JP2016006398A - Predictive diagnosis method of spall of concrete structure - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a predictive diagnosis method for photographing a structure with an infrared camera and quantitatively evaluating a risk of spalling of covering concrete from the structure using the photographed thermal image.SOLUTION: The predictive diagnosis method of spalls of a concrete structure includes: a step 101 of capturing an infrared thermal image of a surface of the concrete structure and measuring an outside temperature in the vicinity of the surface; a step 102 of calculating, on the basis of the infrared thermal image and the measured outside temperature, a detaching-part temperature difference ΔT as a temperature difference between a sound part and a detaching part, and a measurement temperature environment Te as a difference between the surface temperature of the sound part and the outside temperature; steps 103 and 104 of calculating a temperature environment coefficient k as a ratio of the calculated detaching-part temperature difference ΔT to the calculated measurement temperature environment Te and calculating a spall risk Ds according to the temperature environment coefficient k; and a step 105 of comparing the previously-calculated spall risk Ds1 with a currently-calculated spall risk Ds2 to calculate a spall period ts.

Description

The present invention relates to a method for predicting peeling of concrete structures such as bridges, overpasses, and buildings, and in particular, predicting the risk of covering concrete falling from a concrete structure using a thermal image taken by an infrared camera. It relates to a diagnostic method.

It is known that when a reinforcing bar in a concrete structure such as a bridge, an overpass, or a building (hereinafter simply referred to as “structure”) is corroded, expansion pressure is generated, and the cover concrete is cracked. Cracking is not only a problem in terms of accelerated deterioration, aesthetics, and scenery, but also causes third party damage and reduced strength due to the peeling of cover concrete.

In recent years, with many structures aging, non-destructive inspection methods for realizing efficient maintenance are being actively studied. In particular, infrared thermography is a method suitable for diagnosing delamination cracks, and a wide range of inspections can be performed in a non-contact manner, so that application examples to structures are increasing.

In an infrared survey using an infrared camera, an infrared camera is used to detect infrared band energy emitted from a subject, and the detected energy is converted into temperature to generate temperature distribution image data. This two-dimensional image of the temperature distribution is called a thermal image or a thermographic image. An example of an infrared survey is disclosed in Patent Documents 1 and 2 below, for example.

Under the influence of outside air and sunlight, the structure repeatedly absorbs heat from the outside to the inside of the structure and releases heat from the inside of the structure to the outside. Since the defective part accompanied by the cavity during heat absorption and heat dissipation functions as a heat insulating layer, heat transfer is blocked at the defective part. As a result, a temperature difference is generated between a portion having a defect and a portion having no defect, resulting in a difference in infrared emissivity. When a thermal image of a structure is taken with an infrared camera in such a state, a defective portion and a non-defective portion are displayed in different colors. At this time, the part with the defect is locally displayed in the part without the defect. In this way, a portion having a different color from the surroundings is referred to as an abnormal portion, and the other portions are referred to as healthy portions. By observing the thermal image and determining whether or not there is an abnormal part, it is possible to determine the presence or absence of a defect in the structure, and further to determine the position of the defect. Infrared surveys have the advantage that damage can be prevented by determining the presence or absence of defects inside the structure that cannot be determined by visual observation.

In the delamination detection by infrared thermography, the delamination area is specified from the surface temperature distribution by utilizing the property that the air layer at the delamination part blocks the heat flow generated inside the concrete.

Infrared thermography measurement methods are broadly classified into two types: a passive method using heat flow generated by solar radiation and temperature changes, and an active method using heat flow artificially generated by forced heating or forced cooling.

The active method is less constrained by environmental factors than the passive method. However, it is necessary to heat or cool the measurement target point by point, and the inspection efficiency is inferior to the passive method. On the other hand, the measurement results obtained by the passive method are affected by the amount of solar radiation, temperature changes, wind speed and direction, etc., depending on the season, weather, and shooting region.

JP 2005-140622 A JP 2006-329760 A

In the investigation and diagnosis in the maintenance and management of concrete structures, it is important not only to detect the delamination but also to evaluate the risk of delamination for the selection of repair methods.
However, there is not yet a method for quantitatively evaluating the risk of flaking off using infrared thermography.

Therefore, the present invention is a prediction method for photographing a structure with an infrared camera using a passive method with high inspection efficiency and quantitatively evaluating the risk of covering concrete peeling off from the structure using the photographed thermal image. The task is to enable diagnosis.

The first invention is a method for predicting delamination of concrete structures,
Taking an infrared thermal image of the surface of the concrete structure using an infrared camera, measuring the outside air temperature near the surface at the time of shooting,
Based on the infrared thermal image and the measured outside air temperature, as a difference between the separation part temperature difference (ΔT) as a temperature difference between the healthy part and the separation part, and the difference between the surface temperature of the healthy part and the outside air temperature Calculating a measured temperature environment (Te) of:
Calculating a temperature environment coefficient (k) as a ratio of the calculated separation temperature difference (ΔT) to the calculated measurement temperature environment (Te);
A method for predicting a flaking prediction of a concrete structure including a step of calculating a flaking risk (Ds) according to the calculated temperature environment coefficient (k).

The second invention is the first invention,
Compared with the previously calculated flaking risk (Ds1) and the flaking risk (Ds2) calculated this time, this method is a method for predicting flaking prediction of a concrete structure including a step of calculating the flaking time (ts). Features.

According to the present invention, a predictive diagnosis in which a structure is photographed with an infrared camera by a passive method with particularly high inspection efficiency, and the risk of covering concrete falling off from the structure is quantitatively evaluated using the photographed thermal image. As a result, it is possible to reliably prevent damage to third parties and decline in proof stress due to peeling of cover concrete, and to select repair methods appropriately.

FIG. 1 is a flowchart of a method for predicting delamination of a concrete structure. FIG. 2 is a diagram illustrating a state in which an infrared thermal image of the surface of the concrete structure 2 is taken with an infrared camera. 3A and 3B are diagrams illustrating an infrared thermal image. FIG. 3A is a thermal image of the specimen C20D19-1, and FIG. 3B is a specimen C40D19-1. It is a thermal image. FIG. 4 is a diagram showing a temperature profile in the center lines A to B of the infrared image shown in FIG. 3, and is a diagram showing a temperature profile of the specimen C20D19-1 (deterioration level STEP3). FIG. 5 is a diagram showing the relationship among the measured temperature environment Te, the separation temperature difference ΔT, and the temperature environment coefficient k. FIG. 6 is a diagram showing the relationship between the calculated temperature environment coefficient k and the peeling risk Ds. FIG. 7 is a diagram showing the performance of the infrared camera. FIG. 8A is a diagram showing an outline of a specimen when the number of inserted elastic bodies is one, and FIG. 8B is a diagram showing an outline of the specimen when the number of inserted elastic bodies is two. . FIG. 9 is a diagram showing an outline of the loading device. FIG. 10A is a conceptual diagram of peeling cracks, and FIG. 10B is a conceptual diagram of bending cracks and horizontal cracks. FIG. 11 is a table showing the cover reinforcing bar diameter ratio C / D of the test specimen and the assumed fracture mode. FIG. 12 is a table showing the thermal characteristics of the materials used. FIG. 13 is a diagram showing a thermal image immediately before the appearance of a separation crack. FIG. 14 is a diagram showing a center line profile immediately before the appearance of a separation crack. FIG. 15 is a diagram showing a center line profile immediately after the start of loading. FIG. 16 is a diagram showing a differential profile immediately before the separation crack is revealed. FIG. 17 is a diagram showing the relationship between the temperature difference at the peeled portion and the amount of change in radius. FIG. 18 is a table showing the relationship between the amount of change in radius and the temperature difference at the separation part when the separation crack is apparent. FIGS. 19A and 19B are images showing deformation until the specimen C20D13 is peeled off. 20A, 20B, and 20C are images showing deformation until the specimen C30D13 falls off. FIG. 21 is a diagram illustrating an example of a thermal image after confirmation of floating sound. FIG. 22 is a diagram illustrating an example of the difference profile after the floating sound confirmation. FIG. 23 is a diagram showing the relationship between the temperature difference at the peeled portion and the degree of peeling risk. 24A and 24B are views showing the mechanism of the load holding valve. FIG. 25 is a schematic diagram of a measurement temperature environment. FIG. 26 is a table showing deterioration properties at each deterioration level of the peeling crack specimen C20D19-1. FIG. 27 is a table showing deterioration properties at each deterioration level of the peeling crack specimen C20D19-2. FIG. 28 is a table showing deterioration characteristics at each deterioration level of the horizontal crack specimen C40D19-1. FIG. 29 is a table showing deterioration characteristics of each horizontal crack specimen C40D19-2 at each deterioration level. FIG. 30 is a diagram showing a center line profile of a horizontal crack specimen C40D19-1 (deterioration level STEP3). FIG. 31 is a diagram showing an upper end line profile of a horizontal crack specimen C40D19-1 (deterioration level STEP3). FIG. 32 is a diagram showing a difference profile of a horizontal crack specimen C40D19-1 (deterioration level STEP3). FIG. 33 is a diagram showing the relationship between the temperature difference of the peeled portion and the measured temperature environment when the peeled specimen C20D19-1 was photographed with a quantum camera. FIG. 34 is a view showing the relationship between the temperature difference at the peeled portion and the measurement temperature environment when the horizontal crack specimen C40D19-1 is photographed with a quantum camera. FIG. 35 is a table showing the distribution of peel temperature difference data in the measurement temperature environment of 3.0 ° C. FIG. 36 is a diagram showing the distribution of the temperature difference at the separation part of the specimen C20D19-1 (deterioration level STEP3). FIG. 37 is a view showing the distribution of the temperature difference at the separation part of the specimen C40D19-1 (deterioration level STEP3). FIG. 38 is a diagram showing the relationship between the degree of peeling risk and the measured temperature environment.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Embodiments of a concrete structure peeling prediction method according to the present invention will be described below with reference to the drawings.

FIG. 1 is a flowchart showing a method for predicting delamination of a concrete structure.

FIG. 2 shows a state in which an infrared thermal image of the surface of the concrete structure 2 is taken by the infrared camera 1.

First, an infrared thermal image of the surface 2a of the concrete structure (for example, elevated) 2 is taken using the infrared camera 1, and the outside air temperature Tex near the surface 2a at the time of shooting is measured.

FIG. 3A illustrates the infrared thermal image 3 (step 101).

Next, based on the infrared thermal image 3 and the measured outside air temperature Tex, the difference between the peeled portion temperature difference ΔT as the temperature difference between the healthy portion and the separated portion, and the difference between the surface temperature Tc of the healthy portion and the outside air temperature Tex. A measurement temperature environment Te (= Tc−Tex) is calculated as Tc−Tex.

FIG. 4 shows temperature profiles in the center lines A to B of the infrared image 3 shown in FIG.

In FIG. 4, the separation portion temperature difference ΔT (° C.) is, for example, as a difference between the temperature G of the healthy portion and the temperature F of the separation portion,
ΔT = G (temperature of healthy part) −F (temperature of peeled part) (1)
It is represented by The measurement temperature environment Te (° C.) is expressed as the difference between the surface temperature Tc of the healthy part and the outside air temperature Tex,
Te = Tc−Tex (2)
(Step 102).

Next, a temperature environment coefficient k is calculated as a ratio with the calculated separation temperature difference ΔT with respect to the calculated measurement temperature environment Te. FIG. 5 shows the relationship between the measured temperature environment Te, the separation temperature difference ΔT, and the temperature environment coefficient k.
k = ΔT / Te (3)
(Step 103).

Next, the peeling risk Ds is calculated according to the calculated temperature environment coefficient k.

FIG. 6 shows the relationship between the calculated temperature environment coefficient k and the flaking risk Ds. The flaking risk Ds is expressed by the following equation:
Ds = 1.23 × k (4)
It is represented by The greater the flaking risk Ds, the higher the deterioration due to peeling of the structure, and the higher the risk that the cover concrete will flake off (step 104).

  Further, in FIG. 6, the detachment time ts is calculated by comparing the previously calculated detachment risk Ds1 with the currently calculated detachment risk Ds2.

For example, if the risk of dropping according to the inspection result before t is Ds1, and the risk of dropping according to the inspection result of this fiscal year is Ds2, the removal time is determined to be after ts year according to the following equation.
ts = {(1-Ds2) / (Ds2-Ds1)} * t (5)
(Step 105).

As described above, it is possible to perform a predictive diagnosis that quantitatively evaluates the risk of cover concrete falling off from the structure 2, and it is possible to reliably prevent third party damage and deterioration of proof stress due to cover concrete peeling, and repair method. Can be selected appropriately.

Hereinafter, the results of experiments conducted for the present invention will be described, and the present invention will be described in detail.

The infrared camera 1 is roughly classified into two types, a quantum type camera and a thermal type camera, depending on the operating principle of the detection element. In general, the measurement wavelength of a quantum camera is a short wavelength band, and the measurement wavelength of a thermal camera is a long wavelength band. Infrared thermography is affected by noise depending on the measurement wavelength band, and in the short wavelength band, it is susceptible to noise due to the sun reflection and the combination of sun and shade, and in the long wavelength band, the temperature is low to normal. It has been reported that it is susceptible to reflection of objects. For this reason, the quantum camera tends to be used for night photography, and the thermal camera tends to be used for daytime photography. However, as shown in FIG. 7, there are differences in other performances such as sensitivity and response speed between the quantum type camera and the thermal type camera, and it is not appropriate to handle both measurement results equally.

In the investigation and diagnosis in the maintenance and management of concrete structures, it is important not only to detect the delamination but also to evaluate the risk of delamination for the selection of repair methods.

In particular, the present invention aims to quantitatively evaluate the risk of flaking by a passive method with high inspection efficiency. Infrared thermography measurement was performed on specimens at each damage stage in a rebar corrosion expansion pressure simulation experiment. We also tried to propose a highly versatile evaluation method by comparing the measurement results of both the quantum and thermal cameras.

As shown in FIGS. 8 (a) and 8 (b), a reinforcing bar 201 is orthogonally arranged on a square specimen 200 having dimensions of 400 × 400 × 150 mm, and the center of the specimen 200 has the same diameter as that of the vertical reinforcing bar 201. The cylindrical cavity 203 is provided. The elastic body 204 installed in the cylindrical cavity 203 is made by molding silicon rubber having an elastic modulus of 1.39 N / mm 2 and a Poisson's ratio of 0.49, and a center section of the cylindrical cavity 203 is placed by using a positioning jig after placing concrete. Installed. A sufficient amount of lubricating oil is applied and inserted into the elastic body 204, and it is considered that the friction between the elastic body 204 and the concrete or the reinforcing bar 201 is small. Steel rods 205 (FIG. 9) having the same diameter as the cylindrical cavity 203 were inserted into both ends of the elastic body 204.

The state of loading is shown in FIG.

The loading was performed by lowering the shaft 206 with the motor 207, and the vertical displacement and the vertical load were measured with the displacement meter 208 and the load cell 202. Loading was controlled by vertical displacement, and the descending speed of the shaft 206 was set to 0.01 mm / s.

The obtained vertical displacement (dL) and vertical load (P) can be converted into a radius change amount (dr) and an internal pressure (Pi) by the following equations (11) and (12).
Where dL: vertical displacement (mm), P: vertical load (N), E: elastic coefficient of elastic body 204 (N / mm 2), ν: Poisson's ratio of elastic body 204, pi: internal pressure (N / mm 2) , Dr: radius change amount (mm), r0: original radius (mm) of the elastic body 204, and L0: original length (mm) of the elastic body 204.

  FIG. 10 shows the concept of cracking. FIG. 10A shows a peeling crack, and FIG. 10B shows a bending crack and a horizontal crack.

When the reinforcing bar corrosion expansion pressure simulation experiment was performed using the cover C, the diameter D of the reinforcing bar 201, the interval between the reinforcing bars 201, the length of the elastic body 204, and the number of inserted elastic bodies 204 as experimental factors, the surface of the specimen 200 near the maximum internal pressure. It is known that there are many cases where axial cracks occur, and that the fracture mode differs in the region where the internal pressure decreases after reaching the maximum internal pressure due to the difference in the cover reinforcing bar diameter ratio (C / D). In addition, when the cover reinforcing bar diameter ratio C / D is less than 2.1, peeling cracks occur, and when the cover reinforcing bar diameter ratio C / D is greater than 2.1, bending cracks due to extrusion failure occur on the cover surface. However, it has also been found that horizontal cracks occur in the form connecting the reinforcing bars.

Accordingly, the cover, the diameter of the reinforcing bars 201, the interval between the reinforcing bars 201, the length of the elastic body 204, and the number of inserted elastic bodies 204 were selected based on these past experimental results.

The specimen 200 has a rebar interval Lp = 150 mm, the elastic body 204 has a length of 100 mm, and the number of inserted elastic bodies 204 is one. The experimental factors were the cover C (three types of 10 mm, 20 mm, and 30 mm) and the diameter D of the reinforcing bar 201 (two types of D13 and D19), and one body was prepared for each factor. The specimen name is represented by a combination of the cover C and the diameter D of the reinforcing bar 201 (for example, C10D19), and the covering reinforcing bar diameter ratio C / D of each specimen 200 and the assumed failure mode are shown in FIG. . For example, “C10D19” is a specimen 200 having a cover C of 10 mm and a reinforcing bar diameter D of 19 mm.

The water-cement ratio of the concrete used was 62%, the compressive strength at 40 days of age was 28.3 N / mm2, and the tensile strength was 3.03 N / mm2.

In this experiment, an attempt was made to reproduce the heat flow assuming nighttime measurement in a laboratory that is not easily affected by environmental factors. The specimen 200 cured in a separate room (about 25 ° C.) was placed in a laboratory loading device set to 20 ° C., and measurement was started simultaneously with loading. During the measurement, the specimen 200 was heated from the back with a heat source (hot carpet) so that the surface temperature of the specimen 200 was about 3 ° C. higher than the experimental room temperature.

Using the quantum infrared camera 1 shown in FIG. 7, the measurement was performed at intervals of 20 seconds from a point about 4 m away from the specimen 200. In order to consider the effect of thermal diffusion, loading was stopped as appropriate until the effect of peeling appeared on the surface. In addition, the presence or absence of a floating sound was also examined by a hammering test.

The thermal characteristics of the materials used are shown in FIG. Although the thermal characteristics of the elastic body 204 and the steel bar 205 are different from those of concrete, it has already been confirmed that the elastic body 204 and the steel bar 205 have almost no influence on the infrared image.

A thermal image 3 immediately before the peeling crack of the specimen C10D19 appears on the cover surface (hereinafter referred to as immediately before the appearance of the peeling crack) is shown in FIG. 13, and the temperature on the line AB of FIG. 13 (center of the specimen 200). FIG. 14 shows a profile (hereinafter referred to as a center line profile).

As shown in FIGS. 13 and 14, a temperature drop is observed at the center due to the effect of peeling. However, a temperature gradient (hereinafter referred to as temperature unevenness) of the surface of the specimen 200, which is considered to be an effect of heat dissipation from the side surface, appears in FIG. 13 and FIG. Is high, and the temperature is getting lower as it gets closer to the side. Therefore, there is a possibility that the temperature drop due to the influence of peeling cannot be accurately evaluated.

Therefore, when the central line profile immediately after the start of loading was examined, temperature unevenness appeared (FIG. 15). This is considered to be due to the small size of the specimen 200, and is not considered to be a problem in the actual structure 2 in which the boundary portion where heat dissipation may occur is sufficiently separated. Therefore, if the central line profile immediately after the start of loading is differentiated from the central line profile of the thermal image to be evaluated (hereinafter referred to as the differential profile), the influence of the temperature drop due to peeling is evaluated without being affected by temperature unevenness as shown in FIG. I knew it was possible.

In the difference profile,
ΔT (separated part temperature difference) = G1 (differential temperature of healthy part) −F1 (differential temperature of separated part) (for example, the value of G1−F1 in FIG. 16). We examined using.

In this experiment, the fracture mode shown in FIG. 11 was confirmed in all specimens 200.
FIG. 17 shows the result of arranging the separation temperature difference ΔT for each radius change amount dr. Since the specimen C30D13 has a short stroke of the shaft 206, data of only a range in which the displacement can be measured is shown. Referring to FIG. 17, it can be seen that as the radius change amount dr increases, the peel temperature difference ΔT increases, and the peel temperature difference ΔT rapidly increases before any specimen 200 peels off. It can be seen that the temperature is increased to 1.0 ° C. or higher.

FIG. 18 is a summary of the results of the change in radius dr and the temperature difference ΔT of the peeled portion at the time when the flaking cracks are apparent. However, since no peeling cracks appeared on the surface of the specimen C30D13, the radius change amount dr and the peeling portion temperature difference ΔT at the time of confirmation of the floating sound due to the hitting sound are shown.

As shown in FIG. 18, no particular correlation was found between the temperature difference ΔT of the peeling portion when the cover and the peeling crack were apparent. As a cause of this, since it takes time to move the heat flow, in this experiment performed in a short time, the temperature difference ΔT of the separation part is smaller than that of the actual structure 2, and the temperature difference between the surrounding air and the specimen 200 by the specimen 200. May be different.

In this experiment, only the specimen C30D13 was different from the others, and a fracture mode in which bending cracks and horizontal cracks occurred was obtained.

19 and 20 show deformations of the specimen C20D13 and the specimen C30D13 until peeling.

  FIGS. 19A and 19B show the deformation of the specimen C20D13, and FIGS. 20A, 20B, and 20C show the deformation of the specimen C30D13.

For the specimens 200 other than the specimen C30D13, after peeling cracks were generated and propagated, the specimens were peeled along the peeling cracks, and a clear temperature difference was observed between the peeled part and the healthy part in the differential profile. On the other hand, in the specimen C30D13, no peeling cracks occurred, but a plurality of bending cracks occurred, and at the end of loading, partial bending along the bending cracks and horizontal cracks penetrating the side as shown in FIG. 20 (b). There was a fall. When the surface that did not peel off was further struck with a hammer, a wide range of peeling as shown in FIG. 20C was observed, and it was confirmed that horizontal cracks had also developed in the lower left part of the specimen 200.

While peeling cracks and horizontal cracks appear on the surface of the thermal image 3, bending cracks appear linearly. FIG. 21 shows an example of the thermal image 3 of the specimen C30D13 after the confirmation of the floating sound. From FIG. 21, it can be seen that bending cracks appear linearly at the bottom of the specimen 200. FIG. However, it is considered that it is difficult to detect a bending crack on the thermal image 3 because the measurement is performed from a distance when the actual structure 2 is applied. Therefore, when bending cracks and horizontal cracks occur, it is realistic to perform a drop prediction by evaluating the horizontal cracks.

Thereafter, when bending cracks and horizontal cracks occur as in the specimen C30D13, the temperature difference ΔT of the peeled portion is evaluated by the temperature difference between the peeled portion and the healthy portion due to the horizontal crack.

FIG. 17 only shows data up to the deterioration stage where displacement measurement was possible. However, in the specimen C30D13, it is difficult to discriminate between the separated part and the healthy part in the thermal image 3 and the differential profile even after the floating sound confirmation. (FIG. 21, FIG. 22 (difference profile after confirmation of floating sound)), the separation part temperature difference ΔT was hardly increased. Despite the fact that the floating sound was confirmed, the infrared thermography measurement could not accurately evaluate the horizontal crack generated inside. When peeling cracks occur, the cracks approach the cover surface as the deterioration progresses, whereas when horizontal cracks occur, the cracks do not approach the cover surface even when the deterioration progresses. Therefore, it is considered that the time required for the specimen C30D13 to have a temperature difference on the surface as a peeling portion is longer than that of the other specimen 200 in which the separation crack occurred. It is considered that the horizontal crack could not be accurately evaluated because the loading speed of the elastic body experiment was faster than the time until the effect of the horizontal crack appeared on the surface. In this experiment, the temperature difference between the surface temperature of the specimen 200 and the experimental room temperature was set to be about 3.0 ° C., but the heat flow inside the specimen 200 necessary for detecting horizontal cracks was not good. It may be sufficient.
It is known that the radius change amount dr obtained by the rebar corrosion expansion pressure simulation experiment can be converted into the corrosion amount by the following equations (13) and (14).

Here, Wloss: conversion corrosion weight loss, ρ: specific gravity of iron (7.85 mg / mm 3), Δr: rebar radius reduction by corrosion (mm), γ: corrosion expansion ratio (2.5 times).

However, the corrosion weight loss calculated by the rebar corrosion expansion pressure simulation experiment tends to be larger than the result of an experiment such as an electrolytic corrosion experiment that actually corrodes the rebar. As the cause of this, it is assumed that the expansion of the elastic body 204 is uniformly expanded in the circumferential direction, but in the actual structure 2, the corrosion near the cover surface proceeds, and the elastic coefficient of the used elastic body 204 It is conceivable that the required amount of expansion was increased because the rust layer was smaller than the rust layer.

The radius change amount dr is a value obtained from a simulation experiment of reinforcing bar corrosion expansion pressure, and represents the degree of deterioration until peeling, but the radius change amount dr at the time of peeling differs depending on the fog (FIG. 17), so the radius change amount. It is difficult to evaluate the risk of dropping on site only with the value of dr. It is also known that no corrosion cracking due to expansion pressure occurs at the value of the radius change dr amount until the maximum internal pressure is reached. Therefore, as a substitute for reduced corrosion weight loss, a flaking risk Ds expressed by the following equation (15) is newly proposed.

Here, it is assumed that drs: radius change amount at the time of peeling (mm), drpi: radius change amount at the maximum internal pressure (mm).

In the risk of peeling, the risk of peeling is indicated by a value between 0 and 1. FIG. 23 shows the separation temperature difference ΔT with the peeling risk Ds. The specimen C30D13 is not shown in the figure because the radius change amount dr at the time of peeling is unknown. Referring to FIG. 23, it can be seen that most specimens 200 follow the same route until the drop risk Ds reaches 0 to 1. In the actual structure 2, there is a case where a reinforcing bar not shown in the drawing is in the vicinity of the cover, but even if the cover and the diameter of the reinforcing bar are unknown, the degree of deterioration can be evaluated by the peeling risk Ds. Conceivable.

That is, although the peeling portion temperature difference ΔT is affected by the shape and dimensions of the peeling portion, the peeling risk degree Ds calculated from the peeling portion temperature difference ΔT is not affected by these, and is not affected. Progress can be assessed.

For example, suppose that the risk of dropping according to the inspection result t years ago is Ds1, and the risk of dropping according to the inspection result of this year is Ds2.
ts = {(1-Ds2) / (Ds2-Ds1)} * t
Therefore, the drop time is determined to be after ts years.

In actual rebar corrosion, since the corrosion rate is not constant, it is desirable to accumulate more inspection data and compare and compare in order to accurately predict the flaking time. Further, when the peeling risk degree Ds exceeds 0.8, the peeling portion temperature difference ΔT increases rapidly. Therefore, when used at the site, measures such as knocking off are taken when the peeling risk degree Ds exceeds 0.8. It is considered desirable.

The flaking risk degree Ds is a very useful index for flaking prediction. However, when a horizontal crack occurs or when the radius change dr until the flaking is small as in the specimen C10D13, The route may be different from others, so further consideration is required. Moreover, when comparing the accumulated inspection results as shown in Equation (5), it is necessary to compare with the results obtained in the same measurement environment as much as possible. In particular, the amount of solar radiation and changes in temperature are considered to have a large effect on the infrared image 3. However, it is difficult to accumulate inspection data under the same conditions because the amount of solar radiation depends on the weather and the change in temperature depends on the time and amount of solar radiation. It is.

Therefore, in the next section, the influence of the measurement temperature environment on the thermal image 3 was examined.
The measurement temperature environment Te (° C.) is expressed by the above equation (2),
Te = Tc−Tex
Defined by

Here, Tc is the concrete surface temperature (° C.) of the healthy part, and Tex is the outside air temperature (° C.) near the concrete surface.

The experimental factors were the fracture mode (two types of peeling cracks and horizontal cracks), and two each were prepared. In the peeled crack specimen 200, the fog C = 20 mm and the number of inserted elastic bodies 204 were one, and in the horizontal crack specimen 200, the fog C = 40 mm and the number of inserted elastic bodies 204 were two. The reinforcing bar diameter D19, the reinforcing bar interval Lp = 90 mm, and the length of the elastic body 200 are 100 mm. The water-cement ratio of the concrete used was 60%, the compressive strength at the age of 40 days was 26.0 N / mm2, and the tensile strength was 2.83 N / mm2.
In this experiment, five levels of degradation (any five points between the maximum internal pressure and peeling) were simulated by a rebar corrosion expansion pressure reproduction experiment. When the target deterioration level is obtained by loading, the load is unloaded and removed from the loading device. Load holding valves were installed at both ends of the elastic body 204 so that the deformation of the elastic body 204 caused by loading was maintained even after unloading.

The action mechanism of the load holding valve is shown in FIGS. When the valve moves in the insertion direction, the frictional resistance is small, and when the valve moves in the direction opposite to the insertion direction, the frictional resistance is large. Therefore, it can move only in the insertion direction, and does not move even if a force in the direction opposite to the insertion direction is applied. Regarding the performance of the valve, it has already been confirmed that, for a short period of time, the load cannot be removed and the development of cracks is not observed.

After performing infrared thermography measurement by the method described later, loading is performed again to the next deterioration level. This was repeated thereafter, and infrared thermography measurement was performed at five levels of deterioration. When unloading, the maximum bending crack width by crack scale (maximum crack width in the axial direction), the maximum floating width by laser displacement meter, and the presence or absence of floating sound by hammering test were measured. Note that the maximum floating width is the maximum value of the horizontal displacement measured two-dimensionally with a laser displacement meter, and is considered to be approximately the same as the maximum peel crack width or the maximum horizontal crack width. It was.

The specimen 200, whose side and back surfaces were covered with a 12 mm thick heat insulating material (styrofoam), was cured in a separate room (about 28 ° C.), moved to a laboratory set at 20 ° C., and measurement was started. When the surface temperature of the specimen 200 became almost equal to the experimental room temperature, the specimen 200 was moved outdoors (about 28 ° C.), and measurement was performed again. The measurement was finished when the surface temperature of the specimen 200 was almost equal to the outside air temperature. Outdoor measurements were taken on the first basement floor where direct sunlight was not applied, and the outside temperature was measured at 30-second intervals with a sensor thermometer.

A schematic diagram of the measurement temperature environment is shown in FIG.

In this experiment, measurement was performed using a quantum camera and a thermal camera shown in FIG. The measurement was performed at intervals of 30 seconds from a point about 5 m away from the specimen 200. Moreover, the temperature near the concrete surface used the temperature which measured the thin piece of the concrete installed above the heat insulating material with each infrared camera 1. FIG.

26 to 29 show the measurement results of the maximum bending crack width by the crack scale at each deterioration level, the maximum floating width by the laser displacement meter, and the presence or absence of the floating sound by the hammering test. In the floating sound column in FIGS. 26 to 29, x is indicated when no floating sound is confirmed, △ is indicated when it is difficult to determine the floating sound, and ○ is indicated when floating sound is confirmed. doing.

26 to 29, in the cracked specimens (C20D19-1 and C20D19-2), although the axial crack progresses until the peeling crack occurs, the axial crack hardly progresses after the peeling crack occurs. There was a tendency for the floating width to increase. On the other hand, in the horizontal crack specimens (C40D19-1 and C40D19-2), after the occurrence of an axial crack, a crack occurred on the left side of the specimen.

As a reason why such a result was obtained with the specimen 200 having the cover reinforcing bar diameter ratio C / D larger than 2.1, it is considered that the two elastic bodies 204 were not uniformly loaded. However, a plurality of bending cracks occurred at the same time as the separation cracks, and cracks appeared on the right side surface of the specimen 200 at the deterioration level STEP3. From this, it is considered that a horizontal crack has occurred on the right side of the specimen 200. Furthermore, the flaking cracks appearing on the surface after the peeling cracks had hardly progressed, and both the bending crack width and the floating width tended to increase.

FIGS. 3A and 3B are examples of the thermal image 3 (deterioration level STEP3, Te = −3.0 ° C., quantum camera) measured in this experiment. FIG. 3A is a thermal image 3 of the specimen C20D19-1, and FIG. 3B is a thermal image 3 of the specimen C40D19-1. In the peeling crack specimen 200 of the specimen C20D19-1, there was little influence due to temperature unevenness as shown in FIG.

In the delamination crack specimen 200, the delamination temperature difference ΔT is expressed by the above equation (1),
ΔT = G (temperature of healthy part) −F (temperature of peeled part) (1)
It is defined as This is the value of GF in the diagram of FIG.

On the other hand, as shown in FIG. 30, in the horizontal crack specimen 200 of C40D19-1, it is difficult to evaluate the temperature difference at the separation part in the region where the horizontal crack is generated due to the influence of temperature unevenness only by the center line profile. It was.

Therefore, when the temperature profile at the upper end of the specimen 200 considered to be a healthy region is examined, it can be seen that temperature unevenness as shown in FIG. 31 occurs.

FIG. 32 is a temperature profile obtained by subtracting the upper end line profile from the center line profile.

Since the region where the horizontal crack is generated can be clearly seen from FIG. 32, in the horizontal crack specimen 200, the peeling portion temperature difference ΔT is
ΔT (separation temperature difference) =
G1 (Differential temperature of healthy part)-F1 (Differential temperature of peeled part due to horizontal crack) (16)
It is defined as This is a value of G1-F1 in FIG.

FIGS. 33 and 34 show the relationship between the separation temperature difference ΔT and the measurement temperature environment Te obtained from the measurement results of the quantum cameras 1 of the specimens C20D19-1 and C40D19-1, respectively.

  In the specimen C40D19-1, since the separation temperature difference ΔT was 0 ° C. at the deterioration level STEP1, the results from the deterioration level STEP2 are shown. For the specimens C20D19-2 and C40D19-2, the same results as those for the specimens C20D19-1 and C40D19-1 were obtained, respectively.

33 and 34, it can be seen that both the specimens C20D19-1 and C40D19-1 have a monotonically increasing peel temperature difference ΔT on the same deterioration level STEP.

If the measurement temperature environment Te is 0 ° C., no heat flow is theoretically generated, and therefore, the peeling portion temperature difference ΔT is considered to be 0 ° C. Therefore, when linear approximation passing through the origin is performed, approximation can be performed with high accuracy as shown in FIGS. In the deterioration levels STEP1 and STEP2, the peel-off portion temperature difference ΔT is very small, so that the correlation coefficient is smaller than that after the deterioration level STEP3. Further, since the gradient k (referred to as a temperature environment coefficient as described above) increases as corrosion progresses, it is considered possible to evaluate the drop risk Ds using the gradient k. .

Thermal cameras are known to be more prominent in noise and less accurate in detecting defects than quantum cameras. In this experiment, the thermal camera tended to be more difficult to detect delamination than the quantum camera. However, as for the relationship between the temperature difference ΔT of the peeled portion and the measured temperature environment Te, almost the same results were obtained with both cameras. It is considered that the result similar to that of the quantum type camera was obtained even with the thermal type camera having lower performance than the quantum type camera because the number of samples of the thermal image 3 was large. FIG. 35 shows the data distribution of the separation temperature difference ΔT between C20D19-1 (deterioration level STEP3) and specimen C40D19-1 (deterioration level STEP3) when the measurement temperature environment Te is 3.0 ° C. And the graph at the time of assuming that the data of FIG. 35 follows normal distribution is shown in FIG. 36, FIG.

FIG. 36 shows the distribution of the peeling portion temperature difference ΔT of the specimen C20D19-1 (deterioration level STEP3), and FIG. 37 shows the distribution of the peeling portion temperature difference ΔT of the specimen C40D19-1 (deterioration level STEP3). .

36 and FIG. 37, it can be seen that the thermal type camera has a larger variation than the quantum type camera in both the peeling crack specimen 200 of the specimen C20D19-1 and the horizontal crack specimen 200 of the specimen C40D19-1. . This is probably because the thermal camera that detects the long wavelength band has a larger noise due to the reflection of the facing object than the quantum camera that detects the short wavelength band. For this reason, it is desirable to average and evaluate several tens or more of the thermal images 3 when the thermal camera is applied to the actual structure 2.

The temperature environment coefficient k is a parameter obtained from the relationship between the measured temperature environment Te and the separation temperature difference ΔT, and it is considered that the temperature environment coefficient k includes a heat transfer coefficient. Therefore, in order to easily perform the flaking prediction under various measurement temperature environment conditions, it is desirable that the flaking risk Ds can be calculated from the temperature environment coefficient k.

FIG. 38 shows the relationship between the drop risk Ds and the temperature environment coefficient k based on the experimental results described so far. FIG. 38 corresponds to FIG. 5 described above.
As shown in FIG. 38, it was possible to evaluate by the peeling risk Ds without considering the difference in the destruction mode. The relationship between the peeling risk Ds obtained from this experiment and the temperature environment coefficient k is the expression (3) described above,
k = ΔT / Te
And (4) Formula Ds = 1.23 × k
It is represented by

The reason why R2 in the equation (4) is as small as 0.63 is considered to be variation due to a corrosion expansion pressure simulation experiment, measurement accuracy of infrared thermography measurement, and the like. Further, when considering application in the actual structure 2, it is considered that the influence of other environmental factors and the influence of the structure type of the target structure are also added. These formulas are experimental formulas based on the results of this experiment, and the relationship between the temperature environment coefficient k and the heat transfer coefficient represented by formula (3) needs to be clarified in the future by analysis or the like.

As described above, from this experimental result, it is possible to perform the flaking prediction diagnosis of the concrete structure by the procedure shown in the flowchart shown in FIG.

It should be noted that the accuracy of the drop prediction can be improved by repeatedly performing the processing of steps 101 to 105 in FIG. 1 a plurality of times and accumulating a plurality of inspection data.

  1 Infrared camera, 2 structure (concrete structure), 3 infrared image

Claims (2)

A method for predicting delamination of concrete structures,
Taking an infrared thermal image of the surface of the concrete structure using an infrared camera, measuring the outside air temperature near the surface at the time of shooting,
Based on the infrared thermal image and the measured outside air temperature, as a difference between the separation part temperature difference (ΔT) as a temperature difference between the healthy part and the separation part, and the difference between the surface temperature of the healthy part and the outside air temperature Calculating a measured temperature environment (Te) of:
Calculating a temperature environment coefficient (k) as a ratio of the calculated separation temperature difference (ΔT) to the calculated measurement temperature environment (Te);
A method for predicting a flaking prediction of a concrete structure, including a step of calculating a flaking risk (Ds) according to the calculated temperature environment coefficient (k). The prediction of delamination of a concrete structure according to claim 1, further comprising a step of calculating a delamination time (ts) by comparing the delamination risk (Ds1) calculated last time with the delamination risk (Ds2) calculated this time. Method.