DEFECT DETECTION APPARATUS, DEFECT DETECTION METHOD, AND PROGRAM

Abstract

To provide a mechanism which, when a plurality of defective portions is detected from a steel material produced by rolling, can discriminate whether or not the defective portion is generated from the defect of the same generation source in the steel material before rolling.SOLUTION: A plurality of defect parts 501 corresponding to a plurality of defects is extracted from a first binarized image (Fig. 5(c)) obtained by performing the binarization processing on a first image of which the amplitude of received ultrasonic waves is represented in a two-dimensional manner for each measuring point, and the defect parts 501 extracted from the first binarized image are connected by using a second image (FIG. 5 (b)) representing the depth from the surface of a steel material in the two-dimensional manner based on a path of the received ultrasonic wave at each measurement point to define defected areas 502.SELECTED DRAWING: Figure 5

Description

[Technical field]

[0001] The present invention relates to a defect detection device and a defect detection method for detecting defects in a steel material produced by rolling, and a program for causing a computer to execute the defect detection method. [Background technology]

[0002] Conventionally, a method has been proposed for detecting defects in steel materials produced by rolling using ultrasonic waves (for example, see Patent Document 1). Specifically, Patent Document 1 describes a technology in which ultrasonic waves are propagated in the width direction of the material to be detected, which is perpendicular to the direction in which an ultrasonic probe is moved relative to the material to be detected, and defects present in the material to be detected are detected using a two-dimensional image based on the reflected waves. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Publication No. 9-15218 Summary of the Invention [Problem to be solved by the invention]

[0004] For example, in steel produced by rolling, defects that existed in the pre-rolled steel before the rolling (such as inclusions mixed in at the steelmaking stage) are stretched by the rolling, and may exist not only as a uniformly elongated linear defect portion but also as multiple broken defect portions. Therefore, being able to estimate the size of defects that existed in the pre-rolled steel is very useful in reviewing and improving the operating conditions of steelmaking.

[0005] In this regard, the technology described in the above-mentioned Patent Document 1 does not assume any discrimination as to whether or not a plurality of defect portions detected in a steel material produced by rolling are caused by defects of the same source in the pre-rolled steel material before the rolling is performed. Therefore, with the technology described in the above-mentioned Patent Document 1, it is difficult to estimate the size of defects that existed in the pre-rolled steel material.

[0006] The present invention has been made in consideration of such problems, and aims to provide a mechanism that, when multiple defects are detected in a steel material produced by rolling, can determine whether or not the defects arise from the same source in the steel material before rolling. [Means for solving the problem]

[0007] The defect detection device of the present invention is a defect detection device that detects defects in steel material manufactured by rolling, and includes: a transmission / reception means for transmitting and receiving ultrasonic waves between each measurement point set in a two-dimensional manner on the surface of the steel material via the ultrasonic probe when a two-dimensional scan is performed by moving the ultrasonic probe relative to each of the measurement points set in a two-dimensional manner on the surface of the steel material; a first image generation means for generating a first image that represents, in the two-dimensional form, the magnitude of amplitude of received ultrasonic waves, which are ultrasonic waves received by the transmission / reception means during a defect detection period for each of the measurement points; a second image generation means for generating, in the two-dimensional form, a second image that represents, in the first image, the depth from the surface of the steel material based on the path distance of the received ultrasonic waves using the magnitude of the amplitude; a binarization processing means for binarizing the first image to obtain a first binary image; a defect portion extraction means for extracting from the first binary image a plurality of defect portions corresponding to a plurality of the defects; and a defect area definition means for defining a defect area by connecting the defect portions using the second image. The present invention also includes a defect detection method using the above-mentioned defect detection device, and a program for causing a computer to execute the defect detection method. Effect of the Invention

[0008] According to the present invention, when multiple defects are detected in a steel product produced by rolling, it is possible to determine whether or not the defects originate from the same source in the steel product before rolling. This makes it possible to estimate the size of the defects that existed in the steel product before rolling, and as a result, it becomes possible to review and improve the operating conditions of the steelmaking process. [Brief description of the drawings]

[0009] [Figure 1] 1 is a diagram showing an example of a schematic configuration of a defect detection apparatus according to an embodiment of the present invention; [Diagram 2] FIG. 2 is a diagram showing an example of ultrasonic waveform data showing three patterns of ultrasonic waves directed from the ultrasonic probe to the steel material shown in FIG. 1 and ultrasonic waves directed from the steel material to the ultrasonic probe, and showing the amplitudes of ultrasonic waves related to the three patterns in a time series. [Diagram 3] FIG. 2 is a diagram showing an example of processing in which a scanning device two-dimensionally scans an ultrasonic probe at each measurement point set two-dimensionally on a surface of a steel material in a defect detection device according to an embodiment of the present invention. [Figure 4] 4 is a flowchart showing a first example of a processing procedure of a defect detection method performed by the defect detection device according to the embodiment of the present invention. [Diagram 5] 5A to 5C are diagrams for explaining a process of a defect detection method performed by the defect detection device according to the embodiment of the present invention. [Figure 6] 5 is a flowchart showing a second example of a processing procedure of a defect detection method performed by the defect detection device according to the embodiment of the present invention. [Figure 7] 7 is a diagram for explaining the process of defining a defective area in step S201 of FIG. 6. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0010] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, an embodiment of the present invention will be described with reference to the drawings.

[0011] Fig. 1 is a diagram showing an example of a schematic configuration of a defect detection device 100 according to an embodiment of the present invention. This defect detection device 100 is a device that detects defects 201 (for example, inclusions mixed in at the steelmaking stage) in a steel material 200 manufactured by rolling. More specifically, the defect detection device 100 is a device that inspects the presence or absence of defects 201 at each of measurement points 211-0 to 211-N set two-dimensionally (in the example shown in Fig. 1, in the X direction and the Y direction) on a surface 210 of the steel material while performing two-dimensional scanning by moving an ultrasonic probe 110 relatively to each of the measurement points 211-0 to 211-N.

[0012] The defect 201 shown in FIG. 1 is merely an example, and the size and shape of the defect are arbitrary. FIG. 1 also illustrates a surface 210 of the steel material and a back surface 220 of the steel material that constitute the interface of the steel material 200. In the example shown in FIG. 1, the thickness D of the steel material 200 is determined by the length between the surface 210 of the steel material and the back surface 220 of the steel material. As shown in FIG. 1, the back surface 220 of the steel material is a surface that faces the surface 210 of the steel material. FIG. 1 also illustrates an XYZ coordinate system consisting of mutually orthogonal X and Y directions that determine the surface 210 of the steel material and the back surface 220 of the steel material, and a Z direction that is orthogonal to the X and Y directions and indicates the direction of the thickness D of the steel material 200.

[0013] As shown in FIG. 1, the defect detection device 100 is configured to include an ultrasonic probe 110, an ultrasonic transmitting / receiving device 120, a scanning device 130, a control / processing device 140, an information input device 150, a storage device 160, and a display device 170.

[0014] The ultrasonic probe 110, in the cross section of the steel material 200 shown in Fig. 1, performs scanning by moving sequentially over each of the measurement points 211-0 to 211-N on the surface 210 of the steel material through processing by the scanning device 130, and transmits and receives ultrasonic waves at each of the measurement points 211-0 to 211-N. Note that, for the sake of simplicity, Fig. 1 shows an example in which one ultrasonic probe 110 is provided, but a form in which multiple ultrasonic probes 110 are provided, for example, to improve inspection efficiency, is also applicable to the present invention.

[0015] The ultrasonic transmitting / receiving device 120 transmits and receives ultrasonic waves to and from the steel material 200 via the ultrasonic probe 110 under the control of the control and processing device 140. The ultrasonic transmitting / receiving device 120 includes a transmitting section 121 and a receiving section 122.

[0016] The transmitting unit 121, under the control of the control and processing device 140, performs a process of transmitting ultrasonic waves 111 via the ultrasonic probe 110 which moves relatively to the steel material 200 at each of the measurement points 211-0 to 222-N on the steel material surface 210. Also, under the control of the control and processing device 140, the receiving unit 122 performs a process of receiving ultrasonic waves 112 from the steel material 200 via the ultrasonic probe 110 for each of the measurement points 211-0 to 222-N on the steel material surface 210.

[0017] The scanning device 130 performs scanning by sequentially moving the ultrasonic probe 110 to each of the measurement points 211-0 to 211-N on the steel surface 210 under the control of the control and processing device 140. Fig. 1 shows an example in which the scanning device 130 performs scanning by moving the ultrasonic probe 110 in a scanning direction (main scanning direction) 131, which is the X direction. In the example shown in Fig. 1, the ultrasonic probe 110 scans in the order of measurement point 211-0, measurement point 211-1, measurement point 211-2, measurement point 211-3, measurement point 211-4, measurement point 211-5, measurement point 211-6, measurement point 211-7, measurement point 211-8, ..., measurement point 211-N. In this case, the numbers (0, 1, 2, 3, 4, 5, 6, 7, 8,..., N) added with "-" after each measurement point 211 shown in Fig. 1 correspond to the numbers indicating the ascending order of scanning. In this case, in the example shown in Fig. 1, N is an integer greater than 8, but this is not limited to this in this embodiment, and for example, in the case shown in Fig. 1, any number other than 0 (i.e., any integer greater than or equal to 1) is applicable to this embodiment.

[0018] 1 shows an example of relatively moving the ultrasonic probe 110 and the steel material 200 in which the scanning device 130 moves the ultrasonic probe 110 relative to each of the measurement points 211-0 to 211-N on the surface 210 of the steel material, but the present invention is not limited to this form. For example, a form in which the scanning device 130 moves the steel material 200 while the ultrasonic probe 110 is stationary, thereby relatively moving the ultrasonic probe 110 and the steel material 200, is also applicable to the present invention.

[0019] The control and processing device 140 controls each component of the defect detection device 100 based on input information input from, for example, an information input device 150, and generally controls the operation of the defect detection device 100. The control and processing device 140 also performs various processes based on input information input from, for example, the information input device 150. As shown in Fig. 1, the control and processing device 140 is configured to include a first image generating section 141, a second image generating section 142, a binarization processing section 143, a defective portion extracting section 144, a linear defective portion identifying section 145, a defective area defining section 146, a defect size estimating section 147, and a display control section 148. The components 141 to 148 in the control and processing device 140 will be described later.

[0020] The information input device 150 inputs, for example, input information operated and input by a user to the control and processing device 140 .

[0021] The storage device 160 stores various types of information, various types of data, programs, etc. used by the control / processing device 140, as well as various types of information, various types of data, etc. obtained by processing by the control / processing device 140.

[0022] The display device 170 displays various types of information, various types of data, and the like under the control of the control and processing device 140 .

[0023] Fig. 2 is a diagram showing three patterns of ultrasonic waves 111 directed from the ultrasonic probe 110 to the steel material 200 and ultrasonic waves 112 directed from the steel material 200 to the ultrasonic probe 110 shown in Fig. 1, and an example of ultrasonic waveform data showing the amplitude of the ultrasonic waves 112 related to the three patterns in a time series. In Fig. 2, the same reference numerals are used for configurations similar to those shown in Fig. 1.

[0024] Specifically, first, Fig. 2(a) shows three patterns of ultrasonic waves 111 traveling from the ultrasonic probe 110 to the steel material 200 shown in Fig. 1 and ultrasonic waves 112 traveling from the steel material 200 to the ultrasonic probe 110. The first pattern shown on the left side of Fig. 2(a) shows how the ultrasonic waves 111 traveling from the ultrasonic probe 110 to the steel material 200 are reflected by the surface 210 of the steel material and travel as surface-reflected ultrasonic waves 112-S to the ultrasonic probe 110. The second pattern shown in the center of Fig. 2(a) shows how the ultrasonic waves 111 traveling from the ultrasonic probe 110 to the steel material 200 pass through the surface 210 of the steel material, are reflected by a defect 201 inside the steel material 200, and travel as defect-reflected ultrasonic waves 112-F to the ultrasonic probe 110. Furthermore, the third pattern shown on the right side of Figure 2(a) shows how ultrasonic waves 111 traveling from the ultrasonic probe 110 toward the steel material 200 pass through the front surface 210 of the steel material, are reflected by the back surface 220 of the steel material, and travel toward the ultrasonic probe 110 as back surface reflected ultrasonic waves 112-B.

[0025] FIG. 2(b) shows an example of ultrasonic waveform data showing the amplitudes of the surface reflected ultrasonic wave 112-S, the defect reflected ultrasonic wave 112-F, and the back surface reflected ultrasonic wave 112-B shown in FIG. 2(a) in a time series. In FIG. 2(b), the surface reflected ultrasonic wave 112-S shown in FIG. 2(a) is shown as an S echo, the defect reflected ultrasonic wave 112-F is shown as an F echo, and the back surface reflected ultrasonic wave 112-B is shown as a B echo, showing an example of their waveforms. In this embodiment, the time shown on the horizontal axis of the ultrasonic waveform data shown in FIG. 2(b) indicates, for example, the elapsed time since the reception process was started by the receiving unit 122. In this embodiment, the amplitude shown on the vertical axis of the ultrasonic waveform data shown in FIG. 2(b) indicates, for example, a negative amplitude value below the center (0) and a positive amplitude value above the center (0). 2(b), the surface reflected ultrasonic waves 112-S, the defect reflected ultrasonic waves 112-F, and the back surface reflected ultrasonic waves 112-B are received at different times by the receiving unit 122. This is because the surface reflected ultrasonic waves 112-S, the defect reflected ultrasonic waves 112-F, and the back surface reflected ultrasonic waves 112-B have different path lengths (propagation distances) until they reach the ultrasonic probe 110, as shown in FIG.

[0026] For the ultrasonic waveform data shown in Fig. 2(b), the control and processing device 140 sets, for example, a threshold value 1401 for detecting the surface reflected ultrasonic wave 112-S, and in the example shown in Fig. 2(b), the time TS at which the surface reflected ultrasonic wave 112-S first becomes equal to or greater than the threshold value 1401 is set as the reception time of the surface reflected ultrasonic wave 112-S. In the example shown in Fig. 2(b), this time TS is the time that a time T2 has elapsed since the time at which the reception process was started in the receiving unit 122. Then, the control and processing device 140 sets, for example, the period from time Tfs to time Tfe as the defect detection period for detecting the defect reflected ultrasonic wave 112-F based on the defect 201, taking into consideration the period until the surface reflected ultrasonic wave 112-S settles down and becomes stable and the period before the back surface reflected ultrasonic wave 112-B is detected. The defect detection period from time Tfs to time Tfe is appropriately set in consideration of the time from when the ultrasonic wave 111 transmitted from the ultrasonic probe 110 is incident on the front surface 210 of the steel material, to when it propagates in the Z direction inside the steel material 200, is reflected by the back surface 220 of the steel material, and returns to the front surface 210 of the steel material again. Furthermore, the control and processing device 140 sets a threshold value 1402 for detecting defect reflected ultrasonic waves 112-F during the defect detection period from time Tfs to time Tfe. Then, when there is a defect reflected ultrasonic wave 112-F that is equal to or greater than the threshold value 1402 as shown by the dotted line in FIG. 2(b) during the defect detection period from time Tfs to time Tfe, the control and processing device 140 determines that there is a defect 201 inside the steel material 200 at the measurement point 211. Furthermore, if there is no defect reflected ultrasonic wave 112-F that is equal to or greater than the threshold value 1402, as shown by the dotted line in Figure 2(b), during the defect detection period from time Tfs to time Tfe, the control and processing device 140 determines that there is no defect 201 inside the steel material 200 at the measurement point 211.

[0027] Furthermore, when the control and processing device 140 determines that there is a defect 201 inside the steel material 200, it sets, for example, the time TF at which the magnitude of the defect reflected ultrasonic wave 112-F reaches a maximum value Amax as the reception time of the defect reflected ultrasonic wave 112-F. This time TF is the time that a time T1 has elapsed from the time that the reception process was started by the receiving unit 122. Also, this time TF is the time that a time T3 (T3 = T1 - T2) has elapsed from the reception time TS of the surface reflected ultrasonic wave 112-S. In this case, the depth ds from the surface 210 of the steel material shown in Figure 2 (a) to the defect 201 can be expressed by the following equation (1), where Vu is the speed of the ultrasonic wave propagating inside the steel material 200. ds = (Vu × T3) ÷ 2 (1)

[0028] Next, a process example in which the ultrasonic probe 110 is caused to two-dimensionally scan each of the measurement points 211 set two-dimensionally on the surface 210 of the steel material will be described. Fig. 3 is a diagram showing a processing example in which the ultrasonic probe 110 is two-dimensionally scanned by the scanning device 130 at each measurement point 211 set two-dimensionally on the surface 210 of a steel material in the defect detection device 100 according to the embodiment of the present invention. In Fig. 3, the same components as those shown in Fig. 1 are given the same reference numerals. Fig. 3 also shows a schematic diagram of the surface 210 of the steel material as seen from above, and further shows an XYZ coordinate system corresponding to the XYZ coordinate system shown in Fig. 1.

[0029] 3, the defect detection device 100 according to this embodiment performs (M+1) times scanning with one scanning line whose scanning direction 131 is the X direction described with reference to FIG. 1, to two-dimensionally scan each measurement point 211 set two-dimensionally on the surface 210 of the steel material. In this case, the numbers (0, 1, 2, 3, 4, 5, . . . , M) in the squares arranged on the left side of FIG. 3 correspond to the numbers indicating the order in which scanning with each scanning line is performed in ascending order. When performing the two-dimensional scan shown in Fig. 3, the scanner 130 first performs scanning by sequentially moving the ultrasonic probe 110 to each of the measurement points 211-0 to 211-N on the surface 210 of the steel material along the scanning line marked with "0" in the square on the left side of Fig. 3, then moves the ultrasonic probe 110 in the Y direction as the movement direction (sub-scanning direction) 132 to the start position of the next scanning line, and then performs scanning by sequentially moving the ultrasonic probe 110 to each of the measurement points 211-0 to 211-N on the surface 210 of the steel material along the scanning line marked with "1" in the square on the left side of Fig. 3. Thereafter, similarly, scanning is performed by sequentially moving the ultrasonic probe 110 to each of the measurement points 211-0 to 211-N on the surface 210 of the steel material up to the scanning line marked with "M" in the square on the left side of Fig. 3. In this embodiment, the interval between each measurement point 211 is dx, and the interval between each scan line is dy, as shown in Fig. 3. In this case, if an arbitrary measurement point 211 among the measurement points 211-0 to 211-N is i, and an arbitrary scan line among the scan lines 0 to M is j, then, for example, an arbitrary measurement point 211 shown in Fig. 3 can be expressed as p(xi, yj) (where xi=i·dx, yj=j·dy).

[0030] Next, the components 141 to 148 in the control / processing device 140 shown in FIG. 1 will be described with reference to the flowchart shown in FIG.

[0031] FIG. 4 is a flowchart showing a first example of a processing procedure of a defect detection method performed by the defect detection apparatus 100 according to the embodiment of the present invention.

[0032] First, in step S101 of FIG. 4, the ultrasonic transmission / reception device 120 shown in FIG. 1 transmits and receives ultrasonic waves via the ultrasonic probe 110 between each measurement point 211 set two-dimensionally on the surface 210 of the steel material as shown in FIG. 3, for example (i.e., transmits ultrasonic waves 111 from the transmitting unit 121 and receives ultrasonic waves 112 at the receiving unit 122).

[0033] Next, in step S102 of FIG. 4, the first image generating unit 141 shown in FIG. 1 generates a first image (echo height image) that represents, two-dimensionally in the X direction and the Y direction, the magnitude of the amplitude of the received ultrasonic waves, which are ultrasonic waves received by the ultrasonic transmitting / receiving device 120 (receiving unit 122) during the defect detection period from time Tfs to time Tfe shown in FIG. 2(b), for each measurement point 211 set two-dimensionally on the surface 210 of the steel material.

[0034] FIG. 5 is a diagram for explaining the process of the defect detection method by the defect detection device 100 according to the embodiment of the present invention. Specifically, in step S102 in FIG. 4, a first image shown in FIG. 5(a) is generated. In FIG. 5(a), the X direction and the Y direction correspond to the X direction and the Y direction shown in FIG. 3, respectively. The first image shown in FIG. 5(a) is an image that two-dimensionally represents the amplitude of the received ultrasonic wave (here, for example, the maximum amplitude Amax is used) in the defect detection period from time Tfs to time Tfe shown in FIG. 2(b) for each measurement point 211 shown in FIG. 3 in the X direction and the Y direction. More specifically, the first image shown in FIG. 5(a) shows that the white color becomes stronger as the amplitude of the received ultrasonic wave becomes larger.

[0035] Next, in step S103 of FIG. 4, the second image generating unit 142 shown in FIG. 1 generates a second image (depth image) that represents the depth ds from the surface 210 of the steel material based on the path length of the received ultrasonic wave using the magnitude of the amplitude in the first image generated in step S102, two-dimensionally in the X and Y directions.

[0036] Specifically, in step S103 in FIG. 4, a second image shown in FIG. 5(b) is generated. In FIG. 5(b), the X direction and the Y direction correspond to the X direction and the Y direction shown in FIG. 3, respectively. The second image shown in FIG. 5(b) is an image that represents, in a two-dimensional form in the X direction and the Y direction, the depth ds from the surface 210 of the steel material based on the path length of the received ultrasonic wave related to the maximum amplitude Amax during the defect detection period from time Tfs to time Tfe shown in FIG. 2(b) for each measurement point 211 shown in FIG. 3. More specifically, in the second image shown in FIG. 5(b), the same color is applied to the depths ds from the surface 210 of the steel material within a predetermined range that can be considered to be approximately the same (for example, within a range of ±0.02 mm when the thickness D of the steel material is 2 mm).

[0037] Next, in step S104 of FIG. 4, the binarization processing unit 143 shown in FIG. 1 binarizes the first image generated in step S102 to obtain a first binarized image (an echo height image subjected to binarization processing).

[0038] Specifically, in step S104 in Fig. 4, a first binarized image shown in Fig. 5(c) is obtained. The first binarized image shown in Fig. 5(c) is an image obtained by binarizing the first image shown in Fig. 5(a) using the threshold value 1402 shown in Fig. 2(b). More specifically, in the first binarized image shown in Fig. 5(c), the positions of the measurement points 211 that have received received ultrasonic waves whose amplitudes (for example, the maximum amplitude Amax is used here) exceed the threshold value 1402 are shown in white, and the positions of the measurement points 211 that have received received ultrasonic waves whose amplitudes (for example, the maximum amplitude Amax is used here) do not exceed the threshold value 1402 are shown in black.

[0039] Subsequently, in step S105 of FIG. 4, the defect portion extracting section 144 shown in FIG. 1 extracts a plurality of defect portions corresponding to the plurality of defects 201 from the first binarized image acquired in step S104.

[0040] Specifically, in step S105 of Fig. 4, a plurality of defect portions 501-1 to 501-8 corresponding to a plurality of defects 201 are extracted from the first binarized image shown in Fig. 5(c). Each of the defect portions 501 among the plurality of defect portions 501-1 to 501-8 shown in Fig. 5(c) is a portion consisting of a continuous block of white area.

[0041] Next, in step S106 of FIG. 4, the linear defect site identification unit 145 shown in FIG. 1 identifies a linear defect site from among the multiple defect sites extracted in step S105 based on the length ratio between the length in a two-dimensional first direction at each of the multiple defect sites extracted in step S105 and the length in a second direction perpendicular to the first direction.

[0042] Specifically, the process of step S106 in FIG. 4 will be described with reference to FIG. 5(d). In Fig. 5(d), one defect portion extracted in step S105 is illustrated as a defect portion 501. Then, in step S106 in Fig. 4, a linear defect portion is identified from among the multiple defect portions 501-1 to 501-8 extracted in step S105 based on the length ratio between the length Lx of the defect portion 501 in the two-dimensional X direction (first direction) and the length Ly of the defect portion 501 in the Y direction (second direction) perpendicular to the X direction. Here, in this embodiment, the defect portion 501 in which the length ratio Rl (Rl = Ly / Lx) of the length Lx to the length Ly of the defect portion 501 is 0.2 or less is identified as the linear defect portion. Specifically, the example shown in FIG. 5(c) shows a case in which, among multiple defect portions 501-1 to 501-8, defect portion 501-1, defect portions 501-3 to 501-6, and defect portion 501-8 are identified as linear defect portions, and defect portion 501-2 and defect portion 501-7 are not identified as linear defect portions (for example, are identified as point defect portions).

[0043] Next, in step S107 of Fig. 4, the defect area defining unit 146 shown in Fig. 1 defines a defect area by connecting the defect sites extracted in step S105 using the second image generated in step S103. More specifically, in step S107 of Fig. 4, the defect area defining unit 146 shown in Fig. 1 defines a defect area by connecting the linear defect sites identified in step S106 using the second image generated in step S103.

[0044] Specifically, the process of step S107 in FIG. 4 will be described with reference to FIG. Fig. 5(e) shows an image that is the same as the first binarized image shown in Fig. 5(c). In the example shown in Fig. 5(c), as described above in the description of the process of step S106, among the plurality of defect parts 501-1 to 501-8, the defect parts 501-1, 501-3 to 501-6, and 501-8 are specified as linear defect parts. The corresponding positions in the region 510 of the second image shown in Fig. 5(b), where these linear defect parts 501-1, 501-3 to 501-6, and 501-8 are located, are given the same color indicating that the depths ds from the surface 210 of the steel material are within a predetermined range that can be considered to be approximately the same (for example, within a range of ±0.02 mm when the thickness D of the steel material is 2 mm). For this reason, in step S106 in Fig. 4, the defect area demarcation unit 146 shown in Fig. 1 uses the second image shown in Fig. 5(b) to connect linear defect sites 501-3 to 501-6 that belong within a predetermined range in which the depths ds from the surface 210 of the steel material can be considered to be approximately the same, as shown in Fig. 5(e), and defines this as one defect area 502-3. Here, in this embodiment, the defect area 502-3 shown in Fig. 5(e) refers to a rectangular area circumscribing a "connected defect" created by connecting linear defect sites 501-3 to 501-6 that belong within a predetermined range in which the depths ds from the surface 210 of the steel material can be considered to be approximately the same. In the example shown in FIG. 5(e), defect area definition unit 146 shown in FIG. 1 defines defect portion (linear defect portion) 501-1 as one defect area 502-1, defines defect portion 501-2 as one defect area 502-2, defines defect portion 501-7 as one defect area 502-4, and further defines defect portion (linear defect portion) 501-8 as one defect area 502-5.

[0045] Next, in step S108 of Figure 4, the defect size estimation unit 147 shown in Figure 1 estimates the size of the defect that existed in the pre-rolled steel material before rolling, using the length in the rolling direction of the defect area defined in step S107 and the rolling ratio of the steel material 200.

[0046] Specifically, the process of step S108 in FIG. 4 will be described with reference to FIG. 5(d). Here, in Fig. 5(d), one defect area defined in step S107 is illustrated as a defect area 502. Here, in this embodiment, the rolling direction of the steel material 200 is the X direction, and the length of the defect area 502 shown in Fig. 5(d) in the rolling direction is a length Lx. Then, using the rolling ratio Rr of the steel material 200 (Rr = thickness of the steel material before rolling / thickness of the steel material 200 produced by rolling), the defect size estimation unit 147 shown in Fig. 1 estimates the size Sf of the defect that existed in the pre-rolled steel material before rolling according to the following formula (2). Sf = Lx ÷ Rr (2)

[0047] In this embodiment, when there are multiple defect areas 502 defined in step S107 of FIG. 4, the defect size estimation unit 147 shown in FIG. 1 estimates the size Sf of the defect that existed in the pre-rolled steel material for each defect area 502.

[0048] Next, in step S109 of FIG. 4, the display control unit 148 shown in FIG. 1 controls the display device 170 to display the defect area defined in step S107 (for example, the image shown in FIG. 5(e)) and the size Sf of the defect that existed in the pre-rolled steel material estimated in step S108.

[0049] When the process of step S109 in FIG. 4 ends, the process of the flowchart shown in FIG. 4 ends.

[0050] In the process of the flowchart shown in Fig. 4, in order to reduce the load of image processing, etc., in step S106, linear defect portions are specified from among the defect portions 501 extracted in step S105, and the linear defect portions are connected using the second image to define the defect area 502. However, this embodiment is not limited to this embodiment, and for example, a mode in which the defect portions 501 extracted in step S105 are connected using the second image to define the defect area 502 without performing the process of specifying linear defect portions in step S106 is also applicable to this embodiment. Hereinafter, this mode will be described with reference to Figs. 6 and 7.

[0051] FIG. 6 is a flowchart showing a second example of the processing procedure of the defect detection method by the defect detection apparatus 100 according to the embodiment of the present invention.

[0052] In the process of the second example flowchart shown in Fig. 6, first, the process goes through steps S101 to S105 in Fig. 4. As a result, a plurality of defect portions corresponding to the plurality of defects 201 are extracted from the first binarized image acquired in step S104. Specifically, a plurality of defect portions 501-1 to 501-8 corresponding to the plurality of defects 201 are extracted from the first binarized image shown in Fig. 5(c).

[0053] Next, in step S201 of FIG. 6, the defect area defining section 146 shown in FIG. 1 defines a defect area by connecting the defect sites extracted in step S105 using the second image generated in step S103.

[0054] FIG. 7 is a diagram for explaining the process of demarcating the defect area in step S201 in FIG. 6. FIG. 7 shows the same image as the first binarized image shown in FIG. 5(c). The corresponding positions in the region 510 of the second image shown in FIG. 5(b), where the defect parts 501-1 to 501-8 shown in FIG. 5(c) are located, are colored with the same color to indicate that the depth ds from the surface 210 of the steel material is within a predetermined range that can be considered to be approximately the same (for example, within a range of ±0.02 mm when the thickness D of the steel material is 2 mm). Therefore, in step S201 in FIG. 6, the defect area demarcating unit 146 shown in FIG. 1 uses the second image shown in FIG. 5(b) to connect the defect parts 501-1 to 501-8 that belong within a predetermined range that can be considered to be approximately the same in the depth ds from the surface 210 of the steel material, as shown in FIG. 7, and defines this as one defect area 502. Here, in this embodiment, the defect area 502 shown in Figure 7 refers to a rectangular area circumscribing a "connected defect" created by connecting defect sites 501-1 to 501-8 that belong within a predetermined range and whose depth ds from the surface 210 of the steel material can be considered to be approximately the same.

[0055] Next, in step S202 in Fig. 6, the defect size estimation unit 147 shown in Fig. 1 estimates the size of the defect that existed in the pre-rolled steel material before rolling, using the length in the rolling direction of the defect area defined in step S201 and the rolling ratio of the steel material 200. The defect size estimation process in step S202 in Fig. 6 is basically the same as the process described in step S108 in Fig. 4, so a detailed description thereof will be omitted.

[0056] Next, in step S203 of FIG. 6, the display control unit 148 shown in FIG. 1 controls the display device 170 to display the defect area defined in step S201 (e.g., the image shown in FIG. 7) and the size Sf of the defect that existed in the pre-rolled steel material estimated in step S202.

[0057] When the process of step S203 in FIG. 6 ends, the process of the flowchart shown in FIG. 6 ends.

[0058] According to the defect detection device 100 of the present embodiment described above, the defect area is defined by connecting the defect sites extracted from the first binarized image using the second image that two-dimensionally represents the depth ds from the surface 210 of the steel material based on the path length of the received ultrasonic waves, so that when a plurality of defect sites are detected in the steel material 200 manufactured by rolling, it is possible to determine whether or not they are caused by defects of the same source in the steel material before rolling. This makes it possible to estimate the size of the defect that existed in the steel material before rolling, and as a result, it becomes possible to review and improve the operating conditions of the steelmaking process.

[0059] (Other embodiments) As another embodiment, the present invention also includes a form in which software (program) for executing the processing of the flowcharts shown in Figures 4 and 6 is supplied to a system or device via a network or various storage media, and the computer (or CPU, MPU, etc.) of the system or device reads and executes the program. In addition, this program and a computer-readable storage medium storing the program are also included in the present invention.

[0060] It should be noted that the above-mentioned embodiments of the present invention are merely illustrative examples of the implementation of the present invention, and the technical scope of the present invention should not be interpreted as being limited by these. In other words, the present invention can be implemented in various forms without departing from its technical concept or main features. [Explanation of symbols]

[0061] 100: defect detection device, 110: ultrasonic probe, 120: ultrasonic transmission / reception device, 121: transmission section, 122: reception section, scanning device 130, control / processing device 140, 141: first image generation section, 142: second image generation section, 143: binarization processing section, 144: defect portion extraction section, 145: linear defect portion identification section, 146: defect area definition section, 147: defect size estimation section, 148: display control section, 150: information input device, 160: storage device, 170: display device, 200: steel material, 201: defect, 210: surface of steel material, 211-0 to 211-N: measurement points, 220: back surface of steel material, 501: defect portion, 502: defect area

Claims

1. A defect detection device for detecting defects in a steel material produced by rolling, comprising: a transmitting / receiving means for transmitting and receiving ultrasonic waves between each of the measurement points set two-dimensionally on the surface of the steel material through the ultrasonic probe when two-dimensional scanning is performed by moving the ultrasonic probe relative to each of the measurement points; a first image generating means for generating a first image that two-dimensionally represents the magnitude of the amplitude of a received ultrasonic wave, which is an ultrasonic wave received by the transmitting / receiving means during a defect detection period for each of the measurement points; a second image generating means for generating a second image in which a depth from a surface of the steel material based on a path length of the received ultrasonic wave using the magnitude of the amplitude in the first image is represented in the two-dimensional form; a binarization processing means for binarizing the first image to obtain a first binary image; a defect portion extracting means for extracting a plurality of defect portions corresponding to a plurality of the defects from the first binarized image; a defect area defining means for defining a defect area by connecting the defect sites using the second image; A defect detection device comprising:

2. The defect detection device described in claim 1, characterized in that the defect area definition means uses the second image to connect the defect areas that belong within a predetermined range in which the depth from the surface of the steel material can be considered to be approximately the same, thereby defining the defect area.

3. a linear defect portion specifying means for specifying a linear defect portion from among the plurality of defect portions based on a length ratio between a length in the two-dimensional first direction and a length in a second direction perpendicular to the first direction at each of the plurality of defect portions extracted by the defect portion extracting means, 3. The defect detection device according to claim 1, wherein the defect area defining means defines the defect area by connecting the linear defect sites using the second image.

4. A defect detection device as described in any one of claims 1 to 3, further comprising a defect size estimation means for estimating the size of a defect that existed in the pre-rolled steel material before the rolling using the length in the rolling direction of the defect area defined by the defect area definition means and the rolling ratio of the steel material.

5. 5. The defect detection apparatus according to claim 1, further comprising display control means for causing a display device to display the defect area defined by the defect area defining means.

6. A defect detection method using a defect detection device that detects defects in a steel material manufactured by rolling, comprising the steps of: a transmitting / receiving step of transmitting ultrasonic waves to and from each of the measurement points set two-dimensionally on the surface of the steel material via the ultrasonic probe while two-dimensional scanning is being performed by moving the ultrasonic probe relative to each of the measurement points; a first image generating step of generating a first image in which the magnitude of the amplitude of the received ultrasonic wave, which is the ultrasonic wave received during the defect detection period in the transmitting and receiving step, is represented in the two-dimensional form for each of the measurement points; a second image generating step of generating a second image in which a depth from a surface of the steel material based on a path length of the received ultrasonic wave using the magnitude of the amplitude in the first image is represented in the two-dimensional form; a binarization step of binarizing the first image to obtain a first binary image; a defect portion extraction step of extracting a plurality of defect portions corresponding to a plurality of the defects from the first binarized image; a defect area defining step of defining a defect area by connecting the defect sites using the second image; A defect detection method comprising the steps of:

7. A program for causing a computer to execute a defect detection method using a defect detection device for detecting defects in a steel material manufactured by rolling, comprising: a transmitting / receiving step of transmitting ultrasonic waves to and from each of the measurement points set two-dimensionally on the surface of the steel material via the ultrasonic probe while two-dimensional scanning is being performed by moving the ultrasonic probe relative to each of the measurement points; a first image generating step of generating a first image in which the magnitude of the amplitude of the received ultrasonic wave, which is the ultrasonic wave received during the defect detection period in the transmitting and receiving step, is represented in the two-dimensional form for each of the measurement points; a second image generating step of generating a second image in which a depth from a surface of the steel material based on a path length of the received ultrasonic wave using the magnitude of the amplitude in the first image is represented in the two-dimensional form; a binarization step of binarizing the first image to obtain a first binary image; a defect portion extraction step of extracting a plurality of defect portions corresponding to a plurality of the defects from the first binarized image; a defect area defining step of defining a defect area by connecting the defect sites using the second image; A program for causing a computer to execute the following.

Images