Application of surrogate optimization in rotor dynamics design
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摘要:
旋翼动力学设计传统方法以桨叶固有模态避开气动激励频率为准则，从方法原理和工程实践看难以产生最小化桨毂动载荷的设计效果。为探索改进，开展了Kriging代理优化技术在旋翼动力学设计中的应用研究，针对GJB“直升机旋翼动力学设计要求”，构建了以极小化桨毂动载荷为目标，以固有频率间隔为约束的优化模型；在期望改善（EI）加点准则基础上，利用多目标优化Pareto解集，提出了一种并行加点策略，避免训练样本过于集中。对某实验旋翼开展了动力学优化设计，获得了桨叶剖面刚度与线密度的最优分布，桨毂动载荷相比初始值降低了36%，桨叶疲劳载荷也有不同程度降低。
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关键词:
- 旋翼动力学 /
- Kriging代理模型 /
- 优化设计 /
- 减振 /
- 剖面特性
Abstract:The traditional method of rotor dynamics design is based on the criterion that the inherent mode of the blade avoids the aerodynamic excitation frequency. But, this method is difficult to minimize the hub dynamic loads. In order to explore methods of improvement, the application of Kriging surrogate optimization technology in rotor dynamics design was studied. According to GJB “helicopter rotor dynamics design requirements”, an optimization model with the goal of minimizing the hub dynamic loads and the constraint of natural frequencies interval was constructed. Based on expected improvement (EI) method, a parallel infill strategy was proposed by using Pareto solutions which can avoid local concentration of training samples. The dynamic optimization design of an experimental rotor was carried out, and the optimal distribution of blade section stiffness and density was obtained. The results showed that, the hub dynamic load was reduced by 36% compared with the initial value, and the blade fatigue loads were also reduced.
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表 1 旋翼基本参数
Table 1. Basic parameters of the rotor
参数 数值及说明 桨叶片数 5 桨毂形式 球柔式 旋翼半径R/m 2 旋翼转速/（r/min） 1026 前进比 0.2 配平升力系数 0.015 配平阻力系数 0.0003 
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表 2 模态频率对比
Table 2. Comparison of rotor modal frequencies
模态频率 数值 初始 优化 ωβ2 /Ω 2.56 2.47 ωβ3 /Ω 4.31 4.21 ωζ2 /Ω 5.24 5.61
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