摘要
提出基于经验模式分解(EMD)分析的特征提取方法,该方法自适应地将故障信号分解为不同频段上的基本模式分量(IMF)之和,由于只有少数IMF对故障敏感,从而可以有效提取故障特征。实验结果表明该方法可有效提取电机早期隐性故障特征,为飞机机电作动系统的故障预测和健康评估提供必要的前期准备。
An improved feature extraction method based on Empirical Mode Decomposition（EMD）analysis is presented. This method decomposes the fault signal into the sum of Intrinsic Mode Function（IMF）adaptively, which effectively obtains the characteristic information of raw data for only little IMF is sensitive to the fault. As simulation result shows, this method can extract the forepart recessive fault feature, and provide necessary forepart provision for fault prognostics and health evaluation for airplane electro-mechanical actuation system.
出处
《计算机工程与应用》
CSCD
2014年第3期247-249,264,共4页
Computer Engineering and Applications
基金
航空科学基金(No.20080896009)
关键词
机电作动系统
故障诊断
预测与健康管理
经验模式分解
electro-mechanical actuation system
fault diagnosis,prognostics and health management
Empirical Mode Decomposition（EMD）
