CN115041887A - Contour measuring and recognizing system for robot welding workpiece - Google Patents
Contour measuring and recognizing system for robot welding workpiece Download PDFInfo
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- CN115041887A CN115041887A CN202210453653.XA CN202210453653A CN115041887A CN 115041887 A CN115041887 A CN 115041887A CN 202210453653 A CN202210453653 A CN 202210453653A CN 115041887 A CN115041887 A CN 115041887A
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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
- 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
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J11/00—Manipulators not otherwise provided for
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/0081—Programme-controlled manipulators with master teach-in means
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- 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
- B25J9/1656—Programme controls characterised by programming, planning systems for manipulators
- B25J9/1664—Programme controls characterised by programming, planning systems for manipulators characterised by motion, path, trajectory planning
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- Length Measuring Devices By Optical Means (AREA)
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Abstract
The invention discloses a contour measuring and identifying system for a robot welding workpiece, which comprises the following steps: (1) collecting and preprocessing an image; (2) identifying the weld joint through a visual sensor and a laser sensor; (3) calculating the position coordinates of the key points; (4) forming welding line teaching information by carrying out image processing on a welding line image of a workpiece to be welded; (5) and (4) automatic path planning of the robot. According to the invention, the spatial position coordinates of key point positions are processed into robot teaching information through the upper computer, the tail end of a welding gun of the robot is guided to move to a position to be welded, so that the welding robot has the spatial position self-adaptive capacity of a workpiece to be welded, the robot vision intelligent welding seam locating of the welding robot is realized, the visual identification and positioning algorithm based on a deep learning model is established, the boundary pixel detection algorithm is combined, and a dual-camera vision system is adopted to realize the detection, identification and accurate positioning of the welding workpiece and the welding seam track.
Description
Technical Field
The invention relates to the technical field of welding robots, in particular to a contour measuring and recognizing system for a welding workpiece of a robot.
Background
The welding robot is an industrial robot engaged in welding. An industrial robot is defined as a multipurpose, reprogrammable, automatically controlled manipulator with three or more programmable axes for use in the field of industrial automation, according to the international standardization group, which belongs to the standard welding robot. To accommodate different applications, the mechanical interface of the last axis of the robot, usually a connecting flange, may be used to attach different tools or end effectors. Welding robot is exactly at industrial robot's last axial flange dress soldering turret or welder, it can weld to make it, cutting or hot spraying, need use contour measurement and identification system when welding robot moves, but current contour measurement and identification system do not possess when using and wait to weld work piece spatial position adaptive capacity, can not realize welding work piece, the detection of welding seam orbit, discernment and accurate location, and can not rectify a deviation by the welding seam, welding robot is relatively poor to the adaptability that operating condition changes.
The prior art profile measuring and identifying system has the following defects:
1. patent document CN110524581A discloses a flexible welding robot system and a welding method thereof, "comprising: the global vision unit identifies the image information of the workpiece to be welded and positions the position of the workpiece to be welded; the flexible welding robot unit accurately identifies the position of a workpiece to be welded through a fine positioning visual assembly, the image processing controller calculates a welding path, and the flexible welding robot performs welding operation; the flexible detection robot unit identifies the geometric dimension and quality of the welded workpiece through a stereoscopic vision detection assembly, generates a welding quality report according to parameter information set by a user, and transmits information that the welding deviation exceeds a threshold position and deviation amount to the flexible welding robot for repair welding; the master control unit executes image processing, data communication and motion control of the welding robot and the detection robot; and the workbench unit is used for quickly clamping different types of welding workpieces. The problem of the harm that welding operation led to the fact the workman health is solved, realized that high flexibility, intellectuality of flexible welding robot system do not possess and treat welding workpiece spatial position adaptive capacity when using, can not realize detection, discernment and accurate location of welding workpiece, welding seam orbit, and can not rectify a deviation by the welding seam, the welding robot is relatively poor to the adaptability of operation condition change.
Disclosure of Invention
The present invention is directed to a system for measuring and recognizing a profile of a welding workpiece by a robot, which solves the above problems.
In order to achieve the above object, the present invention provides a system for measuring and recognizing a profile of a robot-welded workpiece, comprising: (1) collecting and preprocessing an image; (2) identifying welding seams through a visual sensor and a laser sensor; (3) calculating the position coordinates of the key points; (4) carrying out image processing on the welding seam image of the workpiece to be welded to form welding seam teaching information; (5) and (4) automatic path planning of the robot.
Preferably, in the steps (1) and (5), the welding seam teaching information is formed by performing image processing on the welding seam image of the workpiece to be welded and calculating coordinates of the initial position and the final position of the welding seam through image processing of machine vision and a welding seam locating algorithm.
Preferably, in the step (2), the spatial position coordinates of the key points are processed into robot teaching information through the upper computer, the tail end of a welding gun of the robot is guided to move to a position to be welded, so that the welding robot has the spatial position self-adaption capability of a workpiece to be welded, and the robot vision intelligent welding line locating of the welding robot is realized.
Preferably, in the step (3), by establishing a visual identification and positioning algorithm based on a deep learning model (a deep belief network, a convolutional neural network and a recurrent neural network multilayer perceptron), combining a boundary pixel detection algorithm, and adopting a dual-camera visual system to realize detection, identification and accurate positioning of a welding workpiece and a welding seam track, a point set registration method ICP algorithm based on contour features realizes accurate matching and rapid identification of contour features or point sets of three-dimensional elements, correct correspondence is calculated step by iteration, and multi-view registration is realized to realize contour measurement and identification of the welding workpiece of the robot.
Preferably, in the step (4), a vision sensor and a laser sensor are integrated in the robot welding system, so that the weld seam tracking in the multilayer and multi-pass welding process of the medium plate and the weld seam tracking of the laser deviation corrector through the vision sensor are realized, the motion state of the welding tail end is adjusted in real time, and the weld seam deviation correction is realized through the laser sensor.
Compared with the prior art, the invention has the following beneficial effects:
1. according to the invention, the spatial position coordinates of key point positions are processed into robot teaching information through the upper computer, the tail end of a welding gun of the robot is guided to move to a position to be welded, so that the welding robot has the spatial position self-adaptive capacity of a workpiece to be welded, the robot vision intelligent welding seam locating of the welding robot is realized, the visual identification and positioning algorithm based on a deep learning model is established, the boundary pixel detection algorithm is combined, and a dual-camera vision system is adopted to realize the detection, identification and accurate positioning of the welding workpiece and the welding seam track.
2. The invention integrates a vision sensor and a laser sensor in a robot welding system, and realizes weld seam tracking and laser deviation correction in the multi-layer and multi-pass welding process of medium and heavy plates. The welding line tracking is carried out through visual sensing to realize real-time adjustment of the motion state of the welding tail end, the deviation correction of the welding line is realized through a laser sensor, the adaptability of the robot to the change of the operation condition in the welding process is improved, and the motion precision and the welding quality in the welding process are improved.
Drawings
FIG. 1 is a schematic flow chart of a profile measurement and identification system according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. 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.
In the description of the present invention, it should be noted that the terms "upper", "lower", "inner", "outer", "front", "rear", "both ends", "one end", "the other end", and the like indicate orientations or positional relationships based on those shown in the drawings, and are only for convenience of description and simplicity of description, but do not indicate or imply that the referred device or element must have a specific orientation, be constructed in a specific orientation, and be operated, and thus, should not be construed as limiting the present invention. Furthermore, the terms "first," "second," and the like are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
In the description of the present invention, it should be noted that, unless explicitly stated or limited otherwise, the terms "mounted," "disposed," "connected," and the like are to be construed broadly, such as "connected," which may be fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood in a specific case to those of ordinary skill in the art.
Referring to fig. 1, a system for measuring and recognizing a profile of a robot welding workpiece;
the first embodiment is as follows: a system for profile measurement and identification of a robotic welding workpiece, comprising the steps of: collecting and preprocessing an image; (2) identifying welding seams through a visual sensor and a laser sensor; (3) calculating the position coordinates of the key points; (4) forming welding line teaching information by carrying out image processing on a welding line image of a workpiece to be welded; (5) and (4) automatic path planning of the robot.
In the steps (1) and (5), through image processing of machine vision and a welding seam locating algorithm, welding seam teaching information is formed by performing image processing on a welding seam image of a workpiece to be welded and calculating coordinates of the initial position and the final position of the welding seam.
In the step (2), the spatial position coordinates of the key point positions are processed into robot teaching information through the upper computer, the tail end of a welding gun of the robot is guided to move to a position to be welded, the welding robot has the spatial position self-adaption capability of a workpiece to be welded, and the robot vision intelligent welding line locating of the welding robot is achieved.
In the step (3), the visual identification and positioning algorithm based on a deep learning model (a deep belief network, a convolutional neural network and a recurrent neural network multilayer perceptron) is established, a boundary pixel detection algorithm is combined, a double-camera visual system is adopted to realize the detection, identification and accurate positioning of the welding workpiece and the welding seam track, a point set registration method ICP algorithm based on contour features is adopted to realize the accurate matching and quick identification of the contour features or point sets of three-dimensional elements, the correct corresponding relation is calculated step by iteration, and the multi-view registration is adopted to realize the contour measurement and identification of the welding workpiece of the robot.
In the step (4), the vision sensor and the laser sensor are integrated in the robot welding system, so that the weld tracking in the multilayer and multi-pass welding process of the medium plate and the weld tracking of the laser deviation corrector through the vision sensor are realized, the motion state of the welding tail end is adjusted in real time, the weld deviation correction is realized through the laser sensor, the adaptability of the robot to the change of the operation conditions in the welding process is improved, and the motion precision and the welding quality in the welding process are improved.
The method comprises the steps of setting up an experiment platform, carrying out a weld tracking experiment, controlling a robot to scan a weld at a speed of 1mm/s and obtain a structural light welding seam image, combining the coordinates of a tool point of the robot when the robot shoots the image every time with the processing result of the structural light welding seam image, calculating the actual position of the weld, analyzing data of 10 groups of random weld tracking conditions, and analyzing the tracking precision of the system in X-axis and Y-axis directions, wherein the total average error is within 0.1mm, the tracking error in Z-axis direction is large, the total average error is 0.19mm, and the precision requirement of V-shaped fillet weld tracking of medium and thick plates can be met.
Referring to fig. 1, a system for measuring and recognizing a profile of a robot welding workpiece;
the second embodiment: a system for profile measurement and identification of a robotic welding workpiece, comprising the steps of: collecting and preprocessing an image; (2) identifying the weld joint through a visual sensor and a laser sensor; (3) calculating the position coordinates of the key points; (4) forming welding line teaching information by carrying out image processing on a welding line image of a workpiece to be welded; (5) and (4) automatic path planning of the robot.
In the steps (1) and (5), through image processing of machine vision and a welding seam locating algorithm, welding seam image of a workpiece to be welded is subjected to image processing, and coordinates of initial and final positions of the welding seam are calculated to form welding seam teaching information.
In the step (2), the spatial position coordinates of the key point positions are processed into robot teaching information through the upper computer, the tail end of a welding gun of the robot is guided to move to a position to be welded, the welding robot has the spatial position self-adaption capability of a workpiece to be welded, and the robot vision intelligent welding line locating of the welding robot is achieved.
In the step (3), the detection, identification and accurate positioning of the welding workpiece and the welding seam track are realized by establishing a visual identification and positioning algorithm based on a deep learning model (a deep belief network, a convolutional neural network and a recurrent neural network multilayer perceptron), combining a boundary pixel detection algorithm and adopting a double-camera visual system, and the accurate matching and rapid identification of the contour features or point sets of three-dimensional elements are realized by using a point set registration method ICP algorithm based on the contour features, and the accurate corresponding relation is calculated step by using iteration, and the multi-view registration is realized to realize the contour measurement and identification of the welding workpiece of the robot.
In the step (4), a vision sensor and a laser sensor are integrated in the robot welding system, so that the weld seam tracking in the multilayer multi-pass welding process of the medium plate and the weld seam tracking of the laser deviation corrector through the vision sensor are realized, the motion state of the welding tail end is adjusted in real time, and the weld seam deviation correction is realized through the laser sensor
The method comprises the steps of setting up an experiment platform, carrying out a weld tracking experiment, controlling a robot to scan a weld at a speed of 5mm/s and obtain a structural light welding seam image, combining the coordinates of a tool point of the robot when the robot shoots the image every time with the processing result of the structural light welding seam image, calculating the actual position of the weld, analyzing data of 10 groups of random weld tracking conditions, and analyzing the tracking precision of the system in X-axis and Y-axis directions, wherein the total average error is within 0.5mm, the tracking error in Z-axis direction is large, the total average error is 0.95mm, and the precision requirement of V-shaped fillet weld tracking of medium and thick plates can be met.
Referring to fig. 1, a system for measuring and recognizing a profile of a robot welding workpiece;
example three: a system for profile measurement and identification of a robotic welding workpiece, comprising the steps of: collecting and preprocessing an image; (2) identifying welding seams through a visual sensor and a laser sensor; (3) calculating the position coordinates of the key points; (4) forming welding line teaching information by carrying out image processing on a welding line image of a workpiece to be welded; (5) and (4) automatic path planning of the robot.
In the steps (1) and (5), through image processing of machine vision and a welding seam locating algorithm, welding seam image of a workpiece to be welded is subjected to image processing, and coordinates of initial and final positions of the welding seam are calculated to form welding seam teaching information.
In the step (2), the spatial position coordinates of the key point positions are processed into robot teaching information through the upper computer, the tail end of a welding gun of the robot is guided to move to a position to be welded, the welding robot has the spatial position self-adaption capability of a workpiece to be welded, and the robot vision intelligent welding line locating of the welding robot is achieved.
In the step (3), the detection, identification and accurate positioning of the welding workpiece and the welding seam track are realized by establishing a visual identification and positioning algorithm based on a deep learning model (a deep belief network, a convolutional neural network and a recurrent neural network multilayer perceptron), combining a boundary pixel detection algorithm and adopting a double-camera visual system, and the accurate matching and rapid identification of the contour features or point sets of three-dimensional elements are realized by using a point set registration method ICP algorithm based on the contour features, and the accurate corresponding relation is calculated step by using iteration, and the multi-view registration is realized to realize the contour measurement and identification of the welding workpiece of the robot.
In the step (4), the vision sensor and the laser sensor are integrated in the robot welding system, so that the weld tracking in the multilayer and multi-pass welding process of the medium plate and the weld tracking of the laser deviation corrector through the vision sensor are realized, the motion state of the welding tail end is adjusted in real time, the weld deviation correction is realized through the laser sensor, the adaptability of the robot to the change of the operation conditions in the welding process is improved, and the motion precision and the welding quality in the welding process are improved.
The method comprises the steps of setting up an experiment platform, carrying out a welding seam tracking experiment, firstly controlling a robot to scan a welding seam at a speed of 10mm/s and obtaining a structural light welding seam image, and calculating the actual position of the welding seam by combining the coordinate of a tool point of the robot and the processing result of the structural light welding seam image when the image is shot each time. The data of 10 groups of random welding seam tracking conditions are analyzed, the tracking precision of the system in the X-axis and Y-axis directions is high, the overall average error is within 1mm, the tracking error in the Z-axis direction is large, the overall average error is 1.9mm, and the precision requirement of V-shaped fillet weld seam tracking of medium and heavy plates can be met.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.
Claims (5)
1. A profile measurement and recognition system for a robot-welded workpiece is characterized in that: the method comprises the following steps:
(1) collecting and preprocessing an image;
(2) identifying welding seams through a visual sensor and a laser sensor;
(3) calculating the position coordinates of the key points;
(4) forming welding line teaching information by carrying out image processing on a welding line image of a workpiece to be welded;
(5) and (4) automatic path planning of the robot.
2. A system for profile measurement and identification of a robotic welding workpiece as defined in claim 1, wherein: in the steps (1) and (5), through image processing of machine vision and a welding seam locating algorithm, welding seam teaching information is formed by performing image processing on a welding seam image of a workpiece to be welded and calculating coordinates of the initial position and the final position of the welding seam.
3. A system for profile measurement and identification of a robotic welding workpiece as defined in claim 1, wherein: in the step (2), the spatial position coordinates of the key point positions are processed into robot teaching information through the upper computer, the tail end of a welding gun of the robot is guided to move to a position to be welded, the welding robot has the spatial position self-adaption capability of a workpiece to be welded, and the robot vision intelligent welding line locating of the welding robot is achieved.
4. A system for profile measurement and identification of a robotic welding workpiece as claimed in claim 1, wherein: in the step (3), the visual identification and positioning algorithm based on a deep learning model (a deep belief network, a convolutional neural network and a recurrent neural network multilayer perceptron) is established, a boundary pixel detection algorithm is combined, a double-camera visual system is adopted to realize the detection, identification and accurate positioning of the welding workpiece and the welding seam track, a point set registration method ICP algorithm based on contour features is adopted to realize the accurate matching and quick identification of the contour features or point sets of three-dimensional elements, the correct corresponding relation is calculated step by iteration, and the multi-view registration is adopted to realize the contour measurement and identification of the welding workpiece of the robot.
5. A system for profile measurement and identification of a robotic welding workpiece as claimed in claim 1, wherein: in the step (4), a vision sensor and a laser sensor are integrated in the robot welding system, so that the welding seam tracking in the multilayer multi-pass welding process of the medium plate and the welding seam tracking of the laser deviation corrector through the vision sensor are realized, the motion state of the welding tail end is adjusted in real time, and the welding seam deviation correction is realized through the laser sensor.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115647692A (en) * | 2022-11-03 | 2023-01-31 | 湖南化工职业技术学院（湖南工业高级技工学校） | Automatic welding system and welding method |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115647692A (en) * | 2022-11-03 | 2023-01-31 | 湖南化工职业技术学院（湖南工业高级技工学校） | Automatic welding system and welding method |
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