Application of non-stationary signal characteristics using wavelet packet transformation

Although Fourier-based methods have been standard methods for frequency analysis, they are not well suited for the analysis of nonlinear or non-stationary systems due to their time-varying natures. Thus, in this paper, a wavelet packet-based technique, which calculates time-varying coherence functions for input/output relationships, is developed. The developed method uses the Coiflet wavelet that has been widely used in signal processing. It is applied to obtain the time-varying coherence function, and to detect the impulse signal from the impulse-embedded signal such as an automobile sound/vibration signal with an external impact caused by a collision or passing over rough terrain. Some characteristics of non-stationary behavior such as the wavelet packet coefficients, maximum phase plane (MPP) analysis and fault detection are also demonstrated. The method gives promising results of non-stationary input-output systems, and so may be used as an effective tool for condition monitoring or fault detection area.

[1]  J. S. Bendat System identification from multiple input/output data , 1976 .

[2]  K. Park,et al.  Extraction of Impulse Response Data via Wavelet Transform for Structural System Identification , 1998 .

[3]  J. Tukey,et al.  An algorithm for the machine calculation of complex Fourier series , 1965 .

[4]  I. Daubechies Orthonormal bases of compactly supported wavelets , 1988 .

[5]  Richard A. Brown,et al.  Introduction to random signals and applied kalman filtering (3rd ed , 2012 .

[6]  J. Bendat,et al.  DECOMPOSITION OF WAVE FORCES INTO LINEAR AND NON-LINEAR COMPONENTS , 1986 .

[7]  서상현,et al.  가솔린 엔진의 소음원 검출에 대한 다차원 스펙트럼 해석의 응용 ( Application of Multi - Dimensional Spectral Analysis for Noise Source Identification on Gasoline Engine ) , 1986 .

[8]  N. C. Nigam Introduction to Random Vibrations , 1983 .

[9]  Jean-Michel Poggi,et al.  Wavelets and their applications , 2007 .

[10]  Kan Ge-li WAVELET ANALYSIS AND SPECTROSCOPY SIGNAL PROCESSING , 2004 .

[11]  K. Park,et al.  Identification of Structural Dynamics Models Using Wavelet-Generated Impulse Response Data , 1998 .

[12]  W. J. Staszewski,et al.  ON THE CROSS WAVELET ANALYSIS OF DUFFING OSCILLATOR , 1999 .

[13]  Jing Lin,et al.  Feature Extraction Based on Morlet Wavelet and its Application for Mechanical Fault Diagnosis , 2000 .

[14]  M. Victor Wickerhauser,et al.  Adapted wavelet analysis from theory to software , 1994 .

[15]  I. Daubechies Ten Lectures on Wavelets , 1992 .

[16]  W. J. Staszewski,et al.  Application of the Wavelet Based FRFs to the Analysis of Nonstationary Vehicle Data , 1997 .

[17]  J. S. Bendat Modern analysis procedures for multiple input/output problems , 1980 .

[18]  P. D. McFadden,et al.  APPLICATION OF WAVELETS TO GEARBOX VIBRATION SIGNALS FOR FAULT DETECTION , 1996 .

[19]  Julius S. Bendat,et al.  Engineering Applications of Correlation and Spectral Analysis , 1980 .