航空学报 > 2014, Vol. 35 Issue (9): 2472-2480   doi: 10.7527/S1000-6893.2014.0064

基于实测数据的飞机平台动态温度预计模型

傅耘, 常海娟, 武月琴, 薛和平   

  1. 中国航空综合技术研究所, 北京 100028
  • 收稿日期:2013-11-29 修回日期:2014-04-18 出版日期:2014-09-25 发布日期:2014-04-24
  • 通讯作者: 常海娟,Tel.:010-84380373 E-mail:changhaijuan@163.com E-mail:changhaijuan@163.com
  • 作者简介:傅耘 男,硕士,研究员。主要研究方向:装备环境工程、腐蚀与防护。Tel:010-84380253 E-mail:fuy@cape.ac.cn;常海娟 女,博士,高级工程师。主要研究方向:环境分析与预计。Tel:010-84380373 E-mail:changhaijuan@163.com

Dynamic Temperature Predicted Model for Airplane Platform Based on Measured Data

d:\PDF\.pdfFU Yun, CHANG Haijuan, WU Yueqin, XUE Heping   

  1. China Aero-Polytechnology Establishment, Beijing 100028, China
  • Received:2013-11-29 Revised:2014-04-18 Online:2014-09-25 Published:2014-04-24

摘要:

准确预计飞行过程中飞机平台诱发的温度,可以为提出机载设备环境适应性要求,开展环境适应性设计和试验验证提供更精确的输入。为此,对飞机舱室的热形成机制进行了研究;考虑多种因素对飞机各舱室热环境的综合影响,提出了一种基于实测数据的飞机平台动态温度预计算法;依据所建立模型,以平飞状态为切入点,用线性回归的方法估计并拟合了模型系数随高度、马赫数变化的函数;最后,对模型进行了修正及验证。模型验证结果表明,建立的动态温度预计模型可较准确地预计飞机设备舱内温度随飞行状态变化的曲线。误差分析结果表明,模型对某型飞机95%置信度下的预计误差不超过4.5 ℃。

关键词: 飞机平台, 温度条件, 实测数据, 温度预计, 线性回归

Abstract:

To make more accurate input for giving environmental worthiness requirement of airborne equipment, as well as conducting the design of environmental worthiness and test certification, the prediction of temperature on airplane platform during flying is necessary. Therefore, the mechanics for the formation of thermal is researched; then, considering multi-factors influencing thermal environment of airplane cabin, a dynamic temperature predicted model based on measured data is advanced; still more, starting from level flying state, the model coefficients are regressed and the functions of coefficients versus height and Mach number are fixed; further, the predicted model is corrected and certificated and results show that the dynamic temperature predicted model can predict the curve of temperature of equipment cabin via flying state; finally, results of error analysis indicates that model predicted error is no more than 4.5 ℃ on fiducial probability of 95%.

Key words: airplane platform, temperature condition, measured data, temperature prediction, linear regression

中图分类号: