Extraction of Dynamic Nonnegative Features from Multidimensional Nonstationary Signals

2016 ◽  
pp. 557-566 ◽  
Author(s):  
Rafał Zdunek ◽  
Michalina Kotyla
Keyword(s):  
Nonstationary Signals

Fast detection of system nonlinearity using nonstationary signals

2010 ◽  
Vol 24 (7) ◽  
pp. 2065-2075 ◽  
Author(s):  
E. Zhang ◽  
J. Antoni ◽  
R. Pintelon ◽  
J. Schoukens
Keyword(s):  
Nonstationary Signals ◽  
Fast Detection ◽  
System Nonlinearity

Monitoring Nonstationary Signals

2009 ◽  
Vol 24 (3) ◽  
pp. 1367-1376 ◽  
Author(s):  
A.M. Gaouda ◽  
M.M.A. Salama
Keyword(s):  
Nonstationary Signals

Optimized estimation of moments for nonstationary signals

1997 ◽  
Vol 45 (5) ◽  
pp. 1210-1221 ◽  
Author(s):  
P.W. Wu ◽  
H. Lev-Ari
Keyword(s):  
Nonstationary Signals

scholarly journals A combined generalized Warblet transform and second order synchroextracting transform for analyzing nonstationary signals of rotating machinery

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Kai Wei ◽  
Xuwen Jing ◽  
Bingqiang Li ◽  
Chao Kang ◽  
Zhenhuan Dou ◽  
...  
Keyword(s):  
Vibration Signal ◽  
Rotating Machinery ◽  
Second Order ◽  
Variable Speed ◽  
Short Time Fourier Transform ◽  
Stationary Characteristic ◽  
Nonstationary Signals ◽  
Time Frequency ◽  
Effective Technology ◽  
Short Time

AbstractIn recent years, considerable attention has been paid in time–frequency analysis (TFA) methods, which is an effective technology in processing the vibration signal of rotating machinery. However, TFA techniques are not sufficient to handle signals having a strong non-stationary characteristic. To overcome this drawback, taking short-time Fourier transform as a link, a TFA methods that using the generalized Warblet transform (GWT) in combination with the second order synchroextracting transform (SSET) is proposed in this study. Firstly, based on the GWT and SSET theories, this paper proposes a method combining the two TFA methods to improve the TFA concentration, named GWT–SSET. Secondly, the method is verified numerically with single-component and multi-component signals, respectively. Quantized indicators, Rényi entropy and mean relative error (MRE) are used to analyze the concentration of TFA and accuracy of instantly frequency (IF) estimation, respectively. Finally, the proposed method is applied to analyze nonstationary signals in variable speed. The numerical and experimental results illustrate the effectiveness of the GWT–SSET method.

A Wigner spectral analyzer for nonstationary signals

1989 ◽  
Vol 38 (5) ◽  
pp. 961-966 ◽  
Author(s):  
M. Sun ◽  
C.C. Li ◽  
L.N. Sekhar ◽  
R.J. Sclabassi
Keyword(s):  
Nonstationary Signals ◽  
Spectral Analyzer
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