基于改进粒子群算法的蜘蛛手抓烟速差优化设计OA

To address the issues of fiber drop and hollow head in the handover of double-length cigarettes in ultra-high-speed cigarette making and receiving units,an optimization method based on the improved particle swarm optimization(IPSO)algorithm is proposed,which enhances system stability by reducing the velocity difference between the spider hand and the cigarette during the grabbing process.The mechanism of velocity difference formation between the cigarette and the spider hand's suction claw during the grasping process is investigated,and an optimization model targeting the velocity difference is established.By introducing adaptive adjustment mechanisms,the convergence speed and search efficiency of the particle swarm optimization algorithm are enhanced.The improved particle swarm optimization algorithm is used to solve the velocity difference optimization model,and the results are compared and analyzed.The findings indicate that the improved particle swarm optimization algorithm demonstrates higher convergence efficiency and stability in the optimization of the grasping velocity difference.The velocity difference between the spider hand and the cigarette at the moment of grasping is significantly reduced after optimization,with reductions of 62.1%、99.9%,and 31.1%for cigarettes of 75 mm,84 mm,and 90 mm lengths,respectively.This optimization design method can be flexibly adjusted according to the production requirements of cigarettes of different lengths,providing a theoretical foundation for optimizing and upgrading the spider-hand cigarette handover system.