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基于主元分析法的液体火箭发动机传感器故障检测与诊断 被引量:12

Fault Detection and Diagnosis for Sensors of LRE Based on PCA
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摘要 针对液体火箭发动机的压力、温度、流量等传感器数据,给出了一种基于主元分析法的传感器故障检测与诊断方法。该方法能够在对测量参数相关性分析的基础上,将传感器测量值所组成的测量空间分解为主元和残差两个子空间,通过传感器实际测量数据与正常数据矩阵在残差子空间投影的比较,对传感器的故障进行检测与诊断。以某型LRE传感器组为研究对象,通过故障模拟,给出了该方法对4种典型传感器故障的检测与诊断实例。结果表明主元分析法对LRE传感器具有很好的故障检测和故障诊断能力。 A sensor fault detection and diagnosis method using Principal Component Analysis(PCA) for pressure,temperature and flux data of liquid-propellant rocket engine(LRE) was presented.This method,which divides the measure space into two subspaces: principal component subspace (PCS) and residual subspace(RS) based on the correlation analysis of measure data,can detect and diagnose sensor faults by comparing the projections in RS of actual sensors measurement and normal data matrix.Examples of using PCA to fault d...
出处 《宇航学报》 EI CAS CSCD 北大核心 2007年第6期1668-1672,1703,共6页 Journal of Astronautics
基金 教育部新世纪优秀人才支持计划(NCET-06-0927)
关键词 液体火箭发动机传感器 主元分析法 故障检测与诊断 Sensors of liquid-propellant rocket engine Principal component analysis(PCA) Fault detection and diagnosis
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参考文献5

  • 1[1]Amand T,Heyen G,Kaliventzeff B.Plant monitoring and fault detection synergy between data reconciliation and principal component analysis[J].Computer and Chemical Engineering,2001(25):501-507
  • 2[2]Seongkyu Y,MacGregor J F.Fault Diagnosis with Multivariate Statistical Model Part Ⅰ:Using Steady State Fault Signatures[J].Journal of Process Control,2001,(11):387-400
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  • 5[6]Li W,Consistent S J.Dynamic PCA Based on Error-in-variables subspace identification[J].Journal of Process Control,2001 (11):661 -678

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