JP2019011995A - Rigidity measuring device, rigidity measuring method, and program - Google Patents

Abstract

To provide a rigidity measuring device that accurately and more quickly measures the rigidity of a measuring object by using picked-up images obtained by photographing the measuring object.SOLUTION: A rigidity measuring device 10 measures the rigidity of a measuring object on the basis of picked-up images photographed while exciting the measuring object, and comprises: an image information acquisition unit 35 that acquires a plurality of picked-up images of the measuring object photographed by the imaging unit 20 continuously every predetermined time; a displacement information calculation unit 36 that calculates displacement information from reference positions of a plurality of measuring points of the measuring object on the basis of the plurality of picked-up images; and a rigidity estimation unit 37 that estimates the rigidity of the measuring object on the basis of deflection of the measuring object calculated on the basis of the displacement information and deflection obtained through finite element analysis.SELECTED DRAWING: Figure 2

Description

  The present invention relates to a stiffness detection device, a stiffness detection method, and a program.

  As disclosed in Patent Documents 1 and 2, there is known a method for grasping physical properties such as strength of concrete by measuring the elastic wave velocity propagating inside when hitting the surface of a concrete structure. Yes.

  In the method for diagnosing the deterioration of a floor slab based on the elastic wave velocity ratio of Patent Document 1, a method for estimating the progress of cracks and deterioration from a decrease in elastic wave velocity is shown. This document describes a method of hitting a floor slab with a steel hammer as a method of generating a shock elastic wave.

  In Patent Document 2, as a simple method of oscillating the walls of bridges and tunnels, a large oscillating force can be obtained even in places where the inspector's hand cannot reach easily by throwing gunpowder toward the target point. The methods that can be generated are described.

  On the other hand, as disclosed in Patent Document 3, a laser beam is emitted toward a reflector (target) installed on a measurement target such as a bridge or a wall surface of a building, and the reflected laser beam is received. Devices for measuring vibration and deflection of a measurement object in a non-contact manner are known.

  In a concrete structure or the like, when cracks, local deterioration, damage, or the like occurs, it is known that the rigidity of the portion changes. Therefore, development of a technique for accurately detecting this rigidity is desired. Recently, with the widespread use of high-quality, high-sampling-rate video cameras such as 4K high-speed cameras, technology has been developed to detect various movements of various objects by analyzing captured image data. It is expected to be used for detection of rigidity for damage detection and condition evaluation of the target.

JP 2014-149285 A Japanese Patent Laying-Open No. 2015-203572 JP 2017-53772 A

  However, in the prior art described in Patent Documents 1-3, it is necessary to attach a sensor or a target to a measurement target. When a slant (cable) of a long-span bridge or a cable-stayed bridge is a measurement target, these are attached. It becomes difficult. On the other hand, when a 4K high-speed camera or the like is used, it is not necessary to install a target or the like, but the amount of image data is enormous, and it may be difficult to detect the rigidity of the measurement target at high speed.

  The present invention has been made in view of the above circumstances, and provides a stiffness detector that can detect the stiffness of a measurement target with higher accuracy and higher speed using a captured image obtained by photographing the measurement target. The purpose is to do.

  In order to achieve the above object, the stiffness detector of the present invention is a stiffness detector that detects the stiffness of the measurement target based on a captured image that is taken by vibrating the measurement target, and is provided at predetermined intervals. An image information acquisition unit that acquires a plurality of captured images of the measurement object that are continuously photographed, and displacement information from a reference position of the plurality of measurement points of the measurement object based on the plurality of captured images A displacement information calculation unit, a deflection of the measurement object calculated based on the displacement information, and a rigidity estimation unit that estimates the rigidity of the measurement object based on a deflection by finite element analysis. And

  Here, the stiffness estimator calculates a mean square error between the deflection of the measurement target at all nodes at the time when the maximum value of the deflection is obtained and the deflection by the finite element analysis, and the mean square error is While the value is smaller than the previously calculated mean square error, the stiffness value is updated by changing from a predetermined initial value by a predetermined amount, and the stiffness value when not updated more than a predetermined number of times is defined as the stiffness of the measurement target. It can be configured. Alternatively, the rigidity estimation unit calculates the curvature between adjacent nodes based on the deflection of the measurement object at all nodes at the time when the maximum value of deflection is obtained and the deflection by finite element analysis, A mean square error between the curvature of the measurement object at the node and the curvature of the finite element analysis is calculated, and while the mean square error is smaller than the previously calculated mean square error, the stiffness value is set to a predetermined initial value. It is possible to adopt a configuration in which the stiffness value is updated by varying by a predetermined amount, and the stiffness value when not updated more than a predetermined number of times is set as the stiffness of the measurement object. Furthermore, it can be set as the structure provided with the state detection part which detects the state of the said measuring object based on the rigidity of the said measuring object estimated by the said rigidity estimation part.

  Further, the stiffness detection method of the present invention is a stiffness detection method performed by the stiffness detection apparatus as described above, and a step of acquiring a plurality of captured images of a measurement object continuously photographed every predetermined time; A step of calculating displacement information from a reference position of a plurality of measurement points of the measurement object based on the plurality of captured images, a deflection of the measurement object calculated based on the displacement information, and a deflection by finite element analysis And estimating the rigidity of the measurement object based on the above.

  Further, the program of the present invention includes a computer that acquires a plurality of captured images of a measurement target that are continuously captured every predetermined time, and a plurality of measurements of the measurement target based on the plurality of captured images. It functions as means for calculating displacement information from a reference position of a point, and means for estimating the rigidity of the measurement object based on the deflection of the measurement object calculated based on the displacement information and the deflection by finite element analysis. It is a program for functioning as a program means.

  According to the present invention configured as described above, the displacement information of the plurality of measurement points of the measurement target is calculated based on the plurality of captured images of the measurement target continuously photographed every predetermined time, and the displacement information Based on the above, the deflection shape of the measurement object is calculated. Then, the stiffness distribution of the measurement target is estimated based on the calculated deflection of the measurement target and the deflection by the finite element analysis. Therefore, it is possible to detect the rigidity of the measurement object with higher accuracy and at higher speed using the captured image obtained by photographing the measurement object.

  In addition, the rigidity estimation unit calculates a mean square error between the deflection of the measurement target and the deflection by the finite element analysis, and if the rigidity of the measurement target is estimated based on the mean square error, the entire measurement target Stiffness can be detected. The measurer who observed this rigidity can accurately grasp the state of the overall rigidity of the measurement object. The stiffness estimator calculates the respective curvatures based on the deflection of the measurement target and the deflection of the finite element analysis, calculates the mean square error between the curvature of the measurement target and the curvature of the finite element analysis, and calculates this square. If it is the structure which estimates the rigidity of a measuring object based on an average error, the local rigidity of a measuring object can be detected. A measurer who observes this rigidity can accurately specify a location where a crack, local deterioration, damage, or the like of the measurement target has occurred. In addition, if the configuration includes a state detection unit that detects the state of the measurement target based on the rigidity of the measurement target estimated by the stiffness estimation unit, the measurement target is accurately cracked, locally deteriorated, damaged, and the like. It can be automatically detected and presented to the measurer.

It is a figure for demonstrating the whole structure and rigidity detection condition of the rigidity detection apparatus of 1st Embodiment. It is a functional block diagram showing the function of the rigidity detection apparatus shown in FIG. It is a figure showing an example of the three-dimensional image produced | generated based on the displacement data measured at each measurement point, and its rigid deformation component and bending deformation component by impact-exciting a model bridge. It is a figure for demonstrating the estimation procedure of whole rigidity (EI). It is a figure for demonstrating the estimation procedure of local rigidity (EI). It is a flowchart which shows an example of the process of the rigidity detection method performed with the rigidity detection apparatus of 1st Embodiment. It is a flowchart which shows an example of the process of total rigidity estimation. It is a flowchart which shows an example of the process of local rigidity estimation.

(First embodiment)
Hereinafter, a first embodiment of the present invention will be described with reference to the drawings. FIG. 1 is a diagram for explaining the overall configuration and measurement status of the stiffness detector 10 of the first embodiment. FIG. 2 is a functional block diagram showing functions of the rigidity detection device 10.

  The rigidity detection device 10 of the present embodiment measures a displacement such as vibration or deformation of the measurement target, and estimates (detects) the rigidity of the measurement target based on the displacement. The object to be measured is any structure or form as long as displacement occurs, such as a beam-like structure such as a bridge girder of a bridge, a structure such as a building or a retaining wall, or a feature such as a ground, a slope, or a bedrock. Also good.

  In FIG. 1, the RC girder 2 of the bridge 1 like a concrete railway bridge is illustrated as a measuring object. The RC girder 2 is a concrete structure having a rectangular shape in plan view, and is spanned between the piers 3 and 3. In the RC girder 2, for example, cracks may occur or local deterioration or damage may occur due to an impact caused by traveling of the train T or the like. Since the RC girder 2 has the same cross-sectional shape in the longitudinal direction (line direction), the rigidity of only the portion where a crack or the like occurs changes (decreases).

  Further, the object to be measured may be an elongated object such as a cable stayed cable (cable). For example, when the measurement target is a cable-stayed bridge or a long-span bridge, it may be difficult to photograph a portion where the rigidity is to be detected. In such a case, for example, a captured image obtained by photographing an oblique material can be used.

  As shown in FIG. 1, the rigidity detection device 10 of the present embodiment includes an imaging unit 20 that continuously captures captured images of a structure to be measured every predetermined time, and imaging that is sequentially input from the imaging unit 20. A calculation unit 30 that calculates the displacement of the measurement target based on the image and detects the rigidity based on the displacement, and a cable 40 that connects the imaging unit 20 and the calculation unit 30 are configured.

  In the present embodiment, the imaging unit 20 and the calculation unit 30 transmit and receive captured images and the like via the cable 40, but are not limited to this. For example, image data can be transmitted and received using short-range wireless communication such as Bluetooth (registered trademark) or wireless LAN communication such as WiFi (registered trademark).

  In the present embodiment, the RC girder 2 is hit with the hammer 50 to perform impact excitation. The hammer 50 is provided with a sensor unit 51 such as an acceleration sensor. The sensor unit 51 is connected to the calculation unit 30 by wireless communication as described above, detects the impact excitation by the hammer 50, and outputs the time data and physical property data of the impact excitation to the calculation unit 30. ing. Note that the arithmetic unit 30 and the sensor unit 51 may be connected by wire.

  The imaging unit 20 includes an imaging optical system that forms a subject image of a structure, an imaging device such as a CCD or CMOS that converts the subject image into an electrical signal, and outputs the electrical signal. The imaging unit 20 is not particularly limited as long as the captured image of the structure can be continuously captured every predetermined time and output as image data, but in order to accurately measure the displacement, It is desirable to use a digital video camera with high image quality and high sampling rate. More specifically, it is desirable to use a digital video camera having a resolution of 720 × 480 or higher and a sampling frequency (frame rate frequency) of 60 Hz or higher. In this embodiment, a digital video camera having a resolution of 1,920 × 600, a sampling frequency of 120 Hz, and a high sampling rate is used.

  The captured image captured by the imaging unit 20 may be a still image captured continuously every predetermined time or a frame image of a moving image.

  The imaging unit 20 may be held by a measurer and photographed. However, in the present embodiment, as shown in FIG. 1, the imaging unit 20 is supported by a tripod 21 and fixed to the ground or the like. By taking a picture, blurring and the like are suppressed. The imaging unit 20 can be mounted on a small unmanned aerial vehicle such as a drone so that a measurement object such as a structure can be photographed from the air. Can be taken.

  As the arithmetic unit 30, for example, a personal computer (PC) that includes a display unit 31 such as a liquid crystal display and an operation unit 32 such as a keyboard and a mouse and incorporates a CPU, RAM, ROM and the like can be used. As the PC, a desktop PC may be used, but since it is lightweight and excellent in portability, a notebook PC is used in this embodiment.

  As shown in FIG. 2, the calculation unit 30 includes a control unit (CPU) 33 that controls the operation of the entire stiffness detection apparatus 10, and a storage unit that stores various programs and data including RAM, ROM, flash memory, HDD, and the like. 34 and the like. The control unit 33 controls the rigidity detection apparatus 10 as a whole according to the program stored in the storage unit 34. In addition, the control unit 33 executes a stiffness detection method according to the stiffness detection program stored in the storage unit 34. That is, the control unit 33 also functions as an image information acquisition unit 35, a displacement information calculation unit 36, a rigidity estimation unit 37, a state detection unit 38, and a display image generation unit 39.

  The image information acquisition unit 35 acquires image data of a measurement target captured image input from the imaging unit 20. At this time, the image information acquisition unit 35 performs necessary image processing and processing (for example, coordinate conversion, contrast adjustment, color conversion, brightness adjustment, filter processing, etc.) on the acquired image data. The acquired image data is stored in the storage unit 34 and transferred to the displacement information calculation unit 36. Note that the storage in the storage unit 34 may be temporarily stored in the volatile memory or may be stored in the nonvolatile memory. The same applies to displacement data, deflection data, display image data, and the like described below.

  The displacement information calculation unit 36 determines in advance a plurality of measurement points to be measured for each piece of image data using a suitable image analysis tool for a plurality of pieces of image data obtained by the image information acquisition unit 35 every predetermined time. Displacement information (displacement data) from the predetermined reference position is calculated. Thereby, displacement data of a plurality of measurement points can be acquired. That is, the displacement data is represented as spatio-temporal data having a spatial direction (direction of the position of the measurement point) and a time direction (time axis direction of imaging). The calculated displacement data is stored in the storage unit 34 and transferred to the stiffness estimation unit 37.

  In order to detect the rigidity more accurately based on the displacement, for example, it is desirable to set a number of locations in the longitudinal direction of the RC beam 2 as measurement points. More specifically, the number of measurement points is preferably more than 100 points, more preferably 200 points or more, and it is desirable to measure so-called large-scale multipoint displacement data. By using a picked-up image taken by the image pickup unit 20 with high image quality and a high sampling rate, it is possible to acquire such large-scale multi-point displacement data. Rigidity can be detected with higher accuracy based on this large-scale multi-point displacement data.

  The stiffness estimator 37 extracts a flexure shape based on the displacement data calculated by the displacement information calculator 36, and estimates the stiffness distribution of the structure by numerical analysis using a finite element method based on the flexure shape. .

  It is known that when a beam-like structure such as a bridge is cracked or locally deteriorated or damaged, only the rigidity of the portion locally changes (decreases). Attempts have been made to detect such a local change in stiffness by means of the natural frequency or vibration mode shape, but it has been difficult to detect accurately because of low sensitivity. In addition, high-accuracy measurement of the vibration mode type requires a high-density sensor arrangement, which is difficult to obtain with existing sensors. Furthermore, in the vibration mode type, the influence of the identification error from the waveform data is large, and it is difficult to detect changes due to cracks or the like.

  Therefore, the inventor has focused on the deflection shape at the time of impact excitation among large-scale multi-point displacement data obtained based on the high-quality and high-sampling-rate captured image captured by the imaging unit 20. It has been found that the longitudinal stiffness distribution of the measurement target can be accurately estimated by numerical analysis using the finite element method using this flexure shape, and the present invention has been made.

  Based on the stiffness distribution estimated by the stiffness estimator 37, the state detector 38 determines whether or not the RC girder 2 is cracked, locally deteriorated, damaged, etc. To detect the state of the RC digit 2.

  The display image generation unit 39 generates an image representing the rigidity distribution estimated by the rigidity estimation unit 37 and the detection result of the state, and displays the image on the display unit 31.

  Next, a stiffness detection method performed by the stiffness detection apparatus 10 of the present embodiment will be described based on the flowcharts of FIGS. When detecting the rigidity, first, as shown in FIG. 1, the rigidity detecting device 10 is installed at a position where the entire image of the RC girder 2 of the bridge 1 that is the object of rigidity detection can be imaged. After that, by starting the arithmetic unit 30 and operating the operation unit 32, the stiffness detection program is started, and the imaging unit 20 is started to start photographing of the RC digit 2. Here, a moving image is taken.

  Then, the hammer 50 impacts the center of the RC girder 2 in the longitudinal direction. The imaging unit 20 takes a picture of how the RC girder 2 vibrates due to this impact excitation. Stiffness detection processing is started by outputting image data of a captured image from the imaging unit 20 to the calculation unit 30. The output of the image data may be performed in real time corresponding to the shooting of the moving image, or may be output at once after the shooting of the moving image for a predetermined time is completed. Good. In addition, time data and the like at the time of impact excitation detected by the sensor unit 51 are also output to the calculation unit 30.

  In the stiffness detection process, as shown in FIG. 6, first, in step S <b> 1, the image information acquisition unit 35 is a moving image captured after impact excitation from the imaging unit 20 based on the time data from the sensor unit 51. Image data (frame image data) is acquired. The image data is subjected to necessary image processing and processing. In the next step S2, the displacement information calculation unit 36 calculates and stores displacement data at a plurality of measurement points (for example, 200 points or more) for each frame by image analysis based on the image data acquired in step S1. Store in the unit 34.

  In the next step S3, the stiffness estimator 37 uses time-series displacement data (large-scale multipoint displacement data) at a plurality of measurement points calculated in step S2, the number of rows as time, and the number of columns as space. Reading from the storage unit 34 as a matrix. Next, in step S4, time data of impact excitation from the sensor unit 51 is acquired, and the process proceeds to step S5.

  In step S5, the rigidity estimation unit 37 acquires the deflection shape of the RC girder 2 based on the read displacement data and impact vibration time data. FIG. 3 shows an image of a deflection shape (three-dimensional image) obtained by plotting displacement data in a three-dimensional space of a time axis, a space axis, and a displacement axis. In FIG. 3, “Disp” represents a displacement, “Frame num.” Represents a frame number, that is, time, and “Measurement points” represents a position of a measurement point, that is, a space.

  Then, in step S6, from the deflection shape at the time of impact excitation, that is, the deflection shape at the time when the maximum value of the deflection is obtained (bending deformation component indicated by a thick solid line in FIG. 3), rigid body rotation and rigid body flattening are performed. The component (rigid body deformation component indicated by a thin solid line in FIG. 3) is removed. Specifically, only the bending component is extracted by calculating the slope and intercept of a straight line connecting two points on the left and right fulcrums at the time of impact excitation and subtracting from the deflection shape. Therefore, the calculation accuracy of the rigidity of the measurement object can be improved.

  Next, in step S7, using the beam model, a numerical analysis by a finite element method (FEM) is performed based on the number of measurement points and the number of nodes of the extracted bending shape of the bending component. Hereinafter, the beam model or result of this finite element analysis is referred to as a “finite element beam model”.

  Thereafter, the process proceeds to step S8, where the initial value EI0 of the bending stiffness is arbitrarily set, and the following two-step processing of the overall stiffness estimation in step S9 and the local stiffness estimation in step S10 is performed to estimate the stiffness. . In addition, in this embodiment, although both step S9 and S10 are performed, any one may be performed and either one of whole rigidity and local rigidity may be estimated.

  The procedure of the first stage process (total rigidity estimation) in step S9 will be described along the flowchart of FIG. FIG. 4 is a diagram for explaining the procedure for estimating the overall rigidity (EI). The schematic view of the RC girder 2 to be measured is shown in the upper part of the paper surface of FIG. 4, and the bending deformation component of the measurement target (hereinafter referred to as “measurement bending component deflection”) is indicated by a dashed line. The deflection of the finite element beam model is indicated by a solid line at the bottom of the page of FIG. In this step S9, the overall stiffness (EI) is estimated by comparing the deflection of the measured bending component with the deflection of the finite element beam model.

Specifically, the first stage process is performed according to the following procedure.
1. With respect to the finite element beam model, a load having a magnitude of 1 is loaded at the same position as the impact excitation position of the RC girder 2, and the deflection shape of the finite element beam model is calculated (step S91).
2. A correction coefficient is calculated using the following mathematical formula (step S92).
Correction factor = (Maximum deflection of measured bending component) / (Maximum deflection of finite element beam model)
3. The displacement of each node of the finite element beam model is multiplied by the correction coefficient obtained in step S92 so that the maximum deflection value of the finite element beam model obtained in step S91 is equal to the maximum deflection value of the measured bending component ( Step S93).
4). The mean square error (current) of the deflection of the measured bending component and the deflection of the finite element beam model at all nodes at the time when the maximum bending value of the measured bending component is obtained is calculated (step S94).
5. In order to gradually change the EI values of all nodes from the current EI, first, a new EI value is calculated. The new EI value may be averaged from the previous EI value, or may be generated from a normal distribution with a standard deviation of 10% of the previous EI value, and the EI can be varied randomly (step S95).
6). The deflection (finite element beam model) is calculated again with the new EI value calculated in the above step S95, corrected by multiplying by the correction coefficient, and the mean square error (new) of the deflection of the measured bending component and the deflection of the finite element beam model. ) Is calculated (step S96).
7). It is determined whether the root mean square error calculated in step S96 is smaller than the mean square error of the current EI value (step S97). If it is determined to be smaller (YES), the new EI value is set to the next EI value. The process returns to step S95 to update the EI value.
8). If it is determined in step S97 that the EI value is not reduced (NO), it is then determined whether or not the EI value has been updated a predetermined number of times (for example, 20 times or more) (step S98), and the update is performed a predetermined number of times. When it is determined that the above has been performed (NO), the process returns to step S95 to update the EI value.
9. If it is determined in step S98 that the EI value has not been updated a predetermined number of times (YES), the EI value has converged, and the EI value at that time is set as the overall rigidity (step S99).

  Next, the procedure of the second stage process (local stiffness estimation) in step S10 will be described along the flowchart of FIG. FIG. 5 shows a diagram for explaining the estimation procedure of the local stiffness (EI). The schematic diagram of the RC girder 2 to be measured is shown in the upper left part of the drawing sheet of FIG. 5, and the measured deflection component and the measured deflection component converted into the curvature are indicated by a one-dot chain line. In addition, in the lower left part of FIG. 5, the deflection of the finite element beam model and the deflection of the finite element beam model converted into the curvature are indicated by solid lines. Moreover, the figure which superimposed the curvature (one-dot chain line) of the measurement deflection component and the curvature (solid line) of the finite element beam model is shown on the right side of FIG. In step S10, the local stiffness (EI) is estimated by comparing the curvature of the measured deflection component with the curvature of the finite element beam model.

Specifically, the second stage process is performed according to the following procedure. When both step S9 and step S10 are executed, the following steps S101 to S104 may be omitted and the values calculated in steps S91 to S94 may be used.
1. A load of size 1 is loaded on the finite element beam model having EI obtained by the overall rigidity estimation in step S9 at a position similar to the impact excitation position of the RC girder 2, and a deflection shape is calculated (step S101). ).
2. A correction coefficient is calculated using the following mathematical formula (step S102).
Correction factor = (Maximum deflection of measured bending component) / (Maximum deflection of finite element beam model)
3. The displacement of each node of the finite element beam model is multiplied by the correction coefficient obtained in step S102 so that the maximum deflection value of the finite element beam model obtained in step S101 is equal to the maximum deflection value of the measured bending component. (Step S103).
4). The mean square error (current) of the deflection of the measured bending component and the deflection of the finite element beam model at all nodes at the time when the maximum deflection value of the measured bending component is obtained is calculated (step S104).
5. The difference (curvature) between adjacent nodes is calculated for the deflection of the measured bending component and the deflection of the finite element beam model (step S105).
6). The square error (current) of the curvature of the measured bending component and the curvature of the finite element beam model calculated at each node is calculated (step S106).
7). In order to change the EI value of an element corresponding to a node having a large error, first, a new EI value is calculated. The new EI value may be averaged from the previous EI value, or may be generated from a normal distribution with a standard deviation of 10% of the previous EI value, and the EI can be varied randomly (step S107).
9. The deflection (finite element beam model) is calculated again with the new EI value calculated in step S107, corrected by multiplying the correction coefficient, and the mean square error (new) of the curvature of the measured bending component and the curvature of the finite element beam model. ) Is calculated (step S108).
10. It is determined whether the root mean square error (new) calculated in step S108 is smaller than the mean square error (current) (step S109). If it is determined to be smaller (YES), a new EI value is selected. Returning to step S105 as the next EI value of the element, the EI value is updated.
11. If it is determined in step S109 that the EI value has not been reduced (NO), it is determined whether the EI value has been updated a predetermined number of times (for example, 20 times or more) (step S110), and the update has been performed a predetermined number of times or more. If it is determined (NO), the process returns to step S105 to update the EI value.
12 If it is determined in step S110 that the EI value has not been updated a predetermined number of times (YES), the EI value has converged, and the EI value at that time is set as local stiffness (step S111).

  As described above, when the processing of the overall rigidity estimation in step S9 and the local rigidity estimation process in step S10 is completed, the process proceeds to step S11 (see FIG. 6). In step S11, the state detection unit 38 determines whether cracks, local degradation, damage, or the like has occurred based on the overall stiffness distribution or the local stiffness distribution estimated in steps S9 and S10. If it has occurred, the location of the occurrence is specified and the state of the RC digit 2 is detected. In the examples of FIGS. 4 and 5, it can be detected that damage has occurred near the center of the RC beam 2 from the overall stiffness distribution or the local stiffness distribution.

  If a state is detected, it will progress to step S12 next. In step S <b> 12, the display image generation unit 39 generates an image representing the rigidity detection result such as the overall rigidity distribution, the local rigidity distribution estimated by the rigidity estimation unit 37, and the detected state. For example, a schematic diagram (see FIGS. 4 and 5) of the RC girder 2 to be measured, a numerical value of the stiffness distribution, a state of damage, an occurrence point of damage, and the like are generated and displayed on the display unit 31. .

  If the display image generation unit 39 displays a three-dimensional image of displacement as shown in FIG. 3 on the display unit 31 together with the detection result, the measurement person can visually recognize the deformation. At this time, visibility can be improved by changing the display color according to the magnitude of the displacement to make a gradation, or by making the overlapping portions of the graphs translucent.

  Next, the operation of this embodiment will be described. The rigidity detection apparatus 10 of the present embodiment includes an image information acquisition unit 35 that acquires a plurality of image data (captured images) of a measurement target that are continuously captured by the imaging unit 20 every predetermined time, and a plurality of image data. Based on the displacement information calculation unit 36 that calculates displacement data (displacement information) from the reference position of a plurality of measurement points of the measurement target, the deflection of the measurement target calculated based on the displacement information, and the deflection by the finite element analysis And a rigidity estimation unit 37 for estimating the rigidity of the measurement target.

  Further, the stiffness detection method of the present embodiment is performed by the stiffness detection apparatus 10 of the present embodiment, and acquires a plurality of captured images of the measurement target continuously captured every predetermined time by the imaging unit 20; Based on a plurality of captured images, based on the step of calculating displacement information from the reference position of a plurality of measurement points of the measurement target, the deflection of the measurement target calculated based on the displacement information, and the deflection by finite element analysis, And estimating the rigidity of the measurement object.

  In addition, the program of the present embodiment includes a computer that acquires a plurality of captured images of a measurement target that are continuously captured every predetermined time, and a plurality of measurement points of the measurement target based on the plurality of captured images. A program for functioning as a means for calculating the displacement information from the reference position, and a means for estimating the rigidity of the measurement object based on the deflection of the measurement object calculated based on the displacement information and the deflection based on the finite element analysis. is there.

  Therefore, in the present embodiment, by using the image captured by the imaging unit 20, a conventional target is not necessary, and displacement data at many measurement points can be acquired. In particular, by using the imaging unit 20 with high image quality and high sampling rate, large-scale multipoint displacement data (so-called big data) can be acquired. By calculating the deflection shape based on such large-scale multi-point displacement data (big data) and performing numerical analysis using the finite element method based on this deflection shape, the rigidity of the measurement target can be accurately determined. Can be detected. Further, even for large-scale multipoint displacement data, the rigidity of the measurement object can be detected at high speed by performing numerical analysis using a finite element. Further, an advanced sensor or the like is not necessary. Therefore, it is possible to provide the rigidity detection device 10, the rigidity detection method, and the program capable of detecting the rigidity of the measurement target with higher accuracy and at higher speed. Further, based on this rigidity, it is also possible to accurately detect the occurrence state, occurrence location, and the like of a crack, local deterioration, damage, etc. of the measurement object.

  In the present embodiment, the stiffness estimator 37 calculates the mean square error between the deflection of the measurement target at all nodes at the time when the maximum value of the deflection is obtained and the deflection by the finite element analysis, and the mean square error However, while the value is smaller than the previously calculated mean square error, the stiffness value is changed by a predetermined amount from the predetermined initial value and updated, and the stiffness value when not updated more than a predetermined number of times is determined as the stiffness of the measurement target ( Overall rigidity). The measurer who observed this rigidity can grasp the overall rigidity state of the measurement object.

  In the present embodiment, the rigidity estimation unit 37 calculates the curvature between adjacent nodes based on the deflection of the measurement target at all nodes at the time when the maximum value of deflection is obtained and the deflection by the finite element analysis. Calculate the mean square error between the curvature of the object to be measured at each node and the curvature of the finite element analysis, and while the mean square error is smaller than the previous mean square error, the stiffness value is The value is updated by changing the value by a predetermined amount, and the rigidity value when the value is not updated a predetermined number of times or more is set as the rigidity of the measurement target (local rigidity). A measurer who observes this rigidity can accurately specify a location where a crack, local deterioration, damage, or the like of the measurement target has occurred.

  In the present embodiment, the state detection unit 38 that detects the state of the measurement target based on the rigidity of the measurement target estimated by the rigidity estimation unit 37 is provided. Thereby, the crack of a measuring object, local deterioration, damage, etc. can be detected accurately and automatically, and it can show to a measurement person.

  Although the embodiments of the present invention have been described in detail with reference to the drawings, the specific configuration is not limited to these embodiments, and design changes that do not depart from the gist of the present invention are not limited thereto. include.

  For example, in each of the embodiments described above, the rigidity detection device 10 includes the imaging unit 20 and the captured image captured by the imaging unit 20 is sequentially input to the calculation unit 30, but the configuration is limited to this configuration. It is not a thing. The calculation unit 30 only needs to be able to acquire the captured image. For example, the captured image captured by the imaging unit 20 is recorded in the storage unit of the imaging unit 20 and data of all captured images is transferred to the calculation unit 30. You can also. In addition, it is also possible to adopt a configuration in which captured images taken on site are downloaded via a communication line such as the Internet or installed from a USB memory or an SD memory card.

  Further, the hammer 50 provided with the sensor unit 51 can also be a component of the rigidity detecting device 10. In addition, the calculation unit 30 is not limited to a PC, and a portable terminal such as a tablet terminal or a smartphone can be used as long as it has an ability to process large-scale multipoint displacement data.

  Moreover, in the said embodiment, although equipped with the state detection part 38 which detects the state of a measuring object based on the rigidity distribution estimated by the rigidity estimation part 37, the state is determined automatically by the rigidity detection apparatus 10, It is not limited to this. The rigidity detection device 10 may be configured without providing the state detection unit 38, and the measurer may determine the state of the measurement target based on the rigidity distribution estimated by the rigidity estimation unit 37. The measurer can more accurately determine the state based on the stiffness distribution and the like detected with high accuracy by the stiffness detector 10.

1 Bridge (measurement target)
2 RC digit (measurement target)
DESCRIPTION OF SYMBOLS 10 Rigidity detection apparatus 20 Imaging part 33 Control part 35 Image information acquisition part 36 Displacement information calculation part 37 Rigidity estimation part 38 State detection part

Claims (6)

A rigidity detection device that detects the rigidity of the measurement object based on a captured image that is taken by vibrating the measurement object,
An image information acquisition unit for acquiring a plurality of captured images of the measurement object continuously photographed every predetermined time;
A displacement information calculation unit that calculates displacement information from a reference position of a plurality of measurement points of the measurement target based on the plurality of captured images;
A stiffness detection apparatus comprising: a stiffness estimation unit configured to estimate the stiffness of the measurement target based on the deflection of the measurement target calculated based on the displacement information and the deflection based on the finite element analysis.   The stiffness estimator calculates a mean square error between the deflection of the measurement object at all nodes at the time when the maximum value of the deflection is obtained and the deflection by the finite element analysis, and the mean square error was calculated last time. While it is smaller than the mean square error, the stiffness value is updated by changing it from a predetermined initial value by a predetermined amount, and the stiffness value when not updated more than a predetermined number of times is set as the stiffness of the measurement object. The rigidity detection apparatus according to claim 1.   The stiffness estimator calculates the curvature between adjacent nodes based on the deflection of the measurement target at all nodes at the time when the maximum value of deflection was obtained and the deflection by finite element analysis, and at each node. A mean square error between the curvature of the measurement object and the curvature of the finite element analysis is calculated, and while the mean square error is smaller than the previously calculated mean square error, the stiffness value is determined from a predetermined initial value. The rigidity detection device according to claim 1 or 2, wherein the rigidity value is updated while being changed at a time, and the rigidity value when the update is not performed more than a predetermined number of times is the rigidity of the measurement object.   The state detection part which detects the state of the said measuring object based on the rigidity of the said measuring object estimated by the said rigidity estimation part was provided, The Claim 1 characterized by the above-mentioned. Stiffness detection device. A rigidity detection method performed by the rigidity detection apparatus according to any one of claims 1 to 4,
Acquiring a plurality of captured images of a measurement object continuously photographed every predetermined time;
Calculating displacement information from reference positions of a plurality of measurement points of the measurement object based on the plurality of captured images;
And a step of estimating the rigidity of the measurement object based on the deflection of the measurement object calculated based on the displacement information and the deflection by finite element analysis. Computer
Means for acquiring a plurality of captured images of the measurement object continuously photographed every predetermined time;
Means for calculating displacement information from a reference position of a plurality of measurement points of the measurement object based on the plurality of captured images;
The program for functioning as a means to estimate the rigidity of the said measuring object based on the deflection of the said measuring object calculated based on the said displacement information, and the deflection | deviation by a finite element analysis.