Online demonstration method for 'J'-shaped groove welding robot

A technology of groove welding and teaching method, which is applied in the direction of welding equipment, welding equipment, auxiliary welding equipment, etc., can solve the problems of reducing the robot's working accuracy, error, and distance error at the end of the welding torch, so as to reduce the influence of teaching human factors , Ensure the consistency of weld quality and solve the effect of rapid positioning

Active Publication Date: 2012-07-18
TIANJIN UNIV
6 Cites 27 Cited by

AI-Extracted Technical Summary

Problems solved by technology

[0004] ①For complex welds, general-purpose welding robots can only use teaching methods or offline programming methods for welding seam trajectory planning
As far as its teaching method is concerned, as the complexity of the path increases, the number of teaching points will increase accordingly, and the workload of teaching will inevitably increase; and its offline programming tends to satisfy the trajectory planning between points. , does not take into account the overall planning of the entire weld trajectory, and this method puts forward higher requirements for the professional quality of the operators
[0005] ②In actual engineering, the robot is generally not easy to move, and frequent moving of the robot will cause errors between the robot base coordinate system and the workpiece coordinate system, reducing the working accuracy of the robot
However, if a general-purpose welding robot is used, it is difficult to solve this problem
[0006] ③ When using a general-purpose robot for welding seam trajectory planning, due to differences in worker proficiency and errors in ar...
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Method used

In summary, the embodiment of the present invention provides a kind of on-line teaching method for " J " type groove welding robot, the embodiment of the present invention obviously reduces weld track feature data by B-spline interpolation The number of points; through the judgment and correction of the circumferential deviation and axial deviation by the microprocessor, the problem of rapid positioning between the robot base coordinate system and the workpiece coordinate system is fundamentally solved; by using the laser rangefinder to collect the distance, reduce the number of operators The influence of human error factors improves the ...
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Abstract

The invention discloses an online demonstration method for a 'J'-shaped groove welding robot, which relates to the field of robot welding, and includes the steps: judging whether circumferential deviation is within a first preset range or not by a microprocessor, acquiring axial deviation if the circumferential deviation is within the first preset range, and if the circumferential deviation is not within the first preset range, rectifying the circumferential deviation by the microprocessor, and acquiring a first practical weld shape track; and judging whether the axial deviation is within a second preset range or not by a microprocessor, if the axial deviation is not within the second preset range, rectifying the axial deviation by the microprocessor, and acquiring a second practical weld shape track or a third practical weld shape track, and if the axial deviation is within the second preset range, leading the J-shaped groove welding robot to return to a start point again, turning off a laser range finder and starting to weld so as to complete the process. The online demonstration method for the 'J'-shaped groove welding robot has the advantages that the quantity of weld characteristic data points are obviously decreased by means of B-spline interpolation, the problem of quick positioning of a robot-based coordinate system and a workpiece coordinate system is fundamentally solved by means of judgment and deviation rectifying of the microprocessor, human factor influence on demonstration is reduced, and weld quality consistency is guaranteed.

Application Domain

Technology Topic

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  • Online demonstration method for 'J'-shaped groove welding robot
  • Online demonstration method for 'J'-shaped groove welding robot
  • Online demonstration method for 'J'-shaped groove welding robot

Examples

  • Experimental program(1)

Example Embodiment

[0051] In order to make the objectives, technical solutions and advantages of the present invention clearer, the embodiments of the present invention will be described in further detail below in conjunction with the accompanying drawings.
[0052] In order to reduce the labor intensity of the trajectory taught by workers, improve the efficiency of trajectory teaching, reduce the influence of teaching human factors, and ensure the consistency of weld quality, the embodiment of the present invention provides a "J"-shaped groove welding robot Online teaching method, see figure 2 , image 3 , Figure 4 with Figure 5 , See the description below for details:
[0053] 101: Establish the intersecting line parameter equation through the tube radius r, the spherical curvature R and the eccentric distance e between the tube and the spherical surface;
[0054] Wherein, this step is specifically: establishing a parameter equation reflecting different curvature spheres and intersecting lines of pipes with different radii at different positions on the sphere according to the tube radius r, the spherical curvature R, and the eccentric distance e between the tube and the spherical surface.
[0055] Parametric equation of intersecting line x ′ = r cos θ y ′ = r sin z ′ = - R 2 - ( x ′ ) 2 - ( y ′ + e ) 2 + R 2 + e 2
[0056] Among them, x'y' and z'represent the coordinates of the intersecting line, and θ represents the angle between the projection of a point on the intersecting line and the origin o'in the x'o'y' plane and the x'axis.
[0057] Among them, the workpiece in the embodiment of the present invention is illustrated by taking a circular tube as an example. In specific implementation, it may also be other workpieces, such as a square tube and a rectangular tube, which are not limited in the embodiment of the present invention.
[0058] 102: According to the intersecting line parameter equation, select N J-shaped groove trajectory characteristic data points under different θ;
[0059] Among them, the value of N is set according to the needs in actual applications. For example, when N is 13, θ=0°, θ=30°, θ=60°, θ=90°...θ =330° and θ=360°.
[0060] 103: Perform B-spline interpolation on N J-groove trajectory characteristic data points to obtain the control vertex of the B-spline curve corresponding to the theoretical trajectory, and calculate the walking path of the welding gun along the theoretical trajectory through the control vertex and set the interval;
[0061] Among them, compared with linear interpolation or arc interpolation in the prior art, the use of B-spline interpolation can reduce the number of selection and storage of weld trajectory feature data points, and ensure the accuracy and smoothness of the welding torch trajectory. B-spline curve is a subset or special case of NURBS (non-uniform rational spline curve), and the B-spline curve equation is defined as
[0062] P ( u ) = X i = 0 n d i N i , k ( u ) u∈[0,1]
[0063] Where d i (i=0,1,...,n) is the control vertex, also known as De Boer point, N i, k (u)(i=0,1,...,n) is called the k-order canonical B-spline basis function, and the value of n is an integer greater than or equal to zero.
[0064] 104: The laser rangefinder is twisted to the vertical tube axis, the J-shaped groove welding robot moves along the theoretical trajectory, and the laser rangefinder collects the distance between the end of the welding gun and the surface of the tube and sends it to the microprocessor;
[0065] Among them, in order to reduce human errors, the embodiment of the present invention adopts a laser rangefinder to collect data information on the distance between the end of the welding gun and the surface of the workpiece.
[0066] 105: The microprocessor processes the distance between the end of the welding gun and the surface of the tube, and obtains the circumferential deviation between the actual weld shape and the theoretical weld shape in the set interval according to the actual weld shape and the intersecting line parameter equation ;
[0067] Among them, the microprocessor processing the distance between the end of the welding torch and the surface of the circular tube specifically includes: removing noise and interference data, fitting and smoothing the data points of the distance between the end of the welding torch and the surface of the circular tube.
[0068] Among them, the embodiment of the present invention uses Kalman filtering to remove noise and interference data processing; the embodiment of the present invention uses fuzzy mathematics to fit and smooth data points. In specific implementation, other methods can also be used for processing. The embodiment of the invention does not limit this.
[0069] Among them, during specific implementation, the set interval may be the four quadrants on the coordinate axis, and may also be set to other intervals according to the needs in actual applications, which is not limited in the embodiment of the present invention.
[0070] 106: The microprocessor determines whether the circumferential deviation is within the first preset range, if yes, execute step 108; if not, execute step 107;
[0071] Wherein, the microprocessor determining whether the circumferential deviation is within the first preset range is specifically:
[0072] 1) The microprocessor analyzes the circumferential deviation and finds the largest data point of the first deviation in each set interval;
[0073] 2) The microprocessor judges whether the maximum data point of the first deviation is within the first preset range.
[0074] Wherein, during specific implementation, the first preset range is set according to actual application needs, which is not limited in the embodiment of the present invention.
[0075] 107: The microprocessor corrects the circumferential deviation and obtains the first actual weld shape track;
[0076] Among them, the microprocessor corrects the circumferential deviation, and obtains the first actual weld shape trajectory as follows:
[0077] 1) The particle swarm search method is used to obtain the first B-spline function parameter with the largest deviation in each set interval, and the first B-spline function parameter is used to find the first parameter that needs to be modified. Several control vertices;
[0078] Among them, the number of control vertices is set according to the needs in actual applications, which is not limited in the embodiment of the present invention during specific implementation.
[0079] Among them, the particle swarm search method mainly has 6 basic implementation steps: ①initialize the starting position and speed of each particle; ②calculate the fitness value of each particle; ③for each particle, if its fitness value is better than its own experience The best position of the past, the current fitness value is used as its new best position; ④For the entire particle swarm, if there is an individual whose fitness is better than the historical best position of the entire particle swarm, then the entire particle swarm is used The individual with the best fitness value is regarded as the new overall best position; ⑤For each particle, first recalculate the position of the particle according to the particle swarm calculation formula; ⑥If the maximum number of iterations or minimum criteria is reached, terminate the program; otherwise, Go to step ②.
[0080] 2) Under the condition that the average deviation between the modified trajectory and the theoretical trajectory is the smallest, and the modified trajectory passes the first data point with the largest deviation, the Lagrangian multiplier method is used to calculate the variation of the first several control vertices;
[0081] Among them, from the local nature of the B-spline function, moving one of the control vertices will only affect the shape of the curve on a limited number of node intervals, ensuring that the shape of the curve outside the control vertices remains unchanged. The Lagrangian multiplier method is used to calculate the changes of several control vertices that need to be modified.
[0082] 3) The circumferential deviation is corrected by the variation of the first several control vertices, and the track of the first actual weld shape is obtained.
[0083] Among them, through the above steps, it is finally realized that the trajectory conforming to the actual weld shape is obtained through the optimal modification of the theoretical trajectory model.
[0084] 108: The J-shaped groove welding robot returns to the starting point, and the laser rangefinder is twisted to the direction of the tube axis. The J-shaped groove welding robot moves along the theoretical trajectory or the first actual weld shape trajectory. The laser rangefinder Collect the distance between the end of the welding torch and the J-groove; process the distance between the end of the welding torch and the J-groove, and obtain the actual weld shape and the parameter equation of the intersecting line within the set interval. Axial deviation between theoretical weld shapes;
[0085] Among them, when there is no circumferential deviation, the J-shaped groove welding robot returns to the starting point and twists the laser rangefinder to the direction of the tube axis, and the J-shaped groove welding robot moves along the walking path of the theoretical trajectory; when there is a circumferential direction When there is a deviation, the J-shaped groove welding robot returns to the starting point, twists the laser rangefinder to the direction of the tube axis, and the J-shaped groove welding robot moves along the trajectory of the first actual weld shape.
[0086] 109: The microprocessor determines whether the axial deviation is within the second preset range, if yes, go to step 111; if not, go to step 110;
[0087] Among them, during specific implementation, the second preset range is set according to actual application needs. The second preset range may be the same as the first preset range or different from the first preset range. No restrictions.
[0088] Wherein, the microprocessor determining whether the axial deviation is within the second preset range is specifically:
[0089] 1) The microprocessor analyzes the axial deviation and finds the second largest data point of the deviation in each set interval;
[0090] 2) The microprocessor judges whether the second maximum deviation data point is within the second preset range.
[0091] 110: The microprocessor corrects the axial deviation and obtains the second actual weld shape track or the third actual weld shape track;
[0092] 1) The particle swarm search method is used to obtain the second B-spline function independent variable parameter of the second maximum deviation data point in each set interval, and the second B-spline function independent variable parameter is used to find the second number that needs to be modified Control vertices;
[0093] 2) Under the condition that the average deviation between the modified trajectory and the theoretical trajectory is the smallest, and the modified trajectory passes the second maximum deviation data point, the Lagrangian multiplier method is used to calculate the change of the second number of control vertices;
[0094] 3) Correcting the axial deviation through the changes of the second plurality of control vertices, and obtaining the trajectory of the second actual weld shape or the trajectory of the third actual weld shape.
[0095] Among them, when there is no circumferential deviation but only axial deviation, the microprocessor corrects the axial deviation and obtains the second actual weld shape trajectory; when there is both a circumferential deviation and an axial deviation, the micro The processor corrects the axial deviation and obtains the third actual weld shape track.
[0096] 111: The J-shaped groove welding robot returns to the starting point again, turns off the laser rangefinder, starts welding, and ends the process.
[0097] Wherein, this step specifically includes: when there is no circumferential deviation or axial deviation, start welding along the walking path of the theoretical track; when there is only circumferential deviation, start along the first actual weld shape track Welding; when there is only axial deviation, start welding along the second actual weld shape track; when there are both circumferential deviation and axial deviation, start welding along the third actual weld shape track.
[0098] The following is a specific test to verify the feasibility of an online teaching method for the "J"-shaped groove welding robot provided by the embodiment of the present invention, see Image 6 with Figure 7 , See the description below for details:
[0099] Test conditions: tube radius r=56mm, spherical curvature R=2190mm, and eccentricity between tube and spherical surface e=850mm, 13 characteristic data points are selected, assuming that θ=125° is the first maximum deviation data point, use B The spline function locally modifies the theoretical trajectory, and the modification process refers to step 104 to step 107. The microprocessor is Intel T44002.2GHz CPU, DDR22G memory. Using Visual studio 2008 programming development platform. In the .NET environment, the welding torch end was adjusted along the circumferential direction of the circular tube. After experiments, it was verified that the local modification time (the time before the shape modification to the shape modification) was 20-25ms, and the controllable error was 0.02mm. Therefore, the method in the embodiment of the present invention not only realizes the online teaching of the "J"-shaped groove welding robot, but also achieves better results in terms of accuracy and speed, and meets the needs in practical applications.
[0100] To sum up, the embodiment of the present invention provides an online teaching method for a "J"-shaped groove welding robot. The embodiment of the present invention significantly reduces the number of weld trajectory feature data points through B-spline interpolation. ; Through the microprocessor's judgment and correction of the circumferential deviation and the axial deviation, the problem of rapid positioning between the robot base coordinate system and the workpiece coordinate system is fundamentally solved; the laser rangefinder is used to collect the distance to reduce the operator's human error factor It also reduces the labor intensity of the trajectory teaching by workers, improves the efficiency of trajectory teaching, reduces the influence of teaching human factors, and ensures the consistency of weld quality.
[0101] Those skilled in the art can understand that the accompanying drawings are only schematic diagrams of a preferred embodiment, and the serial numbers of the above-mentioned embodiments of the present invention are only for description, and do not represent the advantages and disadvantages of the embodiments.
[0102] The above descriptions are only preferred embodiments of the present invention and are not intended to limit the present invention. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection of the present invention. Within range.
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