Fault detection and diagnosis for railway track circuits using neuro-fuzzy systems

2008 ◽  
Vol 16 (5) ◽  
pp. 585-596 ◽  
Author(s):  
J. Chen ◽  
C. Roberts ◽  
P. Weston
Keyword(s):  
Fault Detection ◽  
Fuzzy Systems ◽  
Fault Detection And Diagnosis ◽  
Railway Track ◽  
Neuro Fuzzy ◽  
Track Circuits ◽  
Detection And Diagnosis

Induction Motors Stator Fault Analysis based on Artificial Intelligence

2016 ◽  
Vol 2 (1) ◽  
pp. 69 ◽  
Author(s):  
Hussein Taha Hussein ◽  
Mohamed Ammar ◽  
Mohamed Moustafa Hassan
Keyword(s):  
Artificial Intelligence ◽  
Fault Detection ◽  
Short Circuit ◽  
Fault Analysis ◽  
Fault Detection And Diagnosis ◽  
Neuro Fuzzy ◽  
Detection Approach ◽  
Three Phase ◽  
Detection And Diagnosis ◽  
Stator Fault

This article presents a method for fault detection and diagnosis of stator inter-turn short circuit in three phase induction machines. The technique is based on the stator current and modelling in the dq frame using an Adaptive Neuro-Fuzzy artificial intelligence approach. The developed fault analysis method is illustrated using MATLAB simulations. The obtained results are promising based on the new fault detection approach.

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