Search

Robot off-line programming is widely used in the field of spatial intersection curve welding. However, several existing problems are needed to be resolved which include the following: the operation process depends on the third-party CAD software, the welding trajectory planning depends on the precise analytical formula, and the determination of welding posture lacks fusion of geometrical features of surrounding surfaces. This paper presents an off-line programming method of spatial intersection curve welding based on visualization toolkit (VTK). In this method, the visualization pipeline and observer/command mode of VTK are used to display the 3D model of the robot welding system and pick up the surfaces around the welding seam respectively. By calculating the normal vectors of the picked surfaces, the equidistant cutter planes perpendicular to these surfaces can be automatically created to form the planning weld nodes on the intersection of the surfaces, and the position and posture of the welding torch on weld nodes can be extracted. Furthermore, the position and posture along the weld curve are discretized by B-spline curve interpolation and quaternion spherical linear interpolation, respectively. Finally, the motion simulation is realized by the application of robot inverse kinematics. This method does not depend on the specific form of intersection, and all calculation processes are completed within the system, avoiding tedious external data calculation and import process. The correctness and practicability of the method are verified by the welding experiment of saddle-shaped cylindrical intersection pipes.

During the flatness control process, there are frequently some uncoordinated regulating behaviors in the flatness actuator group. This has a bad influence on the flatness control accuracy and the flatness control efficiency. Therefore, a collaboration strategy based on conflict resolution for the flatness actuator group has been proposed in this paper. First of all, the feature of flatness measurement value is extracted through establishing the actual flatness condition discriminating factor. After that, the coordination cooperation that is appropriate to the actual flatness condition is developed for the flatness actuator group. Finally, the optimal adjustment of the actuator population is solved by the coordinated algorithm of Topkis-Veinott and genetic algorithm collaborative optimization. The collaboration strategy proposed in this paper has been successfully applied to a flatness control system of a 1450 mm five-stand cold rolling mill.