Severity and Location Detection of Three Phase Induction Motor Stator Fault Using Sample Shifting Technique and Adaptive Neuro Fuzzy Inference System

2018 ◽  
pp. 423-437
Author(s):  
S. Samanta ◽  
J. N. Bera ◽  
G. Sarkar
Keyword(s):  
Induction Motor ◽  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Inference System ◽  
Neuro Fuzzy ◽  
Three Phase ◽  
Location Detection ◽  
Stator Fault

scholarly journals Stator inter-turn fault detection of an induction motor using neuro-fuzzy techniques

2010 ◽  
Vol 20 (3) ◽  
pp. 363-376 ◽  
Author(s):  
Rudra Dash ◽  
Bidyadhar Subudhi
Keyword(s):  
Fault Detection ◽  
Induction Motor ◽  
Fault Location ◽  
Single Phase ◽  
Fuzzy Inference ◽  
Induction Machine ◽  
Inference System ◽  
Neuro Fuzzy ◽  
Three Phase ◽  
Fuzzy Techniques

Stator inter-turn fault detection of an induction motor using neuro-fuzzy techniquesMotivated by the superior performances of neural networks and neuro-fuzzy approaches to fault detection of a single phase induction motor, this paper studies the applicability these two approaches for detection of stator inter-turn faults in a three phase induction motor. Firstly, the paper develops an adaptive neural fuzzy inference system (ANFIS) detection strategy and then compares its performance with that of using a multi layer perceptron neural network (MLP NN) applied to stator inter-turn fault detection of a three phase induction motor. The fault location process is based on the monitoring the three phase shifts between the line current and the phase voltage of the induction machine.

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