含噪信号经验模式分解虚假分量识别方法  

Illusive component identification method in noisy signal EMD processing

作　　者：李纪永[1] 李舜酩[1] 陈晓红[2] 江星星[1] 

机构地区：[1]南京航空航天大学能源与动力学院,南京210016 [2]南京航空航天大学理学院,南京210016

出　　处：《航空动力学报》2014年第10期2486-2492,共7页Journal of Aerospace Power

基　　金：航空自然科学基金(2012ZD52054);青年科学基金(61403193);南京航空航天大学基本科研业务费科研项目(NS2014081)

摘　　要：针对含噪信号Hilbert-Huang变换存在虚假分量,提出改进的奇异值分解(SVD)方法进行降噪,改进包含两个部分:一是利用重构相空间代替传统矩阵如Hankel矩阵,以去掉信号冗余,再者提出奇异值能量熵分量差分法,更易于定出重构奇异值阶次;二是提出了频谱比值法对虚假分量进行辨识,更有效辨识出虚假分量.首先利用经验模式分解(EMD)得到本征模式分量(IMF),识别并剔除趋势项,重构信号,然后进行SVD,重构降噪后的信号,消除虚假分量,最后进行时频分析.联合方法应用于含噪仿真信号,信噪比(signal noise ratio,SNR)提高了5.5%,虚假分量辨识率提高至100%,用于双跨转子故障振动信号,得到正确的时频结果,表明了所提方法识别含噪信号虚假分量的有效性.According to the fact that there exists illusive components when noisy signal is under Hilbert-Huang transform, an improved singular value decomposition （SVD） was firstly proposed for two improvements： one was that the reconstructed phase space was em- ployed instead of traditional matrix such as Hankle matrix in order to remove redundancy, the other was that a singular value energy entropy component difference method was pro- posed, making it easier to determine order of reconstruction singular value. Secondly, a spectrum ratio method was raised to identify illusive components, making it easier to identify illusive components. Intrisinc mode function （IMF） was obtained by empirical mode decom- position （EMD） and trend term was detrended, then the signal was reconstructed for subse- quent SVD operation; the denoised signal was obtained and illusive component was elimina- ted, lastly the signal time-frequency distribution was calculated. The SNR raised 5.5% when the jointly proposed method employed in simulation signal, the illusive component i- dentity ratio raised to 100%, two-span rotor fault vibration signal analysis results show that the jointly proposed method is effective in time-frequency distribution calculation andidentification of noisy signal illusive components.

关 键 词：HILBERT-HUANG变换 频谱比值 虚假分量 相空间重构 奇异值分解 

分 类 号：V233.1[航空宇航科学与技术—航空宇航推进理论与工程]