关键词: 差分谱, 奇异值分解, 弱故障特征, 小波变换

Abstract: For faint fault feature information hidden in the some complicated signal, the usual two kinds of wavelet-singular value decomposition (SVD) method can’t achieve the good feature extraction effect, and the reason of this defect is analyzed from the aspect of frequency window property of wavelet. Based on the study about the distribution law of singular values of complicated signal, a new method of wavelet-SVD difference spectrum is proposed. In this method, an original signal is decomposed by wavelet transform and a group of detail signals are obtained, however, these detail signals are not simply arrayed a matrix any more, whereas each detail signal is used to create a Hankel matrix of specific configuration, and then SVD operation of each matrix is made to obtain its orthogonal decomposition results, furthermore, the feature singular values are selected by dint of difference spectrum of singular value for the SVD reconstruction, through these procedures the faint feature information can be extracted. The processing results of the vibration signal of a bearing demonstrate the excellent effect of this method on the extraction of faint fault feature information from the complicated signal, and the fault feature waveform extracted is very clear. The defect of usual two kinds of wavelet-SVD methods that they can’t achieve the good effect on extraction of faint fault feature is overcome.

Key words: Difference spectrum, Faint fault feature, Singular value decomposition, Wavelet transform