Dynamic Optimization On Mechatronics System Of Single-pass Flexible Roll-die Forming Machine Considering Forming Force

For the movable mold fixed roll forming machine,vibration and shock during processing have a direct impact on the forming quality of the part.In order to To improve machining accuracy,the demand for optimized design of roll-bending forming machines has been urgenter.In this paper,taking the first pass of the flexible roll-die forming machine as the research object to solve this problem.Based on this,analyzing the dynamic characteristics during the first pass of processing.Then,determining the optimization target and using the quantum particle swarm optimization algorithm that has been improved to optimize dynamic characteristics of the mechatronics system.At first,according to the whole mechanical structure,analyzing the composition of each part of the movement.And establishing the energy conservation equation of the first pass flexible roll-die forming machine based on the principle of energy.By means of the dynamic analysis of the current experimental prototype,it is determined that the experimental prototype needs to be optimized for motion performance.And the maximum acceleration of the large rack movement along the X direction is determined as the optimization object.Then,selecting quantum particle swarm optimization algorithm to perform dynamic optimization of the flexible roll forming electromec-hanical system.Because of problems such as premature local convergence in the optimization process,improving the algorithm and analyzing it.At last,using the improved quantum particle swarm optimization algorithm to optimize the research object.Based on the optimized moving image of the flexible roll forming electromechanical system,comparing the acceleration that before and after optimization.After the optimization,the maximum acceleration of the large frame along the x-direction motion decreases significantly and the acceleration becomes more smoothly in the first 1.5 seconds.This proves that the dynamic performance has been improved significantly after dynamic optimization.