|Table of Contents|

Estimation method for coefficient of kerosene filling temperature rise model under small sample(PDF)

《火箭推进》[ISSN:1672-9374/CN:CN 61-1436/V]

Issue:
2019年06期
Page:
90-94
Research Field:
测控与试验
Publishing date:

Info

Title:
Estimation method for coefficient of kerosene filling temperature rise model under small sample
Author(s):
LIU Jinjie;  XU Qiqi;  FU Shanchuan;  DOU Tianheng
(Xichang Satellite Launch Center, Wenchang 571300, China)
Keywords:
small sample;  kerosene temperature;  coefficient estimation;  Bayes regression
PACS:
V511
DOI:
-
Abstract:
In order to eliminate the deviation between the actual rocket’s kerosene filling temperature and the theoretical result calculated by current filling temperature rise model, and estimate kerosene temperature for accurate injection and precise control, Bayesian regression method was proposed to estimate fluctuation coefficient of the temperature rise model based on a very few sample data at launching site.It takes the empirical parameters as the prior information to give a distribution of parameters to be estimated, and uses real data to calculate Bayesian risk.The parameters of the filling temperature rise model were optimized by minimizing the risk function.Numerical results show that, compared with the given experience parameters and least square results, the kerosene temperature calculated by Bayes regression is much closer to the actual result.With the increase of available data sample capacity, the parameter estimation accuracy of Bayesian regression tends to converge.Bayesian regression can improve the precision of filling temperature rise model efficiently, and provides a foundation to improve the accuracy of propellant filling.

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Last Update: 2019-12-20