Non-Stationary Signal Classification Using Joint Frequency Analysis

2003 ◽  
Author(s):  
Somsak Sukittanon ◽  
Les E. Atlas ◽  
James W. Pitton ◽  
Jack McLaughlin
Keyword(s):  
Frequency Analysis ◽  
Signal Classification ◽  
Joint Frequency ◽  
Non Stationary Signal

Application of the Blind Source Separation Based on Time-Frequency Analysis in Mechanical Fault Diagnosis

2014 ◽  
Vol 945-949 ◽  
pp. 1054-1062 ◽  
Author(s):  
Zhi Nong Li ◽  
Fen Zhang ◽  
Xu Ping He ◽  
Yao Xian Xiao
Keyword(s):  
Fault Diagnosis ◽  
Blind Source Separation ◽  
Frequency Analysis ◽  
Source Separation ◽  
Spectral Feature ◽  
Frequency Domain Analysis ◽  
Mechanical Equipment ◽  
Time Frequency Analysis ◽  
Time Frequency ◽  
Non Stationary Signal

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.

Non-Stationary Signal Analysis Based on Hilbert-Huang Transform and Median Filter

2014 ◽  
Vol 1049-1050 ◽  
pp. 1694-1697
Author(s):  
Xiao Li Wang ◽  
Dian Hong Wang
Keyword(s):  
White Noise ◽  
Frequency Analysis ◽  
Signal Analysis ◽  
Median Filter ◽  
Low Noise ◽  
Analytic Framework ◽  
Noise Resistance ◽  
Hilbert Huang Transform ◽  
Time Frequency ◽  
Non Stationary Signal

The Hilbert-Huang Transform (HHT) is a new time-frequency analysis with adaptability and orthogonality, but it is rather weak in terms of noise resistance, even low noise can disturb the HHT result greatly. The paper launches an investigation on how noises affect the HHT result and proposes the method to solve the problem. The analytic framework for HHT is first introduced, the feature of the test signal is extracted by HHT. Median filter is adopted to reduce the frequency leakage of certain signal component caused by white noise. The method proposed is experimentally simulated and the results demonstrate its effectiveness.

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