一种高空飞艇螺旋桨结构多目标优化设计方法

程俊杰; 王海峰; 尚玲玲

doi:10.13224/j.cnki.jasp.2021.03.014

一种高空飞艇螺旋桨结构多目标优化设计方法

doi: 10.13224/j.cnki.jasp.2021.03.014

基金项目: 国家自然科学基金（51675428）

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- 被引次数: 0
出版历程
- 收稿日期: 2020-07-15
- 刊出日期: 2021-03-28

Multi-objective optimization design method for propeller structure of a high-altitude airship

School of Aeronautics,Northwestern Polytechnical University,Xi’an 710072,China

摘要

摘要: 为了远离旋转激振力的影响避免桨叶共振,需要提高桨叶的弯曲频率,这不可避免的会增加质量。为了解决低质量与高频率之间的矛盾,提出了一种螺旋桨两目标优化方法。以桨叶最小质量和最大弯曲频率作为两个优化目标,以复合材料的铺层角度、铺层厚度和铺层区域作为设计变量,以最大应变、桨尖最大位移和桨叶50%、75%和85%剖面处的扭转角作为约束,使用非支配排序遗传算法(NSGA-Ⅱ)对螺旋桨进行优化设计,得到了关于质量和频率的Pareto解集。转速为520 r/min的两叶桨的转频为8.76 Hz,穿越频率为17.33 Hz,根据频率在Pareto解集上选取远离这两个点的方案。通过制造与测试,得到的实物桨叶频率为12.29 Hz,距离两个共振点都较远,有效的避免了桨叶共振。
- 高空飞艇 /
- 螺旋桨 /
- 复合材料 /
- 弯曲频率 /
- 桨叶共振 /
- 多目标优化 /
- Pareto解集
Abstract: To avoid the resonance of blade caused by rotating exciting force, it is necessary to increase the bending frequency of blade, but this will inevitably increase mass. In order to solve contradiction between low mass and high frequency, a two-objective optimization method of propeller was proposed. The minimum mass and maximum bending frequency were taken as two optimization objectives. The laying angle, thickness and region of the composite were taken as design variables. The maximum strain, maximum tip displacement and torsion angle at the 50%, 75% and 85% section of the blade were taken as constraints. The non-dominated sorting genetic algorthm Ⅱ (NSGA-Ⅱ) algorithm was used to optimize the propeller, and the Pareto solution of mass and frequency was obtained. The rotation frequency of the two blades at 520 r/min was 8.76 Hz and the crossing frequency was 17.33 Hz. The scheme far away from these two points was selected on the Pareto solution set according to the frequency. Through manufacturing and testing, the frequency of the real blade was 12.29 Hz, which was far away from the two resonance points, but can effectively avoid the blade resonance.
- high-altitude airship /
- propeller /
- composite /
- bending frequency /
- blade resonance /
- multi-objective optimization /
- Pareto solution set

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