CN114769962B - Weld joint recognition tracking system of mobile welding robot based on visual sense - Google Patents
Weld joint recognition tracking system of mobile welding robot based on visual sense Download PDFInfo
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- 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
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Abstract
The invention belongs to the technical field of welding robot control, and discloses a welding seam identification tracking system of a mobile welding robot based on visual sensing, wherein a visual sensing module is used for shooting an optical image of a welding seam through a camera, converting the optical image into a target video, and transmitting the target video to an image acquisition card for digitization to form welding seam digital image data; the welding seam track module receives the welding seam digital image data formed by the visual sensing module, sends the obtained welding seam digital image data to the welding robot, and forms welding seam track data according to the welding seam digital image data; and the welding control module is used for receiving the control of the welding seam track module, controlling the position of the welding gun along the welding seam according to the welding seam track data, moving the welding gun and controlling a servo motor of a movement shaft of the welding robot. The invention can acquire enough weld images and provide complete and accurate data for the control of the welding robot and the formation of weld tracks.
Description
Technical Field
The invention belongs to the technical field of welding robot control, and particularly relates to a weld joint identification tracking system of a mobile welding robot based on visual sensing.
Background
At present, in order to realize pre-welding guiding, the position of a workpiece and a welding line must be firstly identified through a visual sensing system, the position of a key point of welding is determined, two-dimensional or three-dimensional coordinates of the key point are established and sent to a robot, an end effector of the robot is moved to a welding starting point, the pre-welding guiding is automatically completed, and the accuracy and the identification precision of the welding line identification directly influence the precision of the welding line tracking.
In the first prior art, CN201710592289.4 is a right-angle flow hole weld joint identification tracking welding method, and discloses a right-angle flow hole weld joint identification tracking method, which comprises the following steps: the ultrasonic sensor detects the distance between the front workpiece and sends out a turning signal; the robot body moves according to the track planning; the movement of the transverse sliding block is realized by superposition of track planning and real-time tracking control; rotating an arc sensor to track welding seams of a welding section; the laser vision sensor identifies characteristic points of the water flow holes; and identifying the type of the water flowing hole according to the characteristic points and the step count of the water flowing hole, guiding the telescopic switching of the welding gun, and completing the automatic identification and tracking of the welding seam. The weld joint identification tracking method is automatically completed by the autonomous mobile welding robot, solves the problem that the existing welding robot cannot automatically identify and track the welding joint of the right-angle flow hole, realizes real welding automation, and improves welding efficiency and welding quality.
In the second prior art, a weld tracking system based on a TOFD flaw detector and a weld tracking method thereof are provided by the CN202010922694. X. The weld tracking system includes: TOFD emission probe, first receiving probe, second receiving probe, scanning frame, TOFD flaw detection module, weld joint identification module, module and mechanical adjustment module. And one TOFD transmitting probe corresponds to the first receiving probe and the second receiving probe simultaneously, the first receiving probe is used for receiving diffraction signals of weld defects to realize TOFD flaw detection of the weld, and the second receiving probe is used for receiving first diffraction secondary reflection signals of weld toes to realize weld center position identification and weld tracking. The welding seam tracking system works in a single-sending double-receiving mode, so that the system realizes welding seam tracking at the same time of welding seam TOFD flaw detection, and the working mode is simple and reliable, thereby being beneficial to improving the detection reliability and the detection efficiency. In addition, the system has simple structure, low cost and good real-time performance, and the weld tracking precision can meet the TOFD flaw detection requirement.
In the third prior art, a fixed structure for a welding seam tracking device and a welding seam tracking device are provided, and the fixed structure for the welding seam tracking device and the welding seam tracking device belong to the technical field of steel pipe production, wherein the fixed structure for the welding seam tracking device comprises a supporting component, a first sleeve, a connecting component, a locking component and a fixed component, and a first through hole and a second through hole which are arranged at intervals and are arranged in a cross shape are arranged on the outer wall of the first sleeve; the support component is connected in the first through hole in a sliding way; one end of the connecting component is connected in the second through hole in a sliding way; the other end of the connecting component is used for fixedly connecting with a weld joint tracking device; the locking component is arranged in the first sleeve in a penetrating way and used for locking the supporting component, the first sleeve and the connecting component as well as the first sleeve; one end of the fixing component is fixedly connected with the other end of the supporting component, the other end of the fixing component is fixedly connected with the aluminum frame, and the provided fixing structure for the weld tracking device can rapidly move and disassemble the weld tracking device, so that the efficiency of inspection work is improved.
Through the above analysis, the problems and defects existing in the prior art are as follows: the prior art cannot acquire enough weld images, which affects the control of the welding robot and the accuracy of the formation of the weld track.
Disclosure of Invention
Aiming at the problems existing in the prior art, the invention provides a weld joint identification tracking system of a mobile welding robot based on visual sensing.
The invention is realized in such a way that a weld joint recognition tracking system of a mobile welding robot based on visual sense comprises:
the visual sensing module is used for shooting an optical image of the welding seam through the camera, converting the optical image into a target video, and transmitting the target video to the image acquisition card for digitization to form welding seam digital image data;
the welding seam track module receives the welding seam digital image data formed by the visual sensing module, sends the obtained welding seam digital image data to the welding robot, and forms welding seam track data according to the welding seam digital image data;
and the welding control module is used for receiving the control of the welding seam track module, controlling the position of the welding gun along the welding seam according to the welding seam track data, moving the welding gun and controlling a servo motor of a movement shaft of the welding robot.
Optionally, the visual sensing module includes:
the image conversion sub-module is used for shooting an optical image of the welding seam through a camera and converting the optical image into a target video;
the image digitizing sub-module is used for transmitting the signal of the target video to an image acquisition card for digitizing;
and the image data forming sub-module is used for forming the welding line digital image data.
Optionally, the image conversion submodule includes:
the optical image processing unit is used for dividing an optical image of the welding seam shot by the camera to obtain a foreground area and a background area; performing iterative transformation of visual depth on the background area, and storing an image obtained by each transformation as a picture frame to obtain a multi-frame optical image;
the multi-frame image processing unit is used for converting the multi-frame optical image into a gray level image, filtering salt and pepper noise in the gray level image by median filtering, and then carrying out inter-frame difference on pixel points in two adjacent frames of gray level images to obtain a processed multi-frame optical image;
and the video signal acquisition unit is used for splicing the processed multi-frame optical images to obtain a target video.
Optionally, the image digitizing submodule includes:
the target video identification unit is used for processing the signal of the target video received by the image acquisition card in real time and identifying the acquired target video;
the noise signal separation unit is used for adopting a digital high-pass filter to process and separate noise signals;
and the digital conversion unit is used for sampling the target video signal from which the noise signal is separated at a high speed and finishing digital conversion.
Optionally, the weld track module includes:
the image data receiving sub-module is used for wirelessly receiving the visual sensing module to form weld digital image data;
the welding seam control sub-module is used for sending the obtained welding seam digital image data to a welding robot;
and the welding seam track data forming sub-module is used for forming welding seam track data according to the welding seam digital image data.
Optionally, the image data receiving submodule includes:
the relay node unit is used for realizing that the source node broadcasts signals to all relay nodes with fixed power, and the relay node collects energy from the signals transmitted by the source node and uses the energy as the subsequent transmitting power; the relay node decodes the signal broadcast by the source node;
the cooperative interference node selection unit is used for selecting the relay node by taking the channel gain between the maximized relay node and the target node as a criterion; selecting the cooperative interference node from the rest relay nodes by taking the channel gain between the maximized cooperative interference node and the eavesdropping node as a criterion;
the interference signal transmitting unit is used for enabling the selected relay node to recode the signal transmitted by the source node and then transmit the recoded signal to the destination node, and the selected cooperative interference node transmits the interference signal to the eavesdropping node;
optionally, the weld control submodule includes:
the control program generating unit is used for acquiring the welding seam digital image data, calling corresponding welding control parameters according to the welding seam digital image data and generating a welding control program;
the welding control unit is connected with the control program generating unit and is used for receiving the welding control program;
the welding control unit is connected with the welding control unit and used for controlling the movement of the welding movement unit according to the welding control program;
and the welding execution unit is arranged on the welding movement unit, and the welding control unit controls the welding execution unit to weld according to the welding control program.
Optionally, the weld track data forming submodule includes:
the weld joint track data processing unit takes the weld joint track data received in the previous time as synthesized weld joint track data; when the weld track data of the weld control sub-module is received, the weld track data and the synthesized weld track data are synthesized to generate weld track data, and the weld track data are used as current weld digital image data to be synthesized; the synthesized weld track data is received at the moment before the weld track data of the weld control submodule is received;
the welding seam track data forming unit is used for receiving welding seam track data at intervals of preset time after receiving the welding seam track data, synthesizing the currently received welding seam track data with synthesized welding seam track data to generate new welding seam track data when receiving each welding seam track data, and taking the new welding seam track data as current welding seam digital image data to be synthesized;
the target track point processing unit is used for sequencing and acquiring target track points of the weld track data according to the time sequence of the weld track data synthesis; extracting target track points based on an image processing algorithm to obtain weld track data;
and the weld track data coordinate unit is used for obtaining weld track data of the three-dimensional positioning coordinates according to the weld track image obtained in real time.
Optionally, the welding execution unit includes:
the acquisition subunit is used for acquiring the corresponding three-dimensional positioning coordinates of each node in the weld track data;
a deduction subunit, configured to determine an initial deduction point in each node in the weld track data; iteratively performing track deduction according to the three-dimensional positioning coordinates corresponding to each node from the next node of the initial deduction point by referring to the initial deduction point to obtain the deduction point corresponding to each node;
the track matching subunit is used for determining the three-dimensional positioning coordinates of the deduction point with the maximum probability in the weld track data to obtain three-dimensional positioning coordinates matched with the deduction point;
and the track correcting subunit is used for correcting the trend of the deduction track formed by the deduction points to be consistent with the direction of the matched three-dimensional positioning coordinates.
Optionally, the trajectory correction subunit includes:
the image processor is used for judging whether the trend of the deduction track formed by the deduction points is consistent with the direction of the matched three-dimensional positioning coordinates;
the off-line deviation correcting instrument is used for taking the detected weld joint points as new teaching points, updating the teaching program of the welding robot and finishing the weld joint deviation correction;
the on-line deviation rectifying instrument is used for calculating the real-time deviation rectifying quantity of the welding gun position of the welding robot through the detected welding point position and inputting the deviation rectifying quantity into the welding robot to control the movement of the tail end welding gun, so that the real-time deviation rectifying of the welding seam is realized.
By combining all the technical schemes, the invention has the advantages and positive effects that: the invention adopts the visual sensing module to acquire the optical image of the welding seam, can acquire enough welding seam images, and provides complete and accurate data for the control of the welding robot and the formation of the welding seam track; meanwhile, the acquisition efficiency of the welding line images is improved, and a technical foundation is laid for intelligent control of the welding robot; according to the invention, the servo motor is controlled according to the obtained weld joint digital image data, so that the control accuracy of the servo motor is improved, a welding gun can accurately reach the weld joint position, and a guarantee is provided for saving welding time and improving welding efficiency; the welding robot works under the optimal welding track according to the welding track data, so that the intelligent control of the welding robot is further improved, and the improvement of the product quality is further promoted.
The invention adopts the image conversion sub-module, the image digitization sub-module and the image data formation sub-module, realizes the whole flow process of the acquisition, conversion and formation of the weld image, and ensures that the effective means for acquiring the weld image is realized, the intelligent control of the welding robot is core, and the intelligent key of the welding robot is improved; according to the invention, the camera shoots the optical image of the welding seam, so that enough welding seam images can be obtained, and complete and accurate data are provided for the control of the welding robot and the formation of the welding seam track; according to the invention, the video signals collected by the camera are converted into the identifiable digital signals, so that the working efficiency of the welding robot is improved, and the calculation speed of the weld track data is increased.
The welding seam track module receives the welding seam digital image data formed by the visual sensing module, provides a data base for the accurate control of the welding robot, realizes the accurate welding of the welding seam, ensures that the intelligent control of the welding robot is further improved, and further promotes the improvement of the product quality. According to the invention, the welding robot works under the optimal welding track according to the welding track data, so that the intelligent control of the welding robot is further improved, and the improvement of the product quality is further promoted.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following description will briefly explain the drawings needed in the embodiments of the present application, and it is obvious that the drawings described below are only some embodiments of the present application, and that other drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic structural diagram of a weld joint recognition tracking system of a mobile welding robot based on visual sensing according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a visual sensing module according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of an image conversion sub-module according to an embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the following examples in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Example 1:
as shown in fig. 1, a weld seam identification tracking system of a mobile welding robot based on visual sensing provided by an embodiment of the invention includes:
the visual sensing module is used for shooting an optical image of the welding seam through the camera, converting the optical image into a target video, and transmitting the target video to the image acquisition card for digitization to form welding seam digital image data;
the welding seam track module receives the welding seam digital image data formed by the visual sensing module, sends the obtained welding seam digital image data to the welding robot, and forms welding seam track data according to the welding seam digital image data;
and the welding control module is used for receiving the control of the welding seam track module, controlling the position of the welding gun along the welding seam according to the welding seam track data, moving the welding gun and controlling a servo motor of a movement shaft of the welding robot.
The invention adopts the visual sensing module to acquire the optical image of the welding seam, can acquire enough welding seam images, and provides complete and accurate data for the control of the welding robot and the formation of the welding seam track; meanwhile, the acquisition efficiency of the welding line images is improved, and a technical foundation is laid for intelligent control of the welding robot; according to the invention, the servo motor is controlled according to the obtained weld joint digital image data, so that the control accuracy of the servo motor is improved, a welding gun can accurately reach the weld joint position, and a guarantee is provided for saving welding time and improving welding efficiency; the welding robot works under the optimal welding track according to the welding track data, so that the intelligent control of the welding robot is further improved, and the improvement of the product quality is further promoted.
Example 2:
as shown in fig. 2, on the basis of embodiment 1, the vision sensing module provided in the embodiment of the present invention includes:
the image conversion sub-module is used for shooting an optical image of the welding seam through a camera and converting the optical image into a target video;
the image digitizing sub-module is used for transmitting the signal of the target video to an image acquisition card for digitizing;
and the image data forming sub-module is used for forming the welding line digital image data.
The invention adopts the image conversion sub-module, the image digitization sub-module and the image data formation sub-module, realizes the whole flow process of the acquisition, conversion and formation of the weld image, and ensures that the effective means for acquiring the weld image is realized, the intelligent control of the welding robot is core, and the intelligent key of the welding robot is improved; according to the invention, the camera shoots the optical image of the welding seam, so that enough welding seam images can be obtained, and complete and accurate data are provided for the control of the welding robot and the formation of the welding seam track; according to the invention, the video signals collected by the camera are converted into the identifiable digital signals, so that the working efficiency of the welding robot is improved, and the calculation speed of the weld track data is increased.
Example 3:
as shown in fig. 3, on the basis of embodiment 2, the image conversion submodule provided in the embodiment of the present invention includes:
the optical image processing unit is used for dividing an optical image of the welding seam shot by the camera to obtain a foreground area and a background area; performing iterative transformation of visual depth on the background area, and storing an image obtained by each transformation as a picture frame to obtain a multi-frame optical image;
the multi-frame image processing unit is used for converting the multi-frame optical image into a gray level image, filtering salt and pepper noise in the gray level image by median filtering, and then carrying out inter-frame difference on pixel points in two adjacent frames of gray level images to obtain a processed multi-frame optical image;
and the video signal acquisition unit is used for splicing the processed multi-frame optical images to obtain a target video.
According to the invention, the optical image of the welding seam shot by the camera is processed to obtain a plurality of frames of optical images, the optical images are segmented to obtain a foreground area and a background area, the characteristics of the welding seam are comprehensively analyzed, positive effects are exerted on the identification of the optical images, and a foundation can be laid for providing more accurate welding seam digital image data; according to the invention, the multi-frame image processing unit is adopted to convert the multi-frame optical image into the gray level image, so that the processing speed of the image conversion submodule is improved, and the time for forming weld track data according to the weld digital image data is shortened; and after the salt and pepper noise in the gray level image is filtered by improving the median filtering, the pixel points in two adjacent frames of images are subjected to inter-frame difference, and the distortion of the gray level image is avoided after the salt and pepper noise.
Example 4:
on the basis of embodiment 2, the image digitizing submodule provided by the embodiment of the invention comprises:
the target video identification unit is used for processing the signal of the target video received by the image acquisition card in real time and identifying the acquired target video;
the noise signal separation unit is used for adopting a digital high-pass filter to process and separate noise signals;
and the digital conversion unit is used for sampling the target video signal from which the noise signal is separated at a high speed and finishing digital conversion.
According to the invention, the target video is processed by adopting the digital high-pass filter, the noise signals are separated, and the target video with noise removed is obtained, so that the target video is more real, no distortion is ensured, and the authenticity of weld joint identification is improved; according to the invention, the digital conversion unit is adopted to sample the target video signal from which the noise signal is separated at a high speed and complete digital conversion, so that the converted welding seam digital image data has strong anti-interference capability, and the welding robot can accurately obtain the welding seam digital image data, so that the servo can accurately act.
Example 5:
on the basis of embodiment 1, the weld track module provided by the embodiment of the invention comprises:
the image data receiving sub-module is used for wirelessly receiving the visual sensing module to form weld digital image data;
the welding seam control sub-module is used for sending the obtained welding seam digital image data to a welding robot;
and the welding seam track data forming sub-module is used for forming welding seam track data according to the welding seam digital image data.
The welding seam track module receives the welding seam digital image data formed by the visual sensing module, provides a data basis for the accurate control of the welding robot, realizes the accurate welding of the welding seam, ensures that the intelligent control of the welding robot is further improved, and further promotes the improvement of the product quality. According to the invention, the welding robot works under the optimal welding track according to the welding track data, so that the intelligent control of the welding robot is further improved, and the improvement of the product quality is further promoted.
Example 6:
on the basis of embodiment 5, the image data receiving submodule provided by the embodiment of the invention includes:
the relay node unit is used for realizing that the source node broadcasts signals to all relay nodes with fixed power, and the relay node collects energy from the signals transmitted by the source node and uses the energy as the subsequent transmitting power; the relay node decodes the signal broadcast by the source node;
the cooperative interference node selection unit is used for selecting the relay node by taking the channel gain between the maximized relay node and the target node as a criterion; selecting the cooperative interference node from the rest relay nodes by taking the channel gain between the maximized cooperative interference node and the eavesdropping node as a criterion;
the interference signal transmitting unit is used for enabling the selected relay node to recode the signal transmitted by the source node and then transmit the recoded signal to the destination node, and the selected cooperative interference node transmits the interference signal to the eavesdropping node;
the image data receiving sub-module comprises a relay node unit, a cooperative interference node selection unit and an interference signal sending unit, and wireless receiving of the welding seam digital image data formed by the visual sensing module is realized through safe transmission in a wireless network with cooperative interference, so that the safety of the welding seam digital image data transmission is ensured, the accuracy of a welding seam track module is ensured, and the intelligent level of the welding robot is further improved.
Example 7:
on the basis of embodiment 5, the welding seam control submodule provided by the embodiment of the invention comprises:
the control program generating unit is used for acquiring the welding seam digital image data, calling corresponding welding control parameters according to the welding seam digital image data and generating a welding control program;
the welding control unit is connected with the control program generating unit and is used for receiving the welding control program;
the welding control unit is connected with the welding control unit and used for controlling the movement of the welding movement unit according to the welding control program;
and the welding execution unit is arranged on the welding movement unit, and the welding control unit controls the welding execution unit to weld according to the welding control program.
According to the invention, the welding seam digital image data is obtained, the corresponding welding control parameters are called according to the welding seam digital image data, and the welding control program is generated, so that the corresponding welding control parameters can be appointed according to the actual welding seam, and the welding efficiency and quality of the welding seam can be improved; and the welding execution unit performs welding according to the welding control program, so that the accuracy of welding is improved, and the automation level of the welding robot is further improved. Thereby providing a basis for the formation of weld track data.
Example 8:
on the basis of embodiment 5, the welding seam track data forming submodule provided by the embodiment of the invention comprises:
the weld joint track data processing unit takes the weld joint track data received in the previous time as synthesized weld joint track data; when the weld track data of the weld control sub-module is received, the weld track data and the synthesized weld track data are synthesized to generate weld track data, and the weld track data are used as synthesized weld track data;
the welding seam track data forming unit is used for receiving welding seam track data at intervals of preset time after receiving the welding seam track data, synthesizing the currently received welding seam track data with synthesized welding seam track data to generate new welding seam track data when receiving each welding seam track data, and taking the new welding seam track data as current welding seam digital image data to be synthesized;
the target track point processing unit is used for sequencing and acquiring target track points of the weld track data according to the time sequence of the weld track data synthesis; extracting target track points based on an image processing algorithm to obtain weld track data;
and the weld track data coordinate unit is used for obtaining weld track data of the three-dimensional positioning coordinates according to the weld track image obtained in real time.
The invention processes and synthesizes each received weld track data, ensures that the omnibearing weld image data can be obtained, provides a data basis for the selection of the welding track of the welding robot, ensures that the welding track is more accurate and reasonable, is beneficial to saving the welding time and improves the efficacy. According to the method, the target track points of the weld track data are obtained in sequence according to the time sequence of the weld track data synthesis, so that the intelligent processing of the weld track of the welding robot is realized, the labor is further saved, and the cost is also saved.
Example 9:
on the basis of embodiment 1, the welding execution unit provided by the embodiment of the invention comprises:
the acquisition subunit is used for acquiring the corresponding three-dimensional positioning coordinates of each node in the weld track data;
a deduction subunit, configured to determine an initial deduction point in each node in the weld track data; iteratively performing track deduction according to the three-dimensional positioning coordinates corresponding to each node from the next node of the initial deduction point by referring to the initial deduction point to obtain the deduction point corresponding to each node;
the track matching subunit is used for determining the three-dimensional positioning coordinates of the deduction point with the maximum probability in the weld track data to obtain three-dimensional positioning coordinates matched with the deduction point;
and the track correcting subunit is used for correcting the trend of the deduction track formed by the deduction points to be consistent with the direction of the matched three-dimensional positioning coordinates.
The trajectory correction subunit includes:
the trajectory correction subunit includes:
the image processor is used for judging whether the trend of the deduction track formed by the deduction points is consistent with the direction of the matched three-dimensional positioning coordinates;
the off-line deviation correcting instrument is used for taking the detected weld joint points as new teaching points, updating the teaching program of the welding robot and finishing the weld joint deviation correction;
the on-line deviation rectifying instrument is used for calculating the real-time deviation rectifying quantity of the welding gun position of the welding robot through the detected welding point position and inputting the deviation rectifying quantity into the welding robot to control the movement of the tail end welding gun, so that the real-time deviation rectifying of the welding seam is realized.
According to the welding seam track data, correction of welding home setting is achieved according to the corresponding three-dimensional positioning coordinates of each node in the welding seam track data, the welding control module is ensured to control the welding gun to move along the welding seam according to the welding seam track data, the servo motor of the movement axis of the welding robot is controlled, accurate welding is achieved, meanwhile, the servo motor is ensured to be accurate in place, the welding gun can weld according to the welding track data, the welding accuracy is improved, and meanwhile, the intelligent level of production of the welding robot and enterprises is improved.
Example 10:
on the basis of embodiment 1, the visual sensing module provided by the embodiment of the invention adjusts the tone of an optical image of a welding line shot by a camera, and specifically comprises the following steps: for one color channel O in an optical image C (x) The tone adjustment function is:
wherein Op (x) is color channel O C (x) Output after tone adjustment, O dmax For the maximum brightness value of the camera, b is the bias parameter,for colour channel O C (x) Maximum value of the middle pixel.
The invention adopts the chromaticity adjusting function to adjust the tone of the optical image of the welding seam shot by the camera, thereby improving the detail and contrast of the optical image and effectively improving the detail information of the optical image; the method provides a guarantee for converting the optical image into a target video, transmitting the target video to an image acquisition card for digitizing and finally forming welding line digital image data; the invention adopts the optical image with higher detail and contrast, provides the accuracy of accurate weld track data, and ensures the control precision of the welding robot.
It should be noted that the embodiments of the present invention can be realized in hardware, software, or a combination of software and hardware. The hardware portion may be implemented using dedicated logic; the software portions may be stored in a memory and executed by a suitable instruction execution system, such as a microprocessor or special purpose design hardware. Those of ordinary skill in the art will appreciate that the apparatus and methods described above may be implemented using computer executable instructions and/or embodied in processor control code, such as provided on a carrier medium such as a magnetic disk, CD or DVD-ROM, a programmable memory such as read only memory (firmware), or a data carrier such as an optical or electronic signal carrier. The device of the present invention and its modules may be implemented by hardware circuitry, such as very large scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, etc., or programmable hardware devices such as field programmable gate arrays, programmable logic devices, etc., as well as software executed by various types of processors, or by a combination of the above hardware circuitry and software, such as firmware.
While the invention has been described with respect to what is presently considered to be the most practical and preferred embodiments, it is to be understood that the invention is not limited to the disclosed embodiments, but on the contrary, is intended to cover various modifications, equivalents, and alternatives falling within the spirit and scope of the invention.
Claims (9)
1. A weld seam identification tracking system of a mobile welding robot based on visual sensing, comprising:
the visual sensing module is used for shooting an optical image of the welding seam through the camera, converting the optical image into a target video, and transmitting the target video to the image acquisition card for digitization to form welding seam digital image data;
the welding seam track module receives the welding seam digital image data formed by the visual sensing module, sends the obtained welding seam digital image data to the welding robot, and forms welding seam track data according to the welding seam digital image data;
the weld trajectory module further comprises:
the welding seam control sub-module is used for sending the obtained welding seam digital image data to a welding robot; the weld control submodule includes: the control program generating unit is used for acquiring the welding seam digital image data, calling corresponding welding control parameters according to the welding seam digital image data and generating a welding control program; the welding control unit is connected with the control program generating unit and is used for receiving the welding control program; the welding control unit is connected with the welding control unit and used for controlling the movement of the welding movement unit according to the welding control program; the welding execution unit is arranged on the welding movement unit, and the welding control unit controls the welding execution unit to weld according to the welding control program;
the welding seam track data forming sub-module is used for forming welding seam track data according to the welding seam digital image data; the weld trajectory data forming sub-module further includes: the weld joint track data processing unit takes the weld joint track data received in the previous time as synthesized weld joint track data; when the weld track data of the weld control sub-module is received, the weld track data and the synthesized weld track data are synthesized to generate weld track data, and the weld track data are used as current weld digital image data to be synthesized; the synthesized weld track data is received at the moment before the weld track data of the weld control submodule is received;
and the welding control module is used for receiving the control of the welding seam track module, controlling the position of the welding gun along the welding seam according to the welding seam track data, moving the welding gun and controlling a servo motor of a movement shaft of the welding robot.
2. The vision-sensing-based weld seam identification tracking system of a mobile welding robot of claim 1, wherein the vision sensing module comprises:
the image conversion sub-module is used for shooting an optical image of the welding seam through a camera and converting the optical image into a target video;
the image digitizing sub-module is used for transmitting the signal of the target video to an image acquisition card for digitizing;
and the image data forming sub-module is used for forming the welding line digital image data.
3. The vision-sensing-based weld seam recognition tracking system of a mobile welding robot of claim 2, wherein the image conversion sub-module comprises:
the optical image processing unit is used for dividing an optical image of the welding seam shot by the camera to obtain a foreground area and a background area; performing iterative transformation of visual depth on the background area, and storing an image obtained by each transformation as a picture frame to obtain a multi-frame optical image;
the multi-frame image processing unit is used for converting the multi-frame optical image into a gray level image, filtering salt and pepper noise in the gray level image by median filtering, and then carrying out inter-frame difference on pixel points in two adjacent frames of gray level images to obtain a processed multi-frame optical image;
and the video signal acquisition unit is used for splicing the processed multi-frame optical images to obtain a target video.
4. The vision-sensing-based weld seam recognition tracking system of a mobile welding robot of claim 2, wherein the image digitizing submodule comprises:
the target video identification unit is used for processing the signal of the target video received by the image acquisition card in real time and identifying the acquired target video;
the noise signal separation unit is used for adopting a digital high-pass filter to process and separate noise signals;
and the digital conversion unit is used for sampling the target video signal from which the noise signal is separated at a high speed and finishing digital conversion.
5. The vision-sensing-based weld seam identification tracking system of a mobile welding robot of claim 1, wherein the weld seam trajectory module comprises:
and the image data receiving sub-module is used for wirelessly receiving the visual sensing module to form welding line digital image data.
6. The vision-sensing-based weld seam recognition tracking system of a mobile welding robot of claim 5, wherein the image data receiving sub-module comprises:
the relay node unit is used for realizing that the source node broadcasts signals to all relay nodes with fixed power, and the relay node collects energy from the signals transmitted by the source node and uses the energy as the subsequent transmitting power; the relay node decodes the signal broadcast by the source node;
the cooperative interference node selection unit is used for selecting the relay node by taking the channel gain between the maximized relay node and the target node as a criterion; selecting the cooperative interference node from the rest relay nodes by taking the channel gain between the maximized cooperative interference node and the eavesdropping node as a criterion;
and the interference signal transmitting unit is used for enabling the selected relay node to recode the signal transmitted by the source node and then transmit the recoded signal to the destination node, and the selected cooperative interference node transmits the interference signal to the eavesdropping node.
7. The vision-sensing-based weld seam identification tracking system of a mobile welding robot of claim 1, wherein the weld seam trajectory data formation sub-module further comprises:
the welding seam track data forming unit is used for receiving welding seam track data at intervals of preset time after receiving the welding seam track data, synthesizing the currently received welding seam track data with synthesized welding seam track data to generate new welding seam track data when receiving each welding seam track data, and taking the new welding seam track data as current welding seam digital image data to be synthesized;
the target track point processing unit is used for sequencing and acquiring target track points of the weld track data according to the time sequence of the weld track data synthesis; extracting target track points based on an image processing algorithm to obtain weld track data;
and the weld track data coordinate unit is used for obtaining weld track data of the three-dimensional positioning coordinates according to the weld track image obtained in real time.
8. The vision-sensing-based weld seam identification tracking system of a mobile welding robot of claim 1, wherein the welding execution unit comprises:
the acquisition subunit is used for acquiring the corresponding three-dimensional positioning coordinates of each node in the weld track data;
a deduction subunit, configured to determine an initial deduction point in each node in the weld track data; iteratively performing track deduction according to the three-dimensional positioning coordinates corresponding to each node from the next node of the initial deduction point by referring to the initial deduction point to obtain the deduction point corresponding to each node;
the track matching subunit is used for determining the three-dimensional positioning coordinates of the deduction point with the maximum probability in the weld track data to obtain three-dimensional positioning coordinates matched with the deduction point;
and the track correcting subunit is used for correcting the trend of the deduction track formed by the deduction points to be consistent with the direction of the matched three-dimensional positioning coordinates.
9. The vision-sensing-based weld seam identification tracking system of a mobile welding robot of claim 8, wherein the trajectory correction subunit comprises:
the image processor is used for judging whether the trend of the deduction track formed by the deduction points is consistent with the direction of the matched three-dimensional positioning coordinates;
the off-line deviation correcting instrument is used for taking the detected weld joint points as new teaching points, updating the teaching program of the welding robot and finishing the weld joint deviation correction;
the on-line deviation rectifying instrument is used for calculating the real-time deviation rectifying quantity of the welding gun position of the welding robot through the detected welding point position and inputting the deviation rectifying quantity into the welding robot to control the movement of the tail end welding gun, so that the real-time deviation rectifying of the welding seam is realized.
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