Neural network-based voltage regulator for an isolated asynchronous generator supplying three-phase four-wire loads

2008 ◽  
Vol 78 (6) ◽  
pp. 985-994 ◽  
Author(s):  
Bhim Singh ◽  
Gaurav Kumar Kasal
Keyword(s):  
Neural Network ◽  
Voltage Regulator ◽  
Three Phase ◽  
Asynchronous Generator

Analysis of a Novel Three-phase Asynchronous Generator Based on Graph Theory for Supplying Single-Phase Load

2021 ◽  
pp. 1-18
Author(s):  
Sambaran Ray ◽  
Himadri S. Chatterjee ◽  
Sankar N. Mahato ◽  
Nirmal K. Roy
Keyword(s):  
Graph Theory ◽  
Single Phase ◽  
Three Phase ◽  
Asynchronous Generator

scholarly journals Faults diagnosis in stator windings of high speed solid rotor induction motors using fuzzy neural network

2021 ◽  
Vol 12 (1) ◽  
pp. 597
Author(s):  
Ahmed Thamer Radhi ◽  
Wael Hussein Zayer
Keyword(s):  
Neural Network ◽  
Equivalent Circuit ◽  
High Speed ◽  
Fuzzy Neural Network ◽  
Induction Motors ◽  
Stator Winding ◽  
Three Phase ◽  
Fuzzy Neural ◽  
Diagnosis Method ◽  
Faults Diagnosis

The paper deals with faults diagnosis method proposed to detect the inter-turn and turn to earth short circuit in stator winding of three-phase high-speed solid rotor induction motors. This method based on negative sequence current of motor and fuzzy neural network algorithm. On the basis of analysis of 2-D electromagnet field in the solid rotor the rotor impedance has been derived to develop the solid rotor induction motor equivalent circuit. The motor equivalent circuit is simulated by MATLAB software to study and record the data for training and testing the proposed diagnosis method. The numerical results of proposed approach are evaluated using simulation of a three-phase high-speed solid-rotor induction motor of two-pole, 140 Hz. The results of simulation shows that the proposed diagnosis method is fast and efficient for detecting inter-turn and turn to earth faults in stator winding of high-speed solid-rotor induction motors with different faults conditions

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