CN111983030A - Friction welding seam defect quantitative detection method and system based on ultrasonic phased array - Google Patents
Friction welding seam defect quantitative detection method and system based on ultrasonic phased array Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N29/00—Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object
- G01N29/04—Analysing solids
- G01N29/06—Visualisation of the interior, e.g. acoustic microscopy
- G01N29/0654—Imaging
- G01N29/0681—Imaging by acoustic microscopy, e.g. scanning acoustic microscopy
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N29/00—Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object
- G01N29/04—Analysing solids
- G01N29/06—Visualisation of the interior, e.g. acoustic microscopy
- G01N29/0654—Imaging
- G01N29/069—Defect imaging, localisation and sizing using, e.g. time of flight diffraction [TOFD], synthetic aperture focusing technique [SAFT], Amplituden-Laufzeit-Ortskurven [ALOK] technique
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N29/00—Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object
- G01N29/22—Details, e.g. general constructional or apparatus details
- G01N29/26—Arrangements for orientation or scanning by relative movement of the head and the sensor
- G01N29/265—Arrangements for orientation or scanning by relative movement of the head and the sensor by moving the sensor relative to a stationary material
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- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N29/00—Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object
- G01N29/44—Processing the detected response signal, e.g. electronic circuits specially adapted therefor
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- G—PHYSICS
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0004—Industrial image inspection
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- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10132—Ultrasound image
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20092—Interactive image processing based on input by user
- G06T2207/20104—Interactive definition of region of interest [ROI]
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30108—Industrial image inspection
- G06T2207/30152—Solder
Abstract
The invention discloses a method and a system for quantitatively detecting weld defects of friction stir welding based on an ultrasonic phased array, wherein an S scanning weld defect image is obtained by performing S scanning on a weld by using an ultrasonic phased array instrument, an interested target area is divided for the S scanning weld defect image, an S scanning signal scale and an S scanning signal image are respectively extracted and converted into a gray scale image, filtering and binarization processing are performed on the gray scale image, and an S scanning signal scale unit is extracted; and reserving points in the upper and lower threshold ranges in the image after the binarization processing of the S scanning signal, determining the central X pixel coordinate, the Y pixel coordinate and the maximum pixel value in the X direction of the image formed by the points, and dividing the central X pixel coordinate of the image by the scale unit of the S scanning signal to obtain the defect size, the defect equivalent length and the defect equivalent width. The method can extract the defect size and position information in real time through the image processing module, and can perform depth positioning and quantitative analysis on the aluminum alloy friction stir welding defects.
Description
Technical Field
The invention relates to the field of phased ultrasonic nondestructive testing, in particular to a friction stir welding weld defect quantitative detection method based on an ultrasonic phased array.
Background
With the continuous improvement of the running speed and the energy-saving and emission-reducing requirements of the railway vehicle, in order to reduce the self weight, a large number of vehicle bodies adopt aluminum alloy section bar structures. Because the friction stir welding has the advantages of good welding seam joint performance, no need of gas protection in the welding process, no smoke dust, no splash and the like, all railway vehicle manufacturing enterprises are popularizing and using the advanced welding technology of aluminum alloy friction stir welding. In the welding process, because the parameters of the friction stir welding process are unreasonable to select, the defects of close contact, fineness and complex orientation often appear in the welding line, and the difficulty of nondestructive testing is increased.
The traditional radiographic detection technology is still the main detection mode of the defects of the aluminum alloy weld joints, and because the traditional radiographic detection cannot quantitatively measure the size and the position of the defects in the height direction of the weld joints, the defects still have defects in the aspect of detection, so that the workload of defect removal is increased, and even because the defect removal direction is wrong, the weld joints are dug through, and the repair welding quality is affected. In order to improve the detection precision and the detection efficiency and save the manual strength, it is necessary to develop a quantitative detection method for the weld defects of the friction stir welding based on the ultrasonic phased array.
Disclosure of Invention
The invention aims to provide a method for quantitatively detecting the weld defects of friction stir welding based on an ultrasonic phased array, which can quickly acquire the size and position information of the defects, reduce the workload in the aspects of positioning and removing the defects, and improve the accuracy and the working efficiency.
The invention adopts the following technical scheme.
On one hand, the invention provides a quantitative detection method for the weld defects of friction stir welding based on an ultrasonic phased array, which comprises the following steps:
s scanning the weld by using an ultrasonic phased array instrument to obtain an S scanning weld defect image, dividing the S scanning weld defect image into interested target areas, and extracting an S scanning signal scale and an S scanning signal image in the interested target areas respectively;
converting the S scanning signal image and the S scanning signal scale into a gray scale image, carrying out filtering and binarization processing on the gray scale image, and extracting the scale unit of the S scanning signal; setting an upper threshold and a lower threshold of an image after binarization of an S scanning signal, reserving points in the range of the upper threshold and the lower threshold in the image after binarization processing of the S scanning signal, determining a defect range according to the reserved points, determining a central X pixel coordinate, a Y pixel coordinate and a maximum pixel value in an X direction of the image formed by the points in the defect range, and dividing the central X pixel coordinate of the image by a scale unit of the S scanning signal to obtain a defect size, a defect equivalent length and a defect equivalent width.
Furthermore, the S-scanning ultrasonic phased array instrument has the key parameters that the probe frequency is 5 MHz-10 MHz, the coupling mode adopts local water immersion, the deflection angle of an acoustic beam is 30-70 degrees, the focusing depth is the thickness of the lap joint plate, and the scanning mode is cross-weld zigzag scanning, so that the thickness of the whole lap joint is fully covered by ultrasonic waves, a detection blind area is avoided, and an S-scanning image is obtained by scanning.
Further, the method further comprises: a scanning is carried out on a welding seam by using an ultrasonic phased array instrument to obtain an A scanning welding seam defect image, an interested target area is divided for the A scanning welding seam defect image, and an A scanning signal scale and an A scanning signal image contained in the A scanning welding seam defect image are respectively extracted from the interested target area;
converting the A scanning signal image and the A scanning signal scale into a gray scale image, carrying out filtering and binarization processing on the gray scale image, and extracting a scale unit of the A scanning signal; converting the image after binarization processing of the scanning signal A into a two-dimensional array represented by pixels; setting an X pixel threshold, reserving points of which the X pixel values are larger than the threshold, and determining a defect range according to the reserved points; the depth of the defect is obtained by dividing the maximum X pixel value among the points within the defect range by the scale unit of the a scanning signal.
Furthermore, key parameters set by the A scanning ultrasonic phased array instrument are as follows, the frequency of a probe is 5 MHz-10 MHz, the coupling mode adopts local water immersion, the deflection angle of an acoustic beam is 45 degrees, and the focusing depth is the thickness of a lap joint plate; the thickness of the whole lap welding seam is fully covered by ultrasonic waves, a detection blind area is avoided, and an A scanning image is obtained through scanning.
Further, before A scanning and S scanning are carried out on the welding seam by using an ultrasonic phased array instrument, the flash and the arc lines on the surface of the welded aluminum alloy after friction stir welding are polished and removed, so that the two surfaces of the welded joint are kept smooth and flat.
In a second aspect, the invention provides a quantitative detection system for weld defects of friction stir welding based on an ultrasonic phased array, which comprises a defect image acquisition module, an S scanning image processing module and a defect information calculation module; the defect image acquisition module is used for carrying out S scanning on the welding seam by using an ultrasonic phased array instrument to obtain an S scanning welding seam defect image;
the S-scanning image processing module is used for dividing the S-scanning weld defect image into interested target areas and extracting an S-scanning signal scale and an S-scanning signal image in the interested target areas respectively;
converting the S scanning signal image and the S scanning signal scale into a gray scale image, carrying out filtering and binarization processing on the gray scale image, and extracting the scale unit of the S scanning signal; setting upper and lower threshold values of the image after the binarization of the S scanning signal, and reserving points in the range of the upper and lower threshold values of the image after the binarization processing of the S scanning signal;
the defect information calculation module is used for determining the central X pixel coordinate, the Y pixel coordinate and the maximum pixel value in the X direction of an image formed by the points reserved by the S scanning image processing module, and dividing the central X pixel coordinate of the image by the scale unit of the S scanning signal to obtain the defect size, the defect equivalent length and the defect equivalent width.
Further, the defect image acquisition module is also used for carrying out A scanning on the welding seam by using an ultrasonic phased array instrument to obtain an A scanning welding seam defect image;
the system also comprises an A scanning image processing module, wherein the A scanning image processing module is used for dividing the A scanning weld defect image into interested target areas and respectively extracting an A scanning signal scale and an A scanning signal image contained in the A scanning weld defect image in the interested target areas; converting the A scanning signal image and the A scanning signal scale into a gray scale image, carrying out filtering and binarization processing on the gray scale image, and extracting a scale unit of the A scanning signal; converting the image after binarization processing of the scanning signal A into a two-dimensional array, and simultaneously rotating the two-dimensional array by 90 degrees to obtain a horizontal image; setting a horizontal threshold line, and reserving points in the horizontal image, which are greater than the height of the threshold line;
the defect information calculation module is further configured to divide the maximum X pixel value among the points retained by the a-scan image processing module by the scale unit of the a-scan signal to obtain the defect depth.
The invention has the following beneficial technical effects:
the ultrasonic phased array probe moves at a constant speed in a direction parallel to the welding seam, receives an image formed by a defect echo signal in the friction stir welding seam of the aluminum alloy vehicle body in real time, extracts the size and position information of the defect in real time through the image processing module, and can perform depth positioning and quantitative analysis on the defect of the friction stir welding of the aluminum alloy.
Drawings
FIG. 1 is a friction stir welding weld defect inspection image reading for an ultrasonic phased array in accordance with an embodiment of the present invention;
FIG. 2 is a scanning scale according to an embodiment of the present invention A;
FIG. 3 shows exemplary embodiment A of the present invention;
FIG. 4 is a graph of RGB scan signals converted to gray scale in accordance with an embodiment of the present invention;
FIG. 5 shows the A-scan signal after filtering binarization according to the embodiment of the present invention;
FIG. 6 is a signal of A scan rotated 90 degrees in accordance with an embodiment of the present invention;
FIG. 7 is a graph of the A-scan signal after thresholding in accordance with an embodiment of the present invention;
FIG. 8 is a S-scan scale according to an embodiment of the present invention;
FIG. 9 shows an embodiment of the present invention S-scan signal;
FIG. 10 is a graph of RGB conversion to gray scale for an S-scan signal according to an embodiment of the present invention;
FIG. 11 shows the filtered binarized S-scan signal according to an embodiment of the present invention;
FIG. 12 is an S-scan signal after thresholding in accordance with an embodiment of the present invention;
FIG. 13 is a flow chart illustrating an embodiment of the present invention.
Detailed Description
The present invention will now be described in further detail with reference to the accompanying drawings.
The following examples scan weld defects based on an ultrasonic phased array instrument of NI LABVIEW8.1 to obtain weld defect images.
The first embodiment is a method for quantitatively detecting a weld defect of friction stir welding based on an ultrasonic phased array, and a flow schematic diagram is shown in fig. 13, and the method comprises the following steps: s scanning the weld by using an ultrasonic phased array instrument to obtain an S scanning weld defect image, dividing the S scanning weld defect image into interested target areas, and extracting an S scanning signal scale and an S scanning signal image in the interested target areas respectively;
converting the S scanning signal image and the S scanning signal scale into a gray scale image, carrying out filtering and binarization processing on the gray scale image, and extracting the scale unit of the S scanning signal; setting the upper and lower threshold values of the image after the binarization of the S scanning signal, reserving points (determining the defect range according to the points) in the upper and lower threshold value range of the image after the binarization processing of the S scanning signal, determining the central X pixel coordinate, the Y pixel coordinate and the maximum pixel value in the X direction of the image formed by the points, and dividing the central X pixel coordinate of the image by the scale unit of the S scanning signal to obtain the defect size, the defect equivalent length and the defect equivalent width.
In the embodiment, flash and arc lines generated in the friction stir welding process are removed, so that two surfaces of a welding joint are kept smooth and flat; and placing the ultrasonic phased array probe on the surface of one side of the welding joint, keeping the end face of the ultrasonic phased array probe parallel to the surface of the test piece, and performing S scanning on the welding seam.
The S-scanning ultrasonic phased array instrument has the key parameters that the probe frequency is 5 MHz-10 MHz, the coupling mode adopts local water immersion, the deflection angle of an acoustic beam is 30-70 degrees, the focusing depth is the thickness of a lap joint plate, and the scanning mode is cross-weld zigzag scanning, so that the thickness of the whole lap joint is fully covered by ultrasonic waves, a detection blind area is avoided, and an S-scanning image is stored.
Image reading: and obtaining an S-scan view through programming, wherein the S-scan image comprises an S-scan image, a gate and an S-scan signal scale. Area division: and dividing the interested target region of the S-scan view, and extracting an S-scan image and an S-scan signal scale. Image processing: carrying out image conversion on the obtained S scanning image, converting a color RGB image into a gray level image, filtering, binarizing and extracting a characteristic value;
calibrating a scale: and carrying out image conversion on the acquired S scanning signal scale, converting the color RGB image into a gray image, filtering, binarizing and extracting scale units.
The second embodiment provides a method for quantitatively detecting the weld defects of friction stir welding based on an ultrasonic phased array, which comprises the following steps:
s scanning the weld by using an ultrasonic phased array instrument to obtain an S scanning weld defect image, dividing the S scanning weld defect image into interested target areas, and extracting an S scanning signal scale and an S scanning signal image in the interested target areas respectively;
converting the S scanning signal image and the S scanning signal scale into a gray scale image, carrying out filtering and binarization processing on the gray scale image, and extracting the scale unit of the S scanning signal; setting upper and lower threshold values of an image after binarization of an S scanning signal, reserving points in the range of the upper and lower threshold values in the image after binarization processing of the S scanning signal, determining a central X pixel coordinate, a Y pixel coordinate and a maximum pixel value in an X direction of the image formed by the points, and dividing the central X pixel coordinate of the image by a scale unit of the S scanning signal to obtain a defect size, a defect equivalent length and a defect equivalent width;
the method further comprises the following steps: a scanning is carried out on a welding seam by using an ultrasonic phased array instrument to obtain an A scanning welding seam defect image, an interested target area is divided for the A scanning welding seam defect image, and an A scanning signal scale and an A scanning signal image contained in the A scanning welding seam defect image are respectively extracted from the interested target area;
converting the A scanning signal image and the A scanning signal scale into a gray scale image, carrying out filtering and binarization processing on the gray scale image, and extracting a scale unit of the A scanning signal; converting the image after binarization processing of the scanning signal A into a two-dimensional array, and simultaneously rotating the two-dimensional array by 90 degrees to obtain a horizontal image; and setting a horizontal threshold line, reserving points which are higher than the height of the threshold line in the horizontal image, and dividing the maximum X pixel value in the reserved points by the scale unit of the A scanning signal to obtain the defect depth.
And placing the ultrasonic phased array probe on the surface of one side of the welding joint, keeping the end face of the ultrasonic phased array probe parallel to the surface of the test piece, and performing A scanning on the welding seam.
The key parameters for the S-scan ultrasonic phased array setup are as shown in example one.
The key parameters set by the A scanning ultrasonic phased array instrument are as follows, the frequency of a probe is 5 MHz-10 MHz, the coupling mode adopts local water immersion, the deflection angle of an acoustic beam is 45 degrees, and the focusing depth is the thickness of a lap joint plate; the thickness of the whole lap weld is fully covered by ultrasonic waves, a detection blind area is avoided, and an A scanning image is stored;
image reading: and acquiring an A-scan view through programming, wherein the A-scan view comprises an A-scan signal, a gate and an A-scan signal scale.
Area division: and dividing the interested target area of the A scanning view, and extracting an A scanning signal and an A scanning signal scale.
Image processing: carrying out image conversion on the obtained A scanning image, converting a color RGB image into a gray level image, filtering, carrying out binarization and extracting a characteristic value;
calibrating a scale: and carrying out image conversion on the acquired A scanning signal scale, converting the color RGB image into a gray image, filtering, binarizing and extracting scale units.
FIG. 1 is a friction stir welding weld defect inspection image of an ultrasonic phased array read under a NI LABVIEW8.1 programming environment.
The target region of interest is partitioned with respect to fig. 1. Fig. 2 is a scanning scale a, where the left side pixel value of the range is 8, the right side pixel value is 19, the top pixel value is 23, the bottom pixel value is 420, and 2mm occupies 58 pixels by calculation, that is, the scanning scale a is 29 pixels/mm.
Scanning signal area range: the left side pixel value is 22, the right side pixel value is 228, the top pixel value is 23, the bottom pixel value is 420, and fig. 3 shows an a-scan signal.
The scanning signal A is an RGB image, G is taken to obtain a monochromatic image, the monochromatic image is converted into a gray image, the pixel value range is 0-15, and 255 is used for replacing the pixel value range, so that a gray image 4 is obtained.
And (5) carrying out median filtering binarization on the image 4 to obtain an image 5.
In order to increase the image processing speed, the image of fig. 5 is converted into a two-dimensional array, and the two-dimensional array is rotated by 90 degrees, thereby obtaining fig. 6.
The extraction is performed on fig. 6, in which the horizontal line is the threshold line, the points in the horizontal image larger than the threshold line height are retained, the value of the division of the scale unit of the a-scan signal lower than the threshold line height is deleted, and fig. 7 is the a-scan signal after the threshold. The maximum X pixel value (peak X pixel coordinate of fig. 7 is 198) among the remaining points was divided by the a-scan scale unit of 29 pixels/mm, resulting in a defect depth of 6.83 mm.
Fig. 8 is an S-scan scale, where the left side pixel value of the range is 233, the right side pixel value is 660, the top side pixel value is 422, and the lower side pixel value is 434, and 2mm occupies 47 pixels by calculation, that is, the S-scan scale is 23.5 pixels/mm.
Fig. 9 shows an S-scan signal, where the left-side pixel value is 233, the right-side pixel value is 661, the top pixel value is 23, and the bottom pixel value is 420.
Fig. 10 is a grayscale map of the conversion of the S scan signal RGB.
Fig. 11 shows the filtered binarized S-scan signal.
Fig. 12 shows the S-scan signal after the threshold, and the number of pixels included in the image formed by the points is 1359, with the points in the upper and lower threshold ranges remaining in the image after the binarization processing of the S-scan signal. The image center has an X pixel coordinate of 158, a Y pixel coordinate of 223, and a maximum of 71 pixels in the X direction. The number is divided by 23.5 pixels/mm on the S-scan scale to give a defect size of 2.46mm2, an equivalent length of 3.02 mm and an equivalent width of 0.81 mm.
In the detection process, the ultrasonic phased array probe moves at a constant speed in a direction parallel to the welding seam, an image formed by a defect echo signal in the friction stir welding seam of the aluminum alloy vehicle body is received in real time, the size and position information of the defect is extracted in real time through the image processing module, the depth of the aluminum alloy friction stir welding defect can be positioned and quantitatively analyzed, compared with the method for judging the approximate position of the defect by simply using a waveform, the detection precision is more accurate, and compared with the workload required by ray detection, the welding seam detection efficiency is higher. The ultrasonic phased array welding line quality inspection device has a large utilization space in the aspect of ultrasonic phased array welding line quality inspection for friction stir welding, can cover a wide range of vehicle types and parts, and is worthy of further popularization and application.
The third embodiment corresponds to the above embodiments, the third embodiment provides a quantitative detection system for the weld defects of friction stir welding based on an ultrasonic phased array, which is characterized by comprising a defect image acquisition module, an S scanning image processing module and a defect information calculation module;
the defect image acquisition module is used for carrying out S scanning on the welding seam by using an ultrasonic phased array instrument to obtain an S scanning welding seam defect image;
the S-scanning image processing module is used for dividing the S-scanning weld defect image into interested target areas and extracting an S-scanning signal scale and an S-scanning signal image in the interested target areas respectively;
converting the S scanning signal image and the S scanning signal scale into a gray scale image, carrying out filtering and binarization processing on the gray scale image, and extracting the scale unit of the S scanning signal; setting an upper threshold and a lower threshold of the image after the binarization of the S scanning signal, reserving points in the range of the upper threshold and the lower threshold in the image after the binarization processing of the S scanning signal, and determining a defect range according to the reserved points;
the defect information calculation module is used for determining the central X pixel coordinate, the Y pixel coordinate and the maximum pixel value in the X direction of an image formed by the points in the defect range reserved by the S scanning image processing module, and dividing the central X pixel coordinate of the image by the scale unit of the S scanning signal to obtain the defect size, the defect equivalent length and the defect equivalent width.
In a fourth embodiment, on the basis of the third embodiment, the present embodiment further includes: the defect image acquisition module is also used for carrying out A scanning on the welding seam by using an ultrasonic phased array instrument to obtain an A scanning welding seam defect image;
the system also comprises an A scanning image processing module, wherein the A scanning image processing module is used for dividing the A scanning weld defect image into interested target areas and respectively extracting an A scanning signal scale and an A scanning signal image contained in the A scanning weld defect image in the interested target areas; converting the A scanning signal image and the A scanning signal scale into a gray scale image, carrying out filtering and binarization processing on the gray scale image, and extracting a scale unit of the A scanning signal; converting the image after binarization processing of the scanning signal A into a two-dimensional array, and simultaneously rotating the two-dimensional array by 90 degrees to obtain a horizontal image; setting a horizontal threshold line, and reserving points in the horizontal image, which are greater than the height of the threshold line;
the defect information calculation module is further configured to divide the maximum X pixel value among the points retained by the a-scan image processing module by the scale unit of the a-scan signal to obtain the defect depth.
It should be noted that the quantitative detection system for the weld defects of friction stir welding based on the ultrasonic phased array provided by the invention corresponds to the quantitative detection method for the weld defects of friction stir welding based on the ultrasonic phased array, and therefore, the detailed description of the quantitative detection system is omitted.
The above description is a preferred embodiment of the present invention, and is not intended to limit the scope of the present invention; it is intended that the following claims be interpreted as including all such alterations, modifications, and equivalents as fall within the true spirit and scope of the invention.
Claims (7)
1. The method for quantitatively detecting the weld defects of the friction stir welding based on the ultrasonic phased array is characterized by comprising the following steps of:
s scanning the weld by using an ultrasonic phased array instrument to obtain an S scanning weld defect image, dividing the S scanning weld defect image into interested target areas, and extracting an S scanning signal scale and an S scanning signal image in the interested target areas respectively;
converting the S scanning signal image and the S scanning signal scale into a gray scale image, carrying out filtering and binarization processing on the gray scale image, and extracting the scale unit of the S scanning signal; setting an upper threshold and a lower threshold of an image after binarization of an S scanning signal, reserving points in the range of the upper threshold and the lower threshold in the image after binarization processing of the S scanning signal, determining a defect range according to the reserved points, determining a central X pixel coordinate, a Y pixel coordinate and a maximum pixel value in an X direction of the image formed by the points in the defect range, and dividing the central X pixel coordinate of the image by a scale unit of the S scanning signal to obtain a defect size, a defect equivalent length and a defect equivalent width.
2. The method for quantitatively detecting the weld defects of the friction stir welding based on the ultrasonic phased array as claimed in claim 1, is characterized in that key parameters set by an S-scanning ultrasonic phased array instrument are as follows, the probe frequency is 5 MHz-10 MHz, the coupling mode adopts local water immersion, the deflection angle of an acoustic beam is 30-70 degrees, the focusing depth is the thickness of an overlap plate, the scanning mode is cross-weld zigzag scanning, the thickness of the whole overlap weld is fully covered by ultrasonic waves, a detection blind area is avoided, and an S-scanning image is obtained by scanning.
3. The ultrasonic phased array based friction stir welding weld defect quantitative detection method according to claim 1, characterized in that the method further comprises: a scanning is carried out on a welding seam by using an ultrasonic phased array instrument to obtain an A scanning welding seam defect image, an interested target area is divided for the A scanning welding seam defect image, and an A scanning signal scale and an A scanning signal image contained in the A scanning welding seam defect image are respectively extracted from the interested target area;
converting the A scanning signal image and the A scanning signal scale into a gray scale image, carrying out filtering and binarization processing on the gray scale image, and extracting a scale unit of the A scanning signal; converting the image after binarization processing of the scanning signal A into a two-dimensional array represented by pixels; setting an X pixel threshold, reserving points of which the X pixel values are larger than the threshold, and determining a defect range according to the reserved points; the depth of the defect is obtained by dividing the maximum X pixel value among the points within the defect range by the scale unit of the a scanning signal.
4. The method for quantitatively detecting the weld defects of the friction stir welding based on the ultrasonic phased array is characterized in that key parameters set by an A scanning ultrasonic phased array instrument are as follows, the probe frequency is 5 MHz-10 MHz, the coupling mode adopts local water immersion, the deflection angle of an acoustic beam is 45 degrees, and the focusing depth is the thickness of a lap joint plate; the thickness of the whole lap welding seam is fully covered by ultrasonic waves, a detection blind area is avoided, and an A scanning image is obtained through scanning.
5. The method for quantitatively detecting the weld defects of the friction stir welding based on the ultrasonic phased array as claimed in claim 1, wherein the ultrasonic phased array instrument is used for polishing and removing flash and arc lines on the surface of the welded joint after the friction stir welding before A scanning and S scanning of the weld, so that two surfaces of the welded joint are kept smooth and flat.
6. The quantitative detection system for the friction stir welding seam defects based on the ultrasonic phased array is characterized by comprising a defect image acquisition module, an S scanning image processing module and a defect information calculation module;
the defect image acquisition module is used for carrying out S scanning on the welding seam by using an ultrasonic phased array instrument to obtain an S scanning welding seam defect image;
the S-scanning image processing module is used for dividing the S-scanning weld defect image into interested target areas and extracting an S-scanning signal scale and an S-scanning signal image in the interested target areas respectively;
converting the S scanning signal image and the S scanning signal scale into a gray scale image, carrying out filtering and binarization processing on the gray scale image, and extracting the scale unit of the S scanning signal; setting an upper threshold and a lower threshold of the image after the binarization of the S scanning signal, reserving points in the range of the upper threshold and the lower threshold in the image after the binarization processing of the S scanning signal, and determining a defect range according to the reserved points;
the defect information calculation module is used for determining the central X pixel coordinate, the Y pixel coordinate and the maximum pixel value in the X direction of an image formed by the points in the defect range reserved by the S scanning image processing module, and dividing the central X pixel coordinate of the image by the scale unit of the S scanning signal to obtain the defect size, the defect equivalent length and the defect equivalent width.
7. The ultrasonic phased array based quantitative detection system for friction stir welding weld defects according to claim 6, wherein the defect image acquisition module is further configured to perform A-scanning on the weld by using an ultrasonic phased array instrument to obtain an A-scanning weld defect image;
the system also comprises an A scanning image processing module, wherein the A scanning image processing module is used for dividing the A scanning weld defect image into interested target areas and respectively extracting an A scanning signal scale and an A scanning signal image contained in the A scanning weld defect image in the interested target areas; converting the A scanning signal image and the A scanning signal scale into a gray scale image, carrying out filtering and binarization processing on the gray scale image, and extracting a scale unit of the A scanning signal; converting the image after binarization processing of the scanning signal A into a two-dimensional array, and simultaneously rotating the two-dimensional array by 90 degrees to obtain a horizontal image; setting a horizontal threshold line, and reserving points in the horizontal image, which are greater than the height of the threshold line;
the defect information calculation module is further configured to divide the maximum X pixel value among the points retained by the a-scan image processing module by the scale unit of the a-scan signal to obtain the defect depth.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114037682A (en) * | 2021-11-08 | 2022-02-11 | 中国科学院光电技术研究所 | Two-dimensional automatic detection method for optical element surface defects |
| CN114354755A (en) * | 2022-01-06 | 2022-04-15 | 中特检深燃安全技术服务(深圳)有限公司 | Detection method of town gas polyethylene pipeline |
| WO2024000953A1 (en) * | 2022-06-21 | 2024-01-04 | 苏州大学 | Testing method for welding quality of friction stir welded surface |
| US11878364B2 (en) | 2022-06-27 | 2024-01-23 | Soochow University | Method for detecting surface welding quality of friction stir welding |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106353410A (en) * | 2016-08-22 | 2017-01-25 | 南京越辰智能科技有限公司 | Ultrasonic phased array imaging detection device for aluminum alloy friction stir weldment |
| CN106841392A (en) * | 2016-12-17 | 2017-06-13 | 中国核工业二三建设有限公司 | A kind of phased array ultrasonic detecting method for nuclear power station BOSS weld seams |
| CN107576729A (en) * | 2017-09-15 | 2018-01-12 | 南京中车浦镇城轨车辆有限责任公司 | Weld defect detection and quick extraction system and method based on ultrasonic phase array |
| CN110687198A (en) * | 2019-10-11 | 2020-01-14 | 江西省锅炉压力容器检验检测研究院 | Method for detecting welding seam defect types of friction stir welding by ultrasonic phased array |
-
2020
- 2020-08-20 CN CN202010841753.0A patent/CN111983030A/en not_active Withdrawn
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106353410A (en) * | 2016-08-22 | 2017-01-25 | 南京越辰智能科技有限公司 | Ultrasonic phased array imaging detection device for aluminum alloy friction stir weldment |
| CN106841392A (en) * | 2016-12-17 | 2017-06-13 | 中国核工业二三建设有限公司 | A kind of phased array ultrasonic detecting method for nuclear power station BOSS weld seams |
| CN107576729A (en) * | 2017-09-15 | 2018-01-12 | 南京中车浦镇城轨车辆有限责任公司 | Weld defect detection and quick extraction system and method based on ultrasonic phase array |
| CN110687198A (en) * | 2019-10-11 | 2020-01-14 | 江西省锅炉压力容器检验检测研究院 | Method for detecting welding seam defect types of friction stir welding by ultrasonic phased array |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114037682A (en) * | 2021-11-08 | 2022-02-11 | 中国科学院光电技术研究所 | Two-dimensional automatic detection method for optical element surface defects |
| CN114354755A (en) * | 2022-01-06 | 2022-04-15 | 中特检深燃安全技术服务(深圳)有限公司 | Detection method of town gas polyethylene pipeline |
| WO2024000953A1 (en) * | 2022-06-21 | 2024-01-04 | 苏州大学 | Testing method for welding quality of friction stir welded surface |
| US11878364B2 (en) | 2022-06-27 | 2024-01-23 | Soochow University | Method for detecting surface welding quality of friction stir welding |
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