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基于自由尾迹方法建立了直升机桨叶空气动力学分析模型,应用人工神经网络方法建立代理模型,采用改进的多目标遗传算法构建了优化框架,对直升机的悬停和大速度前飞状态进行优化.以悬停效率、旋翼等效升阻比及桨叶叶素的最大阻力系数为约束,对两个飞行状态的需用功率进行优化,得到了Pareto最优解集.并以UH-60A直升机的桨叶为算例,对其外形进行优化设计,优化结果表明,提出的桨叶气动外形多目标优化框架是有效可行的.
The aerodynamic analysis model of helicopter blades is established based on the free wake method. The artificial neural network method is used to establish the proxy model. The improved multi-objective genetic algorithm is used to construct the optimization framework to optimize the helicopter hovering and high-speed forward flight. Taking the hover efficiency, the equivalent lift-drag ratio of the rotor and the maximum drag coefficient of the propeller as constraints, the Pareto optimal solution set was optimized for the required power of the two flight states, and the optimal solution set was obtained with UH-60A helicopter The blade is used as an example to optimize the design of the profile. The optimization results show that the proposed multi-objective optimization framework of aerodynamic profile is feasible and effective.