高超声速飞行器烧蚀后退量时序提取及基于神经网络的预测

doi:10.3969/j.issn.1000-1093.2021.06.013

摘要/Abstract

摘要： 为了观测高超声速飞行器头部模型在高温流场下的烧蚀现象，在电弧风洞上开展了热考核试验，基于电荷耦合器件相机图像比色测温方法，获得电弧风洞烧蚀模型表面温度随时间演化数据。通过追踪模型边缘温度场变化，给出模型烧蚀过程中形变过程，提取驻点及其他边缘点后退量随时间变化数据。利用最小二乘法和长短期记忆（LSTM）网络方法对烧蚀后退量数据进行拟合与预测，其中LSTM方法主要包括网络结构设计、模型训练、目标函数设定和预测过程的算法实现等。高超声速飞行器烧蚀模型不同位置后退量时间序列预测与试验对比发现：最小二乘法主要适合烧蚀后退量为线性区域的拟合与预测；LSTM方法不但适用于烧蚀后退量线性区域，还适合于端头边缘烧蚀后退量非线性变化区域数据的拟合与预测。

关键词: 高超声速飞行器, 烧蚀, 电荷耦合器件相机, 比色测温, 后退量, 长短期记忆网络模型

Abstract: The ablation phenomenon of hypersonic vehicle head model in high temperature flow field is studied. The thermal test is made in an arc wind tunnel. The temperature evolution data of the arc wind tunnel ablation model with time is obtained using the colorimetric temperature measurement method of CCD camera image. By tracking the change of the temperature field at the edge of the model, the deformation process of the model during ablation is given, and the time series of stagnation point and other edge points are extracted. Least squares method and long-term short-term memory(LSTM) network method are used to fit and predict the ablation recession data. The LSTM method mainly includes network structure design, network training, objective function setting and algorithm implementation of prediction process. Through comparison between the time series prediction and experiment of ablation recession at different positions of the ablation model, it is found that the least square method is mainly suitable for the fitting and prediction of ablation recession in the linear region; the LSTM method is not only suitable for the linear ablation recession, but also suitable for the fitting and prediction of the nonlinear change of ablation recession.

Key words: hypersonicvehicleablation, chargecoupleddevicecamera, colorimetrictemperaturemeasurement, recession, long-termshort-termmemorynetworkmodel

中图分类号:

V416.4

于哲峰，胥建宇，罗跃，杨鹰，刘进博，兰京川. 高超声速飞行器烧蚀后退量时序提取及基于神经网络的预测[J]. 兵工学报, 2021, 42(6): 1230-1237.

YU Zhefeng， XU Jianyu， LUO Yue， YANG Ying， LIU Jinbo， LAN Jingchuan. Time Series Extraction of Ablation Recession of Hypersonic Vehicle and Its Prediction Based on LSTM Neural Network[J]. Acta Armamentarii, 2021, 42(6): 1230-1237.

参考文献

［1］ RENIER E,MERIAUDEAU F,SUZEAU P, et al.CCD temperature imaging: application in steel industry［C］∥Proceedings of the 1996 IEEE IECON 22nd International Conference on Industrial Electronics,Control and Instrumentation.Taipei,China:IEEE,1996:1295-1300．
［2］王补宣，李天铎，吴占松.图像处理技术用于发光火焰温度分布测量的研究［J］.工程热物理学报,1989，10(4)：446-448．
WANG B X,LI T D,WU Z S.The study of image processing technique used for luminous-flame temperature distribution measurement［J］.Journal of Engineering Thermophysics,1989,10(4):446-448. (in Chinese)
［3］朱德忠，刘云峰.航天飞行器防热材料烧蚀过程中表面温度的测量［J］.宇航测量技术,1997,17(4):37-41.
ZHU D Z,LIU Y F.Surface temperature measurements of aerospace heat-resistant materials during ablation［J］.Journal of Astronautic Metrology and Measurement,1997,17(4):37-41.(in Chinese)
［4］薛飞，李晓东，倪明江，等.基于面阵CCD的火焰温度场测量方法研究［J］.中国电机工程学报，1999,19(1):39-41．
XUE F,LI X D,NI M J，et al.Research on temperature field mea- suring for combustion flame based on plane surface array CCD［J］.Proceedings of the CSEE，1999,19(1):39-41.(in Chinese)
［5］孙元，彭小奇，严军.基于彩色CCD的高温场辐射测温方法［J］.仪器仪表学报，2011,32(11):2579-2584.
SUN Y,PENG X Q,YAN J.High-temperature field radiation thermometry based on colored CCD［J］.Chinese Journal of Scientific Instrument,2011,32(11):2579-2584.(in Chinese)
［6］ EDWARD T，SCHAIRER E T，HEINECK J T,et al.Photogrammetric recession measurements of ablative materials during arcjet testing［C］∥Proceedings of the 45th AIAA Aerospace Sciences Meeting and Exhibit.Reno,NV,US:AIAA,2007．
［7］ EDWARD T,SCHAIRER，JAMES T，et al.Predicting camera views for image-based measurements in wind-tunnels［C］∥Proceedings of the 43rd AIAA Aerospace Sciences Meeting and Exhibit.Reno,NV,US:AIAA，2005:1-5.
［8］ OISHI T,MARTINEZ E R,SANTOS J A.Development and application of a TPS ablation sensor for flight［C］∥Proceedings of the 46th AIAA Aerospace Sciences Meeting and Exhibit.Reno,NV,US:AIAA,2008:7-10.
［9］ SCHAIRER E T，MARTINEZ E R，VENKATAPATHY E，et al.Current developments in future planetary probe sensors for TPS［C］∥ Proceedings of the International Workshop on Planetary Probe Atmospheric Entry and Descent Trajectory Analysis and Science.Lisbon,Portugal:European Space Agency,2003:6-9．
［10］ SCHAIRER E T，HEINECK J T.Photogrammetric recession mea- surements of ablative materials in the NASA Ames 60-megawatt arcjet［C］∥Proceedings of the 22nd International Congress on Instrumentation in Aerospace Simulation Facilities.Pacific Grove,CA,US:IEEE,2007:10-14．
［11］ SCHAIRER E T,HEINECK J T.Photogrammetric recession mea- surements of ablative materials in arcjets［J］.Measurement Science & Technology，2010,21(2):1-15.
［12］ HEINECK J T.Photogrammetric recession measurements of ablative materials during arcjet testing［C］∥Proceedings of the 45th AIAA Aerospace Sciences Meeting and Exhibit.Reno,NV,US:AIAA,2007:8-11．
［13］孙翔宇，张炜，胡淑芳，等.绝热材料动态烧蚀试验方法［J］.推进技术，2011，32(4):597-600.
SUN X Y,ZHANG W,HU S F,et al.Methodology of dynamic ablation test for insulation material［J］.Journal of Propulsion Technology，2011,32(4):597-600.(in Chinese)
［14］张智，欧东斌，高贺，等.驻点防热材料线烧蚀量实时投影测量［J］.计量学报，2016，37(4):380-383．
ZHANG Z，OU D B，GAO H，et al.Real-time recession measurement of stagnation thermal protection materials by projective recession measurement method［J］.Acta Metrologica Sinica,2016,37(4):380-383.(in Chinese)
［15］王希亮，何国强，李江，等.基于RTR技术的绝热层烧蚀实时测量试验［J］.固体火箭技术,2006,29(5):384-386．
WANG X L,HE G Q，LI J，et al.Real-time ablation measurement test of insulation based on RTR technique［J］.Journal of Solid Rocket Technology，2006,29(5):384-386.(in Chinese)
［16］ SU H H,FANG X F,QU Z,et al.Synchronous full-field measurement of temperature and deformation of C/SiC composite subjected to flame heating at high temperature［J］.Experimental Mechanics,2015,56(4):1-13．
［17］ QU Z,FANG X,SU H, et al.Measurements for displacement and deformation at high temperature by using edge detection of digital image［J］.Applied Optics,2015,54(29):8731-8737.
［18］ HOCHREITER S,SCHMIDHUBER J.Long short-term memory［J］.Neural Computation,1997,9(8)：1735-1780.

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