【摘要】 为解决超高速卷接机组双倍长烟支传递中的掉丝与空头问题，提出一种基于改进粒子群算法（IPSO）的优化方法，通过降低蜘蛛手抓烟速差进而提升系统稳定性.探究抓烟过程中烟支与蜘蛛手吸爪速差形成机理，建立以速差为目标的优化模型.通过引入自适应调整机制，提高了粒子群算法的收敛速度和搜索效率.采用改进后的粒子群算法求解速差优化模型，并对抓烟速差优化结果进行了对比分析.结果表明，改进粒子群算法在抓烟速差优化问题中具有更高的收敛效率和稳定性，优化后的蜘蛛手在抓烟瞬间的速差显著降低，其中75 mm、84 mm和90 mm烟支的抓烟速差分别降低62.1%、99.9%和31.1%.该优化设计方法可根据不同长度烟支的生产需求进行灵活调整，为蜘蛛手烟支交接系统的优化升级提供理论依据.更多还原

【Abstract】 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.更多还原