期刊文献+

基于神经网络算法的液体火箭发动机实时故障检测方法研究 被引量:2

Real-time fault detection method based on neural network algorithm for LRE
下载PDF
导出
摘要 以某液体火箭发动机为研究对象,将实时故障检测作为中心,分析了神经网络算法的特点及其实现步骤,利用Lab Windows/CVI与MATLAB混合编程的原理,实现和改进了基于神经网络的发动机实时故障检测方法,并用多次试车数据进行了检验。试车数据验证结果表明,该方法能及时、准确、有效地检测发动机稳态过程的故障。研究结果对发展未来液体火箭发动机的箭载故障检测系统具有重要的参考价值。 The real-time fault detection for a liquid-propellant rocket engine (LRE) is put on emphasis in this paper. The real-time fault detection based on the neural network algorithm is realized and ameliorated by means of analyzing the characteristic and realization steps of neural network (NN) algorithm, using the composite programming method with Lab Windows/CVI and MATLAB. The algorithm proposed in the paper has been tested and verified with a large amount of hot-fire test data of LRE. The results show that the method can detect the faults occurred in the steady-state process of LRE efficiently and accurately. The method presented can be valuable for the development of on-board fault detection system of LRE.
出处 《火箭推进》 CAS 2005年第5期5-10,共6页 Journal of Rocket Propulsion
基金 "八六三"基金资助项目。
关键词 神经网络 液体火箭发动机 混合编程 实时故障检测 neural network liquid-propellant rocket engine composite programming real-time fault detection
  • 相关文献

参考文献2

  • 1[7]Martin T Hagan, Howard B Demuth, Mark H Beale. Neural network design[M]. PWS Publishing Company, 1996.
  • 2[8]The Math Works Inc. Neural Network Toolbox User's Guide(Version 4)[M]. 2001.

同被引文献27

引证文献2

二级引证文献10

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部