基于人工鱼群算法的加农炮内弹道参数优化研究  

Research on the Optimization of Interior Ballistic Parameters of a Cannon Based on the Artificial Fish Swarm Algorithm

作　　者：何新佳 马中亮 代淑兰 HE Xinjia;MA Zhongliang;DAI Shulan(College of Environment and Safety Engineering,North University of China,Taiyuan 030051,Shanxi,China)

机构地区：[1]中北大学环境与安全工程学院,山西太原030051

出　　处：《火炮发射与控制学报》2022年第1期36-41,共6页Journal of Gun Launch & Control

摘　　要：基于100 mm加农炮经典内弹道数学模型,以最大膛压及初速的计算值与靶场射击试验值的平均相对误差为目标函数,以燃速系数和燃速指数作为拟优化的参数,运用人工鱼群算法对加农炮内弹道参数进行了参数优化研究。结果表明,人工鱼群算法对初值要求不高,容许范围大,且收敛速度快,全局寻优能力强,计算得到的目标函数值不超过0.1%。将优化后的参数应用到加农炮内弹道计算中,其计算结果与靶场试验结果相对于参数优化前误差进一步减小,其中参数优化后速度的误差仅为0.017%,优化后计算值与靶场试验值吻合得较好,因此可以将人工鱼群算法作为加农炮内弹道参数优化的一种有效方法。Based on the classic interior ballistic mathematical model of the 100 mm cannon,the ave-rage relative error between the simulation value and the range firing experimental value of the maximum chamber pressure and muzzle velocity is taken as the objective function,and the burning rate coefficient and the burning rate exponent are used as the parameters to be optimized.The artificial fish swarm algorithm is used to optimize the cannon′s interior ballistic parameters.The results show that the artificial fish swarm algorithm does not have high requirement of initial values,has a large allowable range,fast convergence speed,strong global optimization ability,and the calculated objective function value does not exceed 0.1%.The optimized parameters are applied to the interior ballistic calculation of the cannon,and the error between the calculated results and the resultsof the rangeexperiment is further reduced compared with that before the parametric optimization,in which the relative error of velocity after parameter optimization is only 0.017%,the calculated values are in good agreement with the measured values.Therefore,the artificial fish swarm algorithm can be used as an effective method to optimize the interior ballistic parameters of cannons.

关 键 词：加农炮 内弹道 人工鱼群算法 参数优化 平均相对误差 

分 类 号：TJ34[兵器科学与技术—火炮、自动武器与弹药工程]