CN112268841A - Ultrasonic detection method for grain size of low-temperature steel weld joint - Google Patents
Ultrasonic detection method for grain size of low-temperature steel weld joint Download PDFInfo
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- 229910000831 Steel Inorganic materials 0.000 title claims abstract description 27
- 239000010959 steel Substances 0.000 title claims abstract description 27
- 238000001514 detection method Methods 0.000 title claims abstract description 23
- 238000003466 welding Methods 0.000 claims abstract description 41
- 230000007547 defect Effects 0.000 claims abstract description 7
- 238000006243 chemical reaction Methods 0.000 claims description 6
- 239000003086 colorant Substances 0.000 claims description 2
- 238000000034 method Methods 0.000 abstract description 5
- 238000012360 testing method Methods 0.000 abstract description 5
- 239000000463 material Substances 0.000 description 9
- 239000000523 sample Substances 0.000 description 7
- XEEYBQQBJWHFJM-UHFFFAOYSA-N Iron Chemical compound [Fe] XEEYBQQBJWHFJM-UHFFFAOYSA-N 0.000 description 6
- 239000013078 crystal Substances 0.000 description 6
- 238000001914 filtration Methods 0.000 description 6
- 230000004927 fusion Effects 0.000 description 4
- 238000011156 evaluation Methods 0.000 description 3
- 229910052742 iron Inorganic materials 0.000 description 3
- 238000012545 processing Methods 0.000 description 3
- 239000007822 coupling agent Substances 0.000 description 2
- 230000003111 delayed effect Effects 0.000 description 2
- 238000002592 echocardiography Methods 0.000 description 2
- 238000003709 image segmentation Methods 0.000 description 2
- 238000005259 measurement Methods 0.000 description 2
- 238000002604 ultrasonography Methods 0.000 description 2
- 230000005483 Hooke's law Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 239000011248 coating agent Substances 0.000 description 1
- 238000000576 coating method Methods 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 238000001816 cooling Methods 0.000 description 1
- 238000012937 correction Methods 0.000 description 1
- 230000007797 corrosion Effects 0.000 description 1
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- 238000002474 experimental method Methods 0.000 description 1
- 238000009434 installation Methods 0.000 description 1
- 230000014759 maintenance of location Effects 0.000 description 1
- 239000007769 metal material Substances 0.000 description 1
- 238000007431 microscopic evaluation Methods 0.000 description 1
- 238000013021 overheating Methods 0.000 description 1
- 238000002360 preparation method Methods 0.000 description 1
- 238000005070 sampling Methods 0.000 description 1
- 239000002893 slag Substances 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
- 238000000638 solvent extraction Methods 0.000 description 1
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- 238000006467 substitution reaction Methods 0.000 description 1
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- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
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Abstract
The invention discloses an ultrasonic detection method for the grain size of a low-temperature steel weld joint, which is characterized by comprising the following steps: collecting ultrasonic A-type waves of a welding seam; converting the ultrasonic A-type waves to obtain an ultrasonic C scanning image; judging the macroscopic defect of the welding line through the ultrasonic C scanning image, and if the macroscopic defect does not exist, dividing the ultrasonic C scanning image into a plurality of blocks; calculating the grain size of each block by utilizing an SSR model; comparing the grain sizes according to a standard to determine whether the welding seam is qualified; the problem of current low temperature steel welding seam grain size use ultrasonic wave technique testing result error big is solved.
Description
Technical Field
The invention relates to the field of nondestructive detection of low-temperature steel welding seam grain size, in particular to a method for detecting the low-temperature steel welding seam grain size.
Background
The grain size of the low-temperature steel welding seam has great influence on the low-temperature toughness, and the finer the grain is, the better the low-temperature toughness is. During welding, due to the manual operation of a welder, the line energy is easily overlarge, the high-temperature retention time in the welding seam thermal cycle is long, the cooling speed is slow, crystal grains of a joint structure become thick, the low-temperature toughness and the mechanical property of a low-temperature steel structure are reduced, and the safe service life of the low-temperature steel structure is influenced. Meanwhile, the delayed cold cracks of the welding line are widely distributed and can be observed under a microscope, the existence of the delayed cold cracks not only reduces the strength of the welding line, but also causes stress concentration, so that the structure expands when being loaded, thereby accelerating the fatigue fracture and the corrosion fracture of the structure and having the possibility of expansion and even catastrophic consequences.
At present, the grain size of a welding seam is mainly measured by adopting a metallographic method to obtain the grain size of low-temperature steel, but the metallographic method has the problems of long test piece preparation and detection period, damage to the welding seam of the test piece and the like, can be only carried out during the evaluation period of the welding process of the low-temperature steel test piece, and cannot carry out online detection during the welding of the low-temperature steel structure on a construction site.
The ultrasonic technology can only detect single crystal materials and detect the average grain size of the single crystal materials. The grain sizes of a welding seam fusion area and a heat affected area are complex and greatly changed, and the large grain size of the overheating area is averaged by other areas nearby by adopting the conventional average grain size detection method, so that the detection result has large error.
Disclosure of Invention
In view of the above, the invention provides an ultrasonic detection method for the grain size of a low-temperature steel weld joint, which solves the problem that the existing ultrasonic detection method for the grain size of the low-temperature steel weld joint has large error in detection results.
In order to achieve the above object, the ultrasonic detection method for grain size of a weld joint of low-temperature steel is characterized by comprising the following steps:
collecting ultrasonic A-type waves of a welding seam;
converting the ultrasonic A-type waves to obtain an ultrasonic C scanning image;
judging the macroscopic defect of the welding line through the ultrasonic C scanning image, and if the macroscopic defect does not exist, dividing the ultrasonic C scanning image into a plurality of blocks;
calculating the grain size of each block by utilizing an SSR model;
and comparing the grain sizes according to a standard to determine whether the welding seam is qualified.
Further, the conversion is performed by adding a time domain window to the ultrasonic C scanning image after the ultrasonic A-type wave is filtered.
Further, the time domain windowing is performed by assigning different colors for allocation and sequential conversion.
Further, the separating is with a watershed algorithm.
Further, the standard is GB/T6394-2002.
The invention has the following beneficial effects:
the ultrasonic scattering detection method can observe, statistically determine and quantitatively analyze the weld grain boundary type, orientation difference, structure and grain size statistical distribution state thereof, thereby establishing quantitative and semi-quantitative relations between the grain size statistical distribution, the grain boundary structure, the orientation, weld microtexture and the like and between the grain size statistical distribution and the performance of polycrystalline materials, and providing a technical basis for ultrasonic detection and evaluation of welds.
Drawings
FIG. 1 is a diagram of an ultrasonic testing device for grain size of a weld joint of low-temperature steel.
In the figure: 1. 2, a low-temperature steel welding seam, 3, an ultrasonic probe, 4, an adjustable track, 5, an ultrasonic probe controller, 6 and a computer.
Detailed Description
The present invention will be described below based on examples, but it should be noted that the present invention is not limited to these examples. In the following detailed description of the present invention, certain specific details are set forth. However, the present invention may be fully understood by those skilled in the art for those parts not described in detail.
The invention uses the ultrasonic detection device for the grain size of the low-temperature steel welding seam as shown in figure 1 to detect, and the specific detection steps are explained in detail as follows:
(1) weld grain measurement assembly installation
Firstly, removing attachments such as welding slag and the like on the surface of a welding seam, coating a coupling agent on the surface of the welding seam, installing an adjustable rail around the welding seam, installing an ultrasonic probe on the adjustable rail, and connecting the ultrasonic probe with an ultrasonic probe controller. The data is collected and transmitted to a computer through an ultrasonic data acquisition card, and ultrasonic A-type waves and ultrasonic C scanning images are generated in the computer.
(2) Gain correction for ultrasonic scattering detection probe
In the scattering experiments, the upper surface reflection is in the high gain case, since the ultrasound signal acquisition only records the range of-1V to + 1V. Any portion of the signal that exceeds this limit is not recorded and will be marked as a corresponding-1 or + 1. In the backscattering model this requires a suitable gain, which can be neither too small to result in lost information nor too oversaturated. It is desirable to enable the peaks to be viewed in the signal window. The initial signal amplitude increases with increasing gain, but to some extent does not increase.
(3) Weld grain measurement
The ultrasonic waves are transmitted to the center of the fusion zone and the central surface of the heat affected zone of the low-temperature steel welding seam by a transmitting probe through a coupling agent, when the ultrasonic waves are transmitted in the low-temperature steel welding seam, the ultrasonic waves are reflected and scattered by grains to generate echoes, and the time of the echoes is related to the size of the grains, so that the measured ultrasonic transmission speed can be used for evaluating the grain size of the metal material.
Ultrasonic signals and frequency spectrograms thereof of the center of a fusion zone and the surface of the center of a heat affected zone of a low-temperature steel welding seam are collected, and MATLAB software is utilized to perform short-time Fourier transform on the ultrasonic signals to obtain frequency distribution in a certain period of time. The resolution capability can be improved through high-pass filtering in the processing of ultrasonic signals in the center of a weld fusion zone and the center of a heat affected zone, and higher harmonic signals are extracted to evaluate the weld.
(4) Ultrasonic A-wave signal processing
The accuracy in ultrasonic detection of the welding line can be improved through high-pass filtering, and the boundary frequency Ws of a stop band of the high-pass filtering is selected to be 20MHz, and the boundary frequency Wp of a pass band is selected to be 25 MHz. The filtering is mainly used for investigating the high-order harmonic signals in the ultrasonic signals. The passband ripple Rp is less than 1dB, the stopband attenuation Rs is greater than 20dB, and the sampling frequency Fs is 500 MHz.
The high-pass filter carries out filtering processing on the two analyzed points of the ultrasonic signal, the positions of the upper surface and the upper surface can be clearly distinguished, a spectrogram after ultrasonic filtering is obtained, and a frequency band smaller than 20MHz in the spectrogram is omitted, so that a high-frequency band signal is obtained.
(5) Conversion of ultrasonic A-wave and ultrasonic C-scan images
After the ultrasonic A-type wave is filtered, the A-type wave is converted by adding a time domain window, and through color distribution, for example, when the signal amplitude does not exceed a limit value 1, blue is given, when the signal amplitude exceeds the limit value 1 but does not exceed a limit value 2, yellow is given to the point, and when the signal amplitude exceeds the limit value 2, pink is given, and the like, the conversion is carried out in sequence, and finally the ultrasonic C-scanning image can be obtained.
The ultrasonic C scanning image is a false color image, namely, the amplitude of an ultrasonic signal is artificially related to the color.
After the ultrasonic C scanning image is obtained, macroscopically evaluating the material to determine whether the material has a large defect, if not, performing subsequent microscopic evaluation, and meanwhile, in ultrasonic detection of the grain size of the welding seam, partitioning the material by the ultrasonic C scanning image, and respectively calculating the grain size of each block.
(6) Image segmentation of ultrasound C-scan images
And (3) converting the ultrasonic C-scanned image into a gray image by using a watershed algorithm and MATLAB programming, and then carrying out image segmentation on the gray image of the ultrasonic C-scanned image to obtain a segmented image.
And respectively calculating the grain size of the scanned points in the region 1, the region 2 and the region 3 by using an SSR model to obtain the grain size of the corresponding region.
From the ultrasonic C scanning image, the 1 area is probably near the heat affected zone, the grain size is larger, the 2 area is on the welding seam, the 3 area is on the base material, the results of the 2 area and the 3 area are similar theoretically, but the 1 area is obviously different from the 2 area or the 3 area.
(7) Evaluation of weld grain size
And after the welding line ultrasonic C scanning image is partitioned, calculating the covariance of the ultrasonic signals of the scanning points in the area, and solving phi (t).
The covariance of the elastic modulus of the symmetric cubic material can be found by the following equation:
wherein v is c11-c12-2c44。
Vectors p and s represent the propagation directions of the incident and scattered waves, respectively, c11、c12、c44Denotes the anisotropy factor of the single crystal material, ρ denotes the density of the iron single crystal, CLRepresents the propagation velocity of a longitudinal wave in an iron single crystal.
The stiffness coefficients in generalized hooke's law are shown.
Obtained from the fourier transform equation:
whereink represents the number of ultrasonic waves in the solid, and k is ω0and/CL. L is defined as the theoretical grain size of the low temperature steel.
Calculating the numerical values of the 1, 2 and 3 regions by using an MATLAB calculation equation, removing a plurality of the numerical values, and then removing the numerical values if the difference between the actual grain size and the grain size of the general iron is 1-80 mu m, so that the grain size of each region can be finally obtained.
(8) Criteria for discrimination
And according to the calculated grain size value, comparing with each numerical relation table of the microscopic grain sizes of any orientation, uniform and equiaxial grains in GB/T6394-2002, and determining whether the welding seam needs to be repaired.
The above-mentioned embodiments are merely embodiments for expressing the invention, and the description is specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for those skilled in the art, various changes, substitutions of equivalents, improvements and the like can be made without departing from the spirit of the invention, and these are all within the scope of the invention. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (5)
1. An ultrasonic detection method for the grain size of a low-temperature steel welding seam is characterized by comprising the following steps:
collecting ultrasonic A-type waves of a welding seam;
converting the ultrasonic A-type waves to obtain an ultrasonic C scanning image;
judging the macroscopic defect of the welding line through the ultrasonic C scanning image, and if the macroscopic defect does not exist, dividing the ultrasonic C scanning image into a plurality of blocks;
calculating the grain size of each block by utilizing an SSR model;
and comparing the grain sizes according to a standard to determine whether the welding seam is qualified.
2. The ultrasonic detection method for the grain size of the low-temperature steel welding seam according to claim 1, characterized by comprising the following steps:
and the conversion is to convert the ultrasonic A-type wave into the ultrasonic C scanning image in a mode of adding a time domain window after the ultrasonic A-type wave is filtered.
3. The ultrasonic detection method for the grain size of the low-temperature steel welding seam according to claim 2, characterized by comprising the following steps:
the time domain windowing is performed by assigning different colors for allocation and sequential conversion.
4. The ultrasonic detection method for the grain size of the low-temperature steel welding seam according to claim 1, characterized by comprising the following steps:
the separating is by using a watershed algorithm.
5. The ultrasonic detection method for the grain size of the low-temperature steel welding seam according to claim 1, characterized by comprising the following steps:
the standard is GB/T6394-2002.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117268297A (en) * | 2023-11-22 | 2023-12-22 | 国营川西机器厂 | Method and device for detecting transverse size of welding spot of double-layer catheter based on ultrasonic longitudinal wave |
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| CN107941907A (en) * | 2017-10-31 | 2018-04-20 | 武汉大学 | A kind of method of the average grain size based on effective ultrasonic backscattered signal extraction polycrystalline material |
| CN108896660A (en) * | 2018-07-09 | 2018-11-27 | 中南大学 | A kind of hexagonal crystal material near surface tiny flaw detection method based on shear wave back scattering |
| CN111089151A (en) * | 2020-01-15 | 2020-05-01 | 岳西县盛宏工贸有限责任公司 | Anti-fracture chain wheel support structure and forging process thereof |
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|---|---|---|---|---|
| CN107941907A (en) * | 2017-10-31 | 2018-04-20 | 武汉大学 | A kind of method of the average grain size based on effective ultrasonic backscattered signal extraction polycrystalline material |
| CN108896660A (en) * | 2018-07-09 | 2018-11-27 | 中南大学 | A kind of hexagonal crystal material near surface tiny flaw detection method based on shear wave back scattering |
| CN111089151A (en) * | 2020-01-15 | 2020-05-01 | 岳西县盛宏工贸有限责任公司 | Anti-fracture chain wheel support structure and forging process thereof |
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| 中华人民共和国国家质量监督检验检疫总局等: "《TB/T 1632.2-2014 钢轨焊接 第2部分：闪光焊接》", 31 July 2017 * |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117268297A (en) * | 2023-11-22 | 2023-12-22 | 国营川西机器厂 | Method and device for detecting transverse size of welding spot of double-layer catheter based on ultrasonic longitudinal wave |
| CN117268297B (en) * | 2023-11-22 | 2024-02-02 | 国营川西机器厂 | Method and device for detecting transverse size of welding spot of double-layer catheter based on ultrasonic longitudinal wave |
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Application publication date: 20210126 |