摘要
使用空机重量是飞机概念方案设计中的重要参数之一,其相对大小直接体现了飞机的设计效率,表征飞机在材料应用、结构设计、系统架构等方面的先进性。本文对目前使用空机重量估算常用的几种方法进行了研究,分析对比了传统线性拟合方法以及非线性拟合方法在实际应用中的适用性,并以宽体客机为例进行了估算分析。在此基础上,考虑样本数量较少和神经网络方法的优点的情况下,基于径向基(RBF)神经网络建立了一种新的估算模型,并将其应用于飞机使用空机重量估算,结果显示新方法大大提高了估算精度,对民用飞机概念设计阶段的使用空机重量估算具有直接参考价值。
The operational empty weight(OEW)is one of the most important parameters in the aircraft conceptual design,and its relative size directly reflects the design efficiency of the aircraft,which represents the advanced nature of the aircraft in terms of material application,structural design,system architecture and so on.This paper studies several commonly used methods for estimating operational empty weight at present,then the applicability of traditional linear fitting methods and nonlinear fitting methods in practical applications is analyzed and compared by estimating the OEW for the wide-body aircraft as an example.On this basis,considering the small number of aircraft samples,less design parameter data and the advantages of the neural network method,a new estimating model of the operational empty weight for large aircraft is established based on RBF neural networks and applied to the aircraft weight estimation,the results show that the new method greatly improves the estimation accuracy and has direct reference for the estimation of operational empty weight in the conceptual design stage of civil aircraft.
作者
程江涛
白璐
袁昌运
张征
Cheng Jiangtao;Bai Lu;Yuan Changyun;Zhang Zheng(COMAC Beijing Aircraft Technology Research Institute,Beijing 102211,China)
出处
《航空科学技术》
2022年第11期21-26,共6页
Aeronautical Science & Technology
关键词
使用空机重量
民用客机
估算方法
线性拟合
非线性拟合
径向基神经网络
operational empty weight
civil airplane
estimation methods
linear fitting
non-linear fitting
RBF neural network
