期刊文献+

非平稳信号的盲源分离在机械故障诊断中的应用 被引量:15

BLIND SOURCE SEPARATION FOR NONSTATIONARY SIGNAL AND IT'S APPLICATION IN MECHANICAL FAULT DIAGNOSIS
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摘要 机械设备发生故障时,故障特征的提取很重要。对于多通道的设备故障振动信号,应用非平稳信号的盲源分离算法,可以有效地提取各自独立的非平稳振动源,从而可以准确地进行机械故障诊断。针对不同时频分布的非平稳盲源分离算法,比较了它们的分离效果。以转子的复合故障为例,验证了该算法在故障诊断中可行性。 It is important to extract fault features when machine would be in fault state.The nonstationary vibration sources that are mutually independent can be effectively identified by using the nonstationary blind source separation(method) from the multi-channel fault vibration signals.The separation efficiency of the nonstationary blind source(seperation) method is assessed by using different time-frequency distribution.The results of an experiment under the rotor's multi-faults case show that this method is feasible for fault diagnosis.
出处 《振动与冲击》 EI CSCD 北大核心 2006年第1期110-114,共5页 Journal of Vibration and Shock
关键词 非平稳盲源分离 故障诊断 时频分布 转子 nonstationary blind source separation,fault diagnosis,time-frequency distribution,rotor
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参考文献7

  • 1吴军彪,陈进,伍星.基于盲源分离技术的故障特征信号分离方法[J].机械强度,2002,24(4):485-488. 被引量:34
  • 2L科恩(著) 白居宪(译).时-频分析:理论与应用[M].西安:西安交通大学出版社,1998..
  • 3Belouchrani A,Merain K,Cardoso J F,Moulines E.A blind source separation techneque using second order statistics.IEEE trans.On signal Processing,1997,45(2):434-443.
  • 4Fevotte C,Doncarli C.Two contributions to blind source separation using time-frequency distributions.Signal Processing Letters,IEEE,Volume:11,Issue:3,March 2004,386-389.
  • 5Belouchrani A,Amin M G.Blind source separation based on time-frequency signal representations.IEEE Trans.Signal Processing,1998,46(11):2888-2897.
  • 6Holobar A,Fevotte C,Doncarli C,Zazula D.Single autoterms selection for blind source separation in time-frequency plane.in Proc.EUSIPCO,2002,1:565-568.
  • 7Guo Z,Durand L,Lee H C.The time-frequency distributions of nonstationary signals based on a Bessel kernel.IEEE Trans.Signal Processing,1994,42(7):1700-1707.

二级参考文献11

  • 1Gelle G, Colas M, Delaunay G. Blind sources separation applied to rotating machines monitoring by acoustical and vibrations analysis. Mechanical Systems and Signal Processing,2000, MSSP-14(3):427 ~ 442.
  • 2Cao X R, Ruey-wen Liu. General approach to blind source separation.IEEE Trans. Signal Processing, 1996, 44(3) :562 ~ 571.
  • 3Cardoso J F. Blind signal separation: statistical principles. Proc. IEEE,1998, 86(10):2009~2025.
  • 4He Zhengya, Yang Luxi, Liu Ju, et al. Blind source separation using clustering-based multivariate density estimation algorithm. IEEE Trans. Signal Processing,2000, 48(2) :575 ~ 579.
  • 5Belouchrani A, Abed-Meraim K, Moulines E. A blind source separation technique using second-order statistics. IEEE Trans. Signal Processing,1997,45(2) :434 ~ 444.
  • 6Yeredor A. Blind source separation via the second characteristic function.Signal Processing, 2000, SP-80 (3): 897 ~ 902.
  • 7Cardoso J F, Souloumiac A. Blind beamforming for non-Gaussian signals.Proc. IEE, 1993, 140(6): 362 ~ 370.
  • 8Wang H, Kaveh M. Coherent signal-subspace processing for the detection and estimation of angles of arrival of multiple wide-band sources. IEEE Trans. Aeoustics, Speech, and Signal Processing, 1985, ASSP-33(4):823~831.
  • 9Cardoso J F, Souloumiac A. Jacobi angles for simultaneous diagonalization.SIAM Journal on Martix Analysis and Applications, 1996, 17( 1 ): 161 ~164.
  • 10蒋伟康,高田博,西择男.声近场综合试验解析技术及其在车外噪声分析中的应用[J].机械工程学报,1998,34(5):76-84. 被引量:18

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