南京航空航天大学学报（英文版）2021，Vol.38Issue(4)：535-544,10.
基于深度神经网络的飞机结冰冰形预测模型
Prediction Model of Aircraft Icing Based on Deep Neural Network
摘要
Abstract
Icing is an important factor threatening aircraft flight safety. According to the requirements of airworthiness regulations,aircraft icing safety assessment is needed to be carried out based on the ice shapes formed under different icing conditions. Due to the complexity of the icing process,the rapid assessment of ice shape remains an important challenge. In this paper,an efficient prediction model of aircraft icing is established based on the deep belief network (DBN)and the stacked auto-encoder(SAE),which are all deep neural networks. The detailed network structures are designed and then the networks are trained according to the samples obtained by the icing numerical computation. After that the model is applied on the ice shape evaluation of NACA0012 airfoil. The results show that the model can accurately capture the nonlinear behavior of aircraft icing and thus make an excellent ice shape prediction. The model provides an important tool for aircraft icing analysis.关键词
飞机结冰/冰形预测/深度神经网络/深度置信网络/栈式自动编码器Key words
aircraft icing/ice shape prediction/deep neural network/deep belief network/stacked auto-encoder分类
数理科学引用本文复制引用
易贤,王强,柴聪聪,郭磊..基于深度神经网络的飞机结冰冰形预测模型[J].南京航空航天大学学报（英文版）,2021,38(4):535-544,10.基金项目
This work was supported in part by the National Natural Science Foundation of China(No.51606213)and the National Major Science and Technology Projects(No.J2019-Ⅲ-0010-0054). （No.51606213）
