基于粒子群算法的驱动机构多目标动平衡优化

The Multi-objective Optimization of Dynamic Balance in Driving Mechanism Based on the Particle Swarm Algorithm

1.
School of Mechanical Engineering, Jiangsu University, Zhenjiang 212013;
2.
School of Mechanical Engineering, Jiangsu University of Science and Technology, Zhenjiang 212003

摘要: 针对机构动平衡优化问题,综合考虑惯性力、运动副反力和输入扭矩三项动平衡优化性能指标。以冷轧管机驱动机构为对象,根据经典多目标处理方法中的理想点法,建立了衡量机构动平衡优化程度的数学模型。该模型采用粒子群智能算法进行实时优化,算法效率高,能够快速准确地获得平衡参数最优解,实现机构系统整体优化效果。仿真分析表明,该方法能够尽可能地逼近各项平衡性能指标的最优值,有效地解决了机构的多目标动平衡优化问题。
- 粒子群算法 /
- 驱动机构 /
- 多目标优化 /
- 动平衡
Abstract: In this paper, three dynamic balancing performances including inertia force, subsidiary reacting force and inputting torque are considered for the specific problem in dynamic balance optimization. For the driving mech-anism of cold rolling mills, the mathematic model for measuring the degree of dynamic balance optimization is con-structed based on the ideal point method. It could be able to obtain the optimal parameters by proceeding to real-time optimization based on the particle swarm algorithm quickly and accurately. The simulation results indicate that the present method can achieve the optimal value of every dynamic balance performance and effectively solve muhi-objective dynamic balance problems.
- particle swarm algorithm /
- driving mechanism /
- multi-objective optimization /
- dynamic balance

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