An independent component analysis algorithm through solving gradient equation combined with kernel density estimation

2009 ◽  
Vol 14 (2) ◽  
pp. 204-209
Author(s):  
Yun-feng Xue ◽  
Yu-jia Wang ◽  
Jie Yang
Keyword(s):  
Independent Component Analysis ◽  
Density Estimation ◽  
Kernel Density Estimation ◽  
Kernel Density ◽  
Component Analysis ◽  
Independent Component ◽  
Analysis Algorithm ◽  
Independent Component Analysis Algorithm

A Periodic Noise Separation Method Research of well Field Three-Dimensional Drill String Vibration Signal

2013 ◽  
Vol 318 ◽  
pp. 27-32
Author(s):  
Hao Cheng Wu ◽  
Yong Shou Dai ◽  
Wei Feng Sun ◽  
Li Gang Li ◽  
Ya Nan Zhang
Keyword(s):  
Independent Component Analysis ◽  
Vibration Signal ◽  
Component Analysis ◽  
Drill String ◽  
Independent Component ◽  
Analysis Algorithm ◽  
String Vibration ◽  
Periodic Noise ◽  
Well Field ◽  
Independent Component Analysis Algorithm

Periodic noise is an important manifestation of the drill string vibration signal noise. In order to extract the characteristics of the signals which reflect the situation of the tools in drilling, the periodic components which influence the original drill string vibration signal in the well field were researched and the independent component analysis algorithm which is on the basis of negative entropy for periodic vibration noise separation was adopted. At the same time, the effect of algorithm demixing was improved where periodic noise components which existed in three directions of drill string vibration signals were used, combining with the improved particle swarm optimization algorithm to seek the optimal mixed matrix by which the multi-channel mixed-signal of independent component analysis algorithm could be structured. This method in operation was fast. And after separation each signal was of high similarity. Through the experimental simulation, the method was proven effective in the drill string vibration periodic noise signal separation.

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