宇航计测技术 ›› 2017, Vol. 37 ›› Issue (2): 30-35.doi: 10.12060/j.issn.1000-7202.2017.02.07

• 论文 • 上一篇    下一篇

基于ARVM模型的液体火箭发动机试验台故障预测方法

马军强1;陈文丽1;杨思锋1;孙树江1   

  1. 1、北京航天试验技术研究所,北京 100074
  • 出版日期:2017-04-25 发布日期:2017-04-25
  • 作者简介:马军强(1986-),男,硕士,工程师,主要研究方向:液体火箭发动机试验台故障预测。
  • 基金资助:
    装备预先研究航天支撑资助项目(617010604)

Fault Prediction Method for Liquid Rocket Engine Test Stand Based on ARVM Model

MA Jun-qiang1;CHEN Wen-li1;YANG Si-feng1;SUN Shu-jiang1   

  1. 1、Beijing Institute of Aerospace Testing Technology, Beijing 100074, China
  • Online:2017-04-25 Published:2017-04-25

摘要: 针对液体火箭发动机试验台故障子样少,故障预测精度低,故障维修保障困难等问题,在分析标准RVM优缺点的基础之上,提出了一种自适应能力较强的故障预测模型——ARVM(Adaptive Relevance Vector Machine)。为测试该模型,以某型轨控发动机高空模拟试验台管路流量、燃烧室压力为输入参量对推力矢量进行了预测,预测结果表明,ARVM方法能够有效跟踪推力矢量参数的变化趋势,并且获得了较高的预测精度和模型稀疏性。该方法对于复杂系统的故障预测和维修保障具有一定的理论价值和工程应用意义。

关键词: 液体火箭, 发动机试验台, ARVM, 故障预测

Abstract: Aiming at the problems of rare faulty samples, low accuracy of fault prediction and difficulty in maintenance and repair of liquid rocket engine test stand,based on the analysis of the advantages and disadvantages of standard RVM, a fault prediction ARVM model with strong adaptive ability is proposed. In order to test this model, the thrust vector of the high-altitude simulation test stand of a certain orbit control engine is predicted using the flow rate and combustor pressure as input parameters. The prediction result shows that, ARVM method can effectively track the trend of the thrust vector parameters, and obtain a higher prediction accuracy and model sparseness. This method has certain theoretical value and engineering application significance for fault prediction and maintenance of complex systems.

Key words: Liquid rocket, Engine test-stand, ARVM, Fault prediction