A seamless steel pipe diameter measurement and surface defect detection system

Abstract

The present invention relates to a seamless steel pipe diameter measurement and surface defect detection system, which system includes a bench, a first guide rail, a first strip light source, a second strip light source, a parallel light source, a area array camera, a second guide rail, an auxiliary rotating shaft, a driving rotating shaft, a display screen, an image processing device and a motor. The image processing device counts a first reference number, a second reference number, a first reference total number N1 of multiple imaginary marking lines and a second reference total number N2 of multiple imaginary marking lines. The first reference total number is the sum of the first reference numbers of the multiple imaginary marking lines; the second reference total number is the sum of the second reference numbers of the multiple imaginary marking lines. The image processing device calculates the first reference total number N1 divided by the second reference total number N2. If N1 / N2≥V, it is determined that there is a defect; if N1 / N2<V, it is determined that there is no defect, where V is a constant specified by a technician according to the allowable defect size.

Description

Technical Field

[0001] The invention relates to the technical field of seamless steel pipe detection, and in particular to a seamless steel pipe diameter measurement and surface defect detection system. Background Art

[0002] Seamless steel pipe is a kind of cross-section steel with high practicality. It is in great demand in production and life, such as oil, boilers, power stations, ships, machinery manufacturing, automobiles, aviation, aerospace, energy, geology, construction and military industries. The diameter and surface defect information of seamless steel pipe are important criteria for judging the quality of seamless steel pipe, and are also the most concerned part for enterprises and customers. The market demand for seamless steel pipe is increasing, and traditional seamless steel pipe detection methods are difficult to meet the production requirements of enterprises. Summary of the invention

[0003] The present invention aims to provide a seamless steel pipe diameter measurement and surface defect detection system, and the technical problems to be solved include how to simultaneously complete the diameter size measurement and surface defect detection through a single acquisition.

[0004] The object of the present invention is to solve the deficiencies of the prior art and provide a seamless steel pipe diameter measurement and surface defect detection system, which includes a bench, a first guide rail, a first strip light source, a second strip light source, a parallel light source, a line array camera, a second guide rail, an auxiliary rotating shaft, a driving rotating shaft, a display screen, an image processing device and a motor. The first guide rail is arranged on the top of the bench; the first strip light source, the second strip light source and the line array camera are all installed on the first guide rail and can slide left and right along the first guide rail; the auxiliary rotating shaft is rotatably installed on one side of the bench, and the driving rotating shaft is rotatably installed on the other side of the bench. The seamless steel pipe to be detected is installed and clamped between the auxiliary rotating shaft and the driving rotating shaft; the end of the driving rotating shaft is connected to the motor, and the driving rotating shaft is driven by the motor to rotate; the driving rotating shaft further drives the auxiliary rotating shaft and the seamless steel pipe to rotate; the line array camera is respectively connected to the display screen and the image processing device through data lines, so that while the image captured by the line array camera is displayed on the display screen, the image captured by the line array camera is sent to the image processing device for processing; the image processing device performs second-order differentiation on the brightness value of the image of the seamless steel pipe captured by the line array camera to generate a second-order differential image; at the same time, the image processing device respectively generates second-order differential curves for a plurality of imaginary marking lines in the second-order differential image. The plurality of imaginary marking lines are closed annular lines surrounding the seamless steel pipe on the second-order differential image, and the surface formed by the annular line is perpendicular to the central axis of the seamless steel pipe; the second-order differential curve represents the change of the second derivative value on the imaginary marking line in the second-order differential image; the image processing device further counts a first reference number, and the first reference number is the number of times the second-order differential curve intersects the first limit value on the annular line; the image processing device further counts a second reference number, and the second reference number is the number of times the second-order differential curve intersects the second limit value on the annular line; the image processing device further counts a first reference total number N1 and a second reference total number N2. The first reference total number is the sum of the first reference numbers of the plurality of imaginary marking lines; the second reference total number is the sum of the second reference numbers of the plurality of imaginary marking lines; the image processing device calculates the first reference total number N1 divided by the second reference total number N2. If N1 / N2≥V, it is determined that there is a defect; if N1 / N2 <V, it is determined that there is no defect, where V is a constant specified by a technician according to the allowable defect size.

[0005] Both the first limit value and the second limit value are the brightness values of the second-order differential image. The first limit value corresponds to the extreme value of the defect depth used as the boundary line between the allowable defect surface and the normal surface in surface defect detection, and the second limit value corresponds to the extreme value of the surface roughness of the seamless steel pipe to be detected that can be allowed in surface defect detection.

[0006] The second limit value is smaller than the first limit value.

[0007] Preferably, the image processing device fits the left and right boundaries of the collected seamless steel pipe to be inspected into a left boundary L1 and a right boundary L2:

[0008] L1:y=k1x+b1

[0009] L2: y = k2x + b2;

[0010] Among them, the specific values ​​of k1, k2, b1 and b2 are the least squares estimates calculated by fitting the straight line using the least squares method;

[0011] Let (x1, y1) and (x2, y2) represent the two endpoints of the left boundary L1, and (x1', y1') and (x2', y2') represent the two endpoints of the right boundary L2. Then, according to the distance formula from a point to a straight line, we can get the distance L from (x1, y1) to the right boundary L2. 12 for:

[0012]

[0013] The distance L from (x2, y2) to the right boundary L2 is calculated in the same way 22 、(x1', y1') The distance L' to the left boundary L1 21 and the distance L' from (x2', y2') to the left boundary L1 22 , take L 12 , L 22 , L' 21 and L' 22 The mean value of is taken as the diameter d of the seamless steel pipe, that is:

[0014]

[0015] Preferably, the first guide rail and the second guide rail are both arranged parallel to the central axis of the seamless steel pipe.

[0016] The first strip light source and the second strip light source are symmetrically arranged on the left and right sides of the area array camera respectively.

[0017] The optical axis directions of the first strip light source and the second strip light source form an angle of 25° to 60° with the surface of the seamless steel pipe.

[0018] The central axes of the auxiliary rotating shaft, the driving rotating shaft and the seamless steel pipe coincide with each other to form a same straight line.

[0019] The first strip light source and the second strip light source are arranged above the seamless steel pipe. The light emitted by the first strip light source and the second strip light source is irradiated onto the seamless steel pipe and then reflected by the seamless steel pipe, and the reflected light enters the area array camera.

[0020] The parallel light source is arranged below the seamless steel pipe.

[0021] Beneficial Effects

[0022] Compared with the prior art, the beneficial effects of the present invention are as follows: the seamless steel pipe diameter measurement and surface defect detection system of the present invention uses a single array camera combined with a rotating forward scheme to complete the image acquisition of cylindrical seamless steel pipes, and can simultaneously complete the diameter size measurement and surface defect detection through a single acquisition. The problem of surface reflection and retention of boundary information of steel pipes is solved by adopting a combined light source composed of a double-strip light source and a parallel light source, while also increasing the stability and scalability of the image acquisition device, ensuring that the image has a clear outline while ensuring that the surface features of the image are obvious. Using the seamless steel pipe diameter measurement and surface defect detection system of the present invention, the diameter measurement error is less than 0.01mm, and the detection rate of surface defects with a size of 0.2mm×0.2mm or more is higher than 95%. The measurement of the diameter of seamless steel pipes and the detection of surface defects meet production requirements. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The accompanying drawings are used to provide a further understanding of the technical solution of the present invention and constitute a part of the specification. Together with the specific embodiments of the present application, they are used to explain the technical solution of the present invention and do not constitute a limitation on the technical solution of the present invention.

[0024] Figure 1 It is a flowchart of the method for manufacturing the seamless steel pipe diameter measurement and surface defect detection system of the present invention.

[0025] Figure 2 is a schematic diagram of the second-order differential curve.

[0026] Figure 3 It is a schematic diagram of left and right boundary fitting of the collected image of the seamless steel pipe to be inspected. DETAILED DESCRIPTION

[0027] The present invention is described in more detail hereinafter to facilitate understanding of the present invention.

[0028] like Figure 1 and Figure 2As shown, the seamless steel pipe diameter measurement and surface defect detection system of the present invention includes a stand 1, a first guide rail 3, a first strip light source 4, a second strip light source 5, a parallel light source 6, an array camera 7, a second guide rail 8, an auxiliary shaft 9, a driving shaft 10, a display screen 11, an image processing device 12 and a motor 13, wherein the first guide rail 3 is arranged on the top of the stand 1; the first strip light source 4, the second strip light source 5 and the array camera 7 are all installed on the first guide rail 3 and can slide left and right along the first guide rail; the auxiliary shaft 9 is rotatably installed on one side of the stand, and the driving shaft 10 is rotatably installed on the other side of the stand, and the seamless steel pipe 2 to be detected is installed and clamped between the auxiliary shaft 9 and the driving shaft 10; the end of the driving shaft 10 is connected to the motor 13, and the driving shaft 10 is driven by the motor 13 The driving shaft 10 further drives the auxiliary shaft 9 and the seamless steel pipe 2 to rotate; the area array camera 7 is connected to the display screen 11 and the image processing device 12 through data cables, so that the image captured by the area array camera 7 is displayed on the display screen 11 and transmitted to the image processing device 12 for processing; the image processing device 12 performs a second derivative on the brightness value of the image of the seamless steel pipe captured by the area array camera 7 to generate a second-order differential image; at the same time, the image processing device 12 generates a second-order differential curve L for a plurality of imaginary marking lines in the second-order differential image, and the plurality of imaginary marking lines are closed annular lines H surrounding the seamless steel pipe on the second-order differential image, and the surface formed by the annular lines is perpendicular to the central axis of the seamless steel pipe; the second-order differential curve represents the change of the second-order derivative value on the imaginary marking line in the second-order differential image; the image processing device 12 further counts the first reference number n1, The first reference number is the number of times the second-order differential curve L intersects the first limit value B1 on the annular line H; the image processing device 12 further counts the second reference number n2, and the second reference number is the number of times the second-order differential curve L intersects the second limit value B2 on the annular line H.

[0029] The first limit value B1 and the second limit value B2 are both brightness values ​​of the second-order differential image. The first limit value corresponds to the extreme value of the defect depth used as the boundary line between the allowable defect surface and the normal surface in surface defect detection, and the second limit value corresponds to the extreme value of the surface roughness of the seamless steel pipe to be inspected that is allowable in surface defect detection.

[0030] The second limit value B2 is smaller than the first limit value B1.

[0031] During the experiment, the applicant found that if there are defects on the surface of the seamless steel pipe to be detected, the second derivative value of the brightness value in the actual image becomes larger at the position where the defect is deep. That is to say, by comparing the second derivative value of each brightness value with a relatively large first limit value B1, it can be detected whether there are defects. In addition, during the actual detection process, the applicant found that the brightness value in the actual image is also affected by the surface roughness of the seamless steel pipe. By comparing the second derivative value of each brightness value with a relatively small second limit value B2, the actual influence of the surface roughness of the seamless steel pipe on the detection of surface defects of the seamless steel pipe can be detected.

[0032] The image processing device 12 further statistically counts a first reference total number N1 and a second reference total number N2. The first reference total number is the sum of the first reference numbers n1 of the multiple imaginary marking lines; the second reference total number is the sum of the second reference numbers n2 of the multiple imaginary marking lines.

[0033] The image processing device 12 calculates the first reference total number N1 divided by the second reference total number N2. If N1 / N2≥V, it is determined that there are defects; if N1 / N2<V, it is determined that there are no defects, where V is a constant specified by a technician according to the allowable defect size.

[0034] As an example, when the allowable defect is greater than 0.2mm×0.2mm, V = 4 is taken; when the allowable defect is less than or equal to 0.2mm×0.2mm, V = 2 is taken.

[0035] There are usually two methods for measuring the diameter of a seamless steel pipe: collecting images at the end of the seamless steel pipe and collecting images on the side wall of the seamless steel pipe. Collecting images at the end of the seamless steel pipe requires a planar array camera to be separately set at the end of the seamless steel pipe, which results in at least two planar array cameras being required for the seamless steel pipe diameter measurement and surface defect detection system, and each camera also requires a separate optical lens, greatly increasing the manufacturing cost of the detection system. In addition, since the diameter of the seamless steel pipe changes along its length direction (i.e., the direction of the central axis), measuring only the diameter at the end is not sufficient to characterize the actual diameter of the entire seamless steel pipe.

[0036] Collecting images on the side wall of the seamless steel pipe is to use a planar array camera to take pictures from top to bottom, which appears as a rectangular figure in the image, and measuring the width of the rectangle can obtain the diameter of the seamless steel pipe. This measurement method only requires a planar array camera set above the seamless steel pipe, reducing the manufacturing cost of the seamless steel pipe diameter measurement and surface defect detection system. In addition, since the planar array camera set above the seamless steel pipe can move along the length direction of the seamless steel pipe (i.e., the direction of the central axis), the actual diameter of the entire seamless steel pipe can be accurately shown.

[0037] To measure the diameter of a seamless steel pipe by collecting images of the side wall of the seamless steel pipe, it is necessary to locate the boundaries of the collected images. Specifically:

[0038] like Figure 3 As shown, since the diameter of the seamless steel pipe along the length direction is not a consistent fixed value, the actual left and right boundaries of the seamless steel pipe are not strict straight lines. The image processing device 12 is required to fit the left and right boundaries of the collected seamless steel pipe 2 to be detected into a left boundary L1 and a right boundary L2:

[0039] L1:y=k1x+b1

[0040] L2: y = k2x + b2;

[0041] Among them, the specific values ​​of k1, k2, b1 and b2 are the least squares estimates calculated by fitting the straight line using the least squares method;

[0042] like Figure 3 As shown, let (x1, y1) and (x2, y2) represent the two endpoints of the left boundary L1, and (x1', y1') and (x2', y2') represent the two endpoints of the right boundary L2. Then, according to the distance formula from a point to a straight line, we can get the distance L from (x1, y1) to the right boundary L2. 12 for:

[0043]

[0044] The distance L from (x2, y2) to the right boundary L2 is calculated in the same way 22 、(x1', y1') The distance L' to the left boundary L1 21 and the distance L' from (x2', y2') to the left boundary L1 22 , theoretically L 12 , L 22 , L' 21 and L' 22 Both can represent the distance between the left boundary L1 and the right boundary L2. However, since the left boundary L1 and the right boundary L2 are not absolutely parallel straight lines in actual calculation, there is actually a very small angle between the left boundary L1 and the right boundary L2. In order to reduce the error, L 12 , L 22 , L' 21 and L' 22 The mean value of is taken as the diameter d of the seamless steel pipe, that is:

[0045]

[0046] Preferably, the first guide rail 3 and the second guide rail 8 are both arranged parallel to the central axis of the seamless steel pipe 2 .

[0047] The first strip light source 4 and the second strip light source 5 are symmetrically arranged on the left and right sides of the area array camera 7 respectively.

[0048] The optical axis directions of the first strip light source 4 and the second strip light source 5 form an angle of 25° to 60° with the surface of the seamless steel pipe 2. This angle makes the image of the seamless steel pipe 2 captured by the area array camera 7 brighter overall, and can highlight the contour of the seamless steel pipe 2 and the uneven areas on the surface.

[0049] The central axes of the auxiliary rotating shaft 9, the driving rotating shaft 10 and the seamless steel pipe 2 coincide with each other and form a same straight line.

[0050] The first strip light source 4 and the second strip light source 5 are arranged above the seamless steel pipe 2 . The light emitted by the first strip light source 4 and the second strip light source 5 irradiates the seamless steel pipe 2 and is reflected by the seamless steel pipe 2 . The reflected light enters the area array camera 7 .

[0051] The parallel light source 6 is arranged below the seamless steel pipe 2. In this way, the backlighting effect is achieved, so that the image captured by the area array camera 7 has a clear outline, which is convenient for dimensional measurement.

[0052] The above describes the preferred embodiments of the present invention, but it is not intended to limit the present invention. Those skilled in the art may make improvements and changes to the embodiments disclosed herein without departing from the scope and spirit of the present invention.

Claims

1. A seamless steel pipe diameter measurement and surface defect detection system, characterized in that: The seamless steel pipe diameter measurement and surface defect detection system includes a bench, a first guide rail, a first strip light source, a second strip light source, a parallel light source, a line array camera, a second guide rail, an auxiliary rotating shaft, a driving rotating shaft, a display screen, an image processing device, and a motor. The first guide rail is arranged on the top of the bench; the first strip light source, the second strip light source, and the line array camera are all installed on the first guide rail and can slide left and right along the first guide rail; the auxiliary rotating shaft is rotatably installed on one side of the bench, and the driving rotating shaft is rotatably installed on the other side of the bench. The seamless steel pipe to be detected is installed and clamped between the auxiliary rotating shaft and the driving rotating shaft; the end of the driving rotating shaft is connected to the motor, and the driving rotating shaft is driven by the motor to rotate; the driving rotating shaft further drives the auxiliary rotating shaft and the seamless steel pipe to rotate; the line array camera is respectively connected to the display screen and the image processing device through data lines, so that the image captured by the line array camera is displayed on the display screen and at the same time, the image captured by the line array camera is sent to the image processing device for processing; the image processing device performs second-order differentiation on the brightness value of the image of the seamless steel pipe captured by the line array camera to generate a second-order differential image; at the same time, the image processing device respectively generates second-order differential curves for a plurality of imaginary marking lines in the second-order differential image. The plurality of imaginary marking lines are closed circular lines surrounding the seamless steel pipe on the second-order differential image, and the surface formed by the circular line is perpendicular to the central axis of the seamless steel pipe; the second-order differential curve represents the change of the second derivative value on the imaginary marking line in the second-order differential image; the image processing device further counts the first reference number of times, and the first reference number of times is the number of times the second-order differential curve intersects the first limit value on the circular line; the image processing device further counts the second reference number of times, and the second reference number of times is the number of times the second-order differential curve intersects the second limit value on the circular line; the image processing device further counts the first reference total number N1 and the second reference total number N2. The first reference total number is the sum of the first reference number of times of the plurality of imaginary marking lines; the second reference total number is the sum of the second reference number of times of the plurality of imaginary marking lines; the image processing device calculates the first reference total number N1 divided by the second reference total number N2. If N1 / N2≥V, it is determined that there is a defect; if N1 / N2<V, it is determined that there is no defect, where V is a constant specified by a technician according to the allowable defect size; Both the first limit value and the second limit value are the brightness values of the second-order differential image. The first limit value corresponds to the extreme value of the defect depth used as the boundary line between the allowable defect surface and the normal surface in surface defect detection, and the second limit value corresponds to the extreme value of the surface roughness of the seamless steel pipe to be detected that can be allowed in surface defect detection; The second limit value is less than the first limit value; The central axes of the auxiliary rotating shaft, the driving rotating shaft, and the seamless steel pipe coincide as the same straight line; The first strip light source and the second strip light source are arranged above the seamless steel pipe, and the light emitted by the first strip light source and the second strip light source is irradiated onto the seamless steel pipe and then reflected by the seamless steel pipe, and the reflected light enters the area array camera; The parallel light source is arranged below the seamless steel pipe.

2. The seamless steel pipe diameter measurement and surface defect detection system according to claim 1 is characterized in that: The image processing device fits the left and right boundaries of the collected seamless steel pipe to be detected into a left boundary L1 and a right boundary L2: L1:y=k1x+b1 L2: y = k2x + b2; Among them, the specific values ​​of k1, k2, b1 and b2 are the least squares estimates calculated by fitting the straight line using the least squares method; Let (x1, y1) and (x2, y2) represent the two endpoints of the left boundary L1, and (x1', y1') and (x2', y2') represent the two endpoints of the right boundary L2. Then, according to the distance formula from a point to a straight line, we can get the distance L from (x1, y1) to the right boundary L2. 12 for: The distance L from (x2, y2) to the right boundary L2 is calculated in the same way 22 、The distance L' from (x1', y1') to the left boundary L1 21 and the distance L' from (x2', y2') to the left boundary L1 22 , take L 12 , L 22 , L' 21 and L' 22 The mean value of is taken as the diameter d of the seamless steel pipe, that is:

3. The seamless steel pipe diameter measurement and surface defect detection system according to claim 1, characterized in that: The first guide rail and the second guide rail are both arranged parallel to the central axis of the seamless steel pipe.

4. The seamless steel pipe diameter measurement and surface defect detection system according to claim 1, characterized in that: The first strip light source and the second strip light source are symmetrically arranged on the left and right sides of the area array camera respectively.

5. The seamless steel pipe diameter measurement and surface defect detection system according to claim 1, characterized in that: The optical axis directions of the first strip light source and the second strip light source form an angle of 25° to 60° with the surface of the seamless steel pipe.

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