[1]胥永刚[1],李强[1],王正英[1],王太勇[1].基于独立分量分析的机械故障信息提取[J].天津大学学报,2006,39(9):1066-1071.
[2]李力,屈梁生.应用独立分量分析提取机器的状态特征[J].西安交通大学学报,2003,37(1):45-48.
[3]陈长征[1],程锦生[1],韩丽娅[2],李明辉[3],王胤龙[1],周勃[1].基于盲源分离的齿轮箱状态检测与故障诊断[J].沈阳工业大学学报,2008,30(4):444-448.
[4]陈仲生[1],杨拥民[1],沈国际[1].独立分量分析在直升机齿轮箱故障早期诊断中的应用[J].机械科学与技术,2004,23(4):481-483.
[5]钟振茂,陈进,钟平.盲源分离技术用于机械故障诊断的研究初探[J].机械科学与技术,2002,21(2):282-284.
[6]Ypma A, Leshem A, Duin RPW. Blind Separation of Rotating Machine Sources..Bilinear Forms and Con- volutive Mixtures[J]. Neuro-- computing, 2002,49 (4) :349-368.
[7]Gelle G,Colas M, Delaunay G. Blind Source Separa- tion Applied to Rotating Machines Monitoring by Acoustical and Vibrations Analysis[J]. Mechanical System and Signal Processing, 2000, 14 (3):427- 442.
[8]Hyvarinen A, Oja E. Independent Component Anal- ysis : Algorithms and Applications [J]. Neural Net- works,2000,13(4/5) :411-430.
[9]Hyvarinen A, Karhunen J, Oja E. Independent Component Analysis[M]. New York: John Wiley & Sons. ,Inc. ,2001.
[10]李舜酩[1],雷衍斌[1].基于负熵的转子混叠振动信号盲识别[J].中国机械工程,2009,10(4):437-441.
[11]Huang N E,ghen Z,Long S R,et al. The Empirical Mode Decomposition and the Hilbert Spectrum for Nonlinear and Nonstationary Time Series Analysis [J]. Proceedings of the Royal of London Series A, 1998,454 : 903-995.
[12]于德介,程军圣,杨宇著.机械故障诊断的HIBERT-HUANG变换方法[M],2006:194.
[13]Cortes C,Vapnik V. Support Vector Networks[J].Machine Learning,1995,20(2):273-297.
[14]Suykens J A K, Vandewalle J. Least Squares Sup- port Vector Machine Classifiers [J]. Neural Pro- cessing Letters (S1370-4621), 1999,9 (3):293- 300. |