基于改进粒子群算法的最小二乘影响系数法的理论及实验研究

摘要

For the problem that the residual vibration of some measured points and the balancing weight were comparatively larger in a rotor balance process with the least-square influence coefficient method, a particle swarm optimization with cross-factors was introduced into the least-square influence coefficient method for rotor balancing. Theoretical analysis showed that the improved algorithm has a good convergence and an ability of global searching; it can reduce the maximum balancing weight and the maximum residual vibration effectively, compared with the basic least-square influence coefficient method. Tests verified the correctness and feasibility of the proposed method.%针对最小二乘影响系数法平衡过程中出现的某些测点残余振动较大及平衡质量较大等问题,将一种基于遗传交叉因子改进的粒子群算法引入到转子动平衡最小二乘影响系数法中.实例计算说明改进后的算法具有很好收敛特性和全局搜索能力,与基本最小二乘影响系数法计算结果相比,有效降低最大配重质量和最大残余振动大小.通过实验验证了结果的正确性和方法的可行性.