柔性机翼承载能力的试验与预测

对柔性机翼进行了承载能力的试验及预测研究,首先对柔性机翼的翼型结构进行建模,并对充气机翼的结构进行了分析和优化;其次应用正交试法确定出影响柔性机翼承载能力的主要影响因素,以优化后的结果建立实物模型和主要影响因素为变量进行试验;最后以大量的试验数据为训练样本建立改进的神经网络模型,并进行承载能力预测.试验与预测结果对比研究表明:在初始阶段,柔性机翼在压强一定时,载荷与挠度近似呈线性关系;在同一气压值下,载荷增加到一定值时,载荷与挠度的关系曲线呈近似线性关系,而是斜率突然减小;神经网络测试值和试验实测值最大相对误差与标准方差只有12%和0.39%,人工神经网络解析方法可以用于对充气机翼抗弯刚度的分析.

Experimental and prediction study for bearing capacity of inflatable wing

Experimental and prediction study for bearing capacity of inflatable wing have been done and described in this paper.Firstly,model of aerofoil was established,structure of inflatable wing was analyzed and optimized,then method of orthogonal experiment was used to ascertain the main impact of influence bearing capacity and experimental of inflatable wing was finished for bearing capacity.Artificial neural network was finally adopted to predict bearing capacity.The results show that : (1) In the initial experiment,at the same pressure,the relationship between loading and deflection approximately abides by linearity relations.When reached the fixed pressure,the relationship between loading and deflection is also linearity,but the slope abruptly increases.(2)The relative error between the predicted result and the experiment result is 12%,and standard deviation 0.39%,and show that the bearing capacity prediction model of neural net work can predict the bearing capacity of inflatable wing accurately and rapidly.