摘要
针对人工鱼群算法能够解决传统优化算法在局部极值、算法收敛稳定性较差、初始参数设置要求较高等方面的缺陷,提出将人工鱼群算法应用到高射炮经典内弹道数学模型中,以优化高射炮的内弹道性能。优化方案的弹丸炮口速度在满足最大膛压的约束条件下,从初始方案的997.5 m/s提高到1013.36 m/s,通过几次独立的优化过程得到了6种优化方案,方案之间炮口速度和最大压力的差异很小,进一步说明了人工鱼群算法优化过程的稳定性以及应用到高射炮内弹道性能优化的适用性,该研究结果可以为内弹道装药的优化设计提供一定的指导意义。
As the artificial fish swarm algorithm can solve such defects of traditional optimization algorithms as local extremes,poor algorithm convergence stability,and high initial parameter setting requirements etc.,it is proposed to apply artificial fish swarm algorithm to the classical interior ballistic mathematical model of anti-aircraft guns to optimize the interior ballistics performance of anti-aircraft guns.The projectile’s muzzle velocity of the optimization scheme is increased from 997.5 m/s in the initial scheme to 1013.36 m/s under the constraint condition meeting with maximum chamber pressure.Then,six optimization schemes are obtained through several independent optimization processes.The differences of muzzle velocity and maximum pressure among schemes are very small,which further illustrates the stability of the artificial fish swarm algorithm optimization process and the applicability of the optimization of the interior ballistic performance of anti-aircraft guns.The results of this study can provide a certain guiding significance for optimization design of interior ballistic charges.
作者
何新佳
马中亮
代淑兰
HE Xin-jia;MA Zhong-liang;DAI Shu-lan(College of Environment and Safety Engineering,North University of China,Taiyuan 030051,China)
出处
《火力与指挥控制》
CSCD
北大核心
2022年第2期152-156,161,共6页
Fire Control & Command Control
基金
中北大学国防重点实验室基金资助项目。
关键词
高射炮
人工鱼群算法
性能优化
内弹道
收敛稳定性
anti-aircraft gun
artificial fish swarm algorithm
performance optimization
interior ballistics
convergence stability
作者简介
何新佳(1995-),男,四川资阳人,硕士研究生。研究方向:火炮内弹道性能研究。
