基于改进粒子群算法的自动机性能评估

由于自行高炮自动机状态监测中缺乏行之有效的机构性能评估手段,引入了改进粒子群算法。建立了自动机动力学模型,对后坐过程进行了动力学仿真,确定了反映机构性能的浮动曲线特征量。针对粒子群算法收敛速度慢、精度低等缺陷,对其进行改进,并结合曲线特征量对自动机性能参数进行了评估。结果表明:改进后粒子群算法的算法收敛性和结果精度都有明显的改善,有效实现了自动机的性能参数评估。

Performance Assessment of Auto-mechanism Based on Improved PSO

For the lack of effective method in the condition monitoring of the auto-mechanism of self-propelled anti-aircraft gun system,an approach of improved Particle Swarm Optimization(PSO)is introduced. Established the dynamic model of the auto-mechanism to simulate the recoil process and determined the characteristic quantity of the gun chest back curve to reflect the mechanical performance state,an approach of improved Particle Swarm Optimization(PSO)with better convergence and precision is proposed to evaluate the state parameters based on the curve characteristic quantity. The result shows the obvious advantage of the convergence and accuracy,and it achieves the state parameters assessment of auto-mechanism.