. It is a deformation detection program characterized by including a procedure.

  According to a thirteenth aspect of the present invention, in the deformation detection program according to any one of the tenth to thirteenth aspects, the deformation detection procedure is performed on the detection object based on the difference in the relative displacement. A deformation detection program including a procedure for detecting a width of a crack to be generated.

  According to a fourteenth aspect of the present invention, in the deformation detection program according to any one of the tenth to thirteenth aspects, as shown in FIGS. 4, 8, and 9, based on the relative displacement difference. A deformation detection program including a load estimation procedure (S200) for estimating a load acting on the detection object.

  According to a fifteenth aspect of the present invention, in the deformation detection program according to any one of the tenth to fourteenth aspects, as shown in FIG. 9, a visualization for visualizing and displaying the relative displacement difference is provided. A deformation detection program including a visualized image generation procedure (S210) for generating an image.

  According to a sixteenth aspect of the present invention, in the deformation detection program according to any one of the ninth to fifteenth aspects, as shown in FIGS. 1, 2, 4, and 9, the deformation detection procedure is performed. Is a deformation detection program including a procedure for detecting a deformation occurring in the detection object based on a detection result of the vibration detection device (6) for detecting the vibration of the detection object. .

  According to the present invention, it is possible to efficiently and quantitatively evaluate the occurrence state of the deformation of the detection object.

It is a side view which shows typically the structure in which a deformation | transformation is detected by the deformation | transformation detection apparatus which concerns on 1st Embodiment of this invention. It is a side view which shows typically the condition which is detecting the deformation | transformation with the deformation | transformation detection apparatus which concerns on 1st Embodiment of this invention. It is a top view which abbreviate | omits and shows a some picked-up image of the detection target area | region before being divided | segmented by the deformation | transformation detection apparatus which concerns on 1st Embodiment of this invention. 1 is a configuration diagram schematically showing a deformation detection device according to a first embodiment of the present invention. FIG. It is a top view which abbreviate | omits and shows a part of picked-up image of the detection object area | region after dividing | segmenting by the deformation | transformation detection apparatus which concerns on 1st Embodiment of this invention. BRIEF DESCRIPTION OF THE DRAWINGS It is a schematic diagram which shows roughly the crack detection method of the deformation | transformation detection apparatus which concerns on 1st Embodiment of this invention, (A) is the schematic diagram of the picked-up image division | segmentation process which divides | segments the picked-up image before crack generation for every area | region. (B) is a schematic diagram of a captured image dividing step for dividing a captured image after occurrence of a crack into regions, and (C) is a schematic diagram of a relative displacement calculating step for calculating a relative displacement for each region. (D) is a schematic diagram of the crack detection process which pinpoints the generation | occurrence | production position of a crack. It is a schematic diagram for demonstrating the principle of the sampling moire method which the relative displacement calculating part of the deformation | transformation detection apparatus which concerns on 1st Embodiment of this invention performs, (A) is a schematic diagram of the pixel position of an imaging device. , (B) is a schematic diagram of a lattice pattern after occurrence of cracks, (C) is a schematic diagram of a captured image of the lattice pattern after occurrence of cracks, and (D) to (G) are obtained by thinning out the captured images. FIG. 4 is a schematic diagram of a subsequent thinned image, and (H) to (K) are schematic diagrams of a moire fringe image after a complementary process is performed on the thinned image. It is a graph which shows typically the correlation information which the correlation information storage part of the deformation | transformation detection apparatus which concerns on 1st Embodiment of this invention memorize | stores. It is a flowchart in order to demonstrate operation | movement of the deformation | transformation detection apparatus which concerns on 1st Embodiment of this invention. It is a side view which shows typically the condition which is detecting the deformation | transformation with the deformation | transformation detection apparatus which concerns on 2nd Embodiment of this invention. It is a top view which abbreviate | omits and shows a some picked-up image of the detection target area | region before being divided | segmented by the deformation | transformation detection apparatus which concerns on 2nd Embodiment of this invention. It is a top view which abbreviate | omits and shows a some picked-up image of the detection object area | region after dividing | segmenting by the deformation | transformation detection apparatus which concerns on 2nd Embodiment of this invention. It is a schematic diagram for demonstrating the principle of the image correlation method which the relative displacement calculating part of the deformation | transformation detection apparatus which concerns on 2nd Embodiment of this invention performs, (A) is a subset of the captured image before crack generation | occurrence | production. It is a schematic diagram which shows a position, (B) is a schematic diagram which shows the position of the subset in the picked-up image after crack generation. It is a photograph which shows the external appearance of the crack detection system which concerns on the Example of this invention, (A) is a photograph of a crack detection system, (B) is a photograph which shows an example of a grid | lattice-like target. It is a photograph which shows the external appearance of a model bridge used in the dynamic test for verifying the crack detection system which concerns on the Example of this invention, and a crack measurement position. It is a photograph which shows the condition of the bending failure test of PC sleeper for verifying the crack detection system concerning the Example of this invention. It is a photograph of the lattice target used in the bending break test of the PC sleeper for verifying the crack detection system according to the embodiment of the present invention, (A) is a photograph of the lattice target formed by the cutting sheet, (B) is a photograph of a lattice target formed by stamps. It is a graph which shows the measurement result of the dynamic test for verifying the crack detection system based on the Example of this invention, (A) is a graph when vibrating at 10 Hz, (B) is excited at 20 Hz. It is a graph when doing. It is a graph which shows the relationship between the loading load and crack width in a bending fracture test, (A) is a graph which shows the relationship between loading load and displacement, (B) shows the relationship between loading load and relative displacement. It is a graph. It is the photograph which shows the crack distribution of the crack detection system which concerns on the Example of this invention as an example, (A) is a photograph which shows a measurement range and a crack generation condition, (B) is a photograph of the visualization image of relative displacement. (C) is a photograph of a visualized image of a crack occurrence state.

(First embodiment)
Hereinafter, a first embodiment of the present invention will be described in detail with reference to the drawings.
A vehicle 1 shown in FIG. 1 is a moving body that travels along a track 2. The vehicle 1 is a railway vehicle such as a train, a locomotive, a passenger car, or a freight car, and travels on the structure 3. A vehicle 1 shown in FIG. 1 is, for example, a Shinkansen (registered trademark) or a conventional railway vehicle that travels at a high speed. The track 2 is a passage (track) on which the vehicle 1 travels. The track 2 includes a pair of left and right rails that support and guide a pair of left and right wheels of the vehicle 1.

  The structure 3 is a fixed structure that secures a space below the track 2 on which the vehicle 1 travels and supports the load of the train. The structure 3 is a bridge constructed so as to cross a natural object such as a river, a valley, and a lake, a traffic path such as a road or a railroad, and to form a space below. The structure 3 is a concrete structure reinforced with steel bars using concrete as a main material. The structure 3 is, for example, a prestressed concrete bridge that does not allow cracking (PC bridge), or a prestressed concrete bridge that controls cracking width (PRC bridge) while allowing cracking to occur at the limit of use. It is. The structure 3 includes a bridge girder 3a, a pier (peer) 3b, a pier foundation 3c, a support portion 3d, and the like.

  The bridge girder 3a is a structure that is arranged in the horizontal direction and supports the track 2. The bridge girder 3a is a beam member straddling one fulcrum and the other fulcrum with the pier 3b as a fulcrum. The bridge girder 3a is a detection object whose deformation is detected by the deformation detection device 8 shown in FIGS. The pier 3b shown in FIG. 1 is a structure that supports the bridge girder 3a. The pier 3b is, for example, a reinforced concrete column that is constructed of cast-in-place concrete at a predetermined interval in the length direction of the structure 3, and is arranged in the vertical direction. The pier foundation 3c is a structure that supports the structure 3 by transmitting a load acting on the entire structure 3 to the ground. The support portion 3d is a portion that supports the bridge girder 3a on the upper end surface of the pier 3b. In the structure 3, the bridge girder 3a constitutes the upper structure, and the pier 3b and the pier foundation 3c constitute the lower structure. The structure 3 shown in FIG. 1 is, for example, a girder bridge that receives a load by a beam structure and mainly includes a girder, the bridge girder 3a is constructed with concrete as a main material, and the pier 3b is constructed with a rigid body such as concrete. Has been.

The deformation detection system 4 shown in FIG. 1 and FIG. 2 is a system that detects the deformation generated in the bridge girder 3a by measuring the displacement of the lattice pattern 5A formed on the surface of the bridge girder 3a. The deformation detection system 4 detects the deformation of the bridge girder 3a by using the sampling moire method. Here, the sampling moire method (scanning moire method) generates a moire fringe image that is phase-shifted from one captured image of the detection target area A ₀ where the lattice pattern 5A exists, and is displaced from the phase distribution of the moire fringe image. Is a measurement technique for obtaining The sampling moire method is advantageous in that high-accuracy measurement with subpixels can be performed with a relatively short exposure time, and the calculation load during image analysis is small. The Deformation, and the like cracks that occur in the detection target area A _0. The deformation detection system 4 functions as, for example, a crack detection system that detects a crack generated in the bridge girder 3a. The deformation detection system 4 detects the vibration of the structure 3 with the vibration detection device 6, and images the lattice pattern 5 </ b> A with the imaging device 7 when the vehicle 1 passes over the structure 3. The captured image is analyzed by the deformation detection device 8 to detect the deformation of the bridge girder 3a. The deformation detection system 4 includes a lattice pattern 5A shown in FIGS. 1 to 3, a vibration detection device 6 shown in FIGS. 1, 2 and 4, a photographing device 7, a deformation detection device 8, and the like. .

The lattice pattern 5A shown in FIGS. 1 to 3 is a characteristic pattern formed on the surface of the bridge girder 3a. The lattice pattern 5A is a regular lattice target formed in the length direction (lateral direction (X-axis direction)) of the bridge beam 3a and the height direction (vertical direction ((Y-axis direction)) of the bridge beam 3a. 1 and 2, the lattice pattern 5A is formed in the detection target area A ₀ where the deformation of the bridge girder 3a occurs, and the lattice pattern 5A is set at an arbitrary position and with an arbitrary lattice size. The resolution is about 1/500 of the lattice pitch.The lattice pattern 5A is a two-dimensional lattice in which the phase of the lattice pattern 5A changes in the X-axis direction and the Y-axis direction of the bridge beam 3a. Two-dimensional deformation analysis in the X-axis direction and the Y-axis direction is possible, for example, as shown in Fig. 3, the lattice pattern 5A is a two-dimensional grid with black squares on a white background at regular intervals in the vertical and horizontal directions. In the lattice pattern 5A, the occurrence position of the deformation can be predicted in advance. The case,. Grid pattern 5A that this Deformation of generation is formed by specifying an arbitrary target detection area A ₀ to include the position to be predicted, if Deformation of occurrence position is known in advance Alternatively, when the deformation to be investigated is determined in advance, it is formed by designating an arbitrary detection target area A ₀ so as to include this deformation occurrence position or the predetermined deformation. In the lattice pattern 5A, the surface of the bridge girder 3a is smoothed by a file as necessary, and then a black and white square lattice is formed by painting with a stamp, a cutting sheet, or masking.

The vibration detection apparatus 6 shown in FIGS. 1 and 2 is an apparatus that detects vibration of the bridge girder 3a. As shown in FIG. 1, the vibration detection device 6 detects the vibration of the bridge girder 3a generated when the vehicle 1 passes over the bridge girder 3a, and the vehicle 1 approaches the detection target area A ₀ of the bridge girder 3a. As well as the separation of the vehicle 1 from the detection target area A ₀ of the bridge girder 3a. As shown in FIG. 1, the vibration detection device 6 is installed on the bridge girder 3 a above the support portion 3 d that is easily affected by the vibration of the vehicle 1. The vibration detection device 6 is, for example, a vibration detection sensor such as an acceleration sensor, a speed sensor, or a displacement sensor that detects the vibration of the bridge girder 3a in the height direction of the structure 3 orthogonal to the length direction of the structure 3. The vibration detection device 6 converts a vibration detection signal (vibration information) corresponding to the vibration of the bridge girder 3a into a digital signal by a built-in A / D converter and outputs the digital signal to the information input unit 9 of the deformation detection device 8.

The imaging apparatus 7 shown in FIGS. 1 and 2 is an apparatus for imaging the detection target area A ₀ where the lattice pattern 5A exists. Imaging device 7 starts photographing operation when the vehicle 1 approaches the detection target area A ₀ of the bridge girder 3a shown in FIG. 1, the photographing operation when the vehicle 1 from the detection target area A ₀ of the bridge deck 3a is spaced finish. The imaging device 7 is a measurement camera for measuring the deformation of the bridge girder 3a. The imaging device 7 is, for example, a CMOS (Complementary Metal Oxide Semiconductor) monochrome camera using a complementary metal oxide semiconductor, and can capture the lattice pattern 5A using a camera with a relatively low resolution. In the photographing apparatus 7, the photographing magnification is adjusted so that one pitch (vertical and horizontal intervals) of the lattice pattern 5A is approximately N pixels (N is an integer). The photographing device 7 is adjusted to the photographing magnification so that, for example, N = 4 (pixels). As shown in FIG. 1, the photographing device 7 is installed on a solid ground away from the detection target area A ₀ so as not to be affected by the vibration of the vehicle 1 passing over the bridge girder 3a. Imaging device 7, when all or part of the position where the grid pattern 5A is formed as a detection target area A _0, to shoot the target detection area A ₀ as the imaging area. The imaging device 7 captures the detection target area A ₀ every time the vehicle 1 passes over the structure 3, and captures the detection target area A ₀ before and after the occurrence of the deformation. The photographing device 7 converts the photographed image in the detection target area A ₀ into a digital signal by a built-in A / D converter, and outputs the photographed image as photographed image information to the information input unit 9 of the deformation detection device 8. .

The deformation detection device 8 shown in FIGS. 1, 2, and 4 is a device that detects the deformation generated in the bridge girder 3a by measuring the displacement of the lattice pattern 5A formed on the surface of the bridge girder 3a. . For example, as shown in FIG. 5, the deformation detection apparatus 8 includes M (vertical area) A ₁₁ (M and N are integers) areas (small areas) A _{11 of} detection target areas A _{0 in} which a lattice pattern 5 A exists. , ..., divided into a _MN, these regions a _11, ..., to detect the Deformation generated by computing the relative displacement of the a _MN to bridge girder 3a. Here, the relative displacement is a movement amount (displacement) based on the origin (fixed point) O where the position does not change before and after the occurrence of the deformation. The deformation detection device 8 functions as, for example, a crack detection device that detects a crack generated in the bridge girder 3a. As illustrated in FIG. 4, the deformation detection device 8 includes an information input unit 9, a displacement calculation unit 10, a captured image division unit 11, a relative displacement calculation unit 12, a relative displacement difference calculation unit 13, and a deformation. A detection unit 14, a load estimation unit 15, a visualized image generation unit 16, an information storage unit 17, a display unit 18, a control unit 19, and the like are provided. The deformation detection device 8 is configured by a control personal computer or a recording personal computer that controls the operation of the photographing device 7 shown in FIGS. 1, 2, and 4 and records various information. A predetermined process is executed according to the program.

  The information input unit 9 shown in FIG. 4 is means for inputting various information. The information input unit 9 receives the vibration information output from the vibration detection device 6 and the captured image information output from the imaging device 7, and outputs the vibration information and the captured image information to the control unit 19. The information input unit 9 is an interface (I / O) circuit that connects the vibration detection device 6 and the imaging device 7 to the control unit 19 and inputs / outputs various information between them.

Displacement calculating unit 10 shown in FIG. 4 is a means for calculating the displacement in the detection target area A _0. When the displacement calculation unit 10 superimposes the lattice pattern 5A of the photographed image before occurrence of deformation (before deformation) and the lattice pattern 5A of the photographed image after occurrence of deformation (after deformation) as shown in FIG. moire fringes generated, by analyzing the sampled moire method for calculating the displacement in the detection target area a _0. For example, as shown in FIG. 7, the displacement calculation unit 10 calculates the displacement by the sampling moire method disclosed in Japanese Unexamined Patent Publication No. 2009-264852 described in the prior art document. For example, the displacement calculation unit 10 moiré fringes generated when the captured image of the detection target area A ₀ before the occurrence of the deformation and the captured image of the detection target area A ₀ after the occurrence of the deformation are superimposed by image processing. From this, the entire displacement in the detection target area A ₀ is calculated.

As shown in FIG. 7, the displacement calculator 10 calculates the displacement in the detection target area A ₀ by analyzing the phase of moire fringes generated by sampling the lattice pattern 5A. When calculating the displacement of the bridge girder 3a in the length direction (X-axis direction), the displacement calculation unit 10 smoothes one pitch in the Y-axis direction of the lattice pattern 5A so that a moire fringe image in the X-axis direction can be obtained. To erase the lattice in the X-axis direction. On the other hand, when calculating the displacement of the bridge girder 3a in the height direction (Y-axis direction), the displacement calculation unit 10 is equivalent to one pitch in the X-axis direction of the lattice pattern 5A so that a moire fringe image in the Y-axis direction can be obtained. To smooth out the grid in the Y-axis direction. Below, the case where the displacement calculation part 10 calculates the displacement of the length direction (X-axis direction) of the bridge girder 3a shown in FIG. 3 is mentioned as an example, and is demonstrated.

Displacement calculation unit 10, a lattice pattern 5A in the detection target area A ₀ after displacement as shown in FIG. 7 (B), imaging device 7 is taken at the pixel position shown in FIG. 7 (A) (sampling point) The displacement in the detection target area A ₀ is calculated based on the captured image shown in FIG. Here, the photographed image shown in FIG. 7C is photographed by adjusting the photographing magnification of the photographing device 7 so that one pitch of the lattice pattern 5A becomes four pixels.

  The displacement calculation unit 10 performs thinning processing by sampling the captured image shown in FIG. 7C one by one every four pixels, and generates thinned images shown in FIGS. 7D to 7G. The displacement calculation unit 10 thins out the photographed image by changing the sampling starting point every four pixels from the first starting point from the left of the photographed image shown in FIG. 7C, and performs the thinning shown in FIG. Generate an image. Further, the displacement calculating unit 10 thins out the photographed image by changing the sampling starting point every four pixels from the second starting point from the left of the photographed image shown in FIG. A thinned image is generated. Further, the displacement calculation unit 10 thins out the photographed image by changing the sampling starting point every four pixels from the third starting point from the left of the photographed image shown in FIG. A thinned image is generated. Furthermore, the displacement calculation unit 10 thins out the photographed image by changing the sampling starting point every four pixels from the fourth starting point from the left of the photographed image shown in FIG. A thinned image is generated. Here, the black dots shown in FIGS. 7D to 7G are sampling points thinned out from the photographed image shown in FIG. 7C.

  The displacement calculation unit 10 linearly interpolates the luminance values of the thinned out pixels shown in FIGS. 7D to 7G to pixels that are not thinned out in the vicinity so that the luminance changes smoothly. To do. The displacement calculation unit 10 generates a moire fringe image (phase image) that is phase-shifted by 90 degrees as shown in FIGS. 7 (H) to (K) corresponding to the thinned images shown in FIGS. 7 (D) to (G). The image is generated with the same resolution as the captured image shown in FIG. The displacement calculation unit 10 generates a moiré fringe image having a phase shift as shown in FIGS. 7H to 7I from one photographed image as shown in FIG. 7C. The displacement calculation unit 10 calculates the luminance distribution in the X-axis direction according to the following Equation 1, assuming that the luminance distribution of the lattice of the moire fringe images shown in FIGS. 7 (H) to (I) is a cosine wave.

Here, I _{0 to} I ₃ shown in Equation 1 are the luminance distributions of the grids of the moire fringe images shown in FIGS. 7 (H) to (I), respectively. a is the luminance amplitude, b is the luminance of the background, and φ is the phase of the moire fringes. The displacement calculation unit 10 calculates the phase difference Δφ of the moire fringes according to the following _equation 2 using I _{0 to} I ₃ shown in _equation 1.

  The displacement calculator 10 considers that the phase difference between the lattice patterns 5A before and after the occurrence of the deformation corresponds to the phase difference Δφ of the moire fringes shown in Equation 2, and calculates the displacement d in the X-axis direction according to Equation 3 below.

Here, p shown in Equation 3 is the pitch of the lattice pattern 5A in the X-axis direction. When calculating the displacement of the bridge girder 3a in the height direction (Y-axis direction), the displacement calculation unit 10 calculates the displacement in the Y-axis direction by the same procedure as the calculation of the displacement in the X-axis direction. The displacement calculation unit 10 outputs the calculated displacement within the detection target area A _{0 to the} control unit 19 as displacement information.

The photographed image dividing unit 11 shown in FIG. 4 is means for dividing the photographed image of the lattice pattern 5A into a plurality of areas A _{11 ,.} Photographed image dividing unit 11, for example, FIGS. 5 and 6 (A) (B), the target detection area A ₀ of the imaging device 7 regions A ₁₁ to the taken image taken by the lattice pattern 5A is present, .., _AMN , and a plurality of divided images (for example, M × N) are generated from the captured images. The captured image dividing unit 11 divides the plurality of regions into smaller regions based on the calculation result of the relative displacement difference calculating unit 13. The photographed image dividing unit 11 first divides the photographed image of the detection target area A ₀ into a relatively large area, and among these relatively large areas, an area where the difference in relative displacement between adjacent areas is large is a finer area. Repeat the process of subdividing into. The captured image dividing unit 11 divides the captured image of the detection target region A ₀ into divided images for each of the plurality of regions A ₁₁ ,..., _AMN , and outputs the divided images to the control unit 19 as divided image information.

The relative displacement calculator 12 shown in FIG. 4 is a means for calculating the relative displacement of the plurality of regions A _{11 ,.} The relative displacement calculation unit 12 is based on the displacement in the detection target area A ₀ calculated by the displacement calculation unit 10 and the areas A ₁₁ ,..., A _MN divided by the captured image division unit 11 as shown in FIG. The relative displacement for each of the areas A ₁₁ ,..., A _MN shown in FIG. Relative displacement computing unit 12, for example, each region A _11, ..., the average value of the displacement in the A _MN (displacement average) the area A _11, ..., and calculates the relative displacement of each A _MN. When the captured image dividing unit 11 repeats the process of subdividing the detection target area A ₀ from a relatively large area into a relatively small area, the relative displacement calculating unit 12 calculates the relative displacement of each area every time the division is repeated. Repeat the process. The relative displacement calculation unit 12 outputs the calculated relative displacement for each region A ₁₁ ,..., _{AMN to the} control unit 19 as relative displacement information.

The relative displacement difference calculation unit 13 shown in FIG. 4 is a means for calculating a relative displacement difference between adjacent regions A ₁₁ ,..., _AMN based on the calculation result of the relative displacement calculation unit 12. The relative displacement difference calculation unit 13, as shown in FIG. 5 and FIG. 6 (C), the area A ₁₁ relative displacement calculation unit 12 calculates, ..., based on the relative displacement of each A _MN, adjacent regions A ₁₁ ,..., A difference in relative displacement between _MN is calculated. For example, the relative displacement difference calculation unit 13 _performs the relative displacement (large relative displacement) of the region A _M4-1 as shown in FIG. _{6C and} the relative displacement (region A _M4 adjacent to the region A _4M-4 ( Calculate the difference from (relative displacement small). When the captured image dividing unit 11 divides a region having a relatively large relative displacement difference into smaller regions, the relative displacement difference calculating unit 13 calculates a relative displacement difference between adjacent regions after the re-division. When the captured image dividing unit 11 repeats the process of subdividing the detection target area A ₀ from a relatively large area into a relatively small area, the relative displacement difference calculating unit 13 makes a relative displacement between adjacent areas every time the division is repeated. Repeat the process of calculating the difference. The relative displacement difference calculation unit 13 outputs the difference of the relative displacement between the adjacent areas A ₁₁ ,..., _AMN after the calculation to the control unit 19 as relative displacement difference information.

The deformation detection unit 14 shown in FIG. 4 is means for detecting a deformation that occurs in the bridge girder 3 a based on the calculation result of the relative displacement calculation unit 12. When the captured image obtained by capturing the lattice pattern 5A is divided into a plurality of regions A ₁₁ ,..., A _MN , the deformation detection unit 14 _deforms based on the relative displacement of these regions A _{11 ,.} Is detected. When the captured image dividing unit 11 divides a region having a relatively large difference in relative displacement into finer regions, the deformation detecting unit 14 determines the bridge girder 3a based on the difference in relative displacement between adjacent regions after the re-division. Detects the deformation. When the captured image dividing unit 11 repeats the process of re-dividing the detection target area A ₀ from a relatively large area into a relatively small area, the deformation detecting unit 14 repeats the process of detecting the deformation each time the division is repeated. . The deformation detection unit 14 functions as, for example, a crack detection unit that detects the presence / absence of a crack in the detection target area A ₀ , the width of the crack, the position where the crack is generated, and the direction in which the crack propagates. As shown in FIG. 1, the deformation detection unit 14 is based on the detection result of the vibration detection device 6 so that the deformation detection operation is started at the timing when the vehicle 1 passes over the bridge girder 3a and the bridge girder 3a vibrates. Then, the deformation occurring in the bridge girder 3a is detected.

The deformation detection unit 14 detects a deformation that occurs in the bridge girder 3a based on the difference in relative displacement. Deformation detecting section 14, as shown in FIG. 5 and FIG. 6 (C) (D), areas adjacent A _11, ..., on the basis of the difference in the relative displacement between A _MN, in the detection target area A ₀ Detects cracks. For example, as shown in FIG. 6C, the deformation detection unit 14 is a case where the relative displacement of the region A _M4 is small and the relative displacement of the region A _M-14 adjacent to the region A _M4 is large. When the difference between the relative displacement in the region A _{11 and} the relative displacement in the region A ₁₂ is large, it is detected that a crack has occurred in the detection target region A ₀ . The deformation detection unit 14 determines that a crack has occurred when the difference in relative displacement exceeds the threshold value th, and determines that no crack has occurred when the difference in relative displacement is equal to or less than the threshold value th. To do. For example, as illustrated in FIG. 8, the deformation detection unit 14 sets a difference in relative displacement corresponding to an inflection point at which the inclination direction of the correlation function between the difference in relative displacement and the load changes as a threshold value th. . Here, the vertical axis shown in FIG. 8 is the load, and the horizontal axis is the relative displacement difference (crack width).

The deformation detection unit 14 detects the width of a crack generated in the bridge girder 3a based on the difference in relative displacement. The deformation detection unit 14 regards the crack width in the detection target area A ₀ as a relative displacement difference, and detects the relative displacement difference as the crack width. For example, as illustrated in FIG. 6C, the deformation detection unit 14 calculates the difference in relative displacement between the adjacent areas A _M-14 and A _M4 as the areas A _M-14 and A _M4. It is detected as the width of the crack that occurred.

The deformation detection unit 14 detects a crack generation position and a propagation direction based on a difference in relative displacement. Deformation detector 14, the area adjacent A _11, ..., based on a difference in the relative displacement between A _MN, detects the occurrence position and progress direction of the cracks in the target detection area A _0. For example, as illustrated in FIG. 6D, the deformation detection unit 14 generates a crack generation position in a region A _M-14 where the difference in relative displacement between the adjacent region A _M-14 and the region A _M4 is large. And detected as the direction of progress. The deformation detection unit 14 outputs information on the presence / absence of a crack, the width of the crack, the position where the crack is generated, and the direction in which the crack propagates to the control unit 19 as deformation information.

  The load estimation unit 15 shown in FIG. 4 is a means for estimating the load acting on the bridge girder 3a based on the difference in relative displacement. The load estimation unit 15 estimates a load acting on the bridge girder 3a based on the difference between the relative displacements calculated by the relative displacement difference calculation unit 13 and the correlation information stored in the correlation information storage unit 17h. The load estimation unit 15 collates the correlation information indicating the correlation between the load and the relative displacement difference (crack width) as shown in FIG. 8 and the relative displacement difference calculated by the relative displacement difference calculation unit 13. The load corresponding to the relative displacement difference in the correlation information is estimated as the load applied to the bridge girder 3a. The load estimation unit 15 outputs the load corresponding to the relative displacement difference to the control unit 19 as load information.

  The visualized image generation unit 16 shown in FIG. 4 is a means for generating a visualized image for visualizing and displaying the difference in relative displacement. The visualized image generation unit 16 generates a deformation distribution map for visualizing and displaying the relative displacement difference based on the calculation result of the relative displacement difference calculation unit 13. For example, the visualized image generation unit 16 connects points having the same crack width (difference in relative displacement) with lines, draws contour lines (isolines) every time the crack width is a constant value, and between the contour lines. A crack distribution map such as a contour map in which colors are applied step by step is generated. The visualized image generating unit 16 outputs the generated visualized image to the control unit 19 as visualized image information.

  The information storage unit 17 is a means for storing various information. The information storage unit 17 stores, for example, photographed image information, displacement information, divided image information, relative displacement information, relative displacement difference information, deformation information, load information, correlation information, visualized image information, and a deformation detection program. Memory. As shown in FIG. 4, the information storage unit 17 includes a captured image information storage unit 17a, a displacement information storage unit 17b, a divided image information storage unit 17c, a relative displacement information storage unit 17d, and a relative displacement difference information storage unit. 17e, a deformation information storage unit 17f, a load information storage unit 17g, a correlation information storage unit 17h, a visualized image information storage unit 17i, a deformation detection program storage unit 17j, and the like.

Photographed image information storage unit 17a is a part that stores the captured image in the detection target area A ₀ as a photographic image information. The photographed image information storage unit 17a stores the photographed image information output from the photographing device 7 in chronological order in association with the photographing time. Displacement information storage unit 17b is a part that stores the displacement in the detection target area A ₀ as the displacement information. The displacement information storage unit 17b stores the displacement information output by the displacement calculation unit 10 in chronological order in association with the shooting time. The divided image information storage unit 17c is a part that stores the divided images for each of the areas A ₁₁ ,..., _AMN as divided image information. The divided image information storage unit 17c stores the divided image information output from the captured image dividing unit 11 in chronological order in association with the shooting time. The relative displacement information storing unit 17d, the region A _11, ..., is a portion for storing a relative displacement of each A _MN as relative displacement information. The relative displacement information storage unit 17d stores the relative displacement information output from the relative displacement calculation unit 12 in chronological order in association with the photographing time. The relative displacement difference information storage unit 17e, the area adjacent A _11, ..., is a part for storing the difference in the relative displacement between the A _MN as relative displacement difference information. The relative displacement difference information storage unit 17e stores the relative displacement difference information output from the relative displacement difference calculation unit 13 in chronological order in association with the photographing time.

Henjo information storage unit 17f is a unit which stores occurrence of cracks in the target detection area A _0, the width of the crack, the extending direction of the generating position and cracking of cracking as Henjo information. The deformation information storage unit 17f stores the deformation information output by the deformation detection unit 14 in chronological order in association with the shooting time. The load information storage unit 17g is a part that stores a load acting on the bridge girder 3a as load information. The load information storage unit 17g stores the load information output from the load estimation unit 15 in chronological order in association with the photographing time. The correlation information storage unit 17h is a part that stores the correlation between the load and the difference in relative displacement as correlation information. The correlation information storage unit 17h stores, for example, a correspondence between a load and a relative displacement difference (crack width) as illustrated in FIG. The visualized image information storage unit 17i is a part that stores a visualized image for visualizing and displaying a difference in relative displacement as visualized image information. The visualized image information storage unit 17i stores the visualized image information output from the visualized image generation unit 16 in chronological order in association with the shooting time. The deformation detection program storage unit 17j is a part that stores a deformation detection program for detecting a deformation generated in the bridge beam 3a by measuring the displacement of the lattice pattern 5A formed on the surface of the bridge beam 3a. The deformation detection program storage unit 17j stores a deformation detection program read from an information recording medium, a deformation detection program taken in through a telecommunication line, or the like.

  The display unit 18 shown in FIG. 4 is a means for displaying various information. The display unit 18 is, for example, a display device that displays captured image information, displacement information, divided image information, relative displacement information, relative displacement difference information, deformation information, load information, correlation information, and visualized image information.

The control unit 19 is a central processing unit (CPU) that controls various operations related to the deformation detection device 8. The control unit 19 reads the deformation detection program from the deformation detection program storage unit 17j, and executes a predetermined deformation detection process according to the deformation detection program. For example, the control unit 19 instructs the photographing device 7 to start and end the photographing operation based on the vibration information output from the vibration detecting device 6, and stores the photographed image information output from the photographing device 7. or commands the section 17a, and outputs the displacement calculation part 10 from the photographed image information storage unit 17a reads out the photographed image information, or command the operation of the displacement in the detection target region a ₀ to the displacement calculation unit 10, the displacement The displacement information storage unit 17b is instructed to store the displacement information output by the arithmetic unit 10, the captured image information is read from the captured image information storage unit 17a and output to the captured image dividing unit 11, or the captured image dividing unit 11 is read. The divided image information storage unit 17c is instructed to divide the captured image, instruct the captured image dividing unit 11 to re-divide the divided image, or to store the divided image information output by the captured image dividing unit 11. The displacement information is read from the displacement information storage unit 17b and output to the relative displacement calculation unit 12, the divided image information is read from the divided image information storage unit 17c and output to the relative displacement calculation unit 12, or the relative displacement calculation unit. 12 is instructed to calculate relative displacement, the relative displacement information storage unit 17d is instructed to store the relative displacement information output by the relative displacement calculation unit 12, and the relative displacement information is read out from the relative displacement information storage unit 17d. The relative displacement difference information is output to the displacement difference calculator 13, the relative displacement difference information output from the relative displacement difference calculator 13 is instructed to the relative displacement difference information storage unit 17e, or the relative displacement difference information is stored in the relative displacement difference information storage unit 17e. Is read out and output to the deformation detection unit 14, the deformation detection unit 14 is instructed to detect deformation, and the deformation information output from the deformation detection unit 14 is instructed to the deformation information storage unit 17f. Or read out relative displacement difference information from the relative displacement difference information storage unit 17e and output it to the load estimation unit 15, read out correlation information from the correlation information storage unit 17h and output it to the load estimation unit 15, Instructs the estimation unit 15 to estimate the load, instructs the load information storage unit 17g to store the load information output by the load estimation unit 15, and reads the relative displacement difference information from the relative displacement difference information storage unit 17e for visualization. Output to the image generation unit 16, instruct the visualization image generation unit 16 to generate a visualization image, instruct the visualization image information storage unit 17 i to store the visualization image information output from the visualization image generation unit 16, The display unit 18 is instructed to display the information. The control unit 19 includes an information input unit 9, a displacement calculation unit 10, a captured image division unit 11, a relative displacement calculation unit 12, a relative displacement difference calculation unit 13, a deformation detection unit 14, a load estimation unit 15, and a visualized image generation unit. 16, the information memory | storage part 17 and the display part 18 are connected so that it can communicate mutually.

Next, the operation of the deformation detection apparatus according to the first embodiment of the present invention will be described.
Below, it demonstrates centering around operation | movement of the control part 19 shown in FIG.
In step (hereinafter referred to as S) 100 shown in FIG. 9, the control unit 19 reads the deformation detection program from the deformation detection program storage unit 17j. When the measurer operates the deformation detection device 8 shown in FIG. 3 to start the deformation detection operation, power is supplied to the deformation detection device 8 from the power supply unit. As a result, the control unit 19 reads the change detection program from the change detection program storage unit 17j, and the control unit 19 executes a series of change detection processes.

In S110, the control unit 19 determines whether to start the shooting operation. As shown in FIG. 1, the vibration of the bridge beam 3a is increased when the vehicle 1 approaches the target detection area A ₀ of the bridge girder 3a. Therefore, when the control unit 19 determines that the level of the vibration detection signal input from the vibration detection device 6 shown in FIG. 4 to the control unit 19 through the information input unit 9 exceeds a predetermined value, the vehicle 1 is in the detection target region. control unit 19 to be close to a ₀ is determined. As a result, the control unit 19 determines that the photographing operation needs to be started by the photographing apparatus 7, and proceeds to S120. On the other hand, when the control unit 19 determines that the level of the vibration detection signal is equal to or lower than the predetermined value, the control unit 19 determines that the vehicle 1 is not approaching the detection target area A ₀ and the level of the vibration detection signal is The control unit 19 repeats the determination in S110 until the predetermined value is exceeded.

In S120, the control unit 19 instructs the photographing apparatus 7 to start the photographing operation. When the control unit 19 instructs the photographing apparatus 7 to start the photographing operation, the photographing apparatus 7 photographs the detection target area A ₀ where the lattice pattern 5A shown in FIGS. Outputs the captured image information to the control unit 19. As a result, the control unit 19 outputs the captured image information to the captured image information storage unit 17a, and the captured image information storage unit 17a stores the captured image information in chronological order.

In S130, the control unit 19 determines whether or not to end the shooting operation. From the detection target area A ₀ of the bridge girder 3a shown in FIG. 1 when the vehicle 1 is spaced apart vibrating bridge girder 3a is reduced. Therefore, when the vibration detecting device 6 control unit 19 and the level of the vibration detection signal is below the predetermined value to be input to the control unit 19 through the information input unit 9 determines the vehicle 1 is spaced apart from the detection target area A ₀ The control part 19 judges that it is. As a result, the control unit 19 determines that the photographing operation needs to be terminated by the photographing apparatus 7, and the process proceeds to S140. On the other hand, when the control unit 19 determines that the level of the vibration detection signal exceeds the predetermined value, the control unit 19 determines that the vehicle 1 is not separated from the detection target area A _0, and the level of the vibration detection signal is The control unit 19 repeats the determination in S130 until the value becomes equal to or less than the predetermined value.

In S140, the control unit 19 commands the operation of the displacement in the detection target region A ₀ to the displacement calculation unit 10. 4 the photographed image information captured image information from the storage unit 17a in the control unit 19 reads shown, and outputs the control section 19 of the photographed image information captured image dividing unit 11, the whole in the detection target area A ₀ The control unit 19 instructs the displacement calculation unit 10 to calculate the displacement. As a result, as shown in FIG. 7, the Moire fringes of the phase generated by sampling checkered 5A analyzes the displacement calculating unit 10 by the sampling moire method, the total displacement in the detection target area A ₀ shown in FIG. 3 Is calculated by the displacement calculation unit 10. When the displacement calculation unit 10 outputs the displacement information in the detection target area A ₀ to the control unit 19, the displacement information is stored in the displacement information storage unit 17b.

In S150, the control unit 19 instructs the captured image dividing unit 11 to divide the captured image. The control unit 19 reads out the captured image information from the captured image information storage unit 17a illustrated in FIG. 4 and outputs the captured image information to the captured image division unit 11. The control unit 19 outputs the captured image information to the captured image division unit 11. The control unit 19 commands the division. As a result, as shown in FIGS. 5 and 6A, the captured image dividing unit 11 divides the captured image of the detection target area A ₀ where the lattice pattern 5A exists for each of the areas A _{11 ,.} At this time, the captured image dividing unit 11 divides the captured image in the detection target area A ₀ into a relatively large area. When the captured image dividing unit 11 outputs the divided image information for each of the areas A ₁₁ ,..., A _MN to the control unit 19, the divided image information is stored in the divided image information storage unit 17c.

In S160, the area A _11, ..., the control unit 19 instructs the calculation of the relative displacement of each A _MN to the relative displacement calculating part 12. The control unit 19 reads out the displacement information from the displacement information storage unit 17b shown in FIG. 4 and outputs the displacement information to the relative displacement calculation unit 12. The control unit 19 also outputs the divided image information from the divided image information storage unit 17c. 19 reads out, and the control unit 19 outputs the divided image information to the relative displacement calculation unit 12. Region A _11, ..., the control unit 19 calculates the relative displacement of each A _MN to the relative displacement calculating part 12 instructs, the regions A _11, ..., the area average value of the displacement in the A _MN A _11, ..., The relative displacement calculation unit 12 calculates for each _AMN, and the relative displacement calculation unit 12 calculates the average value of the displacements as the relative displacement. When the relative displacement calculation unit 12 outputs the relative displacement information for each of the areas A ₁₁ ,..., A _MN to the control unit 19, the relative displacement information is stored in the relative displacement information storage unit 17d.

In S170, the control unit 19 instructs the relative displacement difference calculating unit 13 to calculate the relative displacement difference between the adjacent areas A _{11 ,.} As shown in FIG. 6D, the control unit 19 reads the relative displacement information from the relative displacement information storage unit 17d shown in FIG. 4 and outputs the relative displacement information to the relative displacement difference calculation unit 13. In addition, the control unit 19 instructs the relative displacement difference calculation unit 13 to calculate the relative displacement difference between the adjacent regions A _{11 ,.} As a result, the relative displacement difference calculation unit 13 calculates the relative displacement difference between the adjacent regions A ₁₁ ,..., _AMN , and the relative displacement difference calculation unit 13 outputs the relative displacement difference information to the control unit 19. The relative displacement difference information storage unit 17e stores the relative displacement difference information.

In S180, the control unit 19 determines whether or not to divide a region having a large relative displacement difference. The control unit 19 determines whether there is a region where the difference in relative displacement between adjacent regions is larger than a predetermined value among the relatively large regions divided by the captured image dividing unit 11. In order to efficiently detect cracks of various widths without being affected by noise, the photographed image in the detection target area A ₀ is divided into relatively large areas, and the relative displacement difference is calculated. It is preferable to calculate a relative displacement difference by finely subdividing only a region having a large difference into relatively small regions. For this reason, when the captured image is divided into relatively large areas, if the difference in relative displacement between adjacent areas is larger than a predetermined value, the area is further divided into differences in relative displacement between adjacent areas. Need to be calculated again. When the control unit 19 determines that it is necessary to subdivide the comparatively large area divided by the captured image dividing unit 11 more finely, the process returns to S150, and the control unit 19 repeats the processing after S150. As a result, in S150, the captured image dividing unit 11 subdivides an area where the difference in relative displacement between adjacent areas is larger than a predetermined value into a relatively small area, and in S160, the average of the displacements in the relatively small area The relative displacement calculation unit 12 calculates the value as a relative displacement. On the other hand, when the captured image is divided into relatively large areas, if the difference in relative displacement between adjacent areas is equal to or less than a predetermined value, the control unit 19 determines that there is no need to further subdivide the captured image. Then, the process proceeds to S190.

In S190, the control unit 19 instructs the deformation detection unit 14 to detect the deformation. The control unit 19 reads out the relative displacement difference information from the relative displacement difference information storage unit 17e shown in FIG. 4 and outputs the relative displacement difference information to the deformation detection unit 14, and the presence / absence of cracks is detected. The control unit 19 instructs the deformation detection unit 14 to detect the width, the occurrence position of the crack, and the direction in which the crack propagates. As a result, the presence / absence of crack generation, crack width, crack generation position, and crack propagation direction in the detection target region A ₀ shown in FIGS. 1 to 3, 5, and 6 (B) to (D) are changed. The detection part 14 detects. When the change detection unit 14 outputs these detection results as change information to the control unit 19, the change information storage unit 17f stores the change information.

  In S200, the control unit 19 instructs the load estimation unit 15 to estimate the load. The control unit 19 reads out the relative displacement difference information from the relative displacement difference information storage unit 17e shown in FIG. 4 and outputs the relative displacement difference information to the load estimation unit 15, and the correlation information from the correlation information storage unit 17h. The control unit 19 reads out the relationship information, and the control unit 19 outputs this correlation information to the load estimation unit 15. When the controller 19 instructs the load estimator 15 to estimate the load, the load estimator 15 refers to the correlation information shown in FIG. 8 and the load estimator 15 identifies the load corresponding to the difference in relative displacement. When the load estimation unit 15 outputs the estimation result as load information to the control unit 19, the load information storage unit 17g stores the load information.

  In S210, the control unit 19 instructs the visualized image generation unit 16 to generate a visualized image. The control unit 19 reads out the relative displacement difference information from the relative displacement difference information storage unit 17e shown in FIG. 4 and outputs the relative displacement difference information to the visualized image generating unit 16, and the visualization image is generated by generating the visualized image. The control unit 19 instructs the generation unit 16. As a result, for example, the visualized image generating unit 16 generates a contour diagram corresponding to the width of the crack, and the visualized image generating unit 16 outputs the visualized image as visualized image information to the control unit 19 to be visualized image information storage unit 17i. Stores the visualized image information.

  In S220, the control unit 19 instructs the display unit 18 to display various information. The control unit 19 reads various information from the information storage unit 17 and outputs this information to the display unit 18. As a result, for example, the display unit 18 displays captured image information, displacement information, divided image information, relative displacement information, relative displacement difference information, deformation information, load information, correlation information, and visualized image information on the display screen. To do.

  In S230, the control unit 19 determines whether or not to detect the deformation. When the measurer operates the change detection device 8 shown in FIG. 4 to end the change detection operation, the control unit 19 determines that the change detection ends, and the control unit 19 performs a series of change detection processes. finish. On the other hand, when the measurer does not operate the change detection device 8 and the change detection operation is not terminated, the process returns to S110, and the control unit 19 repeats the processes after S110.

The deformation detection device and the deformation detection program according to the first embodiment of the present invention have the following effects.
(1) In the first embodiment, a lattice pattern 5A plurality of regions A ₁₁ an imaged image obtained by imaging a, ..., shooting A _MN image dividing unit 11 divides a plurality of regions A _11, ..., the A _MN The relative displacement calculation unit 12 calculates the relative displacement, and the deformation detection unit 14 detects the deformation based on the calculation result of the relative displacement calculation unit 12. For this reason, for example, by comparing the captured images before and after the occurrence of a crack and measuring the relative displacement using an image measurement technique, it is possible to efficiently and quantitatively evaluate the occurrence of a fine crack.

(2) In the first embodiment, based on the calculation result of the relative displacement calculation unit 12, the relative displacement difference calculation unit 13 calculates the difference between the relative displacements between the adjacent areas A _{11 ,.} Based on the relative displacement difference, the deformation detection unit 14 detects the deformation. Therefore, it is possible to easily determine whether or not the deformation has occurred based on the difference in relative displacement between the adjacent areas A ₁₁ ,..., _AMN , and the occurrence of the deformation in the detection target area A ₀ . Can be detected with high accuracy.

(3) In the first embodiment, the captured image dividing unit 11 subdivides the plurality of regions A ₁₁ ,..., _AMN into smaller regions based on the calculation result of the relative displacement difference calculating unit 13. In the first embodiment, the relative displacement difference calculation unit 13 calculates the difference in relative displacement between the plurality of regions A ₁₁ ,..., A _MN after subdivision. Furthermore, in the first embodiment, the deformation detection unit 14 detects a deformation that occurs in the bridge girder 3a based on the difference in relative displacement after the re-division. For example, if the captured image in the detection target area A ₀ is divided into small areas from the beginning, the relative displacement may not be measured if the width of the crack is wide. In the first embodiment, the relative displacement difference between adjacent regions is calculated while the detection target region A ₀ is divided stepwise from a relatively large region to a relatively small region. For this reason, it is possible to detect cracks having various widths such that the width of the crack is larger than one pixel. In addition, it is possible to narrow down the occurrence position of the crack and to efficiently specify the occurrence position of the crack. Furthermore, the amount of information required for the calculation process can be reduced, and the calculation required for crack detection can be completed in a short time.

(4) In the first embodiment, when the difference in relative displacement exceeds the threshold value th, the deformation detection unit 14 determines that a crack has occurred, and the difference in relative displacement is equal to or less than the threshold value th. Sometimes the deformation detection unit 14 determines that no crack has occurred. Therefore, it is possible to easily determine the presence or absence of cracks using the threshold value th as a criterion, and cracks are generated between the regions A ₁₁ ,..., A _MN where the difference in relative displacement is larger than the threshold value th. The occurrence can be easily detected.

(5) In the first embodiment, the deformation detection unit 14 detects the width of the crack based on the calculation result of the relative displacement difference calculation unit 13. For this reason, the difference in relative displacement is regarded as the crack width, and the crack width can be easily specified.

(6) In the first embodiment, the load estimating unit 15 estimates the load acting on the bridge girder 3a based on the relative displacement difference calculated by the relative displacement difference calculating unit 13. For this reason, by detecting the relationship between crack width (difference in relative displacement) and load in advance using the deformation detection system 4 or numerical analysis, this detection is performed from the crack measurement result of the detection object such as an actual structure. The load acting on the object can be easily estimated.

(7) In the first embodiment, the visualized image generating unit 16 generates a visualized image for visualizing and displaying the difference between the relative displacements. For this reason, when the difference in relative displacement is regarded as the crack width, a visualized image like a contour diagram can be easily generated according to the width of the crack. I can grasp it.

(8) In the first embodiment, the deformation detection unit 14 detects the deformation based on the detection result of the vibration detection device 6 that detects the vibration of the bridge girder 3a. For this reason, for example, a dynamic crack such as a concrete structure when passing a train can be efficiently measured and inspected by a crack measurement system based on image measurement. For example, when the bridge girder 3a is a PC girder or a PRC girder, prestress is applied by a tension material or the like, so that even if a crack is generated, the crack may be closed. In the first embodiment, the deflection and vibration bridge girder 3a the vehicle 1 passes, taking the detection subject region A ₀ by the imaging device 7 in cracks open timing, to detect the cracks by Deformation detector 14. Therefore, it is possible to detect the dynamic crack generated in the detection target area A ₀ with high accuracy. Further, by detecting the vibration of the bridge girder 3a, automatically to initiate the Henjo detection operation when the vehicle 1 approaches the detection target area A ₀ of the bridge girder 3a, the vehicle 1 from the detection target area A ₀ of the bridge girder 3a The deformation detection operation can be automatically terminated when the two are separated.

(Second Embodiment)
In the following, the same parts as those shown in FIGS. 1 to 8 are denoted by the same reference numerals and detailed description thereof is omitted.
The deformation detection system 4 shown in FIG. 10 is a system that detects the deformation generated in the bridge girder 3a by measuring the displacement of the random pattern 5B formed on the surface of the bridge girder 3a. The deformation detection system 4 detects the deformation of the bridge girder 3a by using the image correlation method. Here, the image correlation method (digital image correlation method) is a comparison of the captured image of the detection target area A ₀ where the random pattern 5B exists before and after the occurrence of deformation (before and after deformation), and the displacement of the detection target area A ₀ . Is a measurement technique for obtaining The deformation detection system 4 detects the vibration of the structure 3 with the vibration detection device 6, and images the random pattern 5 </ b> B when the vehicle 1 passes over the structure 3 with the imaging device 7. The photographed image is analyzed by the deformation detection device 8 to detect the deformation of the bridge girder 3a of the structure 3. As shown in FIG. 10, the deformation detection system 4 includes a random pattern 5B, a vibration detection device 6, a photographing device 7, a deformation detection device 8, and the like.

The random pattern 5B shown in FIGS. 10 to 12 is a characteristic pattern formed on the surface of the bridge girder 3a. As shown in FIG. 10, the random pattern 5B is irregularly formed on the surface of the bridge beam 3a. When the random pattern 5B is formed on the bridge girder 3a from the beginning, for example, the surface of the bridge girder 3a is soiled, the aggregate is raised from the surface of the bridge girder 3a, or the random pattern formed by the formwork used during construction It is. The random pattern 5B is, for example, a random pattern formed on the surface of the bridge girder 3a by painting with a stamp, a cutting sheet, or masking when the bridge girder 3a is formed later. As shown in FIG. 10, the random pattern 5B is formed in the detection target region A _{0 because} the deformation of the bridge beam 3a has already occurred or is predicted to occur.

An imaging apparatus 7 shown in FIG. 10 is an apparatus that images a detection target area A _{0 where} a random pattern 5B exists. The imaging device 7 is, for example, a CCD (Charge Coupled Device) camera using a charge coupled device. When the whole or a part of the position where the random pattern 5B is formed is the detection target area A ₀ , the imaging device 7 captures the detection target area A ₀ as an imaging area. The imaging device 7 captures the detection target area A ₀ every time the vehicle 1 passes over the structure 3, and captures the detection target area A ₀ before and after the occurrence of the deformation.

The deformation detection device 8 is a device that detects the deformation generated in the bridge beam 3a by measuring the displacement of the random pattern 5B formed on the surface of the bridge beam 3a. Deformation sensing device 8, detection target area A ₀ of the area A ₁₁ that is present in the random pattern 5B, ..., divided into A _MN, this region A _11, ..., the bridge beam 3a calculates the relative displacement of the A _MN Detect the deformation that occurs.

Displacement calculating unit 10 shown in FIG. 4, as shown in FIG. 12, the captured image of the random pattern 5B of Deformation before and after the occurrence (longitudinal deformation) as compared with the image correlation method, the displacement in the detection target area A ₀ Calculate. As shown in FIG. 13, the displacement calculation unit 10 compares the subset A _{S in} the detection target area A ₀ before occurrence of deformation with the subset A _{S in} the detection target area A ₀ after occurrence of deformation, The total displacement in the detection target area A ₀ is calculated. Displacement calculation unit 10, the subset A _S in the detection target area A ₀ of Deformation occurs (before deformation), by locating a position moved after Deformation occurs (after deformation), the detection target area A in ₀ The displacement of is calculated. Here, the subset A _S, a calculation area including a plurality of pixels (e.g., 20 × 20 pixel region). Displacement calculation unit 10, the subset A _S in the detection target area A ₀ before Deformation evolution had moved after Deformation occurrence position calculated by using a correlation of the luminance value portion (light intensity distribution), Deformation occurs The movement amount of the front and rear subsets A _S is calculated as a displacement within the detection target area A ₀ .

As shown in FIG. 13, the displacement calculator 10 calculates the displacement in the detection target area A ₀ in the detection target area A ₀ by analyzing the displacement of the random pattern 5B before and after the occurrence of the deformation. Displacement calculation unit 10, characteristic portion is extracted as a subset A _S, the subset in the photographed image random pattern 5B after Deformation occurs exists in the captured image random pattern 5B before Deformation occurs exists locate the subset a _S having the same characteristics as a _S, the subset a _S before Deformation occurs to analyze whether it has moved much after Deformation occurs. The displacement calculation unit 10 searches the captured image after the occurrence of the deformation for a location where the brightness change in the captured image before the occurrence of the deformation is the same (a location where the correlation value of the luminance distribution becomes an extreme value). Displacement calculation unit 10 locates a subset A _S of the brightness distribution and the brightness distribution was substantially the same as or similar subsets A _S of Deformation occurs in the previous captured image from the captured image after Henjo generation. The displacement calculation unit 10 searches for an area having the same luminance distribution as that of the subset A _S before the occurrence of the deformation by using an evaluation coefficient (correlation coefficient) C shown in the following Expression 4.

Here, F (x, y) shown in Equation 4 is a luminance value at the coordinates (x, y) of the photographed image before the occurrence of the deformation, and G (x ^* , y ^* ) is a photograph after the occurrence of the deformation. It is a luminance value at the coordinates (x ^* , y ^* ) of the image. Displacement calculation unit 10, by locating the moving position of the subset A _S that maximizes the evaluation coefficient C shown in Equation 4, which calculates the displacement in the detection target area A _0.

The captured image dividing unit 11 shown in FIG. 4 is means for dividing a captured image obtained by capturing the random pattern 5B into a plurality of areas A _{11 ,.} As shown in FIG. 12, the photographed image dividing unit 11 divides a photographed image obtained by photographing the detection target region A ₀ where the random pattern 5B exists with the photographing device 7 into regions A _{11 ,.} A plurality of divided images are generated from the image. The photographed image dividing unit 11 first divides the photographed image of the detection target area A ₀ into a relatively large area, and among these relatively large areas, an area where the difference in relative displacement between adjacent areas is large is a finer area. Repeat the process of subdividing into.

The relative displacement calculation unit 12 shown in FIG. 4 is divided into the displacement in the detection target area A ₀ calculated by the image calculation method by the displacement calculation unit 10 and the areas A ₁₁ ,..., A _MN divided by the captured image division unit 11. Based on this, the relative displacement for each of the areas A ₁₁ ,..., A _MN shown in FIG. The relative displacement difference calculation unit 13 calculates a relative displacement difference between adjacent regions A ₁₁ ,..., _AMN based on the calculation result of the relative displacement calculation unit 12. Deformation detecting section 14, as shown in FIG. 12, a random pattern 5B plurality of regions A ₁₁ an imaged image obtained by imaging a, ..., when divided into A _MN, these regions A _11, ..., the A _MN Detect cracks based on relative displacement.

Next, the operation of the deformation detection apparatus according to the second embodiment of the present invention will be described.
In the following, the same processes as those shown in FIG. 9 are denoted by the same reference numerals and detailed description thereof is omitted.
In S120, the control unit 19 commands the start of the photographing operation in the photographing apparatus 7, the target detection area A ₀ random pattern 5B is present imaging device 7 is photographed. In S140, when the control unit 19 instructs the displacement calculation unit 10 to calculate the displacement in the detection target area A ₀ , the displacement calculation unit 10 calculates the displacement in the detection target area A ₀ by the image correlation method. In S150, the detection target region A region A ₁₁ captured images ₀ random pattern 5B are present, ..., photographing each A _MN image dividing unit 11 divides. This second embodiment has the same effect as the first embodiment.

Next, examples of the present invention will be described.
(Dynamic test for model bridge)
In order to verify the crack detection system according to the embodiment shown in FIG. 14A, which has the same structure as the deformation detection system 4 shown in FIGS. 1, 2, and 4, a dynamic test for a model bridge is performed. Carried out. As shown in FIG. 15, using a steel model bridge simulating a crack at the center of the span, the applicability to the dynamic measurement of the crack detection system shown in FIG. Measurements using a pie-type displacement meter were also performed at the same time. As shown in FIG. 14B, the grid target has a pitch of 1 mm in the vertical and horizontal directions (resolution is 0.002 mm), and the grid target is placed above and below the pie-type displacement meter according to the comparative example as shown in FIG. The magnet was bonded and placed. When comparing the crack detection system according to the example and the pi-type displacement meter according to the comparative example, it is assumed that the plane is maintained in the cross section of the simulated crack occurrence position, and the pie-type displacement meter according to the comparative example The displacement obtained from the installed grid target was compared by converting it to a displacement at the same position as the pie-type displacement meter according to the comparative example. Excitation of the model bridge was carried out with a vibrator (SSV-125 manufactured by Sanes Co., Ltd.).

(Bending fracture test for PC sleepers)
In order to verify the crack detection system according to the example shown in FIG. 14, a bending fracture test for PC sleepers was performed. The bending test was based on JIS E1201 and a forward bending test at the rail position was performed with a loading span of 700 mm. In the bending fracture test, as a method for creating a target that follows cracks in concrete, a cutting sheet (PC sleeper 1) with a grid pitch of 10 mm shown in FIG. 17A and a grid pitch of 2 mm shown in FIG. A grid-like target was formed by using two types of stamps (PC sleeper 2), and it was verified whether cracking, crack distribution, crack width, and crack propagation direction could be detected. The camera used was a CMOS monochrome camera capable of shooting at a maximum of 170 fps (frames per second) with 2 million pixels.

(Verification result of dynamic test for model bridge)
FIG. 18 shows a measurement result using a model bridge. The vertical axis shown in FIG. 18 is the crack width (mm), and the horizontal axis is time (s). As shown in FIG. 18, the crack detection system according to the example can detect the width of the crack with a precision comparable to that of the pie-type displacement meter according to the comparative example with respect to a displacement region smaller than about 0.1 mm. It was confirmed. It was also confirmed that the dynamic behavior below 20Hz, which is the target of actual concrete structure measurement, can be captured with high accuracy by photographing at 150fps. From the above, it was confirmed that the crack measurement system according to the example can handle the dynamic measurement of cracks in the actual structure.

(Verification result of bending fracture test for PC sleepers)
FIG. 19A is a load displacement curve at the time of a bending fracture test, in which the vertical axis represents the load load (kN) and the horizontal axis represents the displacement (mm). FIG. 19B shows the relationship between the relative displacement of the lattice target at the position where the crack is sandwiched and the load, the vertical axis is the load (kN), and the horizontal axis is the relative displacement (mm). In the bending fracture test of PC sleepers 1 and 2 shown in FIG. 19, cracks occur at a plurality of locations. The cracks targeted in this bending fracture test are cracks generated immediately below the loading point. As shown in FIG. 19B, cracks occurred at points (inflection points) at which the degree of increase in relative displacement between the lattice targets was increased. As shown in Fig. 19 (B), PC sleeper 2 uses a lattice target with a finer grid pitch than PC sleeper 1, so PC sleeper 2 has less noise than PC sleeper 1. Obtained. Further, as shown in FIG. 19B, it was confirmed that the relationship between the relative displacement (crack width) and the loaded load can be grasped.

  Table 1 is a table showing a comparison of the crack generation load at the time of the bending fracture test detected visually by the crack detection system according to the example. As shown in Table 1, the crack generation load in the crack detection system according to the example is the load at the inflection point shown in FIG. As shown in Table 1, it was confirmed that the crack detection system according to the example can detect the occurrence of cracks at an earlier stage than visual inspection. Moreover, it was confirmed that the loading load of the structure can be evaluated from the result of the crack measurement from the relationship between the relative displacement (crack width) and the loading load.

  FIG. 20 is a crack distribution diagram of the PC sleeper 2 obtained by the crack detection system according to the embodiment of the present invention. In the visualized image of the crack occurrence state shown in FIG. 20 (C), the relative displacement of the inflection point shown in FIG. 19 (B) is set as a threshold value (threshold value th shown in FIG. 8). When the threshold value was exceeded, cracks occurred, and the difference in relative displacement was displayed as the crack width. As a result, as shown in FIG. 20, it was confirmed that the distribution of cracks generated in the PC sleepers can be detected by the crack detection system according to the example. From the above results, it is possible to estimate the load acting from the crack measurement result even in actual structures by grasping the relationship between crack width and load in advance with the crack detection system and numerical analysis according to the example. It was confirmed that there was.

(Other embodiments)
The present invention is not limited to the embodiment described above, and various modifications or changes can be made as described below, and these are also within the scope of the present invention.
(1) In this embodiment, the case where the structure 3 is a concrete structure such as a concrete bridge has been described as an example. However, the present invention can also be applied to a steel structure such as a steel bridge. In this embodiment, the case where the structure 3 is a concrete bridge has been described as an example. However, the present invention can also be applied to a concrete viaduct or the like.

(2) In this embodiment, the case where the detection target is the structure 3 has been described as an example. However, the present invention is also applied to a detection target such as a specimen used in a load test or a fatigue test. can do. Moreover, in this embodiment, the case where the deformation | transformation detection part 14 detects deformation | transformation of the presence or absence of the crack generation | occurrence | production of the bridge girder 3a, the width of a crack, the generation | occurrence | production position of a crack, and the propagation direction of a crack was mentioned as an example and demonstrated. However, the deformation detector 14 can also detect deformation such as expansion or deformation of the concrete of the bridge girder 3a.

(3) In the first embodiment, the case where the relative displacement is calculated by the phase shift method has been described as an example. However, the relative displacement calculation method is not limited to the phase shift method. For example, the present invention can be applied to the case where the relative displacement is calculated by the Fourier transform phase shift method, the feature amount extraction method, the correlation phase shift method, or the integral type phase shift method. In the case of the Fourier transform phase shift method, a display device such as a projector projects a lattice pattern on the surface of the bridge girder 3a, and a photographing device 7 such as a CCD camera photographs the detection target area A ₀ where the lattice pattern exists, Based on the lattice-patterned image, the displacement calculator 10 calculates the displacement in the detection target area A ₀ by the Fourier transform method. The displacement calculation unit 10 performs Fourier transform on the captured image of the lattice pattern after the deformation, inverse Fourier transforms the spectrum after the filtering process, calculates a phase distribution in a complex analysis, and calculates a displacement in the detection target area A ₀ . To do.

(4) In the first embodiment, the case where the grid pattern 5A is formed by arranging black squares on the white background at regular intervals in the vertical and horizontal directions has been described as an example. This invention can be applied. For example, white squares or dots are formed on a black background in a vertical and horizontal direction at regular intervals, black dots are formed on a white background in a vertical and horizontal direction, and black and white straight lines are formed in a vertical and / or vertical direction. Alternatively, they may be formed alternately in the horizontal direction at regular intervals. In the first embodiment, the case where the relative displacement difference corresponding to the inflection point at which the inclination direction of the correlation function between the relative displacement difference and the load is changed is determined as the threshold value has been described as an example. However, it is not limited to such a determination method. For example, if there is a visible crack in the captured image, the threshold is determined by measuring the width of the crack, or if there is no visible crack, the past measurement result or numerical analysis result The present invention can also be applied to a method for determining a threshold from the above.

1 vehicle 2 track 3 structure 3a bridge girder (object to be detected)
4 Deformation detection system 5A Grid pattern (characteristic pattern)
5B Random pattern (characteristic pattern)
DESCRIPTION OF SYMBOLS 6 Vibration detection apparatus 7 Imaging device 8 Deformation detection apparatus 9 Information input part 10 Displacement calculation part 11 Captured image division part 12 Relative displacement calculation part 13 Relative displacement difference calculation part 14 Deformation detection part 15 Load estimation part 16 Visualization image generation part 19 control unit 17 information storage unit 18 display unit A ₀ detection target area A ₁₁ to A _MN area A _S subsets
th threshold

Claims (16)

A deformation detection device for detecting a deformation generated in the detection object by measuring a displacement of a characteristic pattern formed on the surface of the detection object,
A photographed image dividing unit that divides the photographed image of the characteristic pattern into a plurality of regions;
A relative displacement calculator that calculates the relative displacement of the plurality of regions;
Based on the calculation result of the relative displacement calculation unit, a deformation detection unit that detects a deformation that occurs in the detection object;
A deformation detection device comprising: The deformation detection device according to claim 1,
Based on the calculation result of the relative displacement calculation unit, a relative displacement difference calculation unit that calculates the difference of relative displacement between the adjacent regions,
The deformation detection unit detects a deformation generated in the detection object based on the difference in the relative displacement;
A deformation detection device characterized by the above. The deformation detection device according to claim 2,
The captured image division unit re-divides the plurality of regions into finer regions based on the calculation result of the relative displacement difference calculation unit,
The relative displacement difference calculation unit calculates a difference in relative displacement between the plurality of regions after subdivision,
The deformation detection unit detects a deformation generated in the detection object based on a difference between the relative displacements after the subdivision;
A deformation detection device characterized by the above. In the deformation detection device according to claim 2 or 3,
The deformation detection unit determines that a crack has occurred in the detection object when the difference in relative displacement exceeds a threshold value, and detects the detection object when the difference in relative displacement is equal to or less than the threshold value. Determining that there are no cracks in the object,
A deformation detection device characterized by the above. In the deformation detection device according to any one of claims 2 to 4,
The deformation detection unit detects a width of a crack generated in the detection object based on the difference in the relative displacement;
A deformation detection device characterized by the above. In the deformation detection device according to any one of claims 2 to 5,
A load estimation unit for estimating a load acting on the detection object based on the relative displacement difference;
A deformation detection device characterized by the above. In the deformation detection apparatus according to any one of claims 2 to 6,
A visualized image generation unit that generates a visualized image for visualizing and displaying the difference between the relative displacements;
A deformation detection device characterized by the above. In the deformation detection apparatus according to any one of claims 1 to 7,
The deformation detection unit detects a deformation generated in the detection object based on a detection result of a vibration detection device that detects vibration of the detection object;
A deformation detection device characterized by the above. A deformation detection program for detecting a deformation generated in the detection object by measuring a displacement of a characteristic pattern formed on the surface of the detection object,
A captured image dividing procedure for dividing the captured image of the characteristic pattern into a plurality of regions;
A relative displacement calculation procedure for calculating the relative displacement of the plurality of regions;
Based on the calculation result in the relative displacement calculation procedure, a deformation detection procedure for detecting a deformation that occurs in the detection object;
Deformation detection program that causes a computer to execute. In the deformation detection program according to claim 9,
Based on a calculation result in the relative displacement calculation procedure, including a relative displacement difference calculation procedure for calculating a difference in relative displacement between the adjacent regions,
The deformation detection procedure includes a procedure of detecting a deformation occurring in the detection object based on the difference in the relative displacement.
Deformation detection program characterized by In the deformation detection program according to claim 9 or 10,
The captured image dividing procedure includes a procedure of re-dividing the plurality of regions into finer regions based on a calculation result in the relative displacement difference calculating procedure.
The relative displacement difference calculation procedure includes a procedure for calculating a difference of relative displacement between the plurality of regions after the subdivision,
The deformation detection procedure includes a procedure of detecting a deformation that occurs in the detection object based on the difference in the relative displacement after the subdivision.
Deformation detection program characterized by In the deformation detection program according to claim 10 or 11,
The deformation detection procedure determines that a crack has occurred in the detection target when the difference in relative displacement exceeds a threshold value, and detects the detection target when the difference in relative displacement is equal to or less than the threshold value. Including a procedure to determine that the object has not been cracked,
Deformation detection program characterized by In the deformation detection program according to any one of claims 10 to 13,
The deformation detection procedure includes a procedure of detecting a width of a crack generated in the detection object based on the difference of the relative displacement.
Deformation detection program characterized by In the deformation detection program according to any one of claims 10 to 13,
Including a load estimation procedure for estimating a load acting on the detection object based on the difference of the relative displacement,
Deformation detection program characterized by In the deformation detection program according to any one of claims 10 to 14,
Including a visualized image generation procedure for generating a visualized image for visualizing and displaying the difference between the relative displacements;
Deformation detection program characterized by In the deformation detection program according to any one of claims 9 to 15,
The deformation detection procedure includes a procedure of detecting a deformation that occurs in the detection target based on a detection result of a vibration detection device that detects vibration of the detection target;
Deformation detection program characterized by