Blind Source Separation Based on Wavelet and Cross-Wavelet

2011 ◽  
Vol 328-330 ◽  
pp. 2064-2068 ◽  
Author(s):  
Jing Hui Wang ◽  
Yuan Chao Zhao

In this paper, a novel blind separation approach using wavelet and cross-wavelet is presented. This method extends the separate technology from time-frequency domain to time-scale domain. The simulation showed that this method is suitable for dealing with non-stationary signal.

2014 ◽  
Vol 945-949 ◽  
pp. 1054-1062 ◽  
Author(s):  
Zhi Nong Li ◽  
Fen Zhang ◽  
Xu Ping He ◽  
Yao Xian Xiao

Blind source separation provides a new method for the separation of mechanical sources under high level background noise, as well as the diagnosis of the compound fault. At present, the blind source separation has been successfully applied to the mecanical fault diagnosis. But the traditional mechanical source separation methods are restricted to non-gauss, stationary and mutually independent source signals. However, the mechanical fault signals do not suffice to these conditions, and generally exhibit non-stationarity and non-independence. For the non-stationary signal, its spectral feature is time-varying. Thus only the time-domain or frequency-domain analysis is not sufficient to describe the characteristics of non-stationary signal. The time-frequency analysis, which can provide the information about that the spectrum of the signal varies with the time, is a useful tool for non-stationary signal analysis. In this paper, combined time-frequency analysis with blind source separation, a blind source separation method for the non-stationary signal of the mechanical equipment based on time-frequency analysis is proposed and studied. The simulation and experimental results show that the proposed approach is feasible and effective.


Sign in / Sign up

Export Citation Format

Share Document