【摘要】 为进一步提升在线动平衡的精度和效率问题，提出了一种基于粒子群的转子在线动平衡质量补偿优化方法。根据机械式在线动平衡原理建立了一种双配重转子在线动平衡质量补偿模型，运用粒子群算法求解在线动平衡最优量抵消不平衡量；通过搭建高速动平衡电主轴转子实验平台，在不同转速和不同不平衡量条件下进行动平衡质量补偿优化对比实验。结果表明，优化后的动平衡精度相比未优化动平衡精度平均提高18.62%,平均平衡时间降低28.09%。基于粒子群的转子在线动平衡质量补偿优化方法可以有效提高转子动平衡精度及效率，提升旋转机械设备自愈能力。更多还原

【Abstract】 In order to solve the problem of further improving the accuracy and efficiency of online dynamic balance, a mass compensation strategy optimization method of rotor online dynamic balance is proposed based on particle swarm.According to the principle of online dynamic balance, a mass compensation model of rotor online dynamic balance with double counterweights is established, and the mass optimal compensation phase of rotor online dynamic balance is solved to offset unbalance by the particle swarm algorithm.By building an online dynamic balance test platform for motorized spindle, a comparative experiment on dynamic balance mass compensation optimization under different unbalances and different speeds is carried out.The results show that the dynamic balance accuracy after mass compensation optimization is 18.62% higher than that of unoptimized one on average.The average balance time can be reduced by 28.09%.The mass compensation optimization method of online rotor dynamic balance by particle swarm can effectively improve the rotor dynamic balance accuracy and efficiency, and enhance the self-healing ability of rotating machinery.更多还原