Implementation of online air-gap torque monitor for detection of squirrel cage rotor faults using TMS320C31

2002 ◽  
Author(s):  
V.V. Thomas
Keyword(s):  
Air Gap ◽  
Rotor Faults ◽  
Squirrel Cage ◽  
Cage Rotor

Detection of Stator and Rotor Faults in Asynchronous Motor Using Artificial Intelligence Method

2018 ◽  
pp. 278-285
Author(s):  
K. Vinoth Kumar ◽  
Prawin Angel Michael
Keyword(s):  
Induction Motor ◽  
Asynchronous Motor ◽  
Feed Forward Neural Network ◽  
Identification Scheme ◽  
Hardware System ◽  
Rotor Faults ◽  
Squirrel Cage ◽  
Three Phase ◽  
Neural Network Structure ◽  
Trained Network

This chapter deals with the implementation of a PC-based monitoring and fault identification scheme for a three-phase induction motor using artificial neural networks (ANNs). To accomplish the task, a hardware system is designed and built to acquire three phase voltages and currents from a 3.3KW squirrel-cage, three-phase induction motor. A software program is written to read the voltages and currents, which are first used to train a feed-forward neural network structure. The trained network is placed in a Lab VIEW-based program formula node that monitors the voltages and currents online and displays the fault conditions and turns the motor. The complete system is successfully tested in real time by creating different faults on the motor.

Transient Modeling of Squirrel-Cage Induction Machine Considering Air-Gap Flux Saturation Harmonics

2008 ◽  
Vol 55 (7) ◽  
pp. 2798-2809 ◽  
Author(s):  
Xiaoping Tu ◽  
L.-A. Dessaint ◽  
R. Champagne ◽  
K. Al-Haddad
Keyword(s):  
Induction Machine ◽  
Air Gap ◽  
Squirrel Cage ◽  
Transient Modeling
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