CN114643448A - Weld joint feature extraction device and method - Google Patents
Weld joint feature extraction device and method Download PDFInfo
- Publication number
- CN114643448A CN114643448A CN202210544632.9A CN202210544632A CN114643448A CN 114643448 A CN114643448 A CN 114643448A CN 202210544632 A CN202210544632 A CN 202210544632A CN 114643448 A CN114643448 A CN 114643448A
- Authority
- CN
- China
- Prior art keywords
- laser
- welding
- image
- welding gun
- ccd camera
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000000605 extraction Methods 0.000 title claims abstract description 39
- 238000000034 method Methods 0.000 title claims description 30
- 238000003466 welding Methods 0.000 claims abstract description 158
- 230000001678 irradiating effect Effects 0.000 claims abstract description 9
- 150000001875 compounds Chemical class 0.000 claims description 18
- 238000004364 calculation method Methods 0.000 claims description 16
- 230000011218 segmentation Effects 0.000 claims description 8
- 239000006059 cover glass Substances 0.000 claims description 5
- 238000007781 pre-processing Methods 0.000 claims description 5
- 239000000428 dust Substances 0.000 claims description 4
- 239000011324 bead Substances 0.000 claims description 3
- 238000012545 processing Methods 0.000 description 12
- 230000008569 process Effects 0.000 description 6
- 238000010586 diagram Methods 0.000 description 4
- 238000001914 filtration Methods 0.000 description 3
- 239000000779 smoke Substances 0.000 description 3
- 230000009977 dual effect Effects 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 230000009467 reduction Effects 0.000 description 2
- 238000012935 Averaging Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 230000007123 defense Effects 0.000 description 1
- 230000018109 developmental process Effects 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 239000011521 glass Substances 0.000 description 1
- 238000009499 grossing Methods 0.000 description 1
- 238000010438 heat treatment Methods 0.000 description 1
- 238000009776 industrial production Methods 0.000 description 1
- 238000009434 installation Methods 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 230000007246 mechanism Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 238000005192 partition Methods 0.000 description 1
- 230000001681 protective effect Effects 0.000 description 1
- 239000004065 semiconductor Substances 0.000 description 1
- 238000003860 storage Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
Images
Classifications
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B23—MACHINE TOOLS; METAL-WORKING NOT OTHERWISE PROVIDED FOR
- B23K—SOLDERING OR UNSOLDERING; WELDING; CLADDING OR PLATING BY SOLDERING OR WELDING; CUTTING BY APPLYING HEAT LOCALLY, e.g. FLAME CUTTING; WORKING BY LASER BEAM
- B23K37/00—Auxiliary devices or processes, not specially adapted to a procedure covered by only one of the preceding main groups
- B23K37/02—Carriages for supporting the welding or cutting element
- B23K37/0252—Steering means
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B23—MACHINE TOOLS; METAL-WORKING NOT OTHERWISE PROVIDED FOR
- B23K—SOLDERING OR UNSOLDERING; WELDING; CLADDING OR PLATING BY SOLDERING OR WELDING; CUTTING BY APPLYING HEAT LOCALLY, e.g. FLAME CUTTING; WORKING BY LASER BEAM
- B23K31/00—Processes relevant to this subclass, specially adapted for particular articles or purposes, but not covered by only one of the preceding main groups
- B23K31/02—Processes relevant to this subclass, specially adapted for particular articles or purposes, but not covered by only one of the preceding main groups relating to soldering or welding
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1628—Programme controls characterised by the control loop
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1694—Programme controls characterised by use of sensors other than normal servo-feedback from position, speed or acceleration sensors, perception control, multi-sensor controlled systems, sensor fusion
- B25J9/1697—Vision controlled systems
Abstract
The invention provides a welding seam feature extraction device and a welding seam feature extraction method. The device comprises: the main control unit is connected with the robot controller and the image acquisition card, and also comprises a sensor module which mainly consists of a first laser, a second laser and a CCD camera and is arranged at the front end of the welding gun; the first laser and the second laser are used for irradiating laser signals to the workpiece; the CCD camera is used for acquiring an image signal containing double laser stripes on the workpiece, and the image signal is converted into a digital signal by an image acquisition card and then is sent to the main control unit; the main control unit is used for obtaining the height of the welding gun and the tracking deviation of the welding seam through welding seam characteristic extraction, sending a deviation signal to the robot controller and controlling the welding gun on the welding robot to be aligned to the welding seam. According to the invention, the two lasers are arranged on the sensor module, so that the height of the welding gun and the tracking deviation of the welding seam can be accurately obtained, and the tracking precision of the welding seam is improved.
Description
Technical Field
The invention belongs to the technical field of welding processing, and particularly relates to a welding seam feature extraction device and method.
Background
Welding is a process of heating or pressurizing or both to make atoms of workpieces to be welded penetrate through each other so as to achieve firm connection. The welding technology is widely applied and is mainly applied to various industrial departments of aviation, aerospace, ships, bridges, large-scale hoisting machinery, national defense and the like at present. At present, a welding robot is generally used at home and abroad to realize automatic welding. In places which are difficult to reach manually and dangerous places such as aerospace, deep sea, narrow space areas and the like, a welding robot is required to be used for automatic welding. The seam tracking is an important means for realizing automatic welding, and the quality of products can be improved. The welding seam tracking means that a welding gun is used as a controlled object, a welding seam tracking sensor is used for collecting images, deviation information of the welding seam relative to the welding seam is obtained through an image processing technology, and the welding gun is controlled to be always positioned right above the welding seam by adopting a certain control method. The robot is used for realizing automatic welding, so that on one hand, the productivity is increased; on the other hand, the quality of the welding seam is improved, and the cost is saved.
The initial positioning of the weld gun is required prior to weld seam tracking. The initial positioning of the welding gun comprises the identification of the transverse deviation of the welding gun and the identification of the height of the welding gun. The welding gun transverse deviation is mainly obtained by processing a welding seam image collected in real time, then the deviation signal is transmitted to a control system, the control system receives the deviation signal and sends out a corresponding control signal, and the deviation is reduced or eliminated by executing a corresponding mechanism. The height identification of the welding gun has important significance for controlling the quality of the welding seam. In the actual welding process, the surface of the workpiece to be welded cannot be absolutely flat, and certain difficulty is brought to the welding process. In the prior art, the height of the welding gun is generally identified by a mark searching method, the height of a sensor is firstly calibrated, then the height value and the corresponding laser stripe distance are stored in a memory of a computer, and the height value of the welding gun is determined by looking up a table. The method has slow searching speed, occupies a large amount of memory of a computer, has discontinuous calibrated height values, and can not search some height values in a table.
Disclosure of Invention
In order to solve the above problems in the prior art, the present invention provides a weld feature extraction device and method.
In order to achieve the above object, the present invention adopts the following technical solutions.
In a first aspect, the present invention provides a weld feature extraction device, including: the main control unit is connected with the robot controller and the image acquisition card, and also comprises a sensor module which mainly consists of a first laser, a second laser and a CCD camera and is arranged at the front end of the welding gun; the first laser and the second laser are used for irradiating laser signals to the workpiece; the CCD camera is used for acquiring an image signal containing double laser stripes on the workpiece, and the image signal is converted into a digital signal by an image acquisition card and then is sent to the main control unit; the main control unit is used for obtaining the height of the welding gun and the tracking deviation of the welding seam through welding seam characteristic extraction, sending a deviation signal to the robot controller and controlling the welding gun on the welding robot to be aligned to the welding seam.
Further, the weld joint feature extraction comprises image preprocessing, double-laser stripe segmentation and curve fitting, and tracking deviation calculation.
Furthermore, the sensor module further comprises a first reflective mirror and a second reflective mirror which are obliquely arranged under the first laser and the second laser respectively, and the first reflective mirror and the second reflective mirror are used for reflecting laser signals emitted by the first laser and the second laser and irradiating the laser signals onto a workpiece.
Further, the sensor module further includes a filter and a polarizer mounted in front of the lens of the CCD camera.
Still further, the sensor module further includes a cover glass plate mounted adjacent to the side of the welding gun for preventing dust and spatter from entering the sensor module.
Still further, the method for calculating the height of the welding gun comprises the following steps:
calculating the actual physical length of each pixel point
：
In the formula (I), the compound is shown in the specification,
the focal height of the CCD camera, i.e. the vertical distance from the workpiece is
The actual length corresponding to the width of the image,
is the number of pixel points of the image width,
the field angle of the CCD camera;
distance between two laser lines on workpiece
Comprises the following steps:
in the formula (I), the compound is shown in the specification,
the distance between two laser stripes on the image is represented by the number of pixel points;
in the formula (I), the compound is shown in the specification,
、
respectively are included angles between the first reflective mirror and the second reflective mirror and the vertical direction,
=
，
，
the distance between the intersection of the laser and the focus of the CCD camera is reflected by a first reflector and a second reflector, and the first reflector and the second reflector are installed at the same height and are symmetrical about the symmetry axis of the CCD camera;
obtained by the formulas (2) and (3):
height of welding gunHComprises the following steps:
in the formula (I), the compound is shown in the specification,
is the height difference between the welding gun and the focus of the CCD camera.
Still further, the method for calculating the weld joint tracking deviation comprises the following steps:
calculating the ordinate of the welding gun in the image:
in the formula (I), the compound is shown in the specification,
the horizontal distance of the welding gun from the center of the sensor module,
calculated by equation (1), the image size is
Pixel points;
fitting equation according to weld line straight line
Calculating the abscissa of the welding gun
：
Calculating the deviation between the welding gun and the welding seamΔ：
In the formula (I), the compound is shown in the specification,
the abscissa of the weld.
Further, the CCD camera is a WAT-704R type industrial camera.
Further, the image acquisition card is a DH-CG410 type acquisition card.
In a second aspect, the invention provides a method for extracting weld features by using the device, which comprises the following steps:
the first laser and the second laser irradiate laser signals to the surface of the workpiece;
the CCD camera shoots an image containing double laser stripes on the surface of the workpiece in real time;
the main control unit acquires the image in real time through an image acquisition card, and the height of the welding gun and the tracking deviation of the welding seam are obtained through welding seam characteristic extraction;
and the robot controller receives the deviation signal sent by the main control unit and controls the welding robot to enable the welding gun to be aligned with the welding seam.
Compared with the prior art, the invention has the following beneficial effects.
The invention is provided with a main control unit, a robot controller, an image acquisition card and a sensor module which mainly comprises a first laser, a second laser and a CCD camera and is arranged at the front end of a welding gun, wherein the first laser and the second laser are used for irradiating laser signals to a workpiece, the CCD camera is used for acquiring image signals containing double laser stripes on the workpiece, and the main control unit is used for obtaining the height of the welding gun and the tracking deviation of the welding seam through welding seam characteristic extraction and sending the deviation signals to the robot controller to control the welding gun on the welding robot to align the welding seam. According to the invention, the two lasers are arranged on the sensor module, so that the height of the welding gun and the tracking deviation of the welding seam can be accurately obtained, and the tracking precision of the welding seam is improved.
Drawings
Fig. 1 is a block diagram of a weld feature extraction apparatus according to an embodiment of the present invention;
FIG. 2 is a schematic view of upper and lower stripes, the left being the upper stripe and the right being the lower stripe;
FIG. 3 is a schematic view of a weld gun height calculation;
FIG. 4 is a schematic diagram of weld bead deviation calculation;
fig. 5 is a flowchart of a method for extracting weld features by using the device according to an embodiment of the present invention.
In the figure: 1-a sensor module, 11-a first laser, 12-a second laser, 13-a CCD camera, 14-a first reflector, 15-a second reflector, 16-a protective glass plate, 2-a main control unit, 3-an image acquisition card, 4-a robot controller and 5-a workpiece.
Detailed Description
In order to make the technical solution and advantages of the present invention more clear and obvious, the present invention is further described with reference to the accompanying drawings and the detailed description. It is to be understood that the described embodiments are merely exemplary of the invention, and not restrictive of the full scope of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Fig. 1 is a block diagram of a weld feature extraction apparatus according to an embodiment of the present invention, including: the device comprises a main control unit 2, a robot controller 4 and an image acquisition card 3 which are connected with the main control unit 2, and a sensor module 1 which mainly comprises a first laser 11, a second laser 12 and a CCD camera 13 and is arranged at the front end of a welding gun; the first laser 11 and the second laser 12 are used for irradiating laser signals to the workpiece 5; the CCD camera 13 is used for acquiring an image signal containing double laser stripes on the workpiece 5, and the image signal is converted into a digital signal by the image acquisition card 3 and then is sent to the main control unit 2; the main control unit 2 is used for obtaining the height of the welding gun and the tracking deviation of the welding seam through welding seam feature extraction, sending a deviation signal to the robot controller 4, and controlling the welding gun on the welding robot to align the welding seam.
The device mainly comprises a main control unit 2, a robot controller 4, an image acquisition card 3 and a sensor module 1, wherein the sensor module 1 mainly comprises a first laser 11, a second laser 12 and a CCD camera 13. The connection relationship of the modules is shown in fig. 1, the robot controller 4 and the image acquisition card 3 are both electrically connected with the main control unit 2, and the image acquisition card 3 is electrically connected with the CCD camera 13. The embodiment realizes the welding operation to the workpiece 5 by controlling the position of the welding gun by the welding robot, and the sensor module 1 and the welding gun are both installed on the welding robot. The functional principle of each component will be described separately below.
The sensor module 1 belongs to a structured light vision sensor and mainly comprises a CCD camera 13 and a laser, wherein the laser emits laser signals to the surface of a workpiece 5, and the CCD camera 13 shoots an image containing laser stripes on the surface of the workpiece 5. The biggest difference from the existing structured light vision sensor is that the sensor module 1 of the present embodiment is modified from the existing single laser to provide two lasers, i.e., the first laser 11 and the second laser 12. The two lasers simultaneously emit laser signals to the surface of the workpiece 5, and the CCD camera 13 can shoot an image containing double laser stripes. The sensor module 1 is arranged at the front end of the welding gun in the welding direction, and a certain height difference exists between the sensor module 1 and the welding gun; the two lasers are located at the same height on both sides of the CCD camera 13. The double laser stripes comprise welding gun height information and welding line deviation information, and feature extraction is carried out based on the double laser stripes, so that high-precision welding gun height and welding line deviation can be obtained. Two lasers, optionally semiconductor lasers, are the most important components of the sensor module 1. Practice shows that the line width of the laser emitted by the laser is less than 1mm when the distance between the laser and an outlet is 120mm, and the effect of the shot image is optimal; when the wavelength is 600-700 nm, the arc light is less, so the wavelength of the laser is 650 nm.
The main control unit 2 is a control and data processing center of the device, is mainly used for completing data processing tasks, and coordinates the work of other modules by outputting various control signals. The data processing tasks completed by the main control unit 2 mainly include: weld joint feature extraction is performed by processing an image shot by the CCD camera 13, and the height of the welding gun and the weld joint deviation are calculated. The main control unit 2 outputs a deviation signal to the robot controller 4 to control the welding robot, thereby controlling the position of the welding gun. Since field control is required, the main control unit 2 generally employs an industrial control computer in which image processing software is installed. The image processing software is written by VC + +6.0 in combination with an open source computer vision library OpenCV. VC + +6.0 is a very powerful software development tool, and is widely used in the fields of industrial production, image processing, robots, etc. because it has the advantages of flexible operation, high efficiency, etc.
The image acquisition card 3 is connected with the CCD camera 13 through a video cable and is mainly used for acquiring images shot by the CCD camera 13 to the main control unit 2. The analog image signal is converted into a digital signal and then stored in the buffer memory of the main control unit 2 for the CPU to call.
And a robot controller 4 for controlling the welding robot. The robot controller 4 is a controller dedicated to control of the robot and associated with the welding robot, and is provided by the manufacturer. The robot controller 4 is connected with the main control unit 2 through an external communication interface, and controls the welding robot by receiving and analyzing a control instruction sent by the main control unit 2.
As an optional embodiment, the weld joint feature extraction comprises image preprocessing, double-laser stripe segmentation and curve fitting, and tracking deviation calculation.
In this embodiment, the weld feature extraction includes several steps, such as image preprocessing, stripe segmentation, fitting, and deviation calculation. The image preprocessing method mainly comprises the following steps: ROI extraction, filtering processing, image threshold segmentation, edge extraction and deburring. When the welding seam is tracked, strict requirements are required on image processing time due to real-time requirements. And the characteristic information in the acquired welding seam image only occupies a small part of the whole image information, so that the processing speed and the welding seam tracking efficiency are improved, ROI extraction needs to be carried out on the acquired welding seam image, and the image processing time is reduced. Common ROI extraction methods include a human-computer interaction method, a method based on a point of regard, a method based on a visual attention model, a method based on specific object segmentation, and the like. Interference such as arc light, smoke, splash and the like can be generated in the welding process, so that a large amount of noise exists in the acquired image, and the noise can influence subsequent feature extraction and feature identification. Therefore, filtering and noise reduction processing is required for the image. The windowed image may be denoised using a fourier transform in the frequency domain. The image threshold segmentation is to segment the image by binarizing the image. Edge extraction and deburring are achieved by acquiring the boundaries of an image by using a Canny operator. The Canny operator has the function of smoothing the image boundary and can play a role in filtering and noise reduction. The double laser stripe segmentation is realized by averaging the extracted image boundaries to obtain the center line of the weld, and the schematic diagram of the obtained upper and lower stripes is shown in fig. 2. Windowing the left straight line, the left oblique straight line, the right oblique straight line and the right straight line of the stripe, linearly fitting the image subjected to windowing by adopting a least square method, and then solving the characteristic point by utilizing intersection of the straight lines subjected to fitting. The tracking deviation calculation comprises height identification of the welding gun and deviation calculation of the welding seam, and is realized by calculation based on the obtained geometric characteristics of the upper and lower stripes and the installation parameters of the sensor module 1. The following examples will give specific calculation methods.
As an optional embodiment, the sensor module 1 further includes a first reflective mirror 14 and a second reflective mirror 15, which are respectively installed under the first laser 11 and the second laser 12 and are obliquely placed, and are respectively used for reflecting the laser signals emitted by the first laser 11 and the second laser 12 and then irradiating the laser signals onto the workpiece 5.
The sensor module 1 of the present embodiment is further provided with a first reflecting mirror 14 and a second reflecting mirror 15 which are installed to be obliquely placed right below the first laser 11 and the second laser 12. The laser generated by the first laser 11 and the laser generated by the second laser 12 are vertically irradiated downwards, irradiate the first reflective mirror 14 and the second reflective mirror 15, reflect and irradiate the surface of the workpiece 5, and then are reflected and scattered by the surface of the workpiece 5 to enter the field range of the CCD camera 13. The angle of inclination of the two mirrors can be adjusted, for example to 15 ° each, as shown in figure 3.
As an alternative embodiment, the sensor module 1 further includes a filter and a polarizer mounted in front of the lens of the CCD camera 13.
Because a lot of smoke and splashes exist in the welding process, in order to prevent the smoke and splashes from entering the field range of the CCD camera 13 of the sensor module 1 and further polluting the acquired image, an optical filter and a polarizing film are arranged in front of the lens of the CCD camera 13.
As an alternative embodiment, the sensor module 1 further comprises a cover glass plate 16 mounted adjacent the side of the torch to prevent dust and spatter from entering the sensor module 1.
In order to prevent the dust and spatter generated during welding from entering the sensor module 1, the present embodiment is further provided with a spatter-proof partition plate, i.e., a cover glass plate 16, at a side close to the welding gun. The mounting position of the cover glass plate 16 is shown in fig. 1.
As an alternative embodiment, the method for calculating the height of the welding gun comprises:
calculating the actual physical length of each pixel point
：
In the formula (I), the compound is shown in the specification,
the focal point height of the CCD camera 13, namely the vertical distance from the workpiece 5 is
The actual length corresponding to the width of the image,
is the number of pixel points of the image width,
the angle of view of the CCD camera 13;
distance between two laser lines on workpiece 5
Comprises the following steps:
in the formula (I), the compound is shown in the specification,
the distance between two laser stripes on the image is shown, and the unit is the number of pixel points;
in the formula (I), the compound is shown in the specification,
、
the angles between the first reflective mirror 14 and the second reflective mirror 15 and the vertical direction are respectively,
=
，
，
the first reflector 14 and the second reflector 15 are installed at the same height and are symmetrical about the symmetry axis of the CCD camera 13 for the distance between the intersection point of the laser reflected by the first reflector 14 and the second reflector 15 and the focus of the CCD camera 13;
obtained by the formulas (2) and (3):
height of welding gunHComprises the following steps:
in the formula (I), the compound is shown in the specification,
is the height difference between the welding gun and the focal point of the CCD camera 13.
The embodiment provides a technical scheme for calculating the height of the welding gun. Because the welding gun and the sensor module 1 are different by a fixed distance when being installed
The calculation of the height of the welding gun can therefore be converted into a calculation of the height of the sensor module 1. The present embodiment calculates the height of the sensor module 1 based on the geometric positional relationship of the first laser 11, the second laser 12, the CCD camera 13, the first reflecting mirror 14, and the second reflecting mirror 15, as shown in fig. 3. The specific calculation model is shown in the above formulas (1) - (6), and the detailed explanation is not provided here.
As an alternative embodiment, the method for calculating the weld joint tracking deviation includes:
calculating the ordinate of the welding gun in the image:
in the formula (I), the compound is shown in the specification,
the horizontal distance of the welding gun from the center of the sensor module 1,
calculated by equation (1), the image size is
Pixel points;
fitting equation according to weld line straight line
Calculating the abscissa of the welding gun
：
Calculating the deviation between the welding gun and the welding seamΔ：
In the formula (I), the compound is shown in the specification,
the abscissa of the weld.
The embodiment provides a technical scheme for calculating the weld joint tracking deviation. In order to automate the welding process and improve the quality of the weld seam, the welding torch must be controlled in real time to be positioned directly above the weld seam, which requires that the deviation between the welding torch and the weld seam be acquired in real time. In the device according to the present embodiment, the sensor module 1 is mounted in front of the welding gun (in the welding direction) at a fixed value
Therefore, the position of the welding gun can be predicted according to the connecting line of the two laser stripe groove vertexes. Compared with the existing weld joint sensor module 1 with a single laser, the dual laser sensing mode of the embodiment can reduce the lead error. The deviation model between the welding gun and the welding seam is shown in figure 4, the position of the welding gun is shown as a point C in the figure, and the deviation model is calibrated before weldingX C . The image is sized to be nxm pixels, and theoretically the welding gun should be in line with the weld if a single one is usedIn the laser, the theoretical position of the torch is B, D points in the figure, and in the twin laser of the present embodiment, the theoretical position of the torch is a point a in the figure. It is clear that the accuracy of the dual laser scheme is better than the accuracy of the single laser scheme, which can effectively reduce the pre-error of the sensor module 1. The specific calculation model of the weld joint deviation is shown in the above formulas (7) - (9), and detailed explanation is not provided here.
As an alternative embodiment, the CCD camera 13 is a WAT-704R type industrial camera.
This embodiment gives a specific model of the CCD camera 13. In this embodiment, the CCD camera 13 is an industrial camera of the model WAT-704R. The camera can meet the requirements of miniaturization and light weight. The main technical parameters are as follows: the focal length is 3.8mm and is adjustable; viewing angle range of (V x H) 510*400(ii) a The effective pixel is (V × H) 768 × 554.
As an alternative embodiment, the image acquisition card 3 is a DH-CG410 type acquisition card.
This embodiment shows a specific model of the image capture card 3. In this embodiment, the image acquisition card 3 is a DH-CG410 type image acquisition card. The main performance characteristics are as follows:
standard PAL, NTSC color/black and white video signals;
maximum resolution of the image: 768 × 576 × 32bit (pal), 640 × 480 × 32bit (ntsc);
flexibly acquiring images: the method can be carried out in various modes such as single field, single frame, continuous field, continuous frame, several fields or several frames at intervals and the like;
the system supports a plurality of image display and storage formats of YUV4:2, RGB32, RGB24, RGB15, RGB16 and Y8 Bit;
the brightness, hue, color saturation, contrast of the image can be programmably set.
Fig. 5 is a flowchart of a method for extracting weld features by using the device according to an embodiment of the present invention, where the method includes the following steps:
103, the main control unit 2 acquires the image in real time through the image acquisition card 3, and the height of the welding gun and the tracking deviation of the welding seam are obtained through welding seam feature extraction;
and 104, the robot controller 4 receives the deviation signal sent by the main control unit 2 and controls the welding robot to enable the welding gun to be aligned with the welding seam.
Compared with the technical solution of the embodiment of the apparatus shown in fig. 1, the method of this embodiment has similar implementation principle and technical effect, and is not described herein again.
The above description is only for the specific embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. A weld feature extraction device, comprising: the main control unit is connected with the robot controller and the image acquisition card, and also comprises a sensor module which mainly consists of a first laser, a second laser and a CCD camera and is arranged at the front end of the welding gun; the first laser and the second laser are used for irradiating laser signals to the workpiece; the CCD camera is used for acquiring an image signal containing double laser stripes on the workpiece, and the image signal is converted into a digital signal by an image acquisition card and then is sent to the main control unit; the main control unit is used for obtaining the height of the welding gun and the tracking deviation of the welding seam through welding seam characteristic extraction, sending a deviation signal to the robot controller and controlling the welding gun on the welding robot to be aligned to the welding seam.
2. The weld joint feature extraction device according to claim 1, wherein the weld joint feature extraction includes image preprocessing, double-laser stripe segmentation and curve fitting, and tracking deviation calculation.
3. The weld joint feature extraction device according to claim 1, wherein the sensor module further comprises a first reflective mirror and a second reflective mirror which are obliquely arranged right below the first laser and the second laser respectively, and are used for reflecting laser signals emitted by the first laser and the second laser and irradiating the laser signals onto a workpiece.
4. The weld bead feature extraction apparatus according to claim 1, wherein the sensor module further includes a filter and a polarizing plate installed in front of a lens of the CCD camera.
5. The weld bead feature extraction apparatus according to claim 1, wherein the sensor module further includes a cover glass plate mounted on a side near the welding gun for preventing dust and spatter from entering the sensor module.
6. The weld feature extraction device according to claim 3, wherein the calculation method of the welding gun height includes:
calculating the actual physical length of each pixel point
：
In the formula (I), the compound is shown in the specification,
the focal height of the CCD camera, i.e. the vertical distance from the workpiece is
The actual length corresponding to the width of the image,
is a pixel of image widthThe number of points is counted,
the angle of view of the CCD camera;
distance between two laser lines on workpiece
Comprises the following steps:
in the formula (I), the compound is shown in the specification,
the distance between two laser stripes on the image is represented by the number of pixel points;
in the formula (I), the compound is shown in the specification,
、
respectively are included angles between the first reflective mirror and the second reflective mirror and the vertical direction,
=
，
，
the distance between the intersection point of the laser reflected by the first reflector and the second reflector and the focus of the CCD camera is obtained, and the first reflector and the second reflector are installed at the same height and are symmetrical about the symmetry axis of the CCD camera;
obtained by the formulas (2) and (3):
height of welding gunHComprises the following steps:
in the formula (I), the compound is shown in the specification,
is the height difference between the welding gun and the focus of the CCD camera.
7. The weld feature extraction device according to claim 6, wherein the calculation method of the weld tracking deviation includes:
calculating the ordinate of the welding gun in the image:
in the formula (I), the compound is shown in the specification,
the horizontal distance of the welding gun from the center of the sensor module,
calculated by equation (1), the image size is
Pixel points;
fitting equation according to weld line straight line
Calculating the abscissa of the welding gun
：
Calculating the deviation between the welding gun and the welding seamΔ：
In the formula (I), the compound is shown in the specification,
the abscissa of the weld.
8. The weld feature extraction device according to claim 1, wherein the CCD camera is a WAT-704R type industrial camera.
9. The weld joint feature extraction device according to claim 1, wherein the image acquisition card is a DH-CG410 type acquisition card.
10. A method for weld feature extraction using the apparatus of claim 1, comprising the steps of:
the first laser and the second laser irradiate laser signals to the surface of the workpiece;
the CCD camera shoots an image containing double laser stripes on the surface of the workpiece in real time;
the main control unit acquires the image in real time through an image acquisition card, and the height of the welding gun and the tracking deviation of the welding seam are obtained through welding seam characteristic extraction;
and the robot controller receives the deviation signal sent by the main control unit and controls the welding robot to enable the welding gun to be aligned with the welding seam.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210544632.9A CN114643448B (en) | 2022-05-19 | 2022-05-19 | Weld joint feature extraction device and method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210544632.9A CN114643448B (en) | 2022-05-19 | 2022-05-19 | Weld joint feature extraction device and method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN114643448A true CN114643448A (en) | 2022-06-21 |
| CN114643448B CN114643448B (en) | 2022-09-27 |
Family
ID=81996582
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210544632.9A Active CN114643448B (en) | 2022-05-19 | 2022-05-19 | Weld joint feature extraction device and method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114643448B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115283780A (en) * | 2022-08-11 | 2022-11-04 | 山东水总有限公司 | Welding seam identification and welding gun positioning construction process |
Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2003154456A (en) * | 2001-11-21 | 2003-05-27 | Fuji Electric Co Ltd | Automatic welding equipment |
| CN102528231A (en) * | 2011-12-30 | 2012-07-04 | 南昌大学 | Double-line cross laser sensing method for seam tracking |
| CN103203526A (en) * | 2012-01-16 | 2013-07-17 | 成都熊谷加世电器有限公司 | Laser visual tracking system |
| CN104668738A (en) * | 2015-02-02 | 2015-06-03 | 南昌大学 | Cross type double-line laser vision sensing welding gun height real-time identification system and method |
| CN104741778A (en) * | 2015-03-30 | 2015-07-01 | 中国石油天然气集团公司 | Welding seam tracking and controlling system for combined welding |
| CN106141426A (en) * | 2015-04-28 | 2016-11-23 | 大族激光科技产业集团股份有限公司 | A kind of optical imaging system followed the trail of for laser welded seam |
| CN109676243A (en) * | 2019-01-21 | 2019-04-26 | 苏州实创德光电科技有限公司 | Weld distinguishing and tracking system and method based on dual laser structure light |
| CN110064819A (en) * | 2019-05-14 | 2019-07-30 | 苏州实创德光电科技有限公司 | The extraction of cylinder longitudinal seam characteristic area, welding seam tracking method and system based on structure light |
| CN111695575A (en) * | 2020-06-06 | 2020-09-22 | 南京理工大学 | Weld image feature point extraction method based on improved mean filtering method |
| CN112296515A (en) * | 2019-08-01 | 2021-02-02 | 通用汽车环球科技运作有限责任公司 | System and method for multi-tasking laser welding |
| CN113798634A (en) * | 2021-08-18 | 2021-12-17 | 中国科学院自动化研究所 | Method, system and equipment for teaching spatial circular weld and tracking weld |
-
2022
- 2022-05-19 CN CN202210544632.9A patent/CN114643448B/en active Active
Patent Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2003154456A (en) * | 2001-11-21 | 2003-05-27 | Fuji Electric Co Ltd | Automatic welding equipment |
| CN102528231A (en) * | 2011-12-30 | 2012-07-04 | 南昌大学 | Double-line cross laser sensing method for seam tracking |
| CN103203526A (en) * | 2012-01-16 | 2013-07-17 | 成都熊谷加世电器有限公司 | Laser visual tracking system |
| CN104668738A (en) * | 2015-02-02 | 2015-06-03 | 南昌大学 | Cross type double-line laser vision sensing welding gun height real-time identification system and method |
| CN104741778A (en) * | 2015-03-30 | 2015-07-01 | 中国石油天然气集团公司 | Welding seam tracking and controlling system for combined welding |
| CN106141426A (en) * | 2015-04-28 | 2016-11-23 | 大族激光科技产业集团股份有限公司 | A kind of optical imaging system followed the trail of for laser welded seam |
| CN109676243A (en) * | 2019-01-21 | 2019-04-26 | 苏州实创德光电科技有限公司 | Weld distinguishing and tracking system and method based on dual laser structure light |
| CN110064819A (en) * | 2019-05-14 | 2019-07-30 | 苏州实创德光电科技有限公司 | The extraction of cylinder longitudinal seam characteristic area, welding seam tracking method and system based on structure light |
| CN112296515A (en) * | 2019-08-01 | 2021-02-02 | 通用汽车环球科技运作有限责任公司 | System and method for multi-tasking laser welding |
| CN111695575A (en) * | 2020-06-06 | 2020-09-22 | 南京理工大学 | Weld image feature point extraction method based on improved mean filtering method |
| CN113798634A (en) * | 2021-08-18 | 2021-12-17 | 中国科学院自动化研究所 | Method, system and equipment for teaching spatial circular weld and tracking weld |
Non-Patent Citations (2)
| Title |
|---|
| 赵滨: "双线激光视觉传感焊缝跟踪图像处理", 《双线激光视觉传感焊缝跟踪图像处理》 * |
| 高向东等: "熔池图像质心算法的焊缝位置测量模型", 《焊接学报》 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115283780A (en) * | 2022-08-11 | 2022-11-04 | 山东水总有限公司 | Welding seam identification and welding gun positioning construction process |
| CN115283780B (en) * | 2022-08-11 | 2024-04-19 | 山东水总有限公司 | Weld joint identification and welding gun positioning construction process |
Also Published As
| Publication number | Publication date |
|---|---|
| CN114643448B (en) | 2022-09-27 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN210046133U (en) | Welding seam visual tracking system based on laser structured light | |
| CN109226967B (en) | Active laser vision steady weld joint tracking system for laser-arc hybrid welding | |
| CN109483017A (en) | A kind of seam tracking system and its optimization method based on image recognition | |
| WO2022188482A1 (en) | Active and passive vision combination-based welding deviation detection system and detection method | |
| CN108127217B (en) | Welding device and method for automatic guided welding of end face weld joint of spiral plate type heat exchanger | |
| CN114643448B (en) | Weld joint feature extraction device and method | |
| CN108032011A (en) | Initial point guiding device and method are stitched based on laser structure flush weld | |
| CN203380508U (en) | Laser processing system with machine vision | |
| CN107843202B (en) | Gap and face difference vision measurement device and method matched with robot | |
| CN114140439A (en) | Laser welding seam feature point identification method and device based on deep learning | |
| CN105414710A (en) | Active and passive visual welding pool composited sensing device and sensing method realized through same | |
| CN113525631A (en) | Underwater terminal docking system and method based on optical visual guidance | |
| CN112304951A (en) | Visual detection device and method for high-reflection welding seam through binocular single-line light path | |
| CN108620714B (en) | Welding deviation detection system based on GMAW (gas metal arc welding) molten pool profile characteristics and detection method thereof | |
| CN107790853A (en) | Ship's ladder robot broken line angle welding intelligent identification device and method | |
| CN113894386A (en) | Dual-sensing dual-wavelength integrated weld joint tracking sensor and deviation rectifying method | |
| Ye et al. | Weld seam tracking based on laser imaging binary image preprocessing | |
| CN206010106U (en) | Ship's ladder robot broken line angle welding intelligent identification device | |
| CN206952357U (en) | Weld seam tracking sensor | |
| CN1511676A (en) | Laser structure light vision sensor | |
| CN112894133B (en) | Laser welding system and welding spot position extraction method | |
| CN114909993A (en) | High-precision laser projection visual three-dimensional measurement system | |
| CN114523236A (en) | Intelligent automatic detection platform based on machine vision | |
| CN109612581B (en) | Diffuse reflection imaging strong laser parameter measuring device with camera protection function | |
| CN209902467U (en) | Multifunctional visual positioning laser main beam system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| TR01 | Transfer of patent right | ||
| TR01 | Transfer of patent right |
Effective date of registration: 20231023 Address after: 430223 plant 1 of Wuhan Meguiar Electronics Co., Ltd., No. 1, No. 2 Road, Dongyi Industrial Park, Donghu Development Zone, Wuhan City, Hubei Province Patentee after: XIANFUSI TECHNOLOGY (WUHAN) CO.,LTD. Patentee after: WUHAN DONGFANG JUNCHI PRECISION MANUFACTURING CO.,LTD. Address before: 430223 plant 1 of Wuhan Meguiar Electronics Co., Ltd., No. 1, No. 2 Road, Dongyi Industrial Park, Donghu Development Zone, Wuhan City, Hubei Province Patentee before: XIANFUSI TECHNOLOGY (WUHAN) CO.,LTD. |