CN114161048B - 3D vision-based parameterized welding method and device for tower legs of iron tower - Google Patents
3D vision-based parameterized welding method and device for tower legs of iron tower Download PDFInfo
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- 238000003466 welding Methods 0.000 title claims abstract description 194
- XEEYBQQBJWHFJM-UHFFFAOYSA-N Iron Chemical compound [Fe] XEEYBQQBJWHFJM-UHFFFAOYSA-N 0.000 title claims abstract description 44
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Classifications
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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
- B23K37/0211—Carriages for supporting the welding or cutting element travelling on a guide member, e.g. rail, track
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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
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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
- B23K37/0247—Driving 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
- B25J11/005—Manipulators for mechanical processing tasks
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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
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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
- B25J9/1628—Programme controls characterised by the control loop
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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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- 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
- B25J9/1679—Programme controls characterised by the tasks executed
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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
- B25J9/1694—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
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Abstract
The application discloses a tower foot parameterized welding method for an iron tower based on 3D vision, which comprises the steps of establishing a tower foot ideal model according to tower foot modeling parameters, carrying out track planning by the tower foot ideal model to obtain weld sequence template data and a motion track sequence, carrying out actual weld scanning identification by a 3D vision sensor according to the weld sequence template data and the motion track sequence, generating a welding track sequence according to a scanning result, and sending the welding track sequence to a robot control execution module, wherein the robot control execution module controls a mechanical arm to move through a welding robot controller, and the mechanical arm carries a welding gun to finish welding of a weld. The application also discloses a 3D vision-based tower foot parameterized welding device for the iron tower. The application can self-adapt to non-standard tower feet and ensure welding quality.
Description
Technical Field
The application relates to a tower foot welding method and device, in particular to a tower foot parameterized welding method and device for an iron tower based on 3D vision.
Background
The iron tower is an important foundation and is an upstream important carrier for 5G communication of an extra-high voltage power grid. The tower feet of the transmission line iron tower are supporting parts of the whole transmission line iron tower structure, and the structural stability and the service life of the transmission line iron tower are directly determined by the structural stability of the transmission line iron tower. The welding of the tower feet of the iron tower is generally completed manually, so that the technical level and the working attitude of welding workers directly influence the quality, the production efficiency and the manufacturing cost of iron tower products. There are also some automatic welding systems for welding tower legs, such as welding robots disclosed in chinese patent publication No. CN108746938A, CN107855703 a. These devices can promote the welding work efficiency of standardized batch, but the tower foot is as the basic construction, must adapt to the environment, the geographical condition and the power supply parameter requirement of place, therefore its essence is a nonstandard and fixed parameter's part, and consequently the problem that the robotic system can not adapt to the change of the processing part that needs to carry out at present is always encountered to the producer when carrying out robotic system application. Therefore, in general, these systems are adapted to the change by teaching a dedicated operator for each device in a specific application, which results in that each batch needs a professional operation of the operator, which essentially causes problems that the basic requirements of the operators are not reduced, and a large number of professional robot operators are required to cooperate, so that the system can be put into welding production of new processing components, and a new problem is generated in terms of cost and input period for enterprises.
The chinese patent with publication number CN112658520A, CN112589303a discloses a method for calculating a weld seam by inputting parameters of tower feet and then welding, which solves the problem that the welding parameters need to be continuously taught for the batch tower feet to be changed to adapt to the product change. However, the tower foot is used as a large thick plate part, the front machining and assembly precision is poor, so that more or less errors exist in the welding seam of each workpiece in the same batch, and the errors are difficult to be individually adjusted in the technical scheme, so that the final welding quality of welding is ensured. And because of nonstandard characteristics of the tower feet, the tower feet have the characteristic of large structural size difference of different batches of change structures, and the problem of detection accessibility of some sensing schemes aiming at error adjustment is caused, so that the final detection method fails.
Disclosure of Invention
Aiming at the defects in the prior art, the application provides a 3D vision-based parameterized welding method for tower legs of an iron tower, which aims to solve the problem of automatic adaptation to the error change of a workpiece of the tower legs and improve the welding quality. The application further aims to provide a 3D vision-based tower foot parameterized welding device for the iron tower.
The technical scheme of the application is as follows: A3D vision-based parameterized welding method for tower feet of an iron tower comprises the following steps:
step 1, inputting tower foot modeling parameters to a tower foot modeling module, and constructing a tower foot ideal model by the tower foot modeling module according to the tower foot modeling parameters;
step 2, the tower foot modeling module sends the tower foot ideal model to a tower foot welding seam module, the tower foot welding seam module converts the data structure of the tower foot ideal model and sends the data structure to a visual detection track planning module, and the visual detection track planning module completes detection track planning according to the tower foot ideal model after the data structure is converted, so that welding seam sequence template data and a movement track sequence are respectively obtained;
step 3, the welding seam sequence template data are sent to a 3D vision sensor, the motion track sequence is sent to a robot control execution module, the robot control execution module controls the mechanical arm to move through a welding robot controller according to the motion track sequence, and the 3D vision sensor is connected to the mechanical arm and controls a scanning path through the welding seam sequence template data;
step 4, acquiring weld surface data from the step 3, transmitting the weld surface data to a weld recognition and three-dimensional reconstruction module, calculating weld characteristic data by the weld recognition and three-dimensional reconstruction module, and transmitting the weld characteristic data to a robot welding track planning module;
and 5, the robot welding track planning module generates a welding track sequence according to the welding seam characteristic data and sends the welding track sequence to the robot control execution module, and the robot control execution module controls a mechanical arm to move through a welding robot controller according to the welding track sequence, and the mechanical arm carries a welding gun to finish welding seam welding.
Further, the step 1 includes inputting welding process parameters to the tower foot welding seam module, the step 5 includes the step that the tower foot welding seam module sends the welding process parameters to the welding track planning module, and the robot welding track planning module jointly generates the welding track sequence according to the welding seam characteristic data and the welding process parameters.
Further, the ideal tower leg model is formed by crossing a main side plate with a first side plate and a second side plate and supporting the main side plate, the first side plate and the second side plate by a bottom plate, wherein the first side plate and the second side plate are respectively positioned at two sides of the main side plate; the tower foot modeling parameters comprise length, width and height data of the main side plate, the first side plate and the second side plate, the length and width data of the bottom plate, the cross intersection points of the main side plate, the first side plate and the second side plate are positioned at the bottom plate, and the included angles of the main side plate, the first side plate and the second side plate and the bottom plate are respectively formed.
Further, the weld sequence template data is obtained by: and establishing a light plane model scanned by laser through linear motion, obtaining a fillet weld biplane model from the tower foot ideal model, obtaining 1 sensor detection welding seam template by intersecting calculation of the light plane model and the fillet weld biplane model, and arranging all the sensor detection welding seam templates to be detected in the whole tower foot according to a sensor scanning sequence to obtain a welding seam sequence template.
Further, the motion trail sequence is obtained by the following steps: establishing a sensor viewpoint coordinate system based on the irradiation direction of the 3D vision sensor, and obtaining a fillet weld biplane model by the tower foot welding seam module, wherein two planes in the fillet weld biplane model are intersected to obtain a welding seam For the weld direction, p i For any point on the weld, the normal of the two planes is added to give the weld normal +.>For any one detection point p on the weld iv Pose of 3D vision sensorAll the poses form a motion track sequence.
The other technical scheme of the application is as follows: the utility model provides a tower foot parameterization welding set based on 3D vision, includes tower foot modeling module, tower foot welding seam module, vision detection track module, 3D vision sensor, welding seam discernment and three-dimensional reconstruction module, robot welding track planning module, robot control execution module, welding robot controller, arm and welder, 3D vision sensor and welder all fixed connection are in on the arm, tower foot welding seam module respectively with tower foot modeling module vision detection track module the welding seam discernment with three-dimensional reconstruction module with robot welding track planning module is connected, 3D vision sensor respectively with vision detection track module with welding seam discernment is connected with three-dimensional reconstruction module, robot control execution module respectively with vision detection track module with robot welding track planning module is connected, robot control execution module is connected with welding robot controller and is used for controlling the motion of arm, welding set carries out the aforesaid tower foot parameterization welding set based on 3D vision.
The technical scheme provided by the application has the advantages that:
according to the method, the welding path parameters do not need to be independently modeled and designed manually for each tower leg workpiece, the built model can adapt to the later similar batch of tower leg welding, the pain points with nonstandard multi-error large tower leg welding are solved, the welding quality is ensured, and the production efficiency is improved.
Drawings
Fig. 1 is a system block diagram of an embodiment 3D vision-based tower foot parametric welding device for an iron tower.
Fig. 2 is a flow chart of a parameterized welding method for tower feet of an iron tower based on 3D vision according to an embodiment.
Fig. 3 is a schematic diagram of an ideal model of a tower foot.
Fig. 4 is a schematic diagram of a sensor detection model simulating a real sensor beam.
FIG. 5 is a schematic representation of a sensor model detecting weld model pose.
Fig. 6 is a schematic diagram of a weld detection point.
FIG. 7 is a schematic diagram of a calculation of a detected position on a weld path.
FIG. 8 is a schematic diagram of a weld profile feature identification process.
Fig. 9 is a schematic diagram of the relative position of the welding gun and the welding workpiece.
Detailed Description
The present application is further described below with reference to examples, which are to be construed as merely illustrative of the present application and not limiting of its scope, and various modifications to the equivalent arrangements of the present application will become apparent to those skilled in the art upon reading the present description, which are within the scope of the application as defined in the appended claims.
Referring to fig. 1, the 3D vision-based tower leg parameterized welding device for an iron tower in this embodiment includes a leg modeling module 1, a leg welding seam module 2, a visual detection track module 3, a 3D visual sensor 4, a welding seam recognition and three-dimensional reconstruction module 5, a robot welding track planning module 6, a robot control execution module 7, a welding robot controller 8, a mechanical arm 9 and a welding gun, wherein the 3D visual sensor 4 and the welding gun are fixedly connected to the mechanical arm 9. The welding seam module of the tower foot is respectively connected with the modeling module of the tower foot, the visual detection track module, the welding seam recognition and three-dimensional reconstruction module and the welding track planning module of the robot, the 3D visual sensor is respectively connected with the visual detection track module and the welding seam recognition and three-dimensional reconstruction module, the robot control execution module is respectively connected with the visual detection track module and the welding track planning module of the robot, and the robot control execution module is connected with the welding robot controller for controlling the movement of the mechanical arm. The specific process of each module for processing and transmitting data is described in detail below for the welding method.
Referring to fig. 2, based on the welding device, the parameterized welding method for the tower foot of the iron tower based on 3D vision in this embodiment is as follows:
step 1, a user of the welding device establishes a tower foot ideal model of tower foot welding through interactive operation by combining known priori information of the tower foot, namely tower foot modeling parameters, through a system software interface in an off-line state. "offline" herein refers to a period of time outside of the system when it is not starting to run on site, so its operation can be performed in the office and downloaded to an on site "on-line controller" via a network or removable storage medium. In addition, the system uses two general categories, namely iron tower welding operators capable of reading and understanding design drawing information, and mainly records related simple tower foot modeling parameters according to the drawing information and interface prompts of a 'tower foot modeling module' interface to finish preliminary modeling of a tower foot ideal model.
The ideal model of the tower leg is shown in fig. 3, the main side plate and the first side plate and the second side plate are crossed, and the main side plate, the first side plate and the second side plate are supported by the bottom plate, so that the modeling parameters of the tower leg comprise respective length, width and height data of the main side plate, the first side plate and the second side plate, the length and width data of the bottom plate, the cross points of the main side plate, the first side plate and the second side plate are positioned at the bottom plate, the included angles of the main side plate, the first side plate and the second side plate and the bottom plate are respectively formed by the included angles of the bottom plate and the XY plane, and the included angles of the main side plate, the first side plate, the second side plate and the bottom plate are positive angles towards the positive direction of the XY axis. The ideal model of the tower foot can be completely defined through the parameters. The user then specifies the relevant weld and matches it with the relevant existing process from within the weld welding process library. The other part is a craftsman who grasps the welding of the automatic equipment of the iron tower, which mainly inputs the existing known process information into the welding seam welding process library 10, and two kinds of skills can be grasped by the same person in some cases.
And 2, the tower foot modeling module sends the tower foot ideal model to the tower foot welding seam module, and the sending mode can be stored through a network port processing program or a mobile storage medium and executed by a software interface in an online controller. And the tower foot welding seam module converts the tower foot ideal model into a data structure and then sends the data structure to the visual detection track planning module, and the visual detection track planning module completes detection track planning according to the tower foot ideal model with the converted data structure to respectively obtain welding seam sequence template data and a movement track sequence.
The acquisition of the weld sequence template data is as follows: a sensor detection model simulating a real sensor beam is built in a visual detection track planning module, as shown in fig. 4, wherein a dotted line part is a simulated single-point laser light plane model scanned By linear motion (mathematically described By plane pi: ax+by+cz+d=0), in addition, after the data structure conversion of a tower foot welding seam module, the fillet welding seam of each tower foot is simulated into a structure described By two planes according to tower foot modeling parameters input By a user, and then the piecewise straight line contour l of a scanning signal of a model sensor can be obtained By calculating plane intersection between the light plane model and a fillet welding seam biplane model 1 And l 2 Single segmented contour combination m i ＝(l i1 ，l i2 ) The method is called 1 sensor detection welding seam template, and all the welding seam templates to be detected in the whole tower leg are arranged according to the scanning sequence of the sensor to obtain welding seam sequence template data M for sensor detection i ＝(m i I=1..n), the model data is used as template data according to which signal data obtained by actually scanning the welding seam by the sensor is used for carrying out welding seam identification.
The acquisition of the motion trail sequence is as follows: as shown in fig. 5, the 3D vision sensor itself is composed of a dual ranging point laser, the center of the field of view of the sensor is to establish a "sensor viewpoint coordinate system", wherein the point on the light beam when the sensor reads at the middle value of the range is used as the reference point of the sensor, the midpoint position of the line between the reference points of the two light beam sensors is set as the origin (i.e. viewpoint) of the coordinate system, the Z axis is defined along the sensor irradiation direction toward the sensor, the pseudo X' axis is defined along the direction of the line of the irradiation points when the other two sensor reads at the middle value, the Y axis of the sensor can be obtained by the right-hand rule, the formal X axis of the coordinate system is further normalized by the right-hand rule, and the above information will completely define the "sensor viewpoint coordinate system".
Obtaining a fillet weld biplane model join through a tower foot weld module i ＝(П j ,П k ) Description data, i.e. biplane description II j He Pi (a Chinese character) k From which the corresponding normal to its plane can be obtainedAnd->Fillet normal +_ can be calculated by adding and normalizing the two normal directions>In addition, through the model and combine with the II j He Pi (a Chinese character) k Intersection calculation can obtain the characteristic of the straight-line path of the welding seamSetting a point p on the straight line characteristic of the weld joint iv Detecting the position of the detection point for the welding line, and finally aiming at sea i The sensor detection pose at a certain position is calculated as +.>Wherein->For vector cross multiplication, all the detected poses form a motion track sequence.
Step 3, welding seam sequence template data are sent to a 3D vision sensor, a motion track sequence is sent to a robot control execution module, the robot control execution module controls a mechanical arm to move through a welding robot controller according to the motion track sequence, and the 3D vision sensor is connected to the mechanical arm and controls a scanning path through the welding seam sequence template data;
and step 4, acquiring weld surface data from the step 3, transmitting the weld surface data to a weld recognition and three-dimensional reconstruction module, calculating weld characteristic data by the weld recognition and three-dimensional reconstruction module, and transmitting the weld characteristic data to a robot welding track planning module.
As shown in fig. 6, the tower foot weld is a typical interior angle weld, the key feature points on the weld will be sampled (typically 2N) by scanning, typically n=1 samples if the weld is relatively short, and if the weld is long, the system will automatically plan to sample N >1 samples.
Referring to fig. 7, let the distance between the weld detection points be D, d=ω·d, where ω Σ be a scaling factor, and be mainly set by the user according to the compromise between efficiency and accuracy.
From the fillet weld straight path feature team in step 2 i Can obtain the length l thereof i Dividing the whole weld intoSegments, thus for the straight weld each segment distance is +.>Calculating the position of the detected point on the straight path characteristic of the welding line as +.>Wherein p is 1 Is the starting point position of the welding line path.
The weld joint recognition and three-dimensional reconstruction module calculates weld joint characteristic points according to a weld joint contour characteristic recognition method in a weld joint tracking characteristic extraction method based on structured light vision, and the data are transmitted back to the tower foot weld joint module to be used as actual data of an ideal model weld joint, and relevant states are updated. And the tower foot welding seam module sends the determined welding process parameters and welding seam characteristic point data to the welding track planning module.
The main idea of calculating the characteristic points of the weld joint is shown in fig. 8, and mainly includes that each time the sensor scans the fillet weld to obtain continuous ranging data, the continuous ranging data is developed on a time axis, the piecewise straight line fitting is completed by adopting the least square piecewise straight line segment fitting based on the double threshold value in the 'a method for extracting the characteristic of weld joint tracking based on structured light vision' for the data, the detected outline symbol description of the fillet weld joint is further obtained according to the primitive definition of the piecewise straight line, and then the symbol description is compared with the weld sequence template data M from the foregoing description i ＝(m i I=1..n.) m in N i Matching the corresponding outline symbol description, if the matching is successful, obtaining a final recognition result, and extracting the m i The definition of the consistent welding seam process position is used as the final characteristic position, namely the welding seam characteristic point is calculated through the internal angle geometric relationship.
Step 5, the robot welding track planning module generates a welding track sequence according to the welding seam characteristic data and sends the welding track sequence to the robot control execution module, wherein the generation of the welding track sequence is as follows:
the pose of the welding gun can be obtained by a rigid body pose transformation relative to a weld characteristic coordinate system (SeamCoord), i.eWherein->And->The pose of the welding gun and the welding seam in the robot base coordinate system are respectively +.>The weld defines a universal homogeneous transformation matrix for the weld gun. However, it is not customary to describe this relationship in a matrix in the welding process, but rather to take the 6-dimensional quantities (i.e., robot tool coordinate system position and euler angle representation) represented by the simpler (x, y, z, α, β, γ) where x, y, z are the positions of the welding gun, directly the position o of the weld coordinate system J Alpha is the welding travel angle, beta is the welding work angle, and gamma is the welding spin angle. Referring to fig. 9, the welding travel angle α is the welding gun x H Axis to weld coordinate System xoy J Projection onto a plane and x J An included angle between the two. In the definition |alpha| is less than or equal to 90 degrees, the actual value should be smaller, and is generally smaller than 45 degrees. And positive for forward leaning and negative for backward leaning. The welding working angle beta is the welding gun x H Axis and weld coordinate system xoy J The included angle between the planes. In the definition |beta| is less than or equal to 90 degrees, the actual value should be smaller, and is generally smaller than 45 degrees. The welding spin angle gamma is a welding redundancy degree of freedom, and alpha is less than or equal to 180 degrees.
The pose relationship between the welding gun and the welding line during the welding of the robot is that
Wherein the method comprises the steps of
Thus, for each join in the tower foot weld module i Actual data obtained by sensor detection and generation of robot welding track points according to secondary calculationIs thatAnd all the weld trajectories are serially connected in the order of execution to be the final weld trajectory sequence. And the robot control execution module controls the mechanical arm to move through the welding robot controller according to the welding track sequence, and the mechanical arm carries the welding gun to finish welding of the welding seam.
Claims (2)
1. The parameterized welding method for the tower feet of the iron tower based on 3D vision is characterized by comprising the following steps of:
step 1, inputting tower foot modeling parameters and welding process parameters to a tower foot welding seam module, and constructing a tower foot ideal model by the tower foot welding seam module according to the tower foot modeling parameters, wherein the tower foot ideal model is formed by a main side plate, a first side plate and a second side plate which are crossed and supported by a bottom plate, and the first side plate and the second side plate are respectively positioned at two sides of the main side plate; the tower foot modeling parameters comprise length, width and height data of the main side plate, the first side plate and the second side plate, the length and width data of the bottom plate, the cross intersection point of the main side plate, the first side plate and the second side plate is positioned at the position of the bottom plate, and the main side plate, the first side plate and the second side plate respectively form included angles with the bottom plate;
step 2, the tower foot welding seam module sends the tower foot ideal model to a visual detection track planning module, and the visual detection track planning module completes detection track planning according to the tower foot ideal model to respectively obtain welding seam sequence template data and a motion track sequence;
the welding seam sequence template data are obtained by the following steps: establishing a light plane model scanned by laser through linear motion, obtaining a fillet weld biplane model from the tower foot ideal model, obtaining 1 sensor detection weld template by intersecting calculation of the light plane model and the fillet weld biplane model, and arranging all the sensor detection weld templates to be detected in the whole tower foot according to a sensor scanning sequence to obtain a weld sequence template;
the motion track sequence is obtained by the following steps: establishing a sensor viewpoint coordinate system based on the irradiation direction of the 3D vision sensor, and obtaining a fillet weld biplane model by the tower foot welding seam module, wherein two planes in the fillet weld biplane model are intersected to obtain a welding seam，/>For the weld direction->For any point on the weld, the normal of the two planes is added to give the weld normal +.>For any one detection point on the weld +.>Pose of 3D vision sensorAll the poses form a motion track sequence;
step 3, the welding seam sequence template data are sent to a 3D vision sensor, the motion track sequence is sent to a robot control execution module, the robot control execution module controls the mechanical arm to move through a welding robot controller according to the motion track sequence, and the 3D vision sensor is connected to the mechanical arm and controls a scanning path through the welding seam sequence template data;
step 4, acquiring weld surface data from the step 3, transmitting the weld surface data to a weld recognition and three-dimensional reconstruction module, calculating weld characteristic data by the weld recognition and three-dimensional reconstruction module, and transmitting the weld characteristic data to a robot welding track planning module;
and 5, the tower foot welding seam module sends the welding process parameters to the welding track planning module, the robot welding track planning module jointly generates a welding track sequence according to the welding seam characteristic data and the welding process parameters and sends the welding track sequence to the robot control execution module, the robot control execution module controls the mechanical arm to move through the welding robot controller according to the welding track sequence, and the mechanical arm carries a welding gun to finish welding of the welding seam.
2. The utility model provides a tower foot parameterization welding set based on 3D vision, its characterized in that includes tower foot modeling module, tower foot welding seam module, vision detection track module, 3D vision sensor, welding seam discernment and three-dimensional reconstruction module, robot welding track planning module, robot control execution module, welding robot controller, arm and welder, 3D vision sensor and welder are all fixed connection be in on the arm, tower foot welding seam module respectively with tower foot modeling module vision detection track module, welding seam discernment with three-dimensional reconstruction module and robot welding track planning module are connected, 3D vision sensor respectively with vision detection track module with welding seam discernment and three-dimensional reconstruction module are connected, robot control execution module respectively with vision detection track module with robot welding track planning module, robot control execution module is connected with welding robot controller and is used for controlling the motion of arm, welding set carries out the tower foot parameterization welding set based on 3D vision according to claim 1.
Priority Applications (1)
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| CN114571165B (en) * | 2022-05-07 | 2022-08-23 | 季华实验室 | Welding track planning method and device, welding system and electronic equipment |
| CN114905124B (en) * | 2022-05-18 | 2024-02-13 | 哈尔滨电机厂有限责任公司 | Automatic welding method for magnetic pole iron support plate based on visual positioning |
| CN115155884B (en) * | 2022-06-24 | 2024-08-20 | 深圳市华众远科技有限公司 | Automatic spraying method and automatic spraying robot |
| CN115026385B (en) * | 2022-07-19 | 2023-11-17 | 湘潭大学 | Method for detecting butt weld track information based on double-linear array CCD |
| CN115673630B (en) * | 2022-11-17 | 2023-10-20 | 广州华夏职业学院 | Nonstandard refrigeration house door welding method, system, terminal and medium based on 3D tracking |
| CN118002977B (en) * | 2024-04-08 | 2024-07-30 | 山东省青腾机械科技有限公司 | Tower foot secondary welding seam method of robot |
| CN118023683B (en) * | 2024-04-12 | 2024-06-28 | 成都环龙智能机器人有限公司 | Welding quality real-time control method and system based on visual detection |
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