JP4969145B2 - Ultrasonic flaw detection data processing method, flaw detection data processing program, and ultrasonic flaw detection data processing apparatus - Google Patents

Description

  The present invention relates to an ultrasonic flaw detection data processing method, and more particularly to a technique useful for evaluating the size of a defect detected by ultrasonic flaw detection by digital arithmetic processing.

  In ultrasonic flaw detection, it is important not only to detect the presence of a defect, but also to evaluate the size of the defect. The size of the detected defect is important information for evaluating the safety of a certain structure.

  Although it is desirable that the defect size is automatically calculated by digital calculation processing, it is not always easy to accurately calculate the defect size by digital calculation processing from the flaw detection data obtained by ultrasonic flaw detection. Not that. One difficulty in ultrasonic flaw detection is that it cannot be said that an ultrasonic image directly represents the structure of a defect. Since the direction in which the ultrasonic wave is reflected depends on the direction of the defect, the ultrasonic wave reflected by the defect may not be detected by the probe depending on the direction of the defect. A portion where the ultrasonic wave is not reflected is not reflected as a defect in the ultrasonic image. For this reason, when the extending direction of the defect changes three-dimensionally, one defect may appear as being separated into a plurality of defect images in the ultrasonic image. This hinders the correct assessment of defect size.

  Japanese Patent Laying-Open No. 2005-274444 discloses a technique for calculating an indicated height from flaw detection data. However, the known technique makes no mention of the difficulties mentioned above.

From this background, when multiple defect images appear in the ultrasound image, a technology to correctly identify whether it is actually caused by a single defect or multiple defects by digital arithmetic processing The provision of
JP 2005-274444 A

  Therefore, the object of the present invention is to more accurately detect whether a defect is actually caused by a single defect or a plurality of defects when a plurality of defect images appear in the ultrasonic image. It is to provide a technique for discriminating.

  In order to achieve the above object, the present invention employs the means described below. In the description of technical matters constituting the means, in order to clarify the correspondence between the description of [Claims] and the description of [Best Mode for Carrying Out the Invention] Number / symbol used in the best mode for doing this is added. However, the added number / symbol should not be used to limit the technical scope of the invention described in [Claims].

The ultrasonic flaw detection data processing method according to the present invention is a processing method for processing flaw detection data obtained by ultrasonic flaw detection by digital arithmetic processing. The ultrasonic flaw detection data processing method is as follows: (A) Based on the flaw detection data, a defect image (21) corresponding to a defect existing in the subject (2) is recognized, and a defect image is detected for each defect image (21). A step (S02 to S04) of determining an area representative point (23) representing the position of (21);
(B) From the distance between the region representative points (23), it is determined whether one defect image (21) of the defect images (21) is caused by the same defect as the other defect images (21). Step (S05, S06)
It comprises.

  The step (B) determines whether the two defect images (21) are caused by the same defect from the distance between the region representative points (23) of the two defect images (21) in the same cross section. It is preferable to include a step (S05) of determining. In the step (B), the two defect images (21) are calculated from the distance in the in-plane direction parallel to the cross section between the region representative points (23) of the two defect images (21) having different cross sections. It is also preferable to include a step (S06) of determining whether or not the same is caused by the same defect.

  In this ultrasonic flaw detection data processing method, the position of the defect image (21) is represented by the area representative point (23), and the defect is based on the distance between the area representative points (23). Identity. Therefore, when a plurality of defect images appear, it can be more accurately determined by digital arithmetic processing whether the plurality of defect images are caused by a single defect or a plurality of defects.

The step (A) includes:
(A1) defining a rectangular region (22) so as to surround the defect image (21);
(A2) Preferably, the step of defining the intersection of the diagonal lines of the rectangular area (22) as the area representative point (23) is provided.

Instead, the step (A)
(A3) a step of defining a rectangular area so as to surround an echo peak area having an echo height equal to or greater than a predetermined value in the defect image (21); and (A4) an intersection of diagonal lines of the rectangular area as the area representative point ( It is also preferable to comprise the step defined as 23).

  In the ultrasonic flaw detection, flaw detection data of a plurality of cross sections may be acquired while scanning the probe (6) along a predetermined scanning direction. In this case, the processing method further includes: (C) a predetermined number of adjacent flaw detection data of the target cross section among the plurality of cross sections adjacent to the target cross section in front of the scan direction and / or rearward in the scan direction. A step (S11) of generating corrected flaw detection data by correcting using the cross-section flaw detection data, and in the step (A), a defect image (21) corresponding to a defect from the corrected flaw detection data is provided. Is preferably recognized.

  The step (C) includes (C1) correcting the flaw detection data of the target cross section so that the echo height data at each position of the target cross section is increased according to the echo height of the same position of the adjacent cross section. It is preferable to include a step (S11) of generating the corrected flaw detection data.

  In this case, in the step (C1), the flaw detection data is set so that the echo height data at each position of the target cross section becomes the maximum value of the echo height at the same position of the target cross section and the adjacent cross section. Preferably, the method includes a step of generating the corrected flaw detection data by correcting.

  The length of the defect in the scanning direction can be measured based on the number of continuous cross sections in which a defect image corresponding to the defect appears. However, when the flaw detection data of the target cross section is corrected using the flaw detection data of the adjacent cross section, the length of the defect is the flaw detection of the target cross section in addition to the number of the adjacent cross sections used for correction. It is preferable to calculate based on the number of the adjacent cross sections used for correcting the data.

The flaw detection data processing program according to the present invention is a program for causing the arithmetic unit (10) to process flaw detection data obtained by ultrasonic flaw detection. The program is
(A) Based on the flaw detection data, a defect image (21) corresponding to a defect existing in the subject (2) is recognized, and a region representative representing the position of the defect image (21) for each defect image (21). Defining a point (23);
(B) From the distance between the region representative points (23), it is determined whether one defect image (21) of the defect images (21) is caused by the same defect as the other defect images (21). And causing the arithmetic unit (10) to execute the step of performing.

The ultrasonic flaw detection data processing apparatus according to the present invention recognizes the defect image (21) corresponding to the defect existing in the subject (2) based on the flaw detection data obtained by the ultrasonic flaw detection, and detects the defect image (21). For each, one defect image in the defect image (21) from the distance between the region representative point (23) representing the position of the defect image (21) and the region representative point (23). Means (10) for determining whether (21) is caused by the same defect as the other defect image (21)
It comprises.

  According to the present invention, when a plurality of defect images appear in an ultrasonic image, it is possible to more accurately determine whether the defect is actually caused by a single defect or a plurality of defects.

(First embodiment)
In the first embodiment, the ultrasonic flaw detection data processing method according to the present invention is applied to ultrasonic flaw detection as described below.

  FIG. 1 shows a configuration of an automatic ultrasonic flaw detection system 1 and a configuration of a subject 2 used in the present embodiment. In this embodiment, the subject 2 to be flawed by the automatic ultrasonic flaw detection system 1 is two steel plates 3 and 4 that are butt welded. In the following, a description will be given of a case where flaw detection is performed on the welded portion 5 of the steel plates 3 and 4 and the periphery thereof, but it will be obvious to those skilled in the art that the subject 2 is not limited to such a structure.

  In the present embodiment, the automatic ultrasonic flaw detection system 1 includes a probe 6, a scanning device 7 that scans the probe 6 in a desired scanning direction, a control device 8, a display device 9, and a calculation device 10. I have. In the present embodiment, the scanning direction of the probe 6 is determined in the direction along the weld line of the steel plates 3 and 4. In the following description, it should be noted that an xyz orthogonal coordinate system is used in which the scanning direction is the z-axis direction, the direction perpendicular to the scanning direction and the direction parallel to the surface of the steel plate 3 is the x-axis direction.

  The probe 6 makes an ultrasonic beam incident on the subject 2 in response to the electrical signal supplied from the control device 8, and further receives the reflected wave from the subject 2 to generate an electrical signal corresponding to the reflected wave. To do. The probe 6 is composed of a plurality of ultrasonic transducers arranged in a line in a plane parallel to the xy plane, and the probe 6 is in a plane parallel to the xy plane. It is possible to function as a phased array that electronically scans the ultrasonic beam.

  The scanning device 7 includes a rail 11 and a probe holding mechanism 12. The rail 11 extends in the scanning direction, that is, the direction of the weld line of the subject 2. The probe holding mechanism 12 holds the probe 6. The probe holding mechanism 12 is placed on the rail 11 so as to be movable in the flaw detection direction, and the probe 6 is scanned by moving the probe holding mechanism 12 on the rail 11. Is called. The position in the scanning direction of the probe 6 can be detected by an encoder (not shown) provided on the rail 11.

  The control device 8 controls the probe 6 and performs various calculations for detecting the subject 2. Specifically, the control device 8 supplies an electric signal to the probe 6 to cause the probe 6 to generate an ultrasonic beam. Furthermore, the control device 8 stores flaw detection data, which is data corresponding to the waveform of the reflected wave received by the probe 6, in a storage device (not shown). The control device 8 further has a function of generating various ultrasonic images, that is, an A scope image, a B scope image, a C scope image, and a D scope image from the flaw detection data, and displaying them on the display device 9.

  The arithmetic device 10 performs various digital arithmetic processes on the flaw detection data stored in the control device 8, thereby analyzing the defects existing in the subject 2, particularly calculating the size of the defects.

  As shown in FIG. 2, the automatic ultrasonic flaw detection system 1 of the present embodiment is configured to electronically scan an ultrasonic beam in the xy plane and mechanically scan in the z-axis direction. Has been. The ultrasonic beam can be incident in any direction from any position on the contact surface between the probe 6 and the subject 2. Specifically, among a plurality of ultrasonic transducers constituting the probe 6, a predetermined number of ultrasonic transducers arranged in succession are selected, and the selected ultrasonic transducers are excited to generate an ultrasonic beam. Is incident on the subject 2. The combination of excited ultrasonic transducers is often called “focal law”. For example, when six ultrasonic transducers are excited simultaneously, the sixth ultrasonic transducer from the left end of the probe 6 constitutes one “focal low”, and the second from the left. Up to the seventh ultrasonic transducer constitutes another “focal low”. The position where the ultrasonic beam is incident is determined by the combination of ultrasonic transducers to be excited (ie, focal law) among the ultrasonic transducers constituting the probe 6, and the direction in which the ultrasonic beam is incident. Is determined by the phase difference of the electrical signal supplied to the excited ultrasonic transducer.

  The path characteristic of the ultrasonic beam is determined by the combination of excited ultrasonic transducers and the incident direction of the ultrasonic beam (that is, the phase difference of the electrical signal). For example, as shown in FIG. 2, the sixth ultrasonic transducer from the left end is selected as the ultrasonic transducer to be excited, and an electrical signal having a predetermined phase difference is supplied to these ultrasonic transducers. As a result, an ultrasonic beam of focal low “1” is generated. The waveform of the reflected wave of the ultrasonic beam is acquired as A scope data of focal law “1”. Similarly, the second to seventh ultrasonic transducers from the left are selected as the ultrasonic transducers to be excited, and an electrical signal having a predetermined phase difference is supplied to these ultrasonic transducers, thereby causing the focal A low "2" ultrasonic beam is generated. The flaw detection data acquired by the automatic ultrasonic flaw detection system 1 includes an identifier for identifying a focal law and A scope data for each focal law (that is, data indicating the waveform of the reflected wave of the ultrasonic beam generated for each focal law). ).

  Acquisition of flaw detection data by the automatic ultrasonic flaw detection system 1 is performed according to the following procedure. With reference to FIG. 3, first, the probe 6 is aligned with the desired cross section i of the subject 2 by the scanning device 7. The focal row having the cross section i is selected, and A scope data is acquired for the focal row. As shown in FIG. 5, in this embodiment, the A scope data is described as the echo height (that is, the signal level of the reflected wave) in each path of the focal law. The echo height is a numerical value in a predetermined numerical range, and is expressed by a numerical value of 0 to 100 in the present embodiment. However, when the signal level of the reflected wave is equal to or higher than a predetermined value, the echo height described in the A scope data is determined as the upper limit value in the numerical range. By the same procedure, A scope data is acquired for all the focal lows defined by the cross section i.

  Subsequently, the probe 6 is moved in the scanning direction (z-axis direction) and aligned with the adjacent section i + 1. Similarly, for the section i + 1, A scope data is acquired for all of the defined focal rows. By repeating the same procedure for all desired cross sections of the subject 2, flaw detection data is acquired for the entire subject 2. In this embodiment, the focal law from which A scope data is acquired is the same for all cross sections. That is, the echo height data of the same path of the same focal law represents the echo height data of the same position in all the cross sections.

  Various ultrasonic images, that is, a B scope image, a C scope image, and a D scope image can be obtained by performing arithmetic processing on the acquired A scope data. For example, from the A scope data obtained for a certain cross section, a B scope image of the cross section can be generated. FIG. 4 is a conceptual diagram of a B-scope image of a certain cross section. The B scope image is an image that represents the height of an echo at each position of a cross section parallel to the xy plane of the subject 2 (that is, perpendicular to the scanning direction) by color tone or gradation. In FIG. 4, the horizontal axis indicates the position where the ultrasonic beam is incident (that is, the combination of excited ultrasonic transducers), and θ indicates the incident direction of the ultrasonic beam. A B-scope image of a certain cross section visually shows a position where a defect is considered to exist in the cross section. As shown in FIG. 4, when the defect image 13 appears in the B scope image, it is considered that a defect exists at the position of the defect image 13.

  Although the B scope image generally represents the position of the defect, there are two problems in obtaining the size of the defect from the B scope image of each cross section. The first problem is that, as described above, the defect image that appears in the B-scope image does not necessarily correspond one-to-one with the defect that actually exists in the subject 2; Even if two defect images appear, they may actually be due to one defect. The second problem is correspondence between defect images appearing in B-scope images of adjacent cross sections. In order to identify the designated length, that is, the length of the defect in the scanning direction, a defect image appearing in a B-scope image of a certain section and a defect image appearing in a B-scope image of another section It is necessary to determine whether or not it is caused by the same defect.

  The subject of the ultrasonic flaw detection data processing method of the present embodiment is that the defect image appearing in the B-scope image is automatically associated with the actual defect by digital arithmetic processing, thereby automatically determining the dimension of the defect. It is to be able to calculate. Hereinafter, the digital arithmetic processing performed by the arithmetic device 10 will be described in detail.

  FIG. 6 is a flowchart showing a processing procedure of digital arithmetic processing performed in the present embodiment. A program for executing the following processing procedure is installed in the arithmetic device 10, and the flaw detection data is processed by executing the program by the arithmetic device 10.

  First, threshold cut processing is performed on the obtained flaw detection data (step S01). In the threshold cut processing, for all A scope data, processing is performed to replace all data having echo heights smaller than a predetermined threshold with 0. This eliminates all background level echoes. This threshold cut processing also has a role of separating defect images from each other. If the echo height at a certain position is not 0 (that is, not less than a predetermined threshold), the position belongs to a region where a defect image corresponding to the defect exists, while the echo height at a certain position If is 0, the position is outside the area of the defect image.

  Subsequently, a B scope image is created (step S02). In this B scope image, the echo height at each position of the subject 2 is expressed as a color tone or gradation.

  Further, a defect image appearing in the B scope image is identified (step S03). The defect image is identified by the following procedure. First, a position where the echo height is not 0 is searched on the B scope image. When a position where the echo height is not 0 is found, the echo height is scanned for all the internal positions including the position by scanning the B scope image in both the vertical direction and the horizontal direction starting from the position. A continuous region with a non-zero value is recognized. The area is recognized as a defect image area.

  Subsequently, a rectangular area is determined for each defect image appearing in the B-scope image of each cross section, and an area representative point is determined for the rectangular area (step S04). The area representative point is a point representing the position of the rectangular area, that is, the position of the defect image. In one embodiment, as shown in FIG. 7A, a rectangular region 22 that circumscribes and surrounds the defect image 21 is defined, and an intersection of diagonal lines of the rectangular region 22 is defined as a region representative point 23.

  Instead, as shown in FIG. 7B, the rectangular area 22 is defined so as to circumscribe the echo peak area 24 in the defect image 21, and the intersection of the diagonal lines of the rectangular area 22 is the area representative. It may be determined as point 23. The echo peak region 24 is a continuous region in which the echo height has an upper limit value at all positions inside it. As described above, it should be noted that an upper limit value is set for the numerical range of the echo height of the A scope data. When the echo height at a certain position of the subject 2 is higher than a predetermined value, the A scope data describes that the echo height at that position is the upper limit value.

  The former method for determining the intersection of diagonal lines of the rectangular region 22 circumscribing the defect image 21 as the region representative point 23 is superior to the latter method based on the echo peak region 24 with a small amount of data processing and transfer. On the other hand, the latter method using the echo peak region 24 is excellent in that the position of the defect can be expressed accurately.

  Subsequently, as shown in FIG. 6, a process of determining whether or not the plurality of defect images 21 appearing on the same cross section is caused by the same defect is performed (step S05). For this determination, the position of the area representative point 23 of the rectangular area 22 defined for each defect image 21 is used. As shown in FIG. 8, when the distance d between the area representative points 23 of the rectangular areas 22 of the two defect images 21 is larger than a predetermined value A, the two defect images 21 are different defects. It is judged to be caused. On the other hand, when the distance between the region representative points 23 is equal to or less than the predetermined value A, it is determined that the two defect images 21 are caused by the same defect.

For example, if the coordinates of the area representative point 23 _j of each rectangular area 22 _j are (x _j , y _j ), the distance d _j between the area representative points 23 _{j and} 23 _{j + 1} of the rectangular areas 22 _j and 22 _{j + 1} respectively _{. j + 1} is represented by the following formula:
d ₁ (j, j + 1) = √ {(x _j −x _{j + 1} ) ² + (y _j −y _{j + 1} ) ² }.
In the example of FIG. 8, since d (j, j + 1) is larger than the predetermined value A, it is determined that the defect images 21 corresponding to the rectangular regions 22 _j and 22 _{j + 1} are caused by different defects. On the other hand, since the distance d ₁ (j + 1, j + 2) between the area representative points 23 _{j + 1 and} 23 _{j + 2} of the rectangular areas 22 _{j + 1} and 22 _{j + 2} is equal to or less than the predetermined value A, it corresponds to the rectangular areas 22 _j and 22 _{j + 1} respectively. The defect image 21 to be determined is caused by the same defect.

  The arithmetic unit 10 associates the defect image 21 determined to be caused by the same defect with respect to each of the cross sections subjected to the ultrasonic flaw detection. This is performed by assigning the same defect ID to the defect image 21 caused by the same defect, and assigning a different defect ID to the defect image 21 caused by the different defect.

Subsequently, as shown in FIG. 6, a process of determining whether or not the defect image 21 appearing in the adjacent cross section is caused by the same defect is performed (step S06). Also in this determination, the position of the area representative point 23 of the rectangular area 22 defined for each of the defect images 21 is used. For all combinations of the defect image 21 of a certain cross section and the defect image 21 of the cross section adjacent thereto, the distance d ₂ in the in-plane direction between the area representative points 23 of the corresponding rectangular area 22 is calculated. The distance d ₂ in the plane direction, definitive when projected area representative point 23 of different cross-section of the rectangular region 22 in the xy plane, is that the distance between the projection points of the area representative point 23. The distance d ₍ in-plane direction) between the area representative point 23 _{i, j} of the rectangular area 22 _{i, j} of the cross section i and the area representative point 23 _{i + 1, k} of the rectangular area 22 _{i + 1, k} of the cross section i + 1 adjacent to the cross section i. _{i, j) (i + 1, k)} is represented by the following formula:
d _{i, i + 1} (j, k) = √ {(x _{i, j} −x _{i + 1, k} ) ² + (y _{i, j} −y _{i + 1, k} ) ² },
Here, (x _{i, j} , y _{i, j} ) is an xy coordinate of the region representative point 23 _{i, j} of the rectangular region 22 _{i, j} of the cross section i, and (x _{i + 1, k} , y _{i + 1, k} ) _Are the xy coordinates of the area representative point 23 _{i + 1, j} of the rectangular area 22 _{i + 1, k} of the cross section i + 1.

As shown in FIG. 9, the area representative points 23 _{i, j} of the rectangular area 22 _{i, j} of the cross section i and the area representative points 23 _{i + 1, k} of the rectangular area 22 _{i + 1, k} of the cross section i + 1 adjacent to the cross section i _. for _k, the distance _{d 2} in the plane direction is larger than the predetermined value B, the rectangular region _{22 i} of the cross section _i, a defect image 21 corresponding to _j, the defect image corresponding to the rectangular region _{22 i + 1, k} of the cross-section i + 1 21 is determined to be caused by a different defect. The predetermined value B is a constant value larger than the predetermined value A used in step S05 described above. On the other hand, when the distance between the region representative points 23 _{i, j} , 23 _{i + 1, k} is equal to or less than the predetermined value B, it is determined that the two defect images 21 are caused by the same defect.

In the example of FIG. 9, the defect image 21 corresponding to each of the rectangular area 22 _{i, j of} the cross section i, the rectangular area 22 _{i + 1, k of} the cross section i + _{1, and} the rectangular area 22 _{i + 1, m} of the cross section i + 2 is caused by the same defect. On the other hand, the defect image 21 corresponding to the rectangular area 22 _{i + 1, n} of the cross section i + 3 is determined to be caused by a different defect.

  The arithmetic unit 10 associates the defect image 21 determined to be caused by the same defect. This is performed by assigning the same defect ID to the defect image 21 caused by the same defect, and assigning a different defect ID to the defect image 21 caused by the different defect.

  It should be noted that even if it is determined in step S05 that two defect images 21 in a certain cross section are caused by different defects, the determination is corrected in step S06, and as a result, the same defect ID can be given. For example, even when it is determined in step S05 that the two defect images 21 of the cross section i are caused by different defects, in step S06, the defect image 21 having the cross section i adjacent to the defect image 21 is identical to the two defect images 21. When it is determined that the defect is caused by the defect, it is finally determined that the three defect images 21 are caused by the same defect, and the same defect ID is given.

  Subsequently, for each of the defects, the indicated length of the defect is measured (step S07). When the defect image 21 determined to be caused by the same defect (that is, given the same defect ID) appears on N consecutive cross sections, the indicated length is (N−1) · D It is judged that. Here, D is the distance between two adjacent cross sections.

  As described above, in the present embodiment, the defect image 21 is the same based on the distance between the region representative points 23 of the rectangular region 22 defined for each defect image 21 in the same cross section. It is determined whether it is caused by the defect. Further, based on the distance in the in-plane direction between the region representative points 23 of the rectangular region 22 defined for each of the defect images 21 in the adjacent cross sections, it is determined whether the defect image 21 is caused by the same defect. The Thereby, it is possible to correctly identify whether the defect image is caused by a single defect or a plurality of defects, and correctly evaluate the size of the defect by digital arithmetic processing.

(Second Embodiment)
When the extending direction of the defect changes three-dimensionally, the defect image may not be correctly associated between adjacent cross sections. FIG. 10 is a diagram for explaining the reason. As shown in FIG. 10, the defect 25 does not necessarily extend parallel to the surface of the subject 2. For example, in the cross sections i ₁ and i ₃ , the extending direction of the defect 25 is parallel to the surface of the subject 2, but in the cross section i ₂ between them, the extending direction of the defect 25 is oblique to the surface of the subject 2. There may be cases. In such a case, although the reflected wave returns to the probe 6 in the cross sections i ₁ and i ₃ , the reflected wave may not return to the probe 6 in the cross section i ₂ . That is, the height of the echo due to the defect 25 is high in the cross sections i ₁ and i ₃ , but the height of the echo due to the defect 25 may be low in the cross section i ₂ . In such cases, it may not appear defective image in the cross section i _2. For example, the height of the echo due to defects 25 in the cross-section i ₂ is lower than the threshold used in the threshold cut processing (step S01), it does not appear defect image corresponding to the defect 25 is in its cross-section i _2. In such a case, the defect image appearing in the cross-sections i ₁ and i ₃ is recognized as two defects despite the single defect 25, and as a result, the size of the defect is not correctly evaluated. .

  In order to prevent such a problem, the cross-section enhancement process is performed in the present embodiment. The cross-section enhancement processing is processing for correcting flaw detection data of a certain target cross section (that is, echo height data at each position of a certain target cross section) using flaw detection data of a cross section in the vicinity of the target cross section. . Hereinafter, the processing procedure of the digital arithmetic processing performed in this embodiment will be described in detail.

  FIG. 11 is a flowchart illustrating a processing procedure of digital arithmetic processing performed in the present embodiment. In the present embodiment, after the threshold cut process (step S01) is performed, the above-described cross-section enhancement process is performed (step S11). Further, a B scope image is created from the flaw detection data that has been subjected to the cross-section enhancement processing (step S12). After that, as in the first embodiment, the defect image recognition (step S02), the definition of the rectangular area and the area representative point (step S04), the defect image identity determination (steps S05 and S06), and the defect The instruction length is calculated (step S07).

In the cross-section enhancement processing (step S11) of the present embodiment, as shown in FIG. 12, the flaw detection data of the cross-section i includes two cross-sections i-2, i-1 adjacent to the rear in the scanning direction, and Correction is performed using flaw detection data of cross sections i + 1 and i + 2 adjacent to the front in the scanning direction. Specifically, in the cross-section enhancement processing according to the present embodiment, the echo height data at a position where the cross section i exists is corrected to the maximum value of the echo height data at the same position of the five cross sections i−2 to i + 2. Is done. In this embodiment in which the focal row from which the A scope data is acquired is the same for all the cross sections, the echo height data H ′ _{i, j, k} of the path k of the focal row j of the cross section i after processing is as follows. Is represented as:
H ′ _{i, j, k} =
max [ _{Hi-2, j, k} , _{Hi-1, j, k} , _{Hi, j, k} , _{Hi + 1, j, k} , _{Hi + 2, j, k} ],
_{Here, max [x 1, x 2} , x 3, x 4, x 5] _is the maximum value of x 1 ~x _{5, H i, j, k} is the path length k of focal row j of section i The echo height.

  FIG. 13 is a graph showing a specific example of the cross-section enhancement processing. The upper part of FIG. 13 shows A scope data of the same focal row having the cross sections i−2 to i + 2, and the lower part shows A scope data of the focal row of the cross section i after the cross-section enhancement processing. . For example, the echo height of the path “4” in the section i-2 is “70”, and the echo height of the path “4” in the other sections i−1, i, i + 1, i + 2 is “0”. In this case, the data of the echo height of the path length “4” of the A-scope data of the focal low of the cross section i after the cross section enhancement processing is “70”. Similarly, the echo height of the path “5” in the cross section i−1 is “80”, and the echo height of the path “5” in the other cross sections i−2, i, i + 1, i + 2 is “0”. In some cases, the echo height data of the path length “5” of the A-scope data of the focal row of the cross section i after the cross section enhancement processing is “80”.

According to such cross-section enhancement processing, even if the echo height at a certain position of a target cross section is low, if the echo height at the same position of an adjacent cross section is high, the echo height at the position of the target cross section is high. The data is corrected to be higher. Therefore, even if the echo height of the target cross section is lowered due to a three-dimensional change in the shape of the defect, the defect image is not lost from the B scope image of the target cross section. This effectively prevents the defect image appearing in the cross sections i ₁ and i _{3 from} being recognized as two defects despite being caused by the single defect 25.

  In the cross-section enhancement processing, when the echo height at the same position in the cross sections i-2, i-1, i + 1, i + 2 is higher than the echo height at the position where the cross section i exists, the echo height at the corresponding position in the cross section i is set. Different processes may be performed as long as the data is corrected so that the data is increased. For example, the echo height data at a position of the cross section i is corrected to the average value only when the level is lower than the average value of the echo height data at the same position of the five cross sections i−2 to i + 2. It is also possible. However, the process of correcting the echo height data at a position of the cross section i to the maximum value of the echo height data at the same position of the five cross sections i−2 to i + 2 reduces the size of the defect. It is preferable in that it is not evaluated.

  In the cross-section enhancement processing of this embodiment, flaw detection data of two cross sections adjacent to the front in the scanning direction and two cross sections adjacent to the rear in the scanning direction are used for correcting the flaw detection data of the target cross section. It will be apparent to those skilled in the art that the number of cross sections used for correction can be changed as appropriate. The flaw detection data of n cross sections adjacent to the front in the scanning direction (n is an integer of 1 or more) and n cross sections adjacent to the rear in the scanning direction can be used for correcting the flaw detection data of the target cross section. is there.

  Further, only flaw detection data of only n cross sections adjacent to the front in the scanning direction are used for correcting the flaw detection data of the target cross section, and n cross sections adjacent to the rear in the scanning direction are not used for correcting the flaw detection data of the target cross section. It is also possible. Similarly, only flaw detection data of only n cross sections adjacent to the rear in the scanning direction is used for correcting the flaw detection data of the target cross section, and n cross sections adjacent to the front of the scanning direction are used for correcting the flaw detection data of the target cross section. It is also possible not to be. However, from the viewpoint of preventing the defect size from being evaluated smaller than the actual size, the cross section of n sheets (n is an integer of 1 or more) adjacent to the front in the scanning direction and n sheets adjacent to the rear in the scanning direction. It is preferred that both cross-section flaw detection data are used to correct the target cross-section flaw detection data.

  By performing the above-described cross section emphasis processing, it is possible to effectively avoid the defect image defect caused by the three-dimensional change in the defect shape, while the defect indication length in step S07 (the length in the scanning direction). ), The indicated length is measured longer than the actual length. For example, when the flaw detection data of two cross sections adjacent to the front in the scanning direction and two cross sections adjacent to the rear in the scanning direction are used for correcting flaw detection data of the target cross section, the instruction length is The measurement is longer than the actual length by four times the interval (that is, the length corresponding to the two cross-sections in the front and rear of the scanning direction).

In order to avoid such overestimation of the instruction length, it is preferable that the instruction length is corrected in step S07 according to the number of cross sections used for correcting the flaw detection data of the target cross section. For example, when flaw detection data of n cross sections adjacent to the front in the scanning direction (n is an integer of 1 or more) and n cross sections adjacent rearward in the scanning direction are used for correcting the flaw detection data of the target cross section. the instruction length L _d is preferably calculated based on the following formula:
L _d = (N−2n−1) · D,
Here, N is the number of cross sections in which defect images corresponding to the same defect appear continuously, and D is the distance between two adjacent cross sections.

Further, when only n cross sections adjacent to the front in the scanning direction are used for correcting the flaw detection data of the target cross section, and only n cross sections adjacent to the rear in the scanning direction are used for correcting the flaw detection data of the target cross section. If so, the indicated length L _d is preferably calculated based on the following formula:
L _d = (N−n−1) · D.

  The cross-section enhancement processing in step S11 can also be performed before the threshold cut processing in step S1. However, from the viewpoint of reducing the amount of calculation, it is more preferable that the cross-section enhancement processing in step S11 is performed after the threshold cut processing in step S01. When the cross-section enhancement processing is performed after the threshold cut processing, the echo of the position of the processing target (that is, the path length) is obtained for all the cross sections used for correcting the target cross section and the flaw detection data of the target cross section. When the height is 0, it is not necessary to calculate the maximum value for the position.

  In the above-described embodiment, scanning of the ultrasonic beam in the x-axis direction is performed by causing the probe 6 to function as a phased array. However, the probe 6 is mechanically moved in the x-axis direction. The flaw detection data may be acquired while scanning. It will be apparent to those skilled in the art that the present invention can be applied without depending on the scanning method of the ultrasonic beam.

FIG. 1 is a diagram showing the configuration of an automatic ultrasonic flaw detection system used in the first embodiment of the ultrasonic flaw detection data processing method according to the present invention. FIG. 2 is a conceptual diagram showing a procedure for acquiring flaw detection data by the automatic ultrasonic flaw detection system of FIG. FIG. 3 is a conceptual diagram showing a procedure for acquiring flaw detection data by the automatic ultrasonic flaw detection system of FIG. FIG. 4 is a conceptual diagram showing an example of a B scope image generated from flaw detection data. FIG. 5 is a conceptual diagram showing an example of A scope data included in flaw detection data. FIG. 6 is a flowchart showing a method of processing ultrasonic flaw detection data in the first embodiment. FIG. 7A is a diagram illustrating a method of determining a rectangular area and area representative points in a defect image. FIG. 7B is a diagram illustrating another method for determining a rectangular region and a region representative point in a defect image. FIG. 8 is a diagram illustrating processing for determining whether or not a plurality of defect images appearing on the same cross section are caused by the same defect. FIG. 9 is a diagram illustrating processing for determining whether or not a defect image appearing in an adjacent cross section is caused by the same defect. FIG. 10 is a diagram for explaining the reason why the defect images may not be correctly associated between adjacent cross sections when the defect extension direction changes three-dimensionally. FIG. 11 is a flowchart illustrating a method of processing ultrasonic flaw detection data according to the second embodiment. FIG. 12 is a diagram for explaining cross-section enhancement processing in the second embodiment. FIG. 13 is a graph for explaining cross-section enhancement processing in the second embodiment.

Explanation of symbols

1: Automatic ultrasonic flaw detection system 2: Subject 3, 4: Steel plate 5: Welded part 6: Probe 7: Scanning device 8: Control device 9: Display device 10: Computing device 11: Rail 12: Probe holding Mechanisms 13, 21: Defect image 22: Rectangular area 23: Area representative point 24: Echo peak area

Claims (5)

A processing method for processing flaw detection data obtained by ultrasonic flaw detection performed on a plurality of cross sections perpendicular to the scanning direction while scanning the probe along a predetermined scanning direction by digital arithmetic processing,
(A) recognizing a defect image corresponding to a defect present in a subject based on the flaw detection data, and determining a region representative point representing the position of the defect image for each of the defect images;
(B) determining whether one defect image of the defect images is caused by the same defect as another defect image from the distance between the region representative points;
The step (B)
(B1) A step of determining whether or not the two defect images are caused by the same defect from a distance between the region representative points of two defect images of the same cross section among the plurality of cross sections.
An ultrasonic flaw detection data processing method comprising: The ultrasonic flaw detection data processing method according to claim 1,
The step (A) includes:
(A1) defining a rectangular region so as to surround the defect image;
(A2) A method for processing ultrasonic flaw detection data, comprising: defining an intersection of diagonal lines of the rectangular area as the area representative point. The ultrasonic flaw detection data processing method according to claim 1,
The step (B)
(B2) The two defect images are caused by the same defect from the distance in the in-plane direction parallel to the plurality of cross sections between the region representative points of two defect images of different cross sections of the plurality of cross sections. A method for processing ultrasonic flaw detection data, comprising the step of determining whether or not to perform. A flaw detection data processing program for causing a computing device to process flaw detection data obtained by ultrasonic flaw detection performed on a plurality of cross sections perpendicular to the scanning direction while scanning a probe along a predetermined scanning direction. ,
(A) recognizing a defect image corresponding to a defect present in a subject based on the flaw detection data, and determining a region representative point representing the position of the defect image for each of the defect images;
(B) causing the arithmetic unit to execute a step of determining whether one defect image of the defect images is caused by the same defect as another defect image from the distance between the region representative points. ,
The step (B)
(B1) A step of determining whether or not the two defect images are caused by the same defect from a distance between the region representative points of two defect images of the same cross section among the plurality of cross sections.
A flaw detection data processing program comprising: A defect image corresponding to a defect present in the subject is obtained based on flaw detection data obtained by ultrasonic flaw detection performed on a plurality of cross sections perpendicular to the scan direction while scanning the probe along a predetermined scan direction. Means for recognizing and determining, for each of the defect images, an area representative point representing the position of the defect image;
From the distance between the area representative point of the two defects images of the same cross-section of the plurality of cross-sectional, the two defect image and means for determining whether caused by the same defect Ultrasonic flaw detection data processing device.

Images