JPS61215960A - Flaw detecting method for pressure container and pipes - Google Patents

Abstract

PURPOSE:To improve the accuracy of the flaw estimation of a pressure container, etc., by obtaining a picture concentration in the estimation area of the prescribed dimensions from a flaw detection plane picture for each flaw detecting area, and estimating the flaw depth from the relation of the picture concentration and the flaw depth which is prepared beforehand. CONSTITUTION:The scope to detect a flaw of the inner surface of a pressure container 10 is divided into a unit area 18 of the prescribed dimensions, and an ultrasonic wave makes incident diagonally and scans from a probe 1 of a hand scanner 11. An ultrasonic echo received by the probe 1 is inputted into an ultrasonic flaw detecting device 12 and a flaw signal is transmitted. Next, at a video control device 13, the video signal of the cross section and a plane picture are outputted by a flaw signal and a position detecting device 5, and displayed at monitoring television sets 14 and 15. Next, from the picture concentration divided at an estimation area 19, a flaw depth is estimated by the relation of the picture concentration and the flaw depth prepared by experiment data beforehand. Thus, the flaw can be estimated with a good accuracy from the external part simply during the using of a pressure container, etc.

Description

DETAILED DESCRIPTION OF THE INVENTION The present invention relates to a flaw detection method for detecting defects by inspecting the inner surfaces of pressure vessels and pipes from the outside and evaluating the depth thereof.

Long summer technique! In order to confirm the safety of pressure vessels and pipes such as city gas holders and spherical low-temperature liquefied gas storage tanks, it is necessary to inspect the walls of the containers and pipes for defects that occur after each predetermined period of service. For defects that occur on the inner surface of a pressure vessel, magnetic particle testing that directly uses the surface to be inspected, dye penetrant testing, etc. cannot be applied while the pressure vessel is in use.
Conventionally, it has been necessary to suspend the use of the pressure vessel for inspection, drain the stored gas, etc., and open the vessel for inspection, which requires a great deal of time and expense. Furthermore, with regard to pipes, it has been impossible to reliably inspect the inner surface for defects not only while they are in service but also when no one is allowed inside.

Regarding the surface defects of the plate, for safety reasons of pressure vessels and piping,
The defect size, especially its depth, is an issue.

A method using ultrasonic waves is known as a method for externally detecting defects occurring inside a board.

Current ultrasonic flaw detection mainly targets internal defects, and the reflected wave from the flaw is captured as a pulse image on the CRT of the flaw detection device, and the peak value and the length indicating the spread of the defect are used as judgment quantities to determine the defect. We are conducting an evaluation. Several principles have been proposed for detecting surface defects using ultrasonic testing, but these methods have not yet reached the level of practical use because there are many factors that disturb defect information and reliable evaluation is difficult. This is the reality.

Typical defect depth estimation methods using ultrasonic flaw detection tests that have been proposed in the past include the edge beak echo method and the corner echo method. However, the edge peak echo method
In experiments using actual defect test pieces, the tip of the defect cannot always be identified reliably, and the corner echo method is as shown in principle in FIG.

An ultrasonic beam having a certain width is made incident on the outer surface of a plate 2 at an incident angle θ by a probe 1, and echoes reflected by a defect 3 on the inner surface are returned to the incident direction. the result,
The echoes returning to the probe 1 behave as if they were reflected from a surface 4 with a width W perpendicular to the ultrasound beam. Defect 3
If the depth of is d, then W = 2 a cos θ - (1), which has advantages such as a high echo level, easy capture of echoes, and the ability to detect defects from either side.

However, actual defects in a board are not necessarily perpendicular to the surface of the board, and the defect surface is not necessarily smooth, so the direction of the reflected echo is not necessarily parallel to the incident direction, and it is attenuated. Also (1
) A considerable error occurs in the defect depth d determined by the formula.

In addition, a hand scanner equipped with an ultrasonic probe and a 1-position detector scans the outer surface of the board, and ultrasonic waves are incident obliquely from the board surface, and ultrasonic echoes reflected by defects on the back surface are detected. The position signal from the position detector, a cross-sectional image along the scanning line, and a defect plane image on the scanning plane are displayed on an image display device such as a CRT.

Cross-sectional image evaluation methods and planar image evaluation methods for externally detecting defects on the back surface are also well known.

The principle of drawing will be explained with reference to FIGS. 10 and 11.

10(a) while emitting ultrasonic waves from the probe 1 at an incident angle of θ along the surface of the plate 2.

In Fig. 11(a), scan from right to left, receive the emitted echo with a probe, input it to an ultrasonic flaw detector, create a defect signal from the echo reflected from the back side defect, and detect it based on the amount of movement caused by scanning. It is input to the video control device together with the position signal, and the output video signal is used to display a cross-sectional image and a planar image on a CRT of a monitor television. FIG. 10(b) and FIG. 11(b) are examples of a cross-sectional image and a planar image displayed on a CRT, respectively. The principle of drawing a cross-sectional image will be explained with reference to FIG. 10(a). The distance w1. W is determined from the difference between the time point at which the ultrasonic wave is transmitted and the time point at which the echo is received.

If the difference is ΔW, then d=ΔW−cosθ・(2) CRT
The upper cross-sectional image displays d by calculating the defect signal and position signal using equation (2).

Furthermore, to explain the principle of drawing a planar image with reference to FIG. 11(a), the probe 1 is
Let Y be the distance scanned by.

Y=d-tanθ-(3) Probe 1
receives a reflected echo due to a defect.

This is then displayed as an image on a CRT. therefore,
A defect image having a width of Y in the scanning direction is displayed on the CRT. The depth d of the defect can be calculated by backward calculation from equation (3).

However, in practice, defects are artificially created in a test piece by electrical discharge machining, and the cross-sectional view and planar image are scanned using the above method.
When displayed above, the results are not necessarily as calculated using equations (2) and (3). Defects with a length of 10 m and a depth of 0.5 m, 1 m, 2 m, 4 m, and 6.8 m were created by electrical discharge machining on 60 kg/cm2 high-tensile steel with a thickness of 20 cm, and were scanned using the above method. , (2) and (3) and display the images. For each defect depth, the cross-sectional image and planar image become as shown in FIG. 12, respectively.

In the cross-sectional images, it is observed that the image depth increases as the depth of the defect increases. however.

When the depth exceeds four cabinets, there is a tendency for saturation. Even if the depth is 4 m or less, the image depth does not necessarily match the actual defect depth d, and is displayed larger than the actual depth on average. This is thought to be due to blurring due to the directivity of the ultrasonic waves. Furthermore, for group defects, a unique correspondence as shown in FIG. 12 is not necessarily obtained, and the situation becomes more complicated. Furthermore, actual group defects have different dimensions, methods, and inclination angles, and it is impossible to analytically evaluate their influence.

Even in the case of planar images, a tendency towards saturation is seen when the depth of the defect exceeds 4 m.

As mentioned above, it is extremely difficult to detect defects on the inner surface of a pressure vessel from the outside and evaluate their depth using the conventional ultrasonic flaw detection method, and this method has not yet reached the level of practical use.

11. In view of the above-mentioned circumstances of the conventionally proposed method of externally detecting flaws on the plate surface using ultrasonic waves, the present invention has been developed to detect flaws using ultrasonic flaw detectors that are commonly used in the past. It is an object of the present invention to provide a method by which defects on the inner surfaces of pressure vessels and tubes can be easily detected from the outside while the pressure vessels and tubes are in use, and the defect depth can be evaluated with practical accuracy.

for pa The method of the present invention achieves the above objectives.

Ultrasonic waves are incident obliquely from the outer surface of the pressure vessel or pipes and scanned using an ultrasonic probe, and defects are detected in each detection area using defect signals from the reflected waves and position signals from the scanning movement of the probe. Displaying a planar image on a display means, determining the image density in an evaluation field of predetermined dimensions from the image of the evaluation area,
The method is characterized in that the defect depth on the inner surface of the pressure vessel or tube in the evaluation area is evaluated based on the relationship between the image density and the defect depth created in advance from experimental data.

Furthermore, a defect detection cross-sectional image for each evaluation area is displayed using the defect signal and position signal generated by the ultrasonic reflected waves, and the maximum image width is determined and multiplied by a predetermined evaluation coefficient according to the detection level. If the pressure vessel inner surface defect depth is evaluated and this evaluation value is compared with the evaluation value of the defect depth evaluated from the image density in the evaluation field of the above-mentioned plane image, the final evaluation depth is obtained. , the evaluation accuracy is further improved.

Other features of the invention will become clear from the following description with reference to one drawing.

As mentioned above, the defect plane image in the defect plane image evaluation method has a large image area compared to the cross section of the defect, and is considered to be an image of the defect projected onto the plate surface in the direction of incidence of the ultrasonic wave.・It is thought that the image area of the defect plane image can be used as an evaluation quantity for the defect depth. The present inventors conducted experiments using many defect test specimens, and based on the experimental results obtained, it was found that Divide the area into unit areas of appropriate size, perform ultrasonic flaw detection on each unit area using a hand scanner, record a plane defect image for each unit area on a printer or hard copy, and then When the maximum image density in a certain size evaluation field of view is read and the relationship between this and the depth of the defect in the relevant unit area of the test piece is plotted, the experimental points vary within a certain range, but the area where the points exist It turns out that it is possible to draw a fairly clear boundary between the absent area and the absent area.

Therefore, using this line as a defect depth evaluation line, it is possible to estimate the maximum depth of defects including group defects from the maximum image density.

Regarding defect cross-sectional images, as mentioned above, the depth of the image should in principle indicate the defect depth, but according to a lot of experimental data, the relationship between image depth varies slightly, but on average It was found that the image depth becomes larger than the defect depth, and the ratio remains constant. Therefore, by multiplying the maximum image depth in the cross-sectional image by using this proportionality constant as an evaluation coefficient, it is possible to estimate the defect depth.

Comparing the above evaluation methods for planar images and cross-sectional images, the evaluation using the former tends to be overestimated, whereas the evaluation using the former tends to be overestimated.
The latter evaluation will be the average evaluation.

Therefore, by combining both evaluation methods and making a final determination, it is possible to improve the evaluation accuracy.

FIG. 1 is a diagram showing a schematic configuration of an example of a system for carrying out the method of the present invention for flaw detection of pressure vessels.

A hand scanner 11 scans the surface of a pressure vessel 10 whose inner surface is to be detected for defects. A hand scanner 11 transmits ultrasonic waves and receives ultrasonic echoes reflected from defects on the inner surface of the container, and a probe 1 and a scanning movement position signal. It also has a position detector 5 that transmits a signal. The ultrasonic echo received by the probe is detected by ultrasonic flaw detector 1.
2 and sends out a defect signal. The defect signal is sent to the video control device 1 together with the position signal transmitted from the position detector 5.
3, calculations based on equations (2) and (3) are performed, and video signals for cross-sectional images and planar images are output,
The defective cross-sectional image and the defective flat image are inputted to a monitor television 14 for displaying a cross-sectional image and a monitor television 15 for displaying a flat image, respectively, and displayed on the respective CRTs. The video signal is also
A copy of the defective image is made by inputting it into a printer or hardcopy 16.

The range in which defects on the inner surface of the pressure vessel 10 are to be detected is divided into unit areas of appropriate size, for example, looaaXroom, and each unit area is assigned a consistent number. FIG. 2 is an example of this, in which unit areas 18 are arranged on both sides along a weld line 17 where defects are likely to occur, and a serial number is assigned to each side.

As shown in FIG. 3, each unit area 18 has, for example, one side
In the case of 001, for example, a zigzag line is drawn on parallel lines with an interval of 10I111 so as to intersect with the parallel lines at an angle close to a right angle, and the hand scanner 11 scans the lines, thereby thoroughly scanning the unit area. The scanning direction for drawing a zigzag line is
It is necessary to set it so that it is perpendicular to the direction in which the defect extends, and if the direction in which the defect extends is unpredictable, set it to 1.
Prior to the actual flaw detection, it is necessary to perform rough flaw detection to get an idea.

In FIGS. 4(a) and 4(b), a unit area 18 of roomXroom is scanned with the hand scanner 11.

This is an example of an obtained defect plane image and the actual state of the defect corresponding thereto. Among them, evaluation field of view 19 (in this example, 25 ■
x25m) and the defect depth is evaluated based on the image density using a preset defect depth evaluation line. FIG. 5 is a diagram showing an example of an evaluation line for evaluating defect depth from the image density of a planar image. In the figure, solid line A is a high-sensitivity evaluation line, and broken line B is a medium-sensitivity evaluation line. The high sensitivity evaluation line is
This is an evaluation line when the flaw detection sensitivity is set to the L detection level, and the middle sensitivity evaluation line is an evaluation line when the flaw detection sensitivity is set to the M detection level. This evaluation line is drawn in advance by detecting a large number of specimens at various detection levels, and for each displayed unit area, the relationship between image density and defect depth for the evaluation visual field is determined horizontally as shown in Figure 6. The points are placed on an orthogonal coordinate plane with the defect depth on the axis and the image density on the vertical axis, and are determined as the boundary line between the existing range and the absent range of the experimental point. In the figure, . indicates an experimental point conducted at the L detection level, and O indicates an experimental point conducted at the M detection level.

When evaluating the defect depth using FIG. 5, the image density in each unit area is read in units of 10%, and the defect depth is determined using an evaluation line according to the detection level. To read the image density,
Draw a frame of the evaluation field of view (25 x 25 m in this example) on a transparent plate, move it by hand against the flat image displayed on the CRT or copy to find the part to be evaluated, and at that position draw the image inside the frame. Just read the concentration. This reading can be easily done with the required accuracy with some experience by comparing and contrasting the ratio of the image in the frame with the image density standard example shown in Figure 7 to find the same level. . Note that the relationship between the image density and the defect depth may be provided in the form of a table other than the evaluation line.

As mentioned above, the depth of the defect cross-sectional image and the actual depth of the defect do not necessarily match depending on the defect occurrence situation, detection level, etc. Figure 8 shows how ultrasonic flaw detection is performed on many defect test specimens by switching the flaw detection sensitivity between medium sensitivity (M detection level) and low sensitivity (H detection level), displaying a cross-sectional image on a CRT, and increasing the image depth. Figure 0 shows an example of the relationship between b) and defect depth d), with the defect depth d) on the horizontal axis and the image depth b) on the vertical axis, indicating medium sensitivity. 0 is the experimental point for low sensitivity.The experimental points for both sensitivities vary considerably, but if you draw their average straight line, the average line for medium sensitivity is 1 point. Chain I
The average line for IA and low sensitivity is as shown by broken line B. In this graph, the image depth b) on the vertical axis and the defect depth d) on the horizontal axis are shown on the same scale, so 451
Straight line C shows the case when d/b = 1, and from the slope of the average straight lines A and B of the experimental points of medium and low sensitivity, d is
/ b = 0.6, d / b = 0. for low sensitivity.
It can be seen that there are 9 relationships. Therefore, on average, if the flaw detection sensitivity is medium, the depth of the cross-sectional image is multiplied by an evaluation coefficient of 0°6, and if the sensitivity is low, the defect depth is multiplied by an evaluation coefficient of 0.9. can be evaluated.

The evaluation values obtained by the above-mentioned planar image evaluation method tend to be overestimated, whereas the evaluation values obtained from cross-sectional images are average values, so the final evaluation should be made from the evaluation values obtained using the one-car evaluation method. This improves accuracy. In that case, if the difference between the two is less than 1+m, it is practical to take the larger value, and if the difference between the two exceeds I, it is practical to use the average value of both as the evaluation value.

In the embodiment described above, the size of the unit area to be scanned for flaw detection is 10100mm x 100+, and the evaluation field of view is 25+
+w×25 mm is shown as an example, but these dimensions are not necessarily limited to these dimensions.

However, according to experimental results, it has been found that good evaluation is possible when the dimensions are approximately in the vicinity of this size.

As described above, according to the present invention, defects on the inner surfaces of pressure vessels and pipes, especially their depth, which have not been put to practical use in the past, can be detected externally by using a conventionally used ultrasonic flaw detection device. Exploration enables evaluation with a practically acceptable accuracy on the safe side, so there is no need to interrupt service and open the pressure vessel and its inner surface for inspection, significantly reducing the time and cost of inspection. It is possible to reduce the

[Brief explanation of drawings]

Fig. 1 is a schematic diagram showing a schematic configuration of an example of a system implementing the method of the present invention, Fig. 2 is a plan view showing an example of dividing the external flaw detection range into unit areas for internal surface defects, and Fig. 3 is a unit A schematic diagram showing how to scan an area, Figures 4(a) and 4(b) are plan views each showing an example of a defect plane image and the corresponding defect situation, and Figure 5 is an evaluation used in the plane image evaluation method. A graph showing one example of the line, Fig. 6 is a graph showing a large number of experimental points showing the relationship between image density and defect depth for determining the above evaluation line, and the evaluation line determined based on this, and Fig. 7 is a graph showing the evaluation line determined from this. A schematic diagram showing an image density standard example for reading the image density of each evaluation area, and Figure 8 shows a number of experimental points showing the relationship between image depth and defect depth to obtain evaluation coefficients used in the cross-sectional image evaluation method. Figure 9 is a schematic diagram explaining the principle of internal defect detection using the corner echo method using known ultrasonic waves, and Figures 10 (a) and (b) are the drawing principles of the cross-sectional image evaluation method, respectively. Figure 11 (a) and (b) are similar diagrams showing the drawing principle of the plane image evaluation method, Figure 12 is a test material with artificial defects created by electrical discharge machining. It is a schematic diagram showing an example of an ultrasonic flaw detection cross-sectional image and a planar image for various defect depths. 1... Probe (ultrasonic transducer) 2... Plate (pressure vessel wall) 3... Inner surface defect 5... Position detector 10...
・Pressure vessel 11...hand scanner 12...
Ultrasonic flaw detector 13...Video control device 14.15...
・Monitor TV 16...Printer 18...Unit area Figure 2 Figure 3 Figure 5 Defect depth (mm) Figure 8 Figure 10 (a) (b) Procedural amendment written in 1985 10 Month 22nd

Claims (6)

[Claims] (1) In a flaw detection method for detecting defects on the inner surface of a pressure vessel or pipes from the outer surface, scanning is performed by obliquely injecting ultrasonic waves from the outer surface using an ultrasonic probe, and the defect signal from the reflected wave and the above-mentioned Based on the position signal generated by the scanning movement of the probe, a defect detection plane image is displayed on the display means, and the image density in the evaluation field of predetermined dimensions is determined from the image, and the image density and defect depth created in advance from experimental data are calculated. A flaw detection method characterized by evaluating the depth of defects on the inner surface of a pressure vessel or pipes in an evaluation area based on the relationship. (2) The dimensions of the above evaluation field of view are approximately 25 mm x 25 mm.
The flaw detection method according to claim 1, characterized in that: (3) The flaw detection method according to claim 1, wherein the image density is determined by reading the image within the evaluation field of view in 10% increments and evaluating the defect depth. (4) In a flaw detection method that searches for defects on the inner surface of a pressure vessel or pipes from the outside surface, ultrasonic waves are applied obliquely to the range to be detected from the outside surface of the pressure vessel or pipes, and the reflected waves are scanned. Based on the defect signal obtained by the above-mentioned defect signal and the position signal obtained by the scanning movement of the probe, a defect detection plane image and a defect detection cross-sectional image are respectively displayed on the display means, and the image density in the evaluation field of predetermined dimensions is calculated from the defect detection plane image. The defect depth on the inner surface of the pressure vessel or pipes in the evaluation area is determined from the relationship between the image density and the defect depth created in advance from experimental data, and this is taken as the first defect depth evaluation value, and the cross section of the above evaluation area is determined. Find the maximum image depth from the image, multiply it by a predetermined evaluation coefficient according to the detection level, use this as the second evaluation value for the pressure vessel inner surface defect depth, and compare the above first and second evaluation values. A flaw detection method characterized by determining the final evaluation depth. (5) The flaw detection method according to claim 4, wherein the image density is determined by reading an image within the evaluation field of view in units of 10% and evaluating the defect depth. (6) If the difference between the first evaluation value and the second evaluation value of the defect depth above is 1 mm or less, the larger value will be used if the difference between the two is 1 m.
5. The flaw detection method according to claim 4, wherein when the flaw detection depth exceeds m, the average value of both is used as the final evaluation depth of the defect.