JP2021148755A - Inspection method and diagnosis method for building - Google Patents

Abstract

To propose an inspection method and a diagnosis method for a building enabling reliable detection of defect areas present in the building.SOLUTION: An inspection method for a building is provided, including: a step 1 of irradiating a structure being an inspection target with an X ray to acquire a digital X-ray transmission image, a step 2 of discriminating defect areas and sound areas from an image obtained by image-processing the digital X-ray transmission image and the digital X-ray transmission image, a step 3 of storing position information of the defect areas and sound areas, a step 4 of acquiring an average luminance of a prescribed area of each of the defect areas and sound areas of the digital X-ray transmission image before the image processing based on the position information and further acquiring a difference in the respective average luminances of the defect areas and sound areas, and a step 5 of acquiring the thicknesses of the defect areas and sound areas from the average luminances of the defect areas and sound areas and the luminance difference between the defect areas and sound areas. A building diagnosis method using the inspection method is also provided.SELECTED DRAWING: Figure 2

Description

The present invention relates to a method for inspecting a structure and a method for diagnosing a structure using the method.

For example, as a method of non-destructively inspecting a structure such as a pipe, a method of irradiating a structure to be inspected with X-rays and determining the presence or absence of defects from the transmitted X-ray image is known. .. This inspection method detects defects based on changes in transmitted X-ray intensity due to defects existing in the structure. However, since the intensity of X-rays transmitted through an object is exponentially attenuated with respect to the thickness of the object, the thicker the object, the smaller the difference in transmitted X-ray intensity due to the presence or absence of defects. , Defect detection becomes difficult. In particular, when the thickness of the object varies greatly within the measurement range, it becomes difficult to ensure the same measurement accuracy in both the thick portion and the thin portion.

Therefore, as a countermeasure to this problem, for example, Patent Document 1 discloses a technique for reducing the influence of a change in the thickness of an object by using a wall thickness correction jig. Further, in Patent Document 2, it is determined for each pixel whether or not the sensor output value is saturated, and the storage capacity is determined for each pixel based on the determination result. A technique for obtaining a good contrast image while reducing an output having poor characteristics is disclosed.

Japanese Unexamined Patent Publication No. 08-254507 Japanese Unexamined Patent Publication No. 2013-062792

However, in the method described in Patent Document 1, it is necessary to prepare a wall thickness correction jig and attach it to the object to be measured, which is troublesome to measure. Further, as mentioned in Patent Document 1, there is a concern that the measurement accuracy may be lowered due to a defect or the like of the wall thickness correction jig itself. Further, the method described in Patent Document 2 is effective for obtaining a good contrast image, but since the measurement conditions are changed for each pixel, strict control of the measurement conditions of the sensor is required, and a wide range of measurements are performed. Not suitable for. Further, since it is difficult to quantitatively compare the measurement results between the pixels, it cannot be applied as a method for quantitatively evaluating the thickness of the defective portion.

The present invention has been made in view of the above-mentioned problems of the prior art, and an object of the present invention is to perform a special process such as changing the storage capacity of the pixels of a special jig or a sensor for each pixel. It is an object of the present invention to propose a structure inspection method capable of reliably detecting a defective portion existing in a structure, and a structure diagnosis method using the method.

The inventors have made extensive studies to solve the above problems. As a result, in addition to analyzing the digital X-ray transmission image obtained by the X-ray inspection and determining the presence or absence of the defect portion, the X-ray transmission image is further subjected to several stages of appropriate image processing to obtain defects. We have found that it is possible to clearly discriminate even minute defects by increasing the average luminance difference between the portion and the sound portion, and have developed the present invention.

That is, the present invention includes step 1 of irradiating a structure to be inspected with X-rays to obtain a digital X-ray transmission image, an image obtained by performing image processing on the digital X-ray transmission image, and the digital X-ray transmission. Based on the image, step 2 for discriminating between the defective portion and the sound portion, step 3 for storing the position information of the defective portion and the sound portion, and the position information, the digital X-ray transmission image before image processing. Step 4 to obtain the average brightness in a predetermined area for each of the defective part and the sound part, and further to obtain the difference in the average brightness between the defective part and the sound part, and the average brightness of the defective part and the sound part and their brightness difference. Therefore, we propose a method for inspecting a structure, which comprises step 5 of determining the wall thickness of a defective portion and a sound portion.

The image processing in the structure inspection method of the present invention is an image of any one of expansion processing, contraction processing, and contrast expansion processing (histogram expansion processing) with respect to the digital X-ray transmission image obtained in step 1. It is characterized in that it comprises a sub-step in which the processing or the image processing in which two or more are combined is sequentially performed a plurality of times.

Further, in step 2 of the above-mentioned structure inspection method of the present invention, in the digital X-ray transmission image obtained in step 1 and the image obtained by subjecting the digital X-ray transmission image to image processing, the average brightness and soundness of a predetermined area are obtained. It is characterized in that a portion where the difference from the average brightness of the portion is 1% or more of the total number of gradations is determined as a defective portion.

Further, the method for inspecting the structure of the present invention is characterized in that the structure is a pipe.

Further, the present invention is characterized in that the reduced wall thickness or the residual wall thickness of the structure is obtained by using the method for inspecting the structure according to any one of the above, and the soundness of the structure is evaluated. Propose a diagnostic method.

According to the structure inspection method of the present invention, by performing image processing on an X-ray transmission image, the existence of a minute defect portion having a small difference in brightness from the sound portion can be reliably identified. Therefore, when the present invention is applied to the diagnosis of piping, etc., the inspection method of the structure is applied to prevent loss and disaster due to leakage trouble, and repair such as patching is performed before the piping reaches the above state. Since it is possible to do so, the effect of the industry is great.

It is a figure which shows an example of the X-ray inspection apparatus system used in this invention. It is a flow figure explaining the defect determination method in step 2 of this invention. It is a figure which shows an example which compared the X-ray transmission image before image processing and after image processing. It is a graph which shows an example of the relationship between the residual wall thickness and the average luminance difference between a defective part and a healthy part.

As described above, the method for inspecting a structure of the present invention includes step 1 of irradiating the structure to be inspected with X-rays to obtain a digital X-ray transmission image, and a defective portion and a sound portion from the X-ray transmission image. Based on the step 2 for determining the above, the step 3 for storing the position information of the defective part and the sound part, and the position information, the average of the defective part and the sound part in the predetermined area of the X-ray transmission image before the image processing. Step 4 for obtaining the brightness and the average brightness difference between the defective portion and the sound portion, and step 5 for obtaining the thickness of the defective portion and the healthy portion and the depth of the defective portion from the brightness and the brightness difference between the defective portion and the healthy portion. The above step 2 is characterized in that a defective portion and a sound portion are discriminated from the X-ray transmission image obtained in step 1 and the image obtained by subjecting the X-ray transmission image to image processing. .. Hereinafter, a specific description will be given.

Step 1
This step 1 is a step of irradiating the structure to be inspected with X-rays to obtain a digital X-ray transmission image. As the X-ray inspection apparatus for obtaining a digital X-ray transmission image, for example, an X-ray inspection apparatus having a system as shown in FIG. 1 can be used. In the figure, 1 is an X-ray source, 2 is a controller that controls the X-ray source, 3 is a personal computer (PC) that controls the X-ray source and the controller, and 4 is a structure to be inspected (FIG. 1 shows). , As an example, a steel pipe is shown). Further, 5 is an X-ray detector that detects X-rays emitted from the X-ray source 3 and transmitted through the structure to be inspected, and 6 is a conversion of X-ray data detected by the X-ray detector into a digital image. It is a PC to do. The X-ray detector is a flat panel display (FPD (Flat Panel Detector)) or an imaging plate (IP (Imaging)) from the viewpoint of obtaining a digital image.
Plate)) is preferable. The X-ray inspection apparatus shown in FIG. 1 is an example and is not limited thereto. For example, PC3 is not essential.

Step 2
This step 2 is a step of analyzing the X-ray transmission image and discriminating between a defective portion and a sound portion. FIG. 2 shows an example of a flow for determining whether or not a defect exists in the structure to be inspected. First, a sub-step 1 for determining the presence or absence of a defect is performed by analyzing the X-ray image as it is obtained in step 1 (this image is also referred to as "original image" hereafter). At this time, the large defect can be easily distinguished from the defective portion and the sound portion from the difference in brightness in the X-ray image. However, a small defect may not be able to recognize the existence of the defective portion because the difference in brightness from the surrounding healthy portion is small.

Further, the state of the X-ray image (original image) obtained by the X-ray inspection changes depending on the surface condition and the amount of wall thinning in addition to the difference in the wall thickness of the defective part, which greatly affects the distinguishability of the defective part. For example, the X-ray transmission image shown in the upper part of FIG. 3 is a test in which a hole simulating a defect portion having a diameter of 10 mmφ and a depth of 1 to 3 mm is provided in the center of the surface of a steel plate of 100 mm square × thickness of 5 mm. An X-ray image obtained when one piece is inspected by the above-mentioned X-ray inspection apparatus of FIG. 1 is shown. FIG. ) Is a depth of 2 mm and a milled smooth surface state, (c) is a depth of 1 mm and a milled smooth surface state and (d) is a depth of 2 mm after heat treatment in an air atmosphere. It has a rusty surface condition.
Therefore, the defective portion cannot be identified only by the analysis of the original image, and there is a possibility that a minute defect may be overlooked.

Therefore, in the present invention, it is determined that the original image is subjected to image processing to increase the brightness difference between the defective portion and the sound portion to improve the detection accuracy of the defective portion and determine the presence or absence of the defective portion. Specifically, as shown in FIG. 2, when the existence of the defective portion cannot be confirmed by the analysis based on the original image (sub-step 1), the existence of the defective portion is performed after performing image processing on the original image. If the presence or absence is determined by moving to the next step (sub-step 2) and the existence of the defective portion cannot be confirmed even after that, the image after the above image processing is further subjected to image processing under different conditions, and then the defective portion is found. Move to the next sub-step to determine the existence. Then, this sub-step is repeated a plurality of times, and when the defective portion does not emerge in any of the sub-steps and the existence cannot be confirmed, it is finally determined that there is no defective portion. The number of times the image processing is performed is preferable because the inspection accuracy can be improved as the number of times is increased, but it is preferably about 5 times in consideration of the time required for the inspection. More preferably, it is in the range of 2 to 5 times.

Here, there are various methods for image processing described above, but in the present invention, it is preferable to apply at least one or more of the methods shown below.
-Expansion processing: If there is even one white pixel in the vicinity of the pixel of interest, the white region of the binary image is increased by replacing the pixel of interest with white.
-Shrinking process: If there is even one black pixel in the vicinity of the pixel of interest, the pixel of interest is replaced with black, which is a process of reducing the white region of the binary image, contrary to the expansion process.
Noise can be reduced by performing the above-mentioned expansion treatment and contraction treatment.
-Contrast (histogram) expansion processing: A processing for enhancing contrast and obtaining a clearer image by adding correction to a histogram showing the distribution of brightness of an image, that is, a histogram of brightness. Specifically, when the number of gradations of the brightness of the original image is 256 (8 bits), the minimum value of the brightness is 0, and the maximum value is 255, when the brightness difference is, for example, 1, the brightness difference is all floors. Since it is only 0.4% of the frequency, it is not possible to identify that there is a difference in brightness. Therefore, for example, when the brightness 25 of the original image is set to 0 and the brightness 50 of the original image is set to the brightness 255 of the corrected image, the brightness difference 1 of the original image is the brightness difference 4 after correction. Can be expanded to.
It is also possible to apply two or more of the methods shown above in combination.
The image processing method is not limited to the above method, and it goes without saying that another method may be used.

By performing the above image processing, it is possible to increase the brightness difference between the defective portion and the sound portion, so that even a small defective portion can be detected. The difference in brightness between the defective portion and the sound portion, which can be clearly determined to have the defective portion, is 1.0% or more of the total number of gradations. Therefore, when the total number of gradations is 4096 (12 bits) and the average luminance difference is 41 or more, the defective portion can be easily detected. It is preferably 1.5% or more.

For reference, for each of the original images (a) to (d) having different hole depths and surface states shown in the upper part of FIG. 3, image processing of expansion processing → contrast expansion processing → expansion processing → contraction processing is performed. The results of the application are shown in the lower part of FIG. From this result, it can be seen that by performing appropriate image processing, the average brightness difference between the defective portion and the sound portion can be increased, and the detection accuracy of the defective portion can be improved.

The area for determining the average brightness of the defective portion and the sound portion is preferably in the range of 10 to 40,000 pixels in terms of the number of pixels, although it depends on the size of the defective portion. If the number of pixels is less than 10, the range is too narrow to obtain the average brightness. On the other hand, if the pixel size exceeds 40,000 pixels, a portion other than the defective portion and a portion other than the sound portion may be included. More preferably, the number of pixels is in the range of 25 to 20000 pixels.

Step 3
This step 3 is a step of storing the position information of the defective portion and the sound portion around the defective portion required in the next step 4 when the defective portion is detected in the above step 2. In addition to the position information of the defective portion and the sound portion, it is desirable to also store the image processing condition (sub-step condition of step 2) in which the defective portion can be found. As a result, for example, when inspecting an adjacent portion at a position where a defect is detected, by preferentially adopting the above image processing conditions, it is possible to shorten the time required for determining the presence or absence of the defective portion and image processing. ..

Step 4
In this step, based on the position information of the defective part and the sound part, the average brightness in a predetermined area of the defective part and the sound part of the X-ray transmission image before image processing and the average brightness difference between the defective part and the sound part are obtained. It's a step. Here, the reason for obtaining the average brightness of the defective portion and the sound portion of the X-ray transmission image (original image) before the image processing is that the brightness of the image after the image processing is changed from the original image. This is because it cannot be used as data for obtaining the thickness of the defective portion and the sound portion in the next step 5. The area for obtaining the average brightness may be the area (number of pixels) for obtaining the average brightness used for determining the presence or absence of defects as described above.

Step 5
This step is a step of obtaining the thickness of the defective portion and the sound portion from the average brightness of the defective portion and the sound portion obtained from the X-ray transmission image (original image) before image processing. The method of determining the thickness of the defective part and the sound part is to obtain the relationship between the wall thickness and the brightness in advance using test pieces having the same surface condition as the structure but different wall thickness, and compare them. Can be found at. Further, the wall thickness of the defective portion can be obtained from the wall thickness of the defective portion and the sound portion.

Further, by comparing the average brightness difference between the defective portion and the sound portion with the previously obtained relationship between the residual wall thickness for each original plate thickness and the average brightness difference between the defective portion and the healthy portion, the residual portion of the defective portion remains. You may ask for the wall thickness.

In the structure inspection method of the present invention described above, the thickness of the defective portion and the sound portion (remaining wall thickness) and the depth of the defective portion (thickness reduction) can be obtained, so that the soundness of the structure is obtained. May be applied to the diagnosis to evaluate. As a result, it is possible to prevent troubles and disasters caused by the structure by determining the degree of deterioration of the structure and the necessity / timing of repair / replacement.

The structure to which the present invention can be applied is not particularly limited, but can be suitably used for inspection of pipes such as steel pipes whose inside cannot be confirmed. Further, the present invention is not limited to the pipe in a bare state, and can be applied to defect inspection of a coated steel pipe wrapped with a heat insulating material, a columnar steel tower, a chimney, and the like.

A test piece having a hole simulating a thickened defect portion having a diameter of 10 mmφ and a depth of 1 mm was provided in the center of the surface of a 100 mm square and 5 mm thick SS400 steel plate, and the acceleration voltage shown in FIG. 1 was 135 kV. X-ray inspection was performed using the small X-ray flaw detection system of. At this time, an FPD (Flat Panel Detector) was used as the X-ray detector, and a monochrome X-ray transmission image (original image) was obtained with 12 bits (number of gradations: 4096). From this image, the average brightness of 2025 pixels at the position corresponding to the defective part and the average brightness of 37700 pixels at the position corresponding to the healthy part around it were obtained. The average brightness was 131.3, and the difference was only 15.4. This luminance difference was 0.4% or less of the total number of gradations, and the luminance difference from the surrounding sound portion was small, so that it was impossible to detect the hole portion.

Therefore, for the above original image, using image processing software (XG Vision Editor manufactured by KEYENCE), expansion processing, contraction processing, and contrast expansion processing are combined to perform expansion processing → contrast expansion processing → expansion processing → contraction processing. Image processing was applied. As a result, when the average brightness of the defective part and the surrounding healthy part in the same position and the same area as before the image processing was obtained, the average brightness of the defective part changed to 44.9 and the average brightness of the healthy part changed to 168.1. However, the average brightness difference between the defective part and the healthy part expanded to 123.2. This luminance difference corresponds to 2.8% of the total number of gradations, and the defective portion could be easily detected.

Next, with respect to the defective portion detected by the above procedure, the average brightness of the defective portion is measured, and the residual wall thickness is estimated from the result.
For that purpose, first, an X-ray transmission test is carried out on several types of thinning test pieces prepared in advance, and from the measurement results, the relationship between the residual wall thickness of the original plate thickness (healthy part) and the brightness difference is determined. I'll ask for it. At that time, if the amount of thickness reduction of the thickened portion is small and the difference between the plate thickness of the thickened portion and the original plate thickness is small, the measurement accuracy is lowered. It is preferable to prepare the above and obtain the relationship between the residual wall thickness of the original plate thickness (healthy portion) and the brightness difference. In this example, an X-ray transmission test was carried out in advance on a thickness reduction test piece made of a steel plate having a base plate thickness of 5 mm and a steel plate having a base plate thickness of 10 mm, and the relationship shown in FIG. 4 was obtained. The difference between the central and peripheral brightness shown on the vertical axis of FIG. 4 is the average brightness of the central portion in the region of the defective portion (black portion) and the region of the healthy portion (white portion) without thinning of the periphery. It is the difference in brightness from the average brightness of.
Next, the average brightness difference between the defective portion and the sound portion in the original image is obtained for the location determined to be the defective portion by the above procedure. In the case of this embodiment, it is 15.4 as already described. In order to estimate the residual wall thickness from this average brightness difference, the relationship between the residual wall thickness and the brightness difference of the original plate thickness (healthy portion) obtained in advance, FIG. 4 is used in this embodiment. In FIG. 4, it can be read that the residual wall thickness corresponding to the case where the average brightness difference is 15.4 is 4 mm. That is, it is estimated that the residual wall thickness is 4 mm. This is consistent with the plate thickness of 4 mm (= plate thickness 5 mm − hole depth 1 mm) of the hole portion of the test piece which is the test material. From this, the effectiveness of the present invention was confirmed.

1: X-ray source 2: X-ray source controller 3: Personal computer for X-ray source control (PC)
4: Inspection target (steel pipe)
5: X-ray detector 6: Personal computer (PC) for X-ray detector
X: X-ray

Claims (5)

Step 1 of irradiating the structure to be inspected with X-rays to obtain a digital X-ray transmission image,
Step 2 of discriminating between a defective portion and a sound portion from the image obtained by subjecting the digital X-ray transmission image to image processing and the digital X-ray transmission image.
Step 3 to store the position information of the defective part and the sound part, and
Based on the above position information, the average brightness in a predetermined area is obtained for each of the defective portion and the sound portion of the digital X-ray transmission image before image processing, and further, the difference in the average brightness between the defective portion and the sound portion is obtained. 4 and
A method for inspecting a structure, which comprises step 5 of obtaining the wall thickness of the defective portion and the sound portion from the average brightness of the defective portion and the sound portion and the difference in brightness between them. In the above image processing, the digital X-ray transmission image obtained in step 1 is subjected to any one of expansion processing, contraction processing and contrast expansion processing (histogram expansion processing), or an image in which two or more are combined. The method for inspecting a structure according to claim 1, wherein the process comprises substeps in which the process is sequentially performed a plurality of times. In step 2, in the digital X-ray transmission image obtained in step 1 and the image obtained by subjecting the digital X-ray transmission image to image processing, the difference between the average brightness of the predetermined area and the average brightness of the sound portion is all gradations. The method for inspecting a structure according to claim 1 or 2, wherein a portion of 1% or more of the number is determined to be a defective portion. The method for inspecting a structure according to any one of claims 1 to 3, wherein the structure is a pipe. A structure characterized in that the reduced wall thickness or the residual wall thickness of the structure is determined by using the method for inspecting the structure according to any one of claims 1 to 4, and the soundness of the structure is evaluated. Diagnostic method.

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