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提出了多级搜索技术设计一个优化的组合箱梁飞行转动叶片,搜索技术称之为粒子群优化(受到鸟群飞行的启发),将连续的几何参数(断面尺寸)和箱梁离散折角作为设计变量,使之达到指定刚度和最大弹性连接的设计目标。目前组合箱梁的最大弹性连接增加了直升机转动叶片的气体弹性稳定性。多目标设计可明确表达为组合优化问题,采用粒子群优化技术求解,得到组合箱梁设计的最佳几何夹角为10°、15°和45°。对粒子群优化方法的性质和计算效率与各种设计方法进行了比较。模拟结果清楚显示,在性能和计算时间方面,粒子群优化方法比其他方法优越。
A multistage search technique is proposed to design an optimized rotor blade of a composite box girder. The search technique is called Particle Swarm Optimization (inspired by flocks of birds). The continuous geometric parameters (section size) Variables that meet the design goals of the specified stiffness and maximum elastic connection. At present, the maximum elastic connection of the composite box girder increases the gas elastic stability of the helicopter rotor blades. The multi-objective design can be clearly expressed as a combinatorial optimization problem, which is solved by using particle swarm optimization. The optimal geometrical included angles of the composite box girder design are 10 °, 15 ° and 45 °. The properties and computational efficiency of particle swarm optimization methods are compared with various design methods. The simulation results clearly show that Particle Swarm Optimization is superior to other methods in terms of performance and computation time.