关键词: 航空薄壁件, 夹具设计, 定位布局, 预测模型, 支持向量回归机, 径向基神经网络

Abstract: Aiming at the characteristics of Aeronautical thin-walled part (ATWP) such as thin wall and low rigidity,to optimize the fixture locating layout and improve the fixture design efficiency,a prediction model for ATWP fixture locating layout design and optimization was developed.The training and testing data sets were generated by running only a few times of Finite Element Analysis (FEA) on the design sites standing for different fixture locating layouts selected through Latin Hypercube Design (LHD).The locating layout optimization prediction model based on Support Vector Regression (SVR) was built by learning from the limited training sample set to approximate the implicit function relationship between fixture locating layout and concerned ATWP strain energy,and meanwhile was compared with Radial Basis Function Neural Network (RBFNN) in terms of prediction accuracy on the same testing sample set.An aircraft fuselage skin case was studied to verify the proposed method.

Key words: aeronautical thin-walled part, fixture design, locating layout, prediction model, support vector regression, radial basis function neural network