Study On Automatic Stacking System Of Turbine Generator’s Stator Core Based On Industrial Robot

The traditional stacking mode of the turbine generator stator core is by hand. It causes high cost and low efficiency. With the rapid development of industrial automation, this mode of production has been unable to meet the needs of the market and automatic stacking of generator stator core by industrial robot has been gradually focused on.In this paper, based on the requirements of turbine generator stator core stacking process, the automatic stacking system of generator stator core by robots, instead of men, has been designed. The system is realized, based on the FANUC R-2000 iB robot, by using iRVision 3DL vision system. The main research of paper contents are following: through the theoretical research on visual positioning technology of robot, determine one edge and one circle of silicon steel sheets as the visual feature; Through the iRvision software, the selection, installation and calibration of the camera are finished and the visual teaching program of silicon steel sheet is realized. To improve the stabilization of the visual system, the visual system has been optimized: using double vision instead of single vision to improve the vision positioning accuracy; Filling controllable light on the visual system to improve the stability of the vision.Compare with several kinds of catching big and thin shaped ferromagnetic workpiece’s mode, chose the permanent magnet as the power to catch the silicon steel sheet. Through learning the theory of permanent magnet and making a modeling analysis, we determine the relation between the air gap and magnetic force and find the method to absorb the silicon steel sheet stably. According to the shape of silicon steel sheet, complete the arrangement of permanent magnets and realize the stable catch of silicon steel sheet.According to the requirements of the stator core production technology, we build the silicon steel sheet automatic stacking system and design the principle of the control system, work flow for robot and operation interface. Finally, we verify the effect on the whole system, and optimize the success rate and cycle time of the system. After testing and optimizing the system several times, the stability of the system has significantly increased and the success rate of the system is more than 99.5% at last.