航空科学技术2024，Vol.35Issue(10)：35-42,8.DOI:10.19452/j.issn1007-5453.2024.10.004
基于神经网络的飞行课目载荷预测研究
Flight Mission Load Prediction Study Based on Artificial Neural Network
摘要
Abstract
The prediction of high accuracy flight load plays a key role in aircraft life monitoring.Compared with the traditional flying parameter analysis method,neural network has obvious advantages in flight load prediction in complex flight condition.However,most of the prediction models are mainly used to predict a single component flight load.There is a lack of global flight load prediction by flight subject.This paper merges the flight missions,searching for the typical representative measurements of all flight missions to establish vector mapping between flight mission and flight feature vector.In this paper,combining with Principal Component Analysis(PCA)and Genetic Algorithm(GA),the flight load prediction models of different flight missions are trained by the artificial neural network,making global prediction come true to form a new load monitoring model.The checksum result shows that neural network has high prediction accuracy on flight mission load.关键词
飞行载荷预测/神经网络/飞行课目归并/主成分分析法/遗传算法Key words
flight load prediction/neural network/flight missions merge/principal component analysis/genetic algorithm分类
航空航天引用本文复制引用
沈文静,蒋盼盼,李彬..基于神经网络的飞行课目载荷预测研究[J].航空科学技术,2024,35(10):35-42,8.基金项目
航空科学基金(2020Z006066001) Aeronautical Science Foundation of China(2020Z006066001) （2020Z006066001）
