On the use of simulated annealing to automatically assign decorrelated components in second-order blind source separation

2006 ◽  
Vol 53 (5) ◽  
pp. 810-820 ◽  
Author(s):  
M. Bohm ◽  
K. Stadlthanner ◽  
P. Gruber ◽  
F.J. Theis ◽  
E.W. Lang ◽  
...  
Keyword(s):  
Simulated Annealing ◽  
Blind Source Separation ◽  
Source Separation ◽  
Second Order

scholarly journals Fault Diagnosis of Rotating Machinery Based on Multi-Sensor Signals and Median Filter Second-Order Blind Identification (MF-SOBI)

2020 ◽  
Vol 10 (11) ◽  
pp. 3735 ◽  
Author(s):  
Feng Miao ◽  
Rongzhen Zhao ◽  
Leilei Jia ◽  
Xianli Wang
Keyword(s):  
Blind Source Separation ◽  
Impulse Noise ◽  
Median Filter ◽  
Source Separation ◽  
Rotating Machinery ◽  
Second Order ◽  
Time Signal ◽  
Blind Identification ◽  
Sensor Signals ◽  
Strong Impulse

Feature extraction plays a crucial role in the diagnosis of rotating machinery faults. However, the vibration signals measured are inherently complex and non-stationary and the features of faulty signals are often submerged by noise. The principle and method of blind source separation are introduced, and we point out that the blind source separation algorithm is invalid in an environment of strong impulse noise. In order to solve the problem of fast separation of multi-sensor signals in an environment of strong impulse noise, first, the window width of the median filter (MF) is calculated according to the sampling frequency, so that the impulse noise and part of the white noise can be effectively filtered out. Next, the filtered signals are separated by the improved second-order blind identification (SOBI) algorithm. At the same time, the method is tested on the strong pulse background noise and rub impact dataset. The results show that this method has higher efficiency and accuracy than the direct separation method. It is possible to apply the method to real-time signal analysis due to its speed and efficiency.

scholarly journals A second-order statistics method for blind source separation in post-nonlinear mixtures

2019 ◽  
Vol 155 ◽  
pp. 63-72 ◽  
Author(s):  
Denis G. Fantinato ◽  
Leonardo T. Duarte ◽  
Yannick Deville ◽  
Romis Attux ◽  
Christian Jutten ◽  
...  
Keyword(s):  
Order Statistics ◽  
Blind Source Separation ◽  
Source Separation ◽  
Second Order ◽  
Second Order Statistics ◽  
Nonlinear Mixtures
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