空气动力学学报2025，Vol.43Issue(12)：99-108,10.DOI:10.7638/kqdlxxb-2024.0099
基于卷积时序网络的防冰翼面瞬态温度场预测
Transient temperature field prediction on anti-icing wing surface based on convolutional temporal networks
摘要
Abstract
Electric heating for anti-icing is a crucial technique to prevent icing on aircraft wings.Accurate prediction of transient temperature fields on the anti-icing surface of a wing is essential for optimizing the design of electric heating systems.To achieve a quick prediction of these transient temperature fields and shorten the optimization cycle of electric anti-icing systems,we propose a predictive method that couples the proper orthogonal decomposition(POD)with the convolutional temporal networks.This method first utilizes POD to perform dimensionality reduction on the temperature data.Subsequently,with the operation parameters as input and the reduced modal time coefficients as output,we construct a convolutional temporal network based on the 1D convolutional neural networks and the temporal convolutional networks,incorporating a multi-head attention mechanism to highlight key features.We introduce the sample accuracy(SA)evaluation metric to evaluate the accuracy of transient temperature field predictions.Additionally,we explore the impact of model hyperparameters on the prediction performance and validate the effectiveness of the network structure through ablation experiments.Experimental results demonstrate that the proposed method achieves an SA of 94.4%on the test set,indicating a high accuracy in predicting transient temperature fields on anti-icing wing surfaces.关键词
温度场预测/防冰翼面/本征正交分解/卷积时序网络/卷积神经网络/时间卷积网络/多头注意力机制Key words
temperature field prediction/anti-icing wing surface/proper orthogonal decomposition/convolutional temporal network/convolutional neural network/temporal convolutional network/multi-head attention分类
航空航天引用本文复制引用
陈志勇,杨先凤,陈宁立,易贤,彭博..基于卷积时序网络的防冰翼面瞬态温度场预测[J].空气动力学学报,2025,43(12):99-108,10.基金项目
四川省自然基金青年基金(2023NSFSC1332) （2023NSFSC1332）
国家重大科技专项(J2019-Ⅲ-0010-0054) （J2019-Ⅲ-0010-0054）
