DocumentCode :
2679248
Title :
Neural Network Based New Energy Conservation Scheme for Three Phase Induction Motor Operating under Varying Load Torques
Author :
Winston, D. Prince ; Saravanan, M. ; Xavier, S. Arockia Edwin
Author_Institution :
EEE Dept., Thiagarajar Coll. of Eng., Madurai, India
fYear :
2011
fDate :
20-22 July 2011
Firstpage :
1
Lastpage :
6
Abstract :
Due to robustness, reliability, low price and maintenance free operation, induction motors are used in most of the industrial applications. The need for energy conservation is increasing nowadays due to continuous increase in energy demand. The influence of these motors in energy intensive industries is significant in total operational cost. This paper describes a new energy conservation scheme for three phase induction motor with the help of neural network. In this new energy conservation scheme voltage compensation was employed for the various load conditions. Here neural network is used to control the voltage level for the various load conditions. Matlab simulation is done for 5 Hp, 400V, 50Hz and 7.3A three phase squirrel cage induction motor employing the new energy conservation scheme with the help of neural network.
Keywords :
frequency control; level control; machine control; neurocontrollers; squirrel cage motors; torque control; voltage control; Matlab simulation; current 7.3 A; energy intensive industries; frequency 50 Hz; frequency control; maintenance free operation; neural network; new energy conservation scheme; operational cost; three phase squirrel cage induction motor; varying load torques; voltage 400 V; voltage compensation; voltage level control; Artificial neural networks; Copper; Energy conservation; Induction motors; Iron; Torque; Voltage control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Process Automation, Control and Computing (PACC), 2011 International Conference on
Conference_Location :
Coimbatore
Print_ISBN :
978-1-61284-765-8
Type :
conf
DOI :
10.1109/PACC.2011.5978959
Filename :
5978959
Link To Document :
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