Independent component analysis approach for fault diagnosis of condenser system in thermal power plant

2014 ◽  
Vol 21 (1) ◽  
pp. 242-251 ◽  
Author(s):  
Ajami Ali ◽  
Daneshvar Mahdi
Keyword(s):  
Fault Diagnosis ◽  
Power Plant ◽  
Independent Component Analysis ◽  
Thermal Power Plant ◽  
Thermal Power ◽  
Component Analysis ◽  
Independent Component ◽  
Analysis Approach

scholarly journals Cancelling ECG Artifacts in EEG Using a Modified Independent Component Analysis Approach

2008 ◽  
Vol 2008 (1) ◽  
Author(s):  
Stéphanie Devuyst ◽  
Thierry Dutoit ◽  
Patricia Stenuit ◽  
Myriam Kerkhofs ◽  
Etienne Stanus
Keyword(s):  
Independent Component Analysis ◽  
Component Analysis ◽  
Independent Component ◽  
Analysis Approach ◽  
Ecg Artifacts

Research on Fault Diagnosis for Petrochemical Running Equipments Based on ICA

2011 ◽  
Vol 48-49 ◽  
pp. 950-953
Author(s):  
Zhi Gang Chen ◽  
Xiao Jiao Lian ◽  
Ming Zhou
Keyword(s):  
Fault Diagnosis ◽  
Independent Component Analysis ◽  
Component Analysis ◽  
Independent Component ◽  
New Method ◽  
Signal Separation ◽  
Signal Extraction ◽  
Vibration Signals ◽  
Signal Preprocessing

For solving the difficulty of feature signal extraction from vibration signals, a new method based on Independent Component Analysis (ICA) is proposed to realize separation and filtering for multi-source vibration signals. Firstly, the principal and algorithm of ICA used to separate mixed signals is introduced. Secondly, application in signal separation and filtering with ICA is studied in diagnosis. In addition, imitation and field examples are given. The experiments show it is feasible to separate and extract feature signal from multi-source vibration signals and it is an effective method in signal preprocessing in fault diagnosis.

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