摘要
根据直升机在舰面系留时的受力情况,提出一种以直升机6个刚体位移为变量的系留载荷计算方法。针对系留索预紧力优化属于多变量连续空间优化这一特点,采用嵌入确定性搜索的连续域蚁群算法对系留索预紧力进行优化,并在算法中加入MMAS策略,防止算法过早陷入局部最优解。结果表明,该蚁群算法经过二十多步迭代后能够使目标值稳定地收敛,较好地解决了直升机系留索预紧力优化问题。最后,对某型直升机无预紧力和预紧力优化后的系留载荷进行对比分析,无预紧力时多条索具持续松弛未起到系留作用,而预紧力优化后系留索最大张力降低了35.02%,且索具张力分布更均匀。
According to the force condition of the helicopter mooring on the ship,we proposed a calculation method for mooring load which takes 6 rigid displacements of helicopter as the variants. The optimisation of mooring cables preload is a problem of multivariable continuous space optimisation. Aiming at this characteristic,we used the ACO algorithm in continuous domain with the deterministic search embedded to optimise the mooring cables preload,and added MMAS strategy to the algorithm to prevent it falling into local optimal solution too early.Results showed that this ACO algorithm enabled the object value stably converging after iterating more than 20 steps,thus well solves the problem of the helicopter mooring cables preload optimisation. Finally,we made the comparative analysis on the mooring load of a certain type of helicopter without the preload and with the optimised preload. When without the preload,the cables went on relaxed and having no mooring role,however the maximum tension of mooring cables had a 35. 02% decrease after the preload being optimised,and the cables tension distributed more evenly as well.
出处
《计算机应用与软件》
CSCD
2016年第3期114-117,132,共5页
Computer Applications and Software
关键词
直升机
系留
预紧力
蚁群算法
优化
Helicopter
Mooring
Preload
Ant colony optimisation（ACO）
Optimisation
